JP7659738B2 - Inspection method and inspection system - Google Patents

Description

Embodiments of the present disclosure relate to an inspection method and an inspection system.

Systems and methods for non-destructively inspecting objects have been proposed. For example, Patent Documents 1 and 2 disclose methods for inspecting the composition or molecular weight of a resin based on a spectrum obtained by irradiating the resin with light.

JP 2019-86412 A JP 2019-86499 A

The spectrum contains noise caused by the testing environment, etc. The greater the noise, the lower the accuracy of the test.

The embodiment of the present disclosure aims to provide an inspection method and an inspection system that can effectively solve such problems.

One embodiment of the present disclosure is an inspection method, comprising:
A first irradiation step of irradiating an object with light;
a first detection step of detecting an intensity of light reflected by the object or transmitted through the object;
A first generation step of generating a target spectrum including information about the intensities at a plurality of wavelength points;
A first processing step of processing the target spectrum,
The first processing step includes:
a local averaging step of locally averaging the target spectrum to generate a locally averaged spectrum;
a first noise evaluation step of calculating a first noise index based on a difference between the target spectrum and the locally averaged spectrum;
and a first recording step of recording the target spectrum when the first noise index is equal to or greater than a first threshold.

In an inspection method according to an embodiment of the present disclosure, the first noise evaluation step may include a step of calculating a standard deviation of the differences, and a step of calculating the first noise index based on the standard deviation.

In an inspection method according to an embodiment of the present disclosure, if the first noise index is less than the first threshold, the first irradiation step, the first detection step, the first generation step, and the first processing step may be performed again.

In an inspection method according to an embodiment of the present disclosure, the local averaging step may include a step of calculating a local average value at each wavelength point of the target spectrum. The local average value may be calculated by averaging the value of the target spectrum at the wavelength point of interest and the values of the target spectrum at 5 to 15 wavelength points located in the vicinity of the wavelength point of interest.

An inspection method according to an embodiment of the present disclosure may include a second irradiation step of irradiating a calibration sample with light, a second detection step of detecting the intensity of light reflected by the calibration sample or light transmitted through the calibration sample, and a second generation step of generating a calibration spectrum including information about the intensity at a plurality of wavelength points. The first generation step may generate the target spectrum by using the calibration spectrum as a reference.

The inspection method according to an embodiment of the present disclosure may include a second processing step of processing the calibration spectrum. The second processing step may include a second differentiation step of generating a second derivative spectrum by second-order differentiation of the calibration spectrum, a second noise evaluation step of calculating a second noise index based on the second derivative spectrum, and a second recording step of recording the calibration spectrum when the second noise index is equal to or greater than a second threshold value.

One embodiment of the present disclosure is an inspection method, comprising:
A first irradiation step of irradiating an object with light;
a first detection step of detecting an intensity of light reflected by the object or transmitted through the object;
A first generation step of generating a target spectrum including information about the intensities at a plurality of wavelength points;
a second irradiation step of irradiating the calibration sample with light;
a second detection step of detecting an intensity of light reflected by the calibration sample or light transmitted through the calibration sample;
a second generation step of generating a calibration spectrum comprising information about the intensities at a plurality of wavelength points;
a second processing step of processing the calibration spectrum,
The second processing step includes:
a second differentiation step of generating a second derivative spectrum by second-deriving the calibration spectrum;
a second noise evaluation step of calculating a second noise index based on the second derivative spectrum;
a second recording step of recording the calibration spectrum when the second noise index is equal to or greater than a second threshold;
The first generating step is an inspection method in which the target spectrum is generated by using the calibration spectrum as a reference.

In an inspection method according to an embodiment of the present disclosure, the second noise evaluation step may include a step of calculating a standard deviation of the second derivative spectrum, and a step of calculating the second noise index based on the standard deviation.

In an inspection method according to an embodiment of the present disclosure, if the second noise index is less than the second threshold, the second irradiation step, the second detection step, the second generation step, and the second processing step may be performed again.

The inspection method according to an embodiment of the present disclosure may record a plurality of the calibration spectra having the second noise index equal to or greater than the second threshold by performing the second irradiation step, the second detection step, the second generation step, and the second processing step a plurality of times. The first generation step may generate the target spectrum by using an average of the plurality of the calibration spectra as a reference.

One embodiment of the present disclosure is an inspection system, comprising:
An illumination device that illuminates an object with light;
a detection device for detecting an intensity of light reflected by or transmitted through the object;
A generation device including a first generation unit that generates a target spectrum including information about the intensities at a plurality of wavelength points;
A processing device including a first processing unit that processes the target spectrum,
The first processing unit is
local averaging, locally averaging the target spectrum to generate a locally averaged spectrum;
a first noise evaluation for calculating a first noise index based on a difference between the target spectrum and the locally averaged spectrum;
and a first recording, recording the spectrum of interest if the first noise index is greater than or equal to a first threshold.

In an inspection system according to one embodiment of the present disclosure, the first processing unit may calculate a standard deviation of the differences and calculate the first noise index based on the standard deviation.

In an inspection system according to an embodiment of the present disclosure, the first processing unit may calculate a local average value at each wavelength point of the target spectrum. The local average value may be calculated by averaging the value of the target spectrum at the wavelength point of interest and the values of the target spectrum at 5 to 15 wavelength points located in the vicinity of the wavelength point of interest.

In an inspection system according to an embodiment of the present disclosure, the generating device may include a second generating unit that generates a calibration spectrum including information about the intensity of light reflected by or transmitted through a calibration sample at a plurality of wavelength points. The first generating unit may generate the target spectrum by using the calibration spectrum as a reference.

In an inspection system according to an embodiment of the present disclosure, the processing device may include a second processing unit that processes the calibration spectrum. The second processing unit may perform a second differentiation to generate a second derivative spectrum by second-order differentiation of the calibration spectrum, a second noise evaluation to calculate a second noise index based on the second derivative spectrum, and a second recording to record the calibration spectrum when the second noise index is equal to or greater than a second threshold value.

One embodiment of the present disclosure is an inspection system, comprising:
An illumination device that illuminates an object with light;
a detection device for detecting an intensity of light reflected by or transmitted through the object;
A generating device including a first generating unit that generates a target spectrum including information about the intensities at a plurality of wavelength points, and a second generating unit that generates a calibration spectrum including information about the intensities of light reflected by a calibration sample or light transmitted through the calibration sample at a plurality of wavelength points;
a processing device including a second processing unit that processes the calibration spectrum;
The second processing unit is
a second derivative of the calibration spectrum to generate a second derivative spectrum;
a second noise evaluation for calculating a second noise index based on the second derivative spectrum;
a second recording, recording the calibration spectrum if the second noise index is greater than or equal to a second threshold;
The first generator is an inspection system that generates the target spectrum by using the calibration spectrum as a reference.

In an inspection system according to an embodiment of the present disclosure, the second processing unit may calculate a standard deviation of the second derivative spectrum and calculate the second noise index based on the standard deviation.

The inspection system according to one embodiment of the present disclosure may include a case that houses the irradiation device and the detection device. The case may include a first surface including a window through which the light passes, a second surface facing the first surface, and a side surface located between the first surface and the second surface.

In an inspection system according to one embodiment of the present disclosure, the case may include a first friction layer provided on the first surface or the outer edge.

In an inspection system according to one embodiment of the present disclosure, the case may include a support member including a first portion fixed to the side surface and a second portion connected to the first portion and parallel to the first surface.

In an inspection system according to one embodiment of the present disclosure, the case may include a second friction layer provided on the second portion.

According to one embodiment of the present disclosure, noise contained in the spectrum can be reduced.

FIG. 2 is a cross-sectional view illustrating an object according to an embodiment. FIG. 1 is a block diagram illustrating an inspection system according to an embodiment. FIG. 2 is a schematic diagram illustrating an illumination device and a detection device of an inspection system according to an embodiment. FIG. 2 is a perspective view showing an example of a case that houses an irradiation device and a detection device. FIG. 1 illustrates an example of how the inspection system can be used. 10 is a flowchart showing an example of an inspection process. FIG. 2 is a diagram illustrating an example of a target spectrum. FIG. 13 is a diagram illustrating an example of an averaged spectrum. FIG. 13 is a diagram illustrating an example of a difference between a target spectrum and an averaged spectrum. FIG. 13 is a diagram showing an example of a calibration spectrum. FIG. 13 is a diagram showing an example of a process for irradiating a calibration sample with light. 13 is a flowchart illustrating an example of a calibration process. FIG. 2 is a perspective view showing an example of a case. FIG. 2 is a perspective view showing an example of a case. FIG. 11 is a diagram showing the measurement results of a first calibration sample in Example 1. FIG. 11 is a diagram showing the measurement results of a first calibration sample in Example 1. FIG. 11 is a diagram showing the measurement results of a second calibration sample in Example 2. FIG. 11 is a diagram showing the measurement results of a second calibration sample in Example 2. FIG. 13 is a diagram showing a measurement result of a first object in Example 3. FIG. 13 is a diagram showing the measurement results of a second object in Example 4. FIG. 13 is a diagram showing the measurement results of a third object in Example 5. FIG. 23 is a diagram showing the measurement results of a fourth object in Example 6. FIG. 23 is a diagram showing the measurement results of the fifth object in Example 7. FIG. 23 is a diagram showing the measurement results of the sixth object in Example 8.

The configuration of an object and an inspection system according to an embodiment of the present disclosure will be described in detail with reference to the drawings. Note that the embodiment described below is an example of an embodiment of the present disclosure, and the present disclosure should not be interpreted as being limited to these embodiments. In this specification, terms such as "substrate" and "sheet" are not distinguished from each other based only on the difference in name. For example, "substrate" is a concept that includes members that may be called sheets or films.

Terms used in this specification that specify shapes, geometric conditions, and their degrees, such as "parallel" and "orthogonal," as well as values of lengths and angles, are not limited to their strict meanings, but are interpreted to include the range within which similar functions can be expected.

In this specification, when multiple upper limit candidates and multiple lower limit candidates are given for a certain parameter, the numerical range of the parameter may be constructed by combining any one of the upper limit candidates and any one of the lower limit candidates. For example, consider a case where "Parameter B is, for example, A1 or more, may be A2 or more, or may be A3 or more. Parameter B is, for example, A4 or less, may be A5 or less, or may be A6 or less." In this case, the numerical range of parameter B may be A1 or more and A4 or less, A1 or more and A5 or less, A1 or more and A6 or less, A2 or more and A4 or less, A2 or more and A5 or less, A2 or more and A6 or less, A3 or more and A4 or less, A3 or more and A5 or less, or A3 or more and A6 or less.

In the drawings referred to in this embodiment, identical parts or parts having similar functions are given the same or similar symbols, and repeated explanations may be omitted. In addition, the dimensional ratios of the drawings may differ from the actual ratios for the convenience of explanation, and some components may be omitted from the drawings.

In one embodiment of the present specification, an example is described in which a target spectrum obtained by irradiating a target with light is used to inspect the composition or molecular weight of a resin contained in the target. However, the use of the target spectrum is not particularly limited, and the target spectrum can be used for various purposes.

(First embodiment)
1 is a diagram showing an example of an object 10. The object 10 is, for example, a resin sheet. Resin sheets are used for various purposes, such as decorative sheets for building materials such as flooring materials, agricultural sheets, encapsulation sheets for semiconductor elements, and packaging sheets.

The object 10 includes a base sheet 11 and a resin layer 12 laminated on the base sheet 11. The resin layer 12 may be provided over the entire surface of the base sheet 11, or may be provided partially on the surface of the base sheet 11 so as to present a pattern. In the following description, the surface of the object 10 located on the resin layer 12 side is referred to as the first surface 10x, and the surface of the object 10 located on the base sheet 11 side is referred to as the second surface 10y.

The base sheet 11 includes, for example, paper, synthetic resin, etc. More specifically, the base sheet 11 may include a cellulose resin, or an olefin-based synthetic resin such as polypropylene. The basis weight of the base sheet 11 is, for example, 50 g/m ² or more. The basis weight of the base sheet 11 is, for example, 300 g/m ² or less, and may be 120 g/m ² or less.

The resin layer 12 includes a resin material. The resin material included in the resin layer 12 is not particularly limited, but is, for example, a polymer resin. Examples of the polymer resin include polyethylene resin, polyvinyl chloride resin (PVC), polyvinyl alcohol resin (PVA), polypropylene, polystyrene, polyvinyl acetate, acrylic resin, polyethylene terephthalate, polyester, polyamide, polycarbonate, polyurethane, and polyimide.
Examples of polyethylene-based resins include polyethylene, as well as ethylene copolymers having ethylene and a component other than ethylene as monomers, such as ethylene-vinyl acetate copolymer resin (EVA) and ethylene-α-olefin copolymer. The resin layer 12 may also contain rubber. Examples of rubber include isoprene rubber, butadiene rubber, acrylonitrile-butadiene copolymer rubber, and styrene-butadiene copolymer rubber. The thickness of the resin layer 12 is, for example, 40 μm or more. The thickness of the resin layer 12 may be 700 μm or less.
As described later, the resin layer 12 may contain a foaming agent or a foaming assistant in addition to the resin material. In this case, the thickness of the resin layer 12 before foaming is, for example, 40 μm or more and 100 μm or less. The thickness of the resin layer 12 after foaming is, for example, 300 μm or more and 700 μm or less.

The resin layer 12 may further contain a coloring material such as a pigment. The pigment may be an inorganic pigment or an organic pigment. Examples of inorganic pigments include titanium oxide, zinc oxide, carbon black, black iron oxide, yellow iron oxide, yellow lead, molybdate orange, cadmium yellow, nickel titanium yellow, chrome titanium yellow, iron oxide (red oxide), cadmium red, ultramarine, Prussian blue, cobalt blue, chromium oxide, cobalt green, aluminum powder, bronze powder, titanium mica, and zinc sulfide. Examples of organic pigments include aniline black, perylene black, azo-based (azo lake, insoluble azo, condensed azo), polycyclic (isoindolinone, isoindoline, quinophthalone, perinone, flavanthrone, anthrapyrimidine, anthraquinone, quinacridone, perylene, diketopyrrolopyrrole, dibromoanzanthrone, dioxazine, thioindigo, phthalocyanine, indanthrone, and halogenated phthalocyanine. The pigment content in the resin layer 12 may be, for example, 5 parts by mass or more, or 15 parts by mass or more, relative to 100 parts by mass of the resin component. The pigment content in the resin layer 12 may be, for example, 50 parts by mass or less, or 30 parts by mass or less, relative to 100 parts by mass of the resin component.

The resin layer 12 may contain a filler. This can increase the strength, hardness, etc. of the resin layer 12. The filler includes inorganic materials such as calcium carbonate, aluminum hydroxide, magnesium hydroxide, antimony trioxide, zinc borate, molybdenum compounds, and talc. The amount of filler contained in the resin layer 12 may be, for example, 0.1 parts by mass or more, or 20 parts by mass or more, relative to 100 parts by mass of the resin material. The amount of filler contained in the resin layer 12 may be, for example, 100 parts by mass or less, or 70 parts by mass or less, relative to 100 parts by mass of the resin material.

The resin layer 12 may contain additives such as antifungal agents, insect repellents, preservatives, antibacterial agents, deodorants, polymerization initiators, polymerization inhibitors, sensitizers, crosslinking agents, plasticizers, flame retardants, charge control agents, heat stabilizers, light stabilizers, conductive agents, defoamers, rust inhibitors, antioxidants, foaming agents, foaming assistants, near-infrared absorbers, ultraviolet absorbers, and emulsifiers.

[Inspection system]
2 is a block diagram showing an inspection system 15 for inspecting the object 10. The inspection system 15 measures a spectrum that represents characteristics of the resin layer 12. The inspection system 15 may determine which of a plurality of candidate compositions the composition of the material constituting the resin layer 12 is, based on the spectrum. Information regarding the plurality of candidate compositions is stored in advance in the inspection system 15.

The candidate composition may represent the resin material contained in the resin layer 12 as a main component, or may represent the resin material contained in the resin layer 12 as a secondary component. The main component is the resin material in the resin layer 12 that has the highest content. The secondary component is the resin material in the resin layer 12 that has a lower content than the main component. The candidate composition may represent the type of additive added to the resin layer 12, or may represent whether or not the resin layer 12 contains an additive.

The inspection system 15 includes an irradiation device 21, a detection device 24, a generation device 25, a processing device 27, and a determination device 28. The irradiation device 21 and the detection device 24 constitute a spectroscopic module 20, which will be described later. The spectroscopic module 20 is housed in a case 40, which will be described later. Some or all of the generation device 25, the processing device 27, and the determination device 28 may be included in the spectroscopic module 20, or may be included in a component other than the spectroscopic module 20. For example, some or all of the generation device 25, the processing device 27, and the determination device 28 may be realized by a computer capable of communicating with the spectroscopic module 20.

[Irradiation device]
The irradiation device 21 irradiates the object 10 with light such as near-infrared light. The irradiation device 21 includes an irradiation unit 211. The irradiation unit 211 irradiates the first surface 10x of the object 10 with light. The wavelength of the light is, for example, 800 nm or more, and may be 900 nm or more. The wavelength of the light is, for example, 2500 nm or less, may be 2000 nm or less, or may be 1700 nm or less.

FIG. 3 is a diagram showing a schematic of the irradiation device 21 and the detection device 24. The irradiation device 21 may include a diffusion section 212. The diffusion section 212 diffuses the light emitted from the irradiation section 211. This allows the light L1 to be irradiated onto the object 10 from various directions. This allows the inspection system 15 to obtain a diffuse reflectance spectrum. The diffusion section 212 is, for example, a diffusion plate disposed between the irradiation section 211 and the object 10.

[Detection device]
The detection device 24 receives the light L2 reflected by the object 10. The detection device 24 can detect the intensity of the light L2. In the following description, the light reflected by the object 10 is also referred to as reflected light L2.

The detection device 24 includes a detection unit 241 that detects reflected light L2 at multiple wavelength points. The number of wavelength points is determined according to the resolution of the detection unit 241. For example, if the detection unit 241 detects the intensity of reflected light L2 in the range of 900 nm to 1800 nm with a resolution of 3 nm, the number of wavelength points is 301. A near-infrared spectrometer, a near-infrared hyperspectral camera, or the like can be used as the detection unit 241.

The detection unit 241 detects the reflected light L2 specularly reflected by the object 10. The detection unit 241 may detect the reflected light L2 diffusely reflected by the object 10 in addition to the reflected light L2 specularly reflected by the object 10. This makes it possible to obtain more information about the resin material. This improves the accuracy of determining the composition of the resin layer 12. In FIG. 3, the symbol H1 represents the distance between the detection unit 241 and the object 10, and the symbol W1 represents the width of the detection unit 241. The distance H1 and the width W1 are appropriately determined so that the reflected light L2 diffusely reflected by the object 10 is incident on the detection unit 241.

[Generation device]
The generating device 25 includes a first generating unit 251 and a second generating unit 252. The first generating unit 251 generates a spectrum including information about the intensity of the reflected light L2 at a plurality of wavelength points. In the following description, the spectrum including information about the intensity of the reflected light L2 reflected by the object 10 is also referred to as an object spectrum.

In this specification, "spectrum" means a group of data corresponding to a wavelength point. When the group of data is illustrated, a graph such as that shown in FIG. 7 described later is generated. The data includes information regarding the intensity of reflected light L2 at the wavelength point. The data may be the intensity of reflected light L2 itself. The data may be calculated by performing some processing on the intensity of reflected light L2 at the wavelength point. For example, the data may be absorbance. Absorbance is a dimensionless quantity that represents the degree to which the object 10 absorbs light. The absorbance Abs is calculated, for example, by the following formula.
Abs=-log ₁₀ (Itar/Iref)
Itar is the intensity of light reflected by the object 10. Iref is the intensity of light reflected by a calibration sample. The calibration sample is, for example, a standard reflector. The standard reflector is also called a standard white plate or a white plate.

The second generation unit 252 generates a spectrum containing information about the intensity of light reflected by the calibration sample at multiple wavelength points. In the following description, the spectrum containing information about the intensity of light reflected by the calibration sample is also referred to as a calibration spectrum. The first generation unit 251 may generate a target spectrum by using the calibration spectrum as a reference, as expressed by the above formula.

[Processing Device]
The processing device 27 includes a first processing unit 271 and a second processing unit 272. The first processing unit 271 performs some processing on the target spectrum. For example, the first processing unit 271 may perform local averaging to generate an averaged spectrum by locally averaging the target spectrum. The first processing unit 271 may perform a first noise evaluation to calculate a first noise index based on the difference between the target spectrum and the locally averaged spectrum. The first processing unit 271 may perform a first recording to record the target spectrum when the first noise index is equal to or greater than a first threshold TH1.

The first processing unit 271 may further perform some processing on the target spectrum recorded by the first recording. For example, the first processing unit 271 may perform processing on the target spectrum including averaging, smoothing, normalization, differentiation, scatter correction, baseline correction, peak shift correction, or a combination thereof. This allows the first processing unit 271 to calculate multiple parameter values corresponding to multiple wavelength points. Details of these processes are described, for example, in JP 2019-86412 A.

The second processing unit 272 may perform some processing on the calibration spectrum. For example, the second processing unit 272 may perform a second differentiation to generate a second derivative spectrum by second-order differentiation of the calibration spectrum. The second processing unit 272 may perform a second noise evaluation to calculate a second noise index based on the second derivative spectrum. The second processing unit 272 may perform a second recording to record the calibration spectrum when the second noise index is equal to or greater than a second threshold value.

[Determination device]
The determination device 28 determines the composition of the resin layer 12 based on information recorded or generated by processing by the first processing unit 271. For example, the determination device 28 determines which of a plurality of candidate compositions the composition of the material constituting the resin layer 12 is, based on parameter values calculated by the first processing unit 271. The determination device 28 may be integrated with the processing device 27. The determination device 28 includes a storage unit 281, an analysis unit 282, and a determination unit 283.

The memory unit 281 is a component that stores in advance multiple regression equations that respectively represent the relationship between multiple parameter values and multiple candidate compositions of the resin layer 12. The memory unit 281 is, for example, a memory such as a ROM or a RAM. Details of the regression equations are described, for example, in JP 2019-86412 A.

The analysis unit 282 applies each of the multiple regression equations in the storage unit 281 to each of the multiple parameter values. This makes it possible to calculate the similarity between the composition of the resin layer 12 and each of the multiple candidate compositions. The analysis unit 282 is, for example, a CPU. Details of the method for calculating the similarity are described in, for example, JP 2019-86412 A.

The determination unit 283 determines the composition of the resin layer 12 based on the similarity calculated by the analysis unit 282. The determination unit 283 extracts the similarity that is closest to the target value from among the multiple similarities. The determination unit 283 determines the candidate composition that corresponds to the regression equation from which the extracted similarity is derived as the composition of the resin layer 12. The determination unit 283 is, for example, a CPU.

Next, a specific structure of the inspection system 15 will be described. As shown in FIG. 4, the inspection system 15 may include a case 40 that houses the spectroscopic module 20. The spectroscopic module 20 includes an irradiation device 21 and a detection device 24. The case 40 preferably has a portable form. The weight of the case 40 that houses the irradiation device 21 and the detection device 24 is, for example, 5 kg or less, may be 2 kg or less, and is preferably 1 kg or less. By carrying the case 40, it is possible to inspect objects 10 located in various locations.

The case 40 may include a first surface 41, a second surface 42, and a side surface. The first surface 41 faces the object 10 when the inspection method using the inspection system 15 is performed. The first surface 41 includes a window 48 through which light passes. The light is light emitted from the irradiation device 21 or reflected light received by the detection device 24. The window 48 may include an opening formed in the first surface 41. The second surface 42 faces the first surface 41. The side surface is located between the first surface 41 and the second surface 42. The side surface may include, for example, a first side surface 43, a second side surface 44, a third side surface 45, and a fourth side surface 46. The second surface 42 faces the first surface 41. The second side surface 44 faces the first side surface 43. The first side surface 43 and the second side surface 44 are located between the first surface 41 and the second surface 42.

The case 40 may include, for example, a first outer edge 411, a second outer edge 412, a third outer edge 413, and a fourth outer edge 414. The first outer edge 411, the second outer edge 412, the third outer edge 413, and the fourth outer edge 414 form the outer edge of the portion of the case 40 that faces the object 10.

A part or all of the first outer edge 411, the second outer edge 412, the third outer edge 413, and the fourth outer edge 414 may be the outer edge of the first surface 41. A part or all of the first outer edge 411, the second outer edge 412, the third outer edge 413, and the fourth outer edge 414 may be the outer edge of a side surface such as the first side surface 43, the second side surface 44, the third side surface 45, and the fourth side surface 46.

The dimension K1 of the first outer edge 411 is, for example, 500 mm or less, may be 400 mm or less, or may be 300 mm or less. The dimension K1 of the first outer edge 411 is, for example, 50 mm or more, may be 100 mm or more, or may be 150 mm or more.
The dimension K2 of the third outer edge 413 is, for example, 500 mm or less, may be 400 mm or less, or may be 300 mm or less. The dimension K2 of the third outer edge 413 is, for example, 50 mm or more, may be 100 mm or more, or may be 150 mm or more.
The distance K3 between the first surface 41 and the second surface 42 is, for example, 500 mm or less, may be 400 mm or less, or may be 300 mm or less. The distance K3 is, for example, 50 mm or more, may be 100 mm or more, or may be 150 mm or more.

Figure 5 is a diagram showing an example of how the inspection system 15 is used. In the example shown in Figure 5, the case 40 is held by a person's right hand 61 and left hand 62. The first surface 41 of the case 40 faces the object 10. When performing an inspection method using the inspection system 15, some or all of the first outer edge 411, the second outer edge 412, the third outer edge 413, and the fourth outer edge 414 may be in contact with the object 10.

[Testing method]
Next, a method for inspecting the object 10 using the inspection system 15 will be described. The inspection method includes an inspection step of inspecting the object 10. The inspection method may also include a calibration step of calibrating the inspection system 15 using a calibration sample 51.

[Inspection process]
First, the inspection process will be described. The inspection process includes a first irradiation process, a first detection process, a first generation process, and a first processing process. Fig. 6 is a flow chart showing an example of the inspection process.

In the first irradiation step, the irradiation device 21 irradiates the object 10 with light L1. In the first detection step, the detection device 24 detects the intensity of the light L2 reflected by the object 10. In the first generation step, the first generation unit 251 of the generation device 25 generates a target spectrum. The target spectrum includes information regarding the intensity of the light L2 at multiple wavelength points. In this way, the target spectrum can be measured, as shown by the symbol S11 in FIG. 6.

The information may be the intensity of the light L2 itself. The information may be calculated by performing some processing on the intensity of the light L2, such as absorbance. FIG. 7 shows an example of a target spectrum S1 that includes absorbance at multiple wavelength points.

Then, the first processing unit 271 of the processing device 27 performs a first processing step to process the target spectrum. The first processing step includes a local averaging step, a first noise evaluation step, and a first recording step.

In the local averaging process, as shown by reference symbol S12 in FIG. 6, the target spectrum is locally averaged. For example, a process of calculating a local average value at each wavelength point of the target spectrum is performed. The local average value is calculated by averaging the value of the target spectrum at the target wavelength point and the values of the target spectrum at multiple wavelength points located in the vicinity of the target wavelength point.

An example will be described in which the value of the target spectrum is absorbance. For example, the local average value at a wavelength point of 1200 nm is calculated as follows.
First, the absorbance Abs (1200) at 1200 nm is obtained. Then, the values of the target spectrum at a plurality of wavelength points located in the vicinity of 1200 nm are obtained. When the resolution of the detection device 24 is 3 nm, for example, the absorbance Abs (1188) at 1188 nm, the absorbance Abs (1191) at 1191 nm, the absorbance Abs (1194) at 1194 nm, the absorbance Abs (1197) at 1197 nm, the absorbance Abs (1203) at 1203 nm, the absorbance Abs (1206) at 1206 nm, the absorbance Abs (1209) at 1209 nm, and the absorbance Abs (1212) at 1212 nm are obtained. Then, the average value of the absorbance at these nine wavelength points is calculated. This average value is the local average value at the wavelength point of 1200 nm.

The local average value is calculated at each wavelength point. This allows the generation of a locally averaged spectrum S2, as shown in Figure 8. In Figure 8, the target spectrum S1 is represented by a dashed line, and the averaged spectrum S2 is represented by a solid line.

The number of wavelength points when calculating the local average value is not limited to nine as described above. The number of wavelength points may be, for example, five or more, and may be seven or more. The number of wavelength points may be, for example, 15 or less, and may be 13 or less.

In the first noise evaluation process, the difference between the target spectrum S1 and the locally averaged spectrum S2 is calculated, as shown by symbol S13 in FIG. 6. For example, at each wavelength point, the local average value of the averaged spectrum S2 is subtracted from the absorbance of the target spectrum S1. The spectrum generated in this way is also called the difference spectrum. FIG. 9 is a diagram showing an example of the difference spectrum S3. In FIG. 9, the target spectrum S1 is represented by a dashed line, the averaged spectrum S2 is represented by a dashed line, and the difference spectrum S3 is represented by a solid line.

Next, in the first noise evaluation step, the standard deviation of the difference between the target spectrum S1 and the locally averaged spectrum S2 is calculated. The standard deviation represents the degree of variation in the difference between the target spectrum S1 and the locally averaged spectrum S2. If the target spectrum S1 does not contain noise, the difference between the target spectrum S1 and the locally averaged spectrum S2 is expected to be almost zero. Therefore, a small standard deviation means that the target spectrum S1 contains little noise. A large standard deviation means that the target spectrum S1 contains a lot of noise.

Note that, regardless of noise, the difference between the target spectrum S1 and the locally averaged spectrum S2 is large at the position of the peak of the target spectrum S1. In order to properly evaluate the noise contained in the target spectrum S1, it is preferable to calculate the standard deviation of the difference at a position away from the peak of the target spectrum S1. For example, as shown in FIG. 9, the standard deviation of the difference may be calculated in a stable region R1 that is away from the peak. Specifically, first, difference values at multiple wavelength points contained in the stable region R1 are obtained. Next, the standard deviation of the multiple difference values is calculated.

The stable region R1 may be determined in advance based on information about the material expected to be contained in the target object 10. For example, if the target object 10 is expected to contain polyethylene, the target spectrum S1 includes a peak that appears at approximately 1200 nm. In this case, the wavelength range from 970 nm to 1100 nm may be determined in advance as the stable region R1.

Next, in the first noise evaluation step, a first noise index is calculated based on the standard deviation. The first noise index is an index of the degree of noise contained in the target spectrum S1. The first noise index is, for example, the reciprocal of the standard deviation. A large first noise index means that the target spectrum S1 contains less noise. A small first noise index means that the target spectrum S1 contains more noise. The calculated first noise index may be displayed on a display of the computer constituting the processing device 27.

Next, in the first noise evaluation step, the first noise index is compared with the first threshold TH1, as shown by reference symbol S14 in FIG. 6. If the first noise index is equal to or greater than the first threshold TH1, the first processing unit 271 performs the first recording step. In the first recording step, as shown by reference symbol S15 in FIG. 6, a target spectrum S1 having a first noise index equal to or greater than the first threshold TH1 is recorded. The recorded target spectrum S1 may be used in the determination device 28. The comparison result between the first noise index and the first threshold TH1 may be displayed on the display of the computer constituting the processing device 27.

If the first noise index is less than the first threshold TH1, steps S11, S12, S13, and S14 may be performed again as shown in FIG. 6. That is, the first irradiation step, the first detection step, the first generation step, and the first processing step may be performed again on the object 10. When the case 40 is held by hand as shown in FIG. 5, it is considered that noise may occur in the target spectrum S1 due to hand movement during the inspection step. According to the inspection step shown in FIG. 6, it is possible to eliminate the target spectrum S1 that contains a lot of noise caused by hand movement, etc. Furthermore, the inspection step can be repeatedly performed until a target spectrum S1 having a first noise index equal to or greater than the first threshold TH1 is obtained. Therefore, an appropriate target spectrum S1 can be recorded.

The inspection process may include a determination process for determining the composition of the resin layer 12 based on the recorded target spectrum S1. For example, the absorbance spectra of multiple candidate compositions may be compared with the target spectrum S1. This makes it possible to determine which of the multiple candidate compositions the composition of the material that constitutes the resin layer 12 is.

The first processing step may include a step of further performing some processing on the target spectrum recorded by the first recording. For example, in the first processing step, processing including averaging, smoothing, normalization, differentiation, scattering correction, baseline correction, peak shift correction, or a combination thereof may be performed on the recorded target spectrum. This allows multiple parameter values corresponding to multiple wavelength points to be calculated. In this case, the determination step may determine which of multiple candidate compositions the composition of the material constituting the resin layer 12 is based on the calculated parameter values. Details of these processes and determinations are described, for example, in JP 2019-86412 A.

[Calibration method]
Next, the calibration process will be described. The calibration process includes a second irradiation process, a second detection process, and a second generation process. In the second irradiation process, the irradiation device 21 irradiates the calibration sample 51 with light L1. In the second detection process, the detection device 24 detects the intensity of the light L2 reflected by the calibration sample 51. In the second generation process, the second generation unit 252 of the generation device 25 generates a calibration spectrum. The calibration spectrum includes information on the intensity of the light L2 at a plurality of wavelength points. The information may be the intensity of the light L2 itself. FIG. 10 is a diagram showing an example of a calibration spectrum.

The calibration process may be performed with the calibration sample 51 in contact with the first surface 41 so as to cover the window 48, as shown in FIG. 11. In this case, the calibration sample 51 may be fixed to the case 40. For example, the calibration sample 51 may be pressed against the window 48 by a rubber band 52 wrapped around the case 40. Although not shown, the calibration sample 51 may be separated from the first surface 41. Note that, when the calibration sample 51 is separated from the first surface 41, it is preferable to make the surroundings a dark room. This can suppress the inspection system 15 from detecting external light. In addition, in the process of inspecting the object 10, it is preferable that the distance between the object 10 and the first surface 41 is the same as the distance between the standard sample 51 and the first surface 41.

The timing of performing the calibration process is arbitrary. For example, the calibration process may be performed before starting the inspection process. Alternatively, the calibration process may be performed between multiple inspection processes.

[Effects of this embodiment]
In this embodiment, the first processing step is performed to evaluate the noise contained in the target spectrum. Therefore, it is possible to eliminate a target spectrum that contains a large amount of noise caused by hand movement or the like. In addition, the inspection step can be repeatedly performed until a target spectrum having a first noise index equal to or greater than the first threshold value TH1 is obtained. Therefore, an appropriate target spectrum can be recorded. Therefore, the composition of the material constituting the resin layer 12 can be appropriately determined.

The embodiment described above can be modified in various ways. Other embodiments will be described below with reference to the drawings as necessary. In the following description and the drawings used in the following description, the same reference numerals are used for parts that can be configured similarly to the embodiment described above as for the corresponding parts in the embodiment described above. Duplicate descriptions will be omitted. Furthermore, if it is clear that the effects obtained in the embodiment described above can also be obtained in other embodiments, the description may be omitted.

Second Embodiment
When the calibration spectrum contains noise, the effect of the noise also appears in the target spectrum. Therefore, it is preferable to reduce the noise in the calibration spectrum as much as possible. In this embodiment, a method for reducing the noise in the calibration spectrum is described. The second embodiment may be implemented in combination with the first processing step in the first embodiment. Alternatively, the second embodiment may be implemented without being combined with the first processing step.

The calibration process includes a second irradiation process, a second detection process, and a second generation process. The calibration process may further include a second processing process. The second processing process processes the calibration spectrum generated in the second generation process.

Figure 12 is a flow chart showing an example of a calibration process. In the second irradiation process, the irradiation device 21 irradiates the calibration sample 51 with light L1. In the second detection process, the detection device 24 detects the intensity of the light L2 reflected by the calibration sample 51. In the second generation process, the second generation unit 252 of the generation device 25 generates a calibration spectrum. The calibration spectrum includes information about the intensity of the light L2 at multiple wavelength points. In this way, the calibration spectrum can be measured, as shown by the symbol S21 in Figure 12.

Then, the second processing unit 272 of the processing device 27 performs a second processing step to process the calibration spectrum. The second processing step includes a second differentiation step, a second noise evaluation step, and a second recording step.

In the second-order differentiation step, the calibration spectrum is second-order differentiated as shown by reference symbol S22 in FIG. 12. This generates a second-order derivative spectrum. A small value of the second-order derivative spectrum means that the calibration spectrum contains less noise.

In the second noise evaluation step, a second noise index is calculated based on the second derivative spectrum. For example, first, as shown by reference symbol S23 in FIG. 12, the standard deviation of the values of the second derivative spectrum at multiple wavelength points is calculated. The standard deviation may be calculated based on the entire wavelength range of the second derivative spectrum, or may be calculated based on a portion of the wavelength range of the second derivative spectrum. For example, as shown in FIG. 10, if the value of the calibration spectrum is expected to decrease in the wavelength range of 1600 nm or more, the standard deviation may be calculated without considering the value of the second derivative spectrum in the wavelength range of 1600 nm or more.

Next, in the second noise evaluation process, a second noise index is calculated based on the standard deviation. The second noise index is an index of the degree of noise contained in the calibration spectrum. The second noise index is, for example, the reciprocal of the standard deviation. A large second noise index means that the calibration spectrum contains less noise. A small second noise index means that the calibration spectrum contains more noise.

Next, in the second noise evaluation process, as shown by reference symbol S24 in FIG. 12, the second noise index is compared with a second threshold value TH2. If the second noise index is equal to or greater than the second threshold value TH2, the second processing unit 272 performs a second recording process. In the second recording process, as shown by reference symbol S25 in FIG. 12, a calibration spectrum having a second noise index equal to or greater than the second threshold value TH2 is recorded.

The first generation unit 251 described above may generate the target spectrum by using the recorded calibration spectrum as a reference. This makes it possible to suppress the influence of noise in the calibration spectrum from appearing in the target spectrum.

If the second noise index is less than the second threshold TH2, it is considered that the entire or part of the surface of the calibration sample 51 is contaminated. In this case, as shown by the reference symbol S26 in FIG. 12, the calibration sample 51 may be changed to another one, or the measurement position on the calibration sample 51 may be changed. Then, steps S21, S22, S23, and S24 may be performed again. That is, the second irradiation step, the second detection step, the second generation step, and the second processing step may be performed again on a new calibration sample 51 or on a new measurement position of the calibration sample 51. According to the calibration step shown in FIG. 12, a calibration spectrum containing a lot of noise caused by contamination on the surface of the calibration sample 51 can be eliminated. In addition, the calibration step can be repeatedly performed until a calibration spectrum having a second noise index equal to or greater than the second threshold TH2 is obtained. Therefore, an appropriate calibration spectrum can be recorded.

The calibration process may be continued until N calibration spectra having a second noise index equal to or greater than the second threshold TH2 are obtained, as indicated by reference symbol S27 in FIG. 12. For example, as indicated by reference symbol S28 in FIG. 12, if the number of recorded calibration spectra is less than N, the measurement position on the calibration sample 51 may be changed. Then, steps S21, S22, S23, and S24 may be performed again. That is, the second irradiation step, the second detection step, the second generation step, and the second processing step may be performed again for the new measurement position on the calibration sample 51. According to the calibration process shown in FIG. 12, N calibration spectra having a second noise index equal to or greater than the second threshold TH2 can be obtained. N is, for example, 2 or more, may be 3 or more, or may be 4 or more. N may be, for example, 10 or less.

In the calibration process, as shown by reference symbol S28 in FIG. 12, the average of the N recorded calibration spectra may be calculated. This allows an averaged calibration spectrum to be generated. The spectral value at each wavelength point of the averaged calibration spectrum is the average of the spectral values of the N calibration spectra. For example, the value of the averaged calibration spectrum at the wavelength point of 1200 nm is the average of the values at the wavelength point of 1200 nm of the N calibration spectra.

The first generation unit 251 described above may generate the target spectrum by using the averaged calibration spectrum as a reference. This can further suppress the influence of noise in the calibration spectrum from appearing in the target spectrum.

Third Embodiment
Fig. 13 is a perspective view showing an example of the case 40. As shown in Fig. 13, the case 40 may include a first friction layer 53 provided on the first surface 41 or the outer edge. In the example shown in Fig. 13, the first friction layer 53 is provided on the first surface 41 along the third outer edge 413 and the fourth outer edge 414.

The static friction force between the first friction layer 53 and the object 10 is greater than the static friction force between the first surface 41 and the object 10. By providing the first friction layer 53 on the case 40, it is possible to prevent the case 40 from moving during the inspection process.

The first friction layer 53 may have any configuration. For example, the first friction layer 53 may be formed of a surface layer of tape attached to the first surface 41. As the tape, an anti-slip tape, item no. 5187 manufactured by Mysto Co., Ltd., or the like may be used.

(Fourth embodiment)
Fig. 14 is a perspective view showing an example of the case 40. As shown in Fig. 14, the case 40 may include a support member 54 fixed to the side surface. In the example shown in Fig. 14, the case 40 includes one support member 54 fixed to the first side surface 43 and two support members 54 fixed to the second side surface 44. Although not shown, the case 40 may include one or two support members 54, or may include four or more support members 54. The support member 54 may be fixed to the third side surface 45 or the fourth side surface 46.

The support member 54 may include a first portion 541 fixed to the side surface, and a second portion 542 connected to the first portion 541. The first portion 541 may extend from the side surface toward the first surface 41. The second portion 542 may include a surface extending parallel to the first surface 41. The second portion 542 may contact the object 10 during the inspection process. This allows the position of the case 40 to be more stably maintained during the inspection process. This makes it possible to suppress noise caused by hand movement, etc. from appearing in the target spectrum.

As shown in FIG. 14, the case 40 may include a second friction layer 55 provided on the second portion 542. The second friction layer 55 includes, for example, rubber. The second friction layer 55 may contact the object 10 during the inspection process. The static friction force between the second friction layer 55 and the object 10 is greater than the static friction force between the first surface 41 and the object 10. By providing the second friction layer 55 on the second portion 542, movement of the case 40 during the inspection process can be further suppressed.

Fifth embodiment
In the above embodiment, an example has been shown in which the composition of the resin layer 12 is determined based on the recorded target spectrum S1. However, the use of the target spectrum is not particularly limited, and the target spectrum may be used for various purposes. For example, the molecular weight of the resin layer 12 may be calculated based on the recorded target spectrum S1.

For example, the first processing step may include a step of further performing some processing on the target spectrum recorded by the first recording. For example, in the first processing step, processing including averaging, smoothing, normalization, differentiation, scattering correction, baseline correction, peak shift correction, or a combination thereof may be performed on the recorded target spectrum. This allows multiple parameter values corresponding to multiple wavelength points to be calculated. In this case, the determination step may calculate the molecular weight of the material constituting the resin layer 12 based on the calculated parameter values. The determination step may also determine the state of the resin material based on the calculated molecular weight. Details of these processes and determinations are described, for example, in JP 2019-86499 A.

Sixth embodiment
In the above-described embodiment, an example has been described in which the detection device 24 detects the intensity of light reflected by the object 10. However, this is not limiting, and although not shown, the detection device 24 may detect the intensity of light transmitted through the object 10. In this case, the inspection system 15 generates an object spectrum including information on the intensity of light transmitted through the object 10. By performing the first processing step described above, the inspection system 15 can eliminate an object spectrum that includes a lot of noise caused by hand movement or the like.

The detection device 24 may detect the intensity of light transmitted through the calibration sample 51. In this case, the inspection system 15 generates a calibration spectrum that includes information about the intensity of light transmitted through the calibration sample 51. The inspection system 15 can eliminate the calibration spectrum that contains a lot of noise by performing the second processing step described above.

Next, the present invention will be described in more detail with reference to examples. However, the present invention is not limited to the description of the following examples as long as it does not deviate from the gist of the invention.

Example 1
Using the above-mentioned inspection system 15, the calibration spectrum of the first calibration sample 51 was measured. Spectralon manufactured by Labsphere was used as the first calibration sample 51. A near-infrared spectroscopy built-in reflection module M-R2 manufactured by innoSpectra was used as the spectroscopic module 20 equipped with the irradiation device 21 and the detection device 24. The calibration process was carried out in a state where the calibration sample 51 was fixed to the case 40 by a rubber band 52 as shown in FIG.

The detector 24 detects the intensity of the light at each wavelength point by decomposing the light into components corresponding to each wavelength point. The detector 24 scans each wavelength point in turn. The conditions for the detection process are as follows:
・Wavelength range: 900nm to 1700nm
・Resolution: 3.5nm
Exposure time: 1.27 ms
Number of integrations: 19 The number of integrations is the number of times each wavelength point is scanned in sequence from the lower limit to the upper limit of the wavelength range. When the number of integrations is 19, the detector 24 has 19 detection values at each wavelength point. The detector 24 outputs the average value of the 19 detection values as the light intensity at each wavelength point.

Figure 15 shows the measurement results of the calibrated spectrum. The second noise index of the calibrated spectrum shown in Figure 15 was 38752. The second threshold TH2 was 25000. Therefore, it can be said that the calibrated spectrum shown in Figure 15 contains little noise. In the following description, the calibrated spectrum shown in Figure 15 is also referred to as spectrum 11.

Next, three more calibration spectra were measured with the measurement position of the first calibration sample 51 changed. The three calibration spectra are also referred to as spectrum 12, spectrum 13, and spectrum 14. The measurement position when spectrum 12 was measured was 2 mm away from the measurement position when spectrum 11 was measured. The measurement position when spectrum 13 was measured was 2 mm away from the measurement position when spectrum 12 was measured. The measurement position when spectrum 14 was measured was 2 mm away from the measurement position when spectrum 13 was measured. Spectra 11 to spectrum 14 are shown in Figure 16. The second noise indices of spectra 12, 13, and 14 were 38793, 35463, and 36466.

It can be said that the noise contained in spectra 11 to 14 is small. An averaged calibration spectrum may be generated by averaging spectra 11 to 14.

Example 2
The calibration spectrum of the second calibration sample 51, which is different from the first calibration sample 51, was measured using the above-described inspection system 15. The measurement conditions were the same as those in the first embodiment.

Figure 17 shows the measurement results of the calibration spectrum. The second noise index of the calibration spectrum shown in Figure 17 was 16724. Therefore, it can be said that the calibration spectrum shown in Figure 17 contains a large amount of noise. In the following description, the calibration spectrum shown in Figure 17 is also referred to as spectrum 21.

Next, three more calibration spectra were measured with the measurement position of the second calibration sample 51 changed. The three calibration spectra are also referred to as spectrum 22, spectrum 23, and spectrum 24. The measurement position when spectrum 22 was measured was 2 mm away from the measurement position when spectrum 21 was measured. The measurement position when spectrum 23 was measured was 2 mm away from the measurement position when spectrum 22 was measured. The measurement position when spectrum 24 was measured was 2 mm away from the measurement position when spectrum 23 was measured. Spectra 21 to spectrum 24 are shown in Figure 18. The second noise indices of spectra 22, 23, and 24 were 9198, 13066, and 17022, respectively.

Example 3
The object spectrum of the first object 10 was measured using the above-described inspection system 15. The first object 10 has a resin layer 12 containing polyethylene. The first object 10 is attached to a wall. The measurement was performed with the inspection system 15 in contact with the object 10 while being held by a human hand. The conditions of the detection process were the same as those in Example 1. The measurement result of the object spectrum is shown in FIG. 19.

Next, a locally averaged spectrum was generated by locally averaging the target spectrum. The locally averaged spectrum is shown in Figure 19. Next, a difference spectrum was generated based on the difference between the target spectrum and the locally averaged spectrum. The difference spectrum is shown in Figure 19. In Figure 19, as in Figure 9, the target spectrum is represented by a dashed dotted line, the averaged spectrum is represented by a solid line, and the difference spectrum is represented by a solid line.

Next, the standard deviation was calculated based on the value of the difference spectrum in the wavelength range of 970 nm to 1100 nm. Next, the first noise index was calculated based on the standard deviation. The first noise index was 4905. The first threshold TH1 was 2500. Therefore, it can be said that the target spectrum shown in FIG. 19 contains little noise.

(Examples 4 to 8)
Using the above-described inspection system 15, object spectra of the second object 10 to the sixth object 10, which are different from the first object 10, were measured. The second object 10 to the sixth object 10 have a resin layer 12 containing polyethylene, similar to the case of Example 3. The measurement conditions are the same as those of Example 3. The measurement results of the object spectra of the second object 10 to the sixth object 10 are shown in Figs. 20 to 24, respectively.

Next, a locally averaged spectrum was generated by locally averaging the target spectrum. The locally averaged spectra of the second to sixth objects 10 are shown in Figures 20 to 24, respectively. Next, a difference spectrum was generated based on the difference between the target spectrum and the locally averaged spectrum. The difference spectra of the second to sixth objects 10 are shown in Figures 20 to 24, respectively.

Next, the standard deviation was calculated based on the difference spectrum values in the wavelength range of 970 nm to 1100 nm. Next, the first noise index was calculated based on the standard deviation. The first noise indexes for the second object 10 to the sixth object 10 were 11188, 7405, 2375, 1641, and 1136, respectively.

(Example 9)
The effect of the exposure time of the detection device 24 on the noise index was verified. Specifically, the object 10 was measured using the first inspection system 15 (machine No. 1) under a plurality of exposure time conditions, and the first noise index was calculated. In addition, the object 10 was measured using the second inspection system 15 (machine No. 2) and the third inspection system 15 (machine No. 3) under a plurality of exposure time conditions, and the first noise index was calculated. The results are shown in Table 1. In Table 1, the column "total measurement time" means the time required for a series of processes from when the irradiation device 21 starts irradiating light to when the computer completes the calculation of the noise index. In the column "device state", "stationary" means that the measurement was performed in a state where the human hand was not touching the inspection system 15. "Handheld" means that the measurement was performed in a state where the human hand was holding the inspection system 15. As shown in Table 1, the noise index when the exposure time was 1.27 ms was larger than the noise index when the exposure time was 0.635 ms. There was no significant difference between the noise index when the exposure time was 1.27 ms and the noise index when the exposure time was 2.54 ms. Therefore, in consideration of efficient measurement in a short time, it can be said that the exposure time is preferably 1.27 ms or its vicinity. For example, the exposure time is preferably 1.0 ms or more and 2.0 ms or less.

(Example 10)
The effect of the number of integration times of the detection device 24 on the noise index was verified. Specifically, under conditions of a plurality of integration times, the object 10 was measured using the second inspection system 15 (machine No. 2) and the third inspection system 15 (machine No. 3), and the first noise index was calculated. The results are shown in Table 2. As shown in Table 2, the noise index when the exposure time was 19 times was larger than the noise index when the exposure time was 10 times. Therefore, it can be said that the number of integration times is preferably 19 or thereabouts. The number of integration times is, for example, 12 times or more, may be 15 times or more, or may be 19 times or more.

10 Object 10x First surface 10y Second surface 11 Base sheet 12 Resin layer 15 Inspection system 20 Spectroscopic module 21 Irradiation device 211 Irradiation section 24 Detection device 241 Detection section 25 Generation device 251 First generation section 252 Second generation section 27 Processing device 271 First processing section 272 Second processing section 28 Determination device 281 Memory section 282 Analysis section 283 Determination section 40 Case 41 First surface 42 Second surface 48 Window 51 Calibration sample 53 First friction layer 54 Support member 541 First portion 542 Second portion 55 Second friction layer

Claims (15)

1. A testing method comprising:
A first irradiation step of irradiating an object with light;
a first detection step of detecting an intensity of light reflected by the object or transmitted through the object;
A first generation step of generating a target spectrum including information about the intensities at a plurality of wavelength points;
a first processing step for processing the target spectrum;
a second irradiation step of irradiating the calibration sample with light;
a second detection step of detecting an intensity of light reflected by the calibration sample or light transmitted through the calibration sample;
a second generation step of generating a calibration spectrum comprising information about the intensities at a plurality of wavelength points;
a second processing step of processing the calibration spectrum,
The first processing step includes:
a local averaging step of locally averaging the target spectrum to generate a locally averaged spectrum;
a first noise evaluation step of calculating a first noise index based on a difference between the target spectrum and the locally averaged spectrum;
a first recording step of recording the target spectrum when the first noise index is equal to or greater than a first threshold,
The second processing step includes:
a second differentiation step of generating a second derivative spectrum by second-deriving the calibration spectrum;
a second noise evaluation step of calculating a second noise index based on the second derivative spectrum;
a second recording step of recording the calibration spectrum when the second noise index is equal to or greater than a second threshold;
An inspection method, wherein the first generating step generates the target spectrum by using the calibration spectrum as a reference. The inspection method according to claim 1, wherein the first noise evaluation step includes a step of calculating a standard deviation of the differences, and a step of calculating the first noise index based on the standard deviation. The inspection method according to claim 1 or 2, wherein, if the first noise index is less than the first threshold, the first irradiation step, the first detection step, the first generation step, and the first processing step are performed again. The local averaging step includes a step of calculating a local average value at each wavelength point of the target spectrum,
4. The inspection method according to claim 1, wherein the local average value is calculated by averaging a value of the target spectrum at a wavelength point of interest and values of the target spectrum at 5 to 15 wavelength points located in the vicinity of the wavelength point of interest. 5. The inspection method according to claim 1, wherein the second noise evaluation step includes the steps of: calculating a standard deviation of the second derivative spectrum; and calculating the second noise index based on the standard deviation. The inspection method according to claim 1 , further comprising the steps of: performing the second irradiation step, the second detection step, the second generation step, and the second processing step again when the second noise index is less than the second threshold value. performing the second irradiation step, the second detection step, the second generation step, and the second processing step a plurality of times to record a plurality of calibration spectra having the second noise index equal to or greater than the second threshold;
The inspection method according to claim 1 , wherein the first generation step generates the target spectrum by using an average of a plurality of the calibration spectra as a reference. 1. An inspection system comprising:
An illumination device that illuminates an object with light;
a detection device for detecting an intensity of light reflected by or transmitted through the object;
A generating device including a first generating unit that generates a target spectrum including information about the intensities at a plurality of wavelength points, and a second generating unit that generates a calibration spectrum including information about the intensities of light reflected by a calibration sample or light transmitted through the calibration sample at a plurality of wavelength points;
a processing device including a first processing unit that processes the target spectrum and a second processing unit that processes the calibration spectrum;
The first processing unit is
local averaging, locally averaging the target spectrum to generate a locally averaged spectrum;
a first noise evaluation for calculating a first noise index based on a difference between the target spectrum and the locally averaged spectrum;
performing a first recording of the target spectrum if the first noise index is equal to or greater than a first threshold;
The second processing unit is
a second derivative of the calibration spectrum to generate a second derivative spectrum;
a second noise evaluation for calculating a second noise index based on the second derivative spectrum;
a second recording, recording the calibration spectrum if the second noise index is greater than or equal to a second threshold;
The first generation unit generates the target spectrum by using the calibration spectrum as a reference. The inspection system according to claim 8 , wherein the first processing unit calculates a standard deviation of the differences, and calculates the first noise index based on the standard deviation. The first processing unit calculates a local average value at each wavelength point of the target spectrum,
10. The inspection system of claim 8 or 9, wherein the local average value is calculated by averaging a value of the target spectrum at a wavelength point of interest and values of the target spectrum at 5 to 15 wavelength points located in the vicinity of the wavelength point of interest. The inspection system according to claim 8 , wherein the second processing unit calculates a standard deviation of the second derivative spectrum, and calculates the second noise index based on the standard deviation. a case for accommodating the irradiation device and the detection device;
12. The inspection system according to claim 8, wherein the case has a first surface including a window through which the light passes, a second surface opposite the first surface, and a side surface located between the first surface and the second surface. The inspection system of claim 12 , wherein the case comprises a first friction layer disposed on the first surface or an outer edge. The inspection system according to claim 12 or 13, wherein the case comprises a support member including a first portion fixed to the side surface and a second portion connected to the first portion and parallel to the first surface. The inspection system of claim 14 , wherein the case includes a second friction layer disposed on the second portion.