JP5812441B2 - Printer, printer abnormality detection device, and abnormality detection method thereof - Google Patents

Description

  The present invention relates to a printer, a printer abnormality detection device, and an abnormality detection method thereof. In particular, the present invention relates to an abnormality detection technique for detecting occurrence of a printer failure and identifying a suspicious part to be repaired or replaced.

  When a printer error such as print stains or white spots occurs in the printer, the maintenance staff of the printer receives a report of the print error, goes to the site where the printer is installed, performs fault diagnosis, and Identify and arrange suspected parts that are presumed to be. After the parts arrive, the printer maintenance staff goes to the site again to replace the parts.

  On the other hand, a technique for checking the state of a printer by taking a printed matter printed by a printer and comparing it with original data is widely known. For example, Patent Document 1 discloses a form printing system that determines whether a print state of a form printed by a printer is good or bad. In the form printing system, pixel data of a print area of form data is stored in a storage unit together with position information of the print area. The image scanner reads the form printed by the printer based on the form data as print result image data. Subsequently, the print result image data is compared with the pixel data of the print area stored in the storage unit. Based on the comparison result, it is determined whether or not the form printed on the printer is normal.

JP 2011-60123 A

  The following analysis is given from the perspective of the present invention.

  The form printing system described in Patent Document 1 can inspect a printed form by determining whether or not the form printed on the printer is normal. However, in the form printing system, no consideration is given to specifying the suspected part when an abnormality is detected in the printing result. For this reason, in order to restore the printer to the normal state, as described above, it is necessary for the maintenance staff of the printer to perform two operations of failure diagnosis and replacement of the suspicious part, which takes time. . Thus, when a printing abnormality is detected by the printer, it is expected to realize a printer abnormality detecting device that can identify a suspected part that is estimated to be the cause of the printing abnormality.

  An object of the present invention is to provide a printer abnormality detection device that can contribute to specifying a suspected part that causes a printing abnormality when a printing abnormality is detected by the printer.

A printer abnormality detection apparatus according to a first aspect of the present invention is a printer abnormality detection apparatus that is mounted on a printer that prints input print data and detects abnormality of the printer, and includes the following components. That is, the printer abnormality detection device includes a pixel data reproducing unit that generates pixel data from the print data. Further, the abnormality detection device of the printer includes a reading unit that reads a printed matter printed by the printer with an image sensor and generates read data. The printer abnormality detection device includes an image comparison unit that compares the pixel data and the read data at positions corresponding to each other and outputs an error. Further, the printer abnormality detection apparatus may previously detect an error that may occur between the pixel data and the read data , and a plurality of error patterns associated with the printing direction horizontal arrangement and / or the printing direction vertical arrangement. And a database in which information on the suspected part corresponding to each of the classified error patterns is stored. Here, when the error output by the image comparison unit is not within a predetermined range, it is determined that the printer is in an abnormal state, and the plurality of errors are classified by the database with reference to the database. The suspected part that is presumed to be the cause of the error is identified by determining which one of the patterns corresponds , the database is set according to the type of printer, and the image comparison unit The error is calculated based on the black pixel ratio .

The printer according to the second aspect of the present invention includes the following components. That is, the printer includes a printing unit that prints input print data. In addition, the printer includes a pixel data reproducing unit that generates pixel data from the print data. In addition, the printer includes a reading unit that reads a printed matter printed by the printing unit with an image sensor and generates read data. In addition, the printer includes an image comparison unit that compares the pixel data and the read data at positions corresponding to each other and outputs an error. Further, the printer classifies in advance an error that may occur between the pixel data and the read data into a plurality of error patterns associated with a printing direction horizontal arrangement and / or a printing direction vertical arrangement , It includes a database in which information on suspected parts corresponding to the classified error patterns is stored. Here, when the error output by the image comparison unit is not within a predetermined range, it is determined that the printer is in an abnormal state, and the plurality of errors are classified by the database with reference to the database. The suspected parts that are presumed to be the cause of the error are identified by determining which of the patterns corresponds , the database is set according to the type of printer, and the image comparison unit The error is calculated based on the black pixel ratio .

A printer abnormality detection method according to a third aspect of the present invention is a printer abnormality detection method for detecting abnormality of a printer that prints input print data, and includes the following steps. That is, the printer abnormality detection method includes a pixel data reproduction step of generating pixel data from the print data. The abnormality detection method of the printer includes a reading step of reading a printed matter printed by the printer with an image sensor and generating read data. The printer abnormality detection method includes an image comparison step of comparing the pixel data and the read data at positions corresponding to each other and outputting an error. In addition, the abnormality detection method of the printer may include an error that may occur between the pixel data and the read data in advance in a plurality of errors that are associated with the print direction horizontal array and / or the print direction vertical array . The method includes a step of preparing a database in which information on a suspicious part corresponding to each of the classified error patterns is stored. The abnormality detection method for the printer includes a step of determining that the printer is in an abnormal state when the error in the image comparison step is not within a predetermined range. Further, the abnormality detection method of the printer refers to the database to determine which of the plurality of error patterns classified in the database corresponds to the error in the image comparison step. Identifying a suspected part that is presumed to be the cause of the problem. The abnormality detection method for the printer includes a step of setting the database according to the type of printer. Further, the printer abnormality detection method includes a step of calculating the error based on a black pixel ratio.

A program according to a fourth aspect of the present invention is a program that causes a computer to detect abnormality of a printer that prints input print data, and causes the computer to execute the following processing. That is, the program compares the pixel data generated from the print data with the read data obtained by reading the printed matter printed by the printer with an image sensor at positions corresponding to each other, and calculates the error in the computer. Let it run. Further, the program causes the computer to execute processing for determining that the printer is in an abnormal state when the error is not within a predetermined range. Further, the program classifies in advance errors that may occur between the pixel data and the read data into a plurality of error patterns associated with the printing direction horizontal arrangement and / or the printing direction vertical arrangement. Referring to a database storing information of suspected parts corresponding to each classified error pattern, it is determined which of the plurality of error patterns classified in the database corresponds to the error. As a result, the computer is caused to execute a process of identifying the suspected part that is estimated to be the cause of the error. Further, the program causes the computer to execute processing for setting the database according to the type of printer. Further, the program causes the computer to execute processing for calculating the error based on the black pixel ratio.

  ADVANTAGE OF THE INVENTION According to this invention, when a printing abnormality is detected with a printer, the abnormality detection apparatus of the printer which can contribute to pinpointing the suspicious part which becomes the cause of this printing abnormality can be provided.

1 is a block diagram illustrating a configuration of a printer abnormality detection device according to a first embodiment. FIG. FIG. 2 is a diagram illustrating a detailed configuration of a printing unit of the printer of FIG. 1 and a reading unit of a printer abnormality detection device. It is a figure which shows the structure of the database in 1st Embodiment. It is an example of the positional information on the database in 1st Embodiment. It is an example of the division area position information acquired from the database in 1st Embodiment. It is an example of the threshold value information of the database in 1st Embodiment. It is an example of the error information of the database in 1st Embodiment. 4 is a flowchart illustrating an operation of the printer abnormality detection device according to the first embodiment. 4 is a flowchart illustrating an operation of the printer abnormality detection device according to the first embodiment.

  First, an outline of an embodiment of the present invention will be described. Note that the reference numerals of the drawings added in the description of the outline of the embodiment are merely examples for helping understanding, and are not intended to be limited to the illustrated modes.

  As shown in FIG. 1, a printer abnormality detection device 2 according to an embodiment is a printer abnormality detection device that is mounted on a printer 1 that prints input print data C <b> 1 and detects abnormality of the printer 1. Of components. That is, the printer abnormality detection device 2 includes a pixel data reproduction unit 20 that generates pixel data C5 from the print data C1. In addition, the printer abnormality detection device 2 includes a reading unit 12 that reads a printed matter C2 printed by the printer 1 with the image sensor 11 and generates read data C3. The printer abnormality detection device 2 includes an image comparison unit 26 that compares the pixel data C5 and the read data C3 at positions corresponding to each other and outputs an error C7. Further, the printer abnormality detection device 2 classifies the errors that may occur between the pixel data C5 and the read data C3 in advance into a plurality of error patterns (for example, eight phenomena shown in FIG. 7). A database 3 in which information on suspected parts corresponding to each error pattern (included in error information 8 in FIG. 7) is stored. Here, when the error C7 output by the image comparison unit 26 is not within the predetermined range (for example, in the case of ε <−5, ε> +5 in FIG. 6), it is determined that the printer 1 is in an abnormal state, and the database 3 By determining which of the plurality of error patterns classified in the database 3 corresponds to the error C7, the suspected part C9 estimated to be the cause of the error C7 is specified.

  According to the above configuration, an error that may occur between the pixel data C5 and the read data C3 is classified into a plurality of error patterns, and information on a suspected part corresponding to each classified error pattern is stored. When the database 3 is prepared and a printing abnormality is detected by the printer 1, the error C7 between the pixel data C5 and the read data C3 corresponds to any of the error patterns in the database 3 with reference to the database 3. By determining whether or not to perform, it is possible to identify the suspected part that is estimated to be the cause of the printing abnormality.

  As shown in FIG. 1, the printer abnormality detection device 2 sets divided region position information 36 indicating the positions of a plurality of divided regions, and based on the divided region position information 36, pixels for each of the plurality of divided regions. A pixel data feature amount calculation unit 22 that calculates a feature amount C6 of data, a read data feature amount calculation unit 14 that calculates a feature amount C4 of read data for each of the plurality of divided regions, based on the divided region position information 36; The image comparison unit 26 may output a difference between the feature amount C6 of the pixel data and the feature amount C4 of the read data as an error C7 for each of the plurality of divided regions.

  The divided region position information 36 is preferably set according to the paper size to be printed.

  The feature amount C4 of the read data and the feature amount C6 of the pixel data may be the black pixel ratio.

  The reading unit 12 may read the printed material C2 with multiple gradations, perform binarization using black data below a predetermined threshold value, and obtain the read data C3.

  The database 3 is preferably set according to the type of printer (laser printer, inkjet printer, dot impact printer, thermal transfer printer, etc.).

  The printer according to the embodiment is a printer in which the printing unit 10 of the printer and the printer abnormality detection device 2 illustrated in FIG. 1 are integrated, and includes the following components. That is, the printer includes a printing unit 10 that prints the input print data C1. The printer also includes a pixel data reproducing unit 20 that generates pixel data C5 from the print data C1. The printer also includes a reading unit 12 that reads the printed matter C2 printed by the printing unit 10 with the image sensor 11 and generates read data C3. The printer also includes an image comparison unit 26 that compares pixel data C5 and read data C3 at positions corresponding to each other and outputs an error C7. Further, the printer classifies in advance errors that may occur between the pixel data C5 and the read data C3 into a plurality of error patterns (for example, eight phenomena shown in FIG. 7), and the classified error patterns. It includes a database 3 that stores information on suspected parts corresponding to each (included in error information 8 of FIG. 7). Here, when the error C7 output from the image comparison unit 26 is not within the predetermined range (for example, in the case of ε <−5, ε> +5 in FIG. 6), it is determined that the printer is in an abnormal state, and the database 3 is stored. The suspected part C9 estimated to be the cause of the error 7 is specified by determining which of the plurality of error patterns classified in the database 3 corresponds to the error C7.

  The printer abnormality detection method according to the embodiment is a printer abnormality detection method for detecting abnormality of the printer 1 that prints the input print data C1, as shown in either FIG. 1 or FIG. Includes steps. That is, in the printer abnormality detection method, the pixel data reproduction step (S10) for generating pixel data C5 from the print data C1, and the printed product C2 printed by the printer 1 is read by the image sensor 11 to generate read data C3. This may occur between the reading step (S17), the image comparison step (S23) that compares the pixel data C5 and the reading data C3 at positions corresponding to each other, and outputs an error C7, and the pixel data C5 and the reading data C3 in advance. Is classified into a plurality of error patterns (for example, eight phenomena shown in FIG. 7), and information on a suspicious part corresponding to each classified error pattern (included in error information 8 in FIG. 7). If the error C7 due to the step of preparing the database 3 storing the image and the image comparison step is not within a predetermined range (for example, In FIG. 6, in the case of ε <−5, ε> +5), the database 3 has the error C7 in the image comparison step with reference to the database 3 in the step of determining that the printer is in an abnormal state (S24, S26). Determining which of the plurality of classified error patterns corresponds to a suspected part that is presumed to be the cause of the error (S27, S28).

  Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings.

[First Embodiment]
(Configuration of the first embodiment)
The first embodiment will be described in detail with reference to FIGS. FIG. 1 is a block diagram showing a configuration of a printer abnormality detection device 2 according to the first embodiment. As shown in FIG. 1, a printer abnormality detection device 2 is a device that is attached to the printer 1 to detect abnormality of the printer 1. The printer 1 includes a printing unit 10 that prints input print data C1.

  FIG. 2 is a diagram showing a detailed configuration of the printing unit 10 of the printer 1 of FIG. 1 and the reading unit 12 of the printer abnormality detection device 2. As shown in FIG. 2, the printer 1 is an electrophotographic laser printer, and the printing unit 10 includes an optical unit (ROS) 32, a developing unit (customer replaceable unit CRU; Customer Replace Unit) 33, The fixing unit 34 is configured. In FIG. 2, the printing unit 10 feeds a paper 31 having a designated paper size C0 and transports the paper 31 to the printing process. In the printing process, the optical unit (ROS) 32 irradiates a laser to form an electrostatic latent image on the drum surface, the developing unit (CRU) 33 charges and develops the drum, and the fixing unit 34 The completed toner image transferred onto the paper 31 is fixed to the paper 31 with heat and pressure, and the printed product C2 is output to the discharge side.

  As shown in FIG. 2, the reading unit 12 of the printer abnormality detection device 2 is arranged after the fixing unit 34, and the image sensor 11 provided in the reading unit 12 reads the printed material C <b> 2. Here, a line CCD sensor is suitable as the image sensor 11, and the printed material C2 conveyed to the discharge side is read, and read data C3 is output.

  Next, returning to FIG. 1, the configuration of the printer abnormality detection device 2 will be described. As shown in FIG. 1, the printer abnormality detection device 2 includes a reading unit 12, a read data feature amount calculation unit 14, a read data feature amount recording unit 16, a pixel data reproduction unit 20, a pixel data feature amount calculation unit 22, and a pixel. The data feature amount recording unit 24, the image comparison unit 26, the error pattern determination unit 28, the error display unit 30, and the database 3 are configured.

  Here, among the components of the abnormality detection device 2 of the printer, the read data feature amount calculation unit 14, the read data feature amount recording unit 16, the pixel data reproduction unit 20, the pixel data feature amount calculation unit 22, and the pixel data feature amount recording The unit 24, the image comparison unit 26, and the error pattern determination unit 28 are units obtained by dividing the printer abnormality detection device 2 into functional units. Each unit is implemented by a program and is executed by a CPU provided in the printer abnormality detection device 2. It is processed. Alternatively, a part or all of each unit may be implemented by hardware using an LSI (Large Scale Integrated circuit) or the like and processed by the hardware.

  The pixel data reproduction unit 20 receives the print data C1 input to the printer 1 and generates pixel data C5 corresponding to the print data C1. Here, the pixel data C5 is a bitmap image obtained by rasterizing the print data C1 with a predetermined resolution (dpi; dots per inch). As the font data used for rasterization, since pixel data C5 and read data C3 of the printed material C2 are compared as described later, it is preferable to use font data similar to that used in the printer 1.

  On the other hand, as described above, the printed matter C2 is read by the image sensor 11 of the reading unit 12 to obtain read data C3. Here, it is desirable that the resolution (dpi) by the reading unit 12 matches the resolution (dpi) of the pixel data reproducing unit 20. However, even if there is a difference between the two resolutions (dpi), conversion can be performed as described later. The image sensor 11 reads the printed material C2 with multiple gradations (256 gradations, etc.). The reading unit 12 performs binarization processing on the multi-gradation data using black data below a predetermined threshold and white data other than the predetermined threshold value as read data C3. Here, it is preferable that the predetermined threshold value is set so that 0 and 1 are interchanged at an intermediate density between white and black.

  The printer abnormality detection device 2 basically detects a printing abnormality by comparing the read data C3 and the pixel data C5 at corresponding positions. However, instead of comparing in units of pixels with the above-mentioned resolution, as will be described later, by comparing in units of divided areas divided into a plurality of parts, the amount of calculation is reduced and processing is speeded up and stable. Anomaly detection is enabled.

  Next, the database 3 will be described in detail. FIG. 3 is a diagram showing the configuration of the database in the first embodiment. As shown in FIG. 3, the database 3 includes position information 6, threshold information 7, and error information 8. FIG. 4 is an example of the position information 6 of the database 3 in the first embodiment. As shown in FIG. 4, for each paper size C0, the position information 6 includes "dimension (vertical x horizontal)" information (unit: mm), "comparison area (vertical x horizontal)" information (unit: mm), "Upper (margin)" information (unit: mm), "Lower (margin)" information (unit: mm), "Left (margin)" information (unit: mm), "Right (margin)" information (Unit: mm), “vertical (number of positions)”, “horizontal (number of positions)” are included.

  The information on the paper size C0 indicates the paper supported by the printer 1, and is represented by “A5 portrait”, “A5 landscape”, “A4 portrait”, “A4 landscape”, and the like. “Dimension (vertical × horizontal)” is a dimension of each paper size C0. “Comparison region (vertical × horizontal)” indicates a region in the “dimension (vertical × horizontal)” where the read data C3 and the pixel data C5 are compared. The four margin data “top (margin)”, “bottom (margin)”, “left (margin)”, and “right (margin)” are “dimensions (vertical x horizontal)” of the “comparison area (vertical x horizontal)”. Left and right, left and right margins (unit: mm).

  “Vertical (number of positions)” and “Horizontal (number of positions)” respectively indicate the number in the vertical direction and the number in the horizontal direction when the “comparison area (vertical × horizontal)” is divided into a plurality of divided areas. . One divided area is 10 × 10 mm. FIG. 5 is an example of the divided region position information 36 acquired from the database 3 in the first embodiment. FIG. 5 shows the divided region position information 36 acquired when the paper size C0 of “A5 portrait” is designated for the position information 6 of the database 3. The divided area position information 36 outputs the positions of 280 divided areas divided into 20 in the vertical direction and 14 in the horizontal direction. Specifically, for example, the position of the divided region represented by AF-6 in FIG. 5 is represented by the diagonal vertex coordinates (x1, y1), (x2, y2) (unit: mm). In this way, data representing the position of each divided area is output as the divided area position information 36.

  Returning to FIG. 1, the pixel data feature amount calculation unit 22 and the read data feature amount calculation unit 14 will be described. The pixel data feature value calculation unit 22 and the read data feature value calculation unit 14 receive the divided region position information 36 output from the database 3 in accordance with the paper size C0. The pixel data feature amount calculation unit 22 obtains pixel data divided region position information obtained by converting the input divided region position information 36 into pixel unit position data on the pixel data C5. Similarly, the read data feature amount calculation unit 14 obtains read data divided region position information obtained by converting the input divided region position information 36 into pixel unit position data on the read data C3.

  In order to perform the above conversion with high accuracy, a test image including alignment marks at four corners is prepared as the print data C1, and the positions of the pixel data C5 and the read data C3 are matched with each other by the alignment marks. What is necessary is just to correct | amend position information. Further, by performing such correction, the difference between the resolution (dpi) of the pixel data C5 and the resolution (dpi) of the read data C3 is also corrected. Become. In the following description, it is assumed that the pixel data divided region position information and the read data divided region position information are converted into position data in units of pixels corresponding to each other position by performing correction using the alignment mark.

  Next, the pixel data feature amount calculation unit 22 calculates the black pixel ratio C6 in each divided region based on the pixel data divided region position information. Here, the black pixel ratio is a ratio of the number of pixels which are black data among pixels (pixels) included in the divided region. Then, the pixel data feature amount recording unit 24 temporarily stores the black pixel ratio C6 of each divided region calculated by the pixel data feature amount calculation unit 22 in a memory (not shown).

  Similarly, the read data feature amount calculation unit 14 calculates the black pixel ratio C4 in each divided region based on the read data divided region position information. Then, the read data feature amount recording unit 16 temporarily stores the black pixel ratio C4 of each divided area calculated by the read data feature amount calculation unit 14 in a memory (not shown).

  Subsequently, the image comparison unit 26 determines the black pixel ratio C4 of each divided region stored in the read data feature amount recording unit 16 and the black pixel ratio C6 of each divided region stored in the pixel data feature amount recording unit 24. Are read out and compared to calculate an error C7. Here, the error C7 has information on the error in each divided region defined by the divided region position information 36.

Next, the threshold information 7 of the database 3 will be described with reference to FIG. FIG. 6 is an example of the threshold information 7 of the database 3 in the first embodiment. An error of the black pixel ratio C4 with respect to the black pixel ratio C6 is evaluated by an error ε represented by Expression (1).

ε = 100 × (C4-C6) / C6 [%] Formula (1)

As shown in FIG. 6, if the error ε calculated by the equation (1) is within the range of −5 ≦ ε ≦ + 5, the printer 1 is determined to be in a normal state, and otherwise, the printer 1 Is determined to be in an abnormal state. More specifically, when ε <−5, it is determined that the printed material C2 by the printer 1 is thin, and when ε> +5, it is determined that the printed material C2 is dark. Here, the thresholds −5 and +5 that define the range of the normal state can be adjusted as appropriate. In the first embodiment, if even one of the divided areas does not have an error ε within a predetermined range (−5 ≦ ε ≦ + 5), an abnormal state is assumed. However, the present invention is not limited to this. For example, when the number of divided regions where the error ε does not fall within a predetermined range exceeds a threshold value, an abnormal state may be set. Deformation is possible.

  Next, the error information 8 in the database 3 will be described with reference to FIG. FIG. 7 is an example of the error information 8 of the database 3 in the first embodiment. The error information 8 in FIG. 7 classifies the error C7 patterns that may occur as patterns of the error C7 (difference between the black pixel ratio C4 of the read data and the black pixel ratio C6 of the pixel data). In FIG. 7, there are eight classifications. The second column (“phenomenon” column) in FIG. 7 shows each abnormal state as an image when the print data C1 is “A”.

  The error information 8 of the database 3 stores error pattern data (not shown) for each abnormal state. Further, as shown in FIG. 7, the error information 8 of the database 3 is assigned error codes ALM-01 to ALM-08 corresponding to each abnormal state. Further, as shown in FIG. 7, in the error information 8 of the database 3, information on a suspected part that causes an abnormal state is registered for each abnormal state.

  In FIG. 7, in the case of error code ALM-01, the printed matter C2 is in an abnormal state of “all white” (a state where nothing is printed on the paper), and the suspected parts are the photosensitive drum and ROS. In the case of the error code ALM-02, the printed material C2 is in an abnormal state of “all black (solid black)”, and the suspected component is ROS, HVPS (High Voltage Power Supply; high voltage power supply unit). In the case of the error code ALM-03, in the abnormal state of “printing direction vertical white stripe” (that is, the error position is the vertical arrangement in the printing direction and the black pixel ratio C4 is low), the suspected parts are the photosensitive drum and ROS. In the case of the error code ALM-04, in the abnormal state of “printing direction horizontal streak” (that is, the error position is the horizontal arrangement in the printing direction and the black pixel ratio C4 is low), the suspected parts are the photosensitive drum, ROS, and transfer roller. It is. In the case of the error code ALM-05, in the abnormal state of “printing direction vertical streaks” (that is, the error position is the vertical arrangement in the printing direction and the black pixel ratio C4 is high), the suspected parts are the fixing device and the photosensitive drum. . In the case of error code ALM-06, in the abnormal state of “printing direction horizontal streaks” (that is, the error position is in the printing direction horizontal arrangement and the black pixel ratio C4 is high), the suspected parts are the fixing device, photosensitive drum, transfer Laura. In the case of error code ALM-07, in the abnormal state of “random dirt” (that is, there is no regular arrangement at the error position and the black pixel ratio C4 is high), the suspected parts are a fixing device, a photosensitive drum, a transfer roller, and a conveyance roller. It is. In the case of the error code ALM-08, the suspected part is a photosensitive drum or ROS in an abnormal state of “light” (that is, the density is light as a whole).

  Next, returning to FIG. 1, the error pattern determination unit 28 will be described. The error pattern determination unit 28 refers to the error information 8 in the database 3 and determines which of the eight error patterns in the error information 8 corresponds to the error C7 of each divided region output from the image comparison unit 26. judge. A specific algorithm for the determination will be described later with reference to the flowchart of FIG.

  Then, the error pattern determination unit 28 outputs an error code C8 corresponding to the determined error pattern and the suspected component C9. Subsequently, the error display unit 30 displays the error code C8 output by the error pattern determination unit 28. Here, the error display unit 30 is a liquid crystal panel type display device (not shown) provided in the printer abnormality detection device 2, and the user of the printer 1 uses the display device to indicate that the printer 1 is in an abnormal state. The error code C8 can be obtained. Further, the printer abnormality detection device 2 may generate an alarm when an abnormal state is detected. Any alarm can be used as long as it can notify the user of the printer 1 such as an alarm sound and blinking of an LED lamp.

  Next, the operation of the printer abnormality detection device 2 according to the first embodiment will be described in detail with reference to FIGS. FIG. 8 is a flowchart showing the operation of the printer abnormality detection device 2 according to the first embodiment. In the description of FIG. 8, the description of the contents already described with reference to FIG. 1 may be omitted.

  A database 3 (including position information 6, threshold information 7, and error information 8) corresponding to the type of printer 1 being used and the paper size is prepared and set in advance (not shown in FIG. 8). In this state, it is assumed that the paper size C0 and the print data C1 are input to the printer 1. Steps S <b> 10 to S <b> 15 in FIG. 8 are processes until the pixel data C <b> 5 is reproduced to calculate the black pixel ratio C <b> 6 of each divided area and the image comparison unit 26 reads the black pixel ratio C <b> 6 of each divided area once stored. Show. Description of the detailed contents of steps S10 to S15 is omitted.

  In steps S16 to S22 in FIG. 8, the print data C2 is printed on the designated paper size C0 and read by the image sensor 11, and the read data C3 is input to calculate the black pixel ratio C4 of each divided area. The process until the black pixel ratio C4 of each divided area once stored is read by the image comparison unit 26 is shown. The detailed description of each step in steps S16 to S22 is omitted.

  Subsequently, the black pixel ratio C4 of each divided region temporarily stored in the read data feature amount recording unit 16 by the image comparison unit 26 and the black pixel ratio C6 of each divided region temporarily stored in the pixel data feature amount recording unit 24. From this, an error C7 of the black pixel ratio of each divided region is calculated (step S23). Subsequently, it is determined whether or not the error of the black pixel ratio is within an allowable range (S24). Specifically, the error ε according to the equation (1) is calculated, and it is determined whether or not the error ε of each divided region falls within an allowable range (for example, −5 ≦ ε ≦ + 5).

  If Yes in step S24, it is determined that the print result is normal (S25). On the other hand, in the case of No in step S24, it is determined that the printing result is abnormal (S26). Subsequently, it is determined which of the error patterns of the error information 8 in the database 3 corresponds to the error C7 (S27). Then, the error code C8 corresponding to the determined error pattern is displayed (S28).

  Next, details of steps S27 and S28 in FIG. 8 will be described with reference to FIG. FIG. 9 is a flowchart showing the operation of the printer abnormality detection apparatus 2 according to the first embodiment, and shows details of steps S27 and S28 in FIG. The frame enclosed by the one-dot chain line on the left side of FIG. 9 (S27) shows an algorithm for determining which of the error patterns in the database 3 corresponds to the error C7. The error code is displayed in the frame surrounded by the one-dot chain line on the right side of FIG. 9 (S28).

  In FIG. 9, first, regarding the case of “all white” and “all black” regardless of the print data C1, the print result (that is, the read data C3) generates an error with respect to the print data C1 after the determination first. Judgment is made when

  First, in FIG. 9, it is determined whether or not the black pixel ratio C4 is the same at the positions of all the divided regions (S30). If Yes in step S30, it is determined whether the black pixel ratio C4 of each divided region is approximately 100% or approximately 0% (S34). If it is determined in step S34 that the black pixel ratio C4 is approximately 0%, it is determined that ALM-01 in FIG. When the black pixel ratio C4 is determined to be approximately 100%, it is determined that ALM-02: “All Black” in FIG. If it is determined in step S34 that the black pixel ratio C4 is neither approximately 0% nor approximately 100%, the process proceeds to step S31 as in the case where it is determined No in step S30.

  Subsequently, it is determined whether or not the error C7 has a black pixel ratio difference (a difference between the black pixel ratio C4 and the black pixel ratio C6) in the vertical direction with respect to the printing direction (S31). If Yes in step S31, it is determined whether the black pixel ratio C4 is high (S35). In the case of No in step S35, it is determined as ALM-03: “printing direction vertical white stripe” in FIG. On the other hand, in the case of Yes in step S35, it is determined as ALM-05: “printing direction vertical streaks” in FIG.

  Subsequently, in the case of No in step S31, it is determined whether or not the error C7 has a difference in black pixel ratio (difference between the black pixel ratio C4 and the black pixel ratio C6) in the horizontal direction with respect to the printing direction (S32). . If Yes in step S32, it is determined whether the black pixel ratio C4 is high (S36). In the case of No in step S36, it is determined as ALM-04: “printing direction horizontal stripe” in FIG. On the other hand, in the case of Yes in step S36, it is determined as ALM-06: “printing direction horizontal streaks” in FIG.

  Subsequently, in the case of No in step S32, it is determined whether or not the error C7 has a high black pixel ratio regardless of the printing direction (S33). In the case of No in step S33, it is determined that ALM-08: “thin” in FIG. On the other hand, in the case of Yes in step S33, it is determined as ALM-07: “random dirt” in FIG.

  Note that when the print result density is abnormal and ALM-08 in FIG. 7 is to be determined as “light”, depending on the threshold value of the binarization process of the reading unit 12, the read data after the binarization process C3 becomes all white, and there is a problem that ALM-01: “all white” is erroneously determined. In order to avoid this, for example, when a binarization process is performed, a multi-gradation histogram is stored, and if it is not all white with reference to the histogram, it is not classified into ALM-02. Good. As described above, in the case of an abnormality relating to the print density, the problem of erroneous determination can be solved by referring to the histogram as appropriate.

  The error pattern determination algorithm in step S27 is not limited to the method in steps S30 to S36, and a known pattern matching method can be applied.

  Subsequently, in steps S37 to S44 included in step S28 of FIG. 9, error codes C8 ("ALM-01" to "ALM-08") corresponding to the determination result of step S27 are displayed.

  As described above, according to the printer abnormality detection device 2 according to the first embodiment, errors that may occur between the pixel data C5 and the read data C3 are classified into a plurality of error patterns. A database 3 storing information on the suspected part corresponding to each error pattern is prepared, and when the printer 1 detects a printing abnormality, the database 3 is referred to and the read data of each divided area is referred to. By determining which of the error patterns in the database 3 corresponds to the error C7 between the black pixel ratio C4 and the black pixel ratio C6 of the pixel data, the suspicious part that causes the printing abnormality can be specified. It becomes possible.

  The user of the printer 1 can obtain the effect that the printer 1 is in an abnormal state and the error pattern information can be obtained by displaying the error code C8.

  The user of the printer 1 contacts the maintenance staff and informs the displayed error code C8. Since the error code C8 and the suspected part C9 correspond as shown in FIG. 7, an effect that the person in charge of maintenance of the printer 1 can specify the suspected part C9 is obtained. That is, the person in charge of maintenance of the printer 1 may arrange the suspected part C9 without performing fault diagnosis at the site, and perform the replacement work of the suspected part by going to the site after the arrival of the part. Conventionally, it has been necessary to perform work twice at the site for failure diagnosis and replacement of suspected parts. However, using the printer abnormality detection device 2 requires only one replacement of suspected parts. The burden on the maintenance staff is reduced and the maintenance cost can be reduced. Further, since time required for failure diagnosis is not required, it is possible to quickly return to the normal state.

  In addition, about the content disclosed by embodiment, the deformation | transformation and correction as shown below are possible.

  In the embodiment, the case where the black pixel ratio of each divided region is used to compare the read data C3 and the pixel data C5 is illustrated, but the present invention is not limited to this. Instead of the black pixel ratio, an arbitrary feature amount representing the characteristics of the image can be used. For example, if the variance value of each divided area is used, it can be checked whether or not the amount of noise has increased in the print result.

  In the embodiment, the case of a monochrome binary image printer is illustrated, but the present invention is not limited to this. For example, the present invention can be applied to a printer for monochrome continuous tone images (grayscale images). In the case of a monochrome continuous tone image, the multi-tone data read by the image sensor is used as it is without being binarized. On the other hand, the pixel data is also a multi-tone bitmap image. When comparing multi-gradation read data and multi-gradation pixel data, for example, an average of gradation values of pixels in each divided region may be used as the feature amount instead of the black pixel ratio.

  Also, the disclosure of the embodiment can be extended and applied to a color printer. Specifically, using a color line CCD or the like as the image sensor of the reading unit 12, read data that has been color-separated with three colors of RGB is acquired. On the other hand, pixel data is also generated for each RGB channel. Then, the read data and pixel data of each divided region may be compared for each color channel.

  Further, in the embodiment, the configuration in which the printer abnormality detection device 2 is mounted on the printer 1 is exemplified, but the present invention is not limited to this. For example, it is possible to provide a printer having a configuration in which an abnormality detection device is incorporated.

  The abnormality detection process disclosed in the embodiment may be performed constantly, or the abnormality detection process may be performed only when the test mode is set.

  Also, the abnormality detection process may be performed by taking a printed matter printed by the printer with a scanner separated from the printer. In this case, since the abnormality detection process is performed off-line, an interface for connecting the abnormality detection apparatus to the printer is not required, and it is possible to easily cope with any printer.

  In the embodiment, an example of an electrophotographic laser printer has been described. However, the present invention is not limited to this, and can be applied to an arbitrary printer. For example, the present invention can be applied to an ink jet printer, a dot impact printer, a thermal transfer printer, and the like. Here, since the error pattern that may occur at the time of abnormality and the suspected part corresponding to the error pattern differ depending on the type of printer, the error information 8 in the database 3 may be prepared for each type of printer. Further, when the error pattern and the suspicious part corresponding to the error pattern differ depending on the model, the error information 8 in the database 3 may be prepared for each model.

  Specifically, the error information 8 in the database 3 can be prepared for each printer type as follows. For example, in the case of an abnormality in which printing is not performed at all (corresponding to ALM-01: “all white” in FIG. 7), the cause is analyzed for each type of printer. In the case of an ink jet printer, causes such as clogging of ink discharge nozzles, abnormality of a control device for converting print data, and the like are considered, and a suspected part corresponding to the cause may be registered. In the case of a dot impact printer, there may be causes such as an abnormality in a portion where an ink ribbon is transferred to paper, an abnormality in a control device for converting print data, and the like, and a suspected part corresponding to the cause may be registered. In the case of a thermal transfer printer, there may be causes such as an abnormality in heating control of the thermal transfer head, an abnormality in a control device that converts print data, etc., and a suspected part corresponding to the cause may be registered. The case of ALM-01: “all white” has been described above. However, in the case of other error patterns, a suspected part corresponding to the cause of the error pattern may be registered according to the type of printer.

  The abnormality detection device for a printer according to the present invention detects a failure of a general printer (including various types of printers such as an ink jet printer, a dot impact printer, a thermal transfer printer, and a laser printer), and is suspected of being repaired or replaced. Can be used to identify parts.

  Note that, within the scope of the entire disclosure (including claims and drawings) of the present invention, the embodiments can be changed and adjusted based on the basic technical concept. Various combinations or selections of various disclosed elements (including each element of each claim, each element of each embodiment, each element of each drawing, etc.) are possible within the scope of the claims of the present invention. . That is, the present invention naturally includes various variations and modifications that could be made by those skilled in the art according to the entire disclosure including the claims and the drawings, and the technical idea. In particular, with respect to the numerical ranges described in this document, any numerical value or small range included in the range should be construed as being specifically described even if there is no specific description.

1: Printer 2: Printer abnormality detection device 3: Database 4: Pixel data divided region position information 5: Read data divided region position information 6: Position information 7: Threshold information 8: Error information 10: Printing unit 11: Image sensor 12 : Reading unit 14: Reading data feature amount calculating unit 16: Reading data feature amount recording unit 20: Pixel data reproducing unit 22: Pixel data feature amount calculating unit 24: Pixel data feature amount recording unit 26: Image comparing unit 28: Error pattern Determination unit 30: error display unit 31: paper 32: optical unit 33: development unit 34: fixing unit 36: divided region position information C0: paper size C1: print data C2: printed material C3: read data C4: black pixel ratio (read) Data features)
C6: Black pixel ratio (pixel data feature value)
C5: Pixel data C7: Error C8: Error code C9: Suspected part

Claims (8)

A printer abnormality detecting device that is mounted on a printer that prints input print data and detects abnormality of the printer,
A pixel data reproducing unit for generating pixel data from the print data;
A reading unit that reads a printed matter printed by the printer with an image sensor and generates read data;
An image comparison unit that compares the pixel data and the read data at positions corresponding to each other and outputs an error;
The error that may occur between the pixel data and the read data is classified in advance into a plurality of error patterns associated with the printing direction horizontal arrangement and / or the printing direction vertical arrangement, and the classified errors A database in which information of suspected parts corresponding to each pattern is stored;
With
When the error output by the image comparison unit is not within a predetermined range, the printer is determined to be in an abnormal state, and the error is classified into the plurality of error patterns classified in the database with reference to the database. By determining which one corresponds to, identify the suspected part that is estimated to be the cause of the error ,
Set the database according to the type of printer,
The printer abnormality detection device , wherein the image comparison unit calculates the error based on a black pixel ratio . Set the division area position information indicating the position of the plurality of division areas,
A pixel data feature amount calculation unit that calculates a feature amount of the pixel data for each of the plurality of divided regions based on the divided region position information;
A read data feature amount calculation unit that calculates a feature amount of the read data for each of the plurality of divided regions based on the divided region position information;
Further comprising
The printer abnormality according to claim 1, wherein the image comparison unit outputs, as the error, a difference between a feature amount of the pixel data and a feature amount of the read data for each of the plurality of divided regions. Detection device.   The printer abnormality detection device according to claim 2, wherein the divided region position information is set according to a paper size to be printed.   4. The printer abnormality detection device according to claim 2, wherein the feature amount is a black pixel ratio.   5. The read unit according to claim 1, wherein the reading unit reads the printed matter with multiple gradations, performs binarization using black data below a predetermined threshold as the read data. The printer abnormality detection device as described. A print section for printing the input print data;
A pixel data reproducing unit for generating pixel data from the print data;
A reading unit that reads a printed matter printed by the printing unit with an image sensor and generates read data;
An image comparison unit that compares the pixel data and the read data at positions corresponding to each other and outputs an error;
The error that may occur between the pixel data and the read data is classified in advance into a plurality of error patterns associated with the printing direction horizontal arrangement and / or the printing direction vertical arrangement, and the classified errors A database in which information of suspected parts corresponding to each pattern is stored;
With
When the error output by the image comparison unit is not within a predetermined range, the printer is determined to be in an abnormal state, and the error is classified into the plurality of error patterns classified in the database with reference to the database. By determining which one corresponds to, identify the suspected part that is estimated to be the cause of the error ,
The database is set according to the type of printer,
The printer according to claim 1, wherein the image comparison unit calculates the error based on a black pixel ratio . A printer abnormality detection method for detecting abnormality of a printer that prints input print data,
A pixel data reproduction step of generating pixel data from the print data;
A reading step of reading a printed matter printed by the printer with an image sensor and generating read data;
An image comparison step of comparing the pixel data and the read data at positions corresponding to each other and outputting an error;
The error that may occur between the pixel data and the read data is classified in advance into a plurality of error patterns associated with the printing direction horizontal arrangement and / or the printing direction vertical arrangement, and the classified errors Preparing a database in which information of suspected parts corresponding to each pattern is stored;
Determining that the printer is in an abnormal state when the error due to the image comparison step is not within a predetermined range;
It is estimated that the error is caused by determining which of the plurality of error patterns classified in the database corresponds to the error in the image comparison step with reference to the database. Identifying the suspected part;
Setting the database according to the type of printer;
Calculating the error based on a black pixel ratio;
An abnormality detection method for a printer, comprising: A program for causing a computer to detect abnormality of a printer that prints input print data,
A process of comparing the pixel data generated from the print data and the read data obtained by reading the printed matter printed by the printer with an image sensor at positions corresponding to each other, and calculating an error;
A process of determining that the printer is in an abnormal state when the error is not within a predetermined range;
The error that may occur between the pixel data and the read data is classified in advance into a plurality of error patterns associated with the printing direction horizontal arrangement and / or the printing direction vertical arrangement, and the classified errors By referring to the database storing the information of the suspicious part corresponding to each pattern, it is determined which of the plurality of error patterns classified in the database corresponds to the error. Processing to identify the suspected parts that are presumed to be the cause,
Processing for setting the database according to the type of printer;
A process of calculating the error based on a black pixel ratio;
A program that causes a computer to execute.

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