JP7759273B2 - Air leak detection method - Google Patents

Description

The present invention relates to an air leak detection method for detecting air leaks in a room.

Conventionally, there have been cases where an airtight space is required in manufacturing sites, research and development sites, and the like. One example of an airtight space is a clean room, and clean rooms of various structures have been proposed (see, for example, Patent Documents 1 and 2). The technology described in Patent Document 1 relates to a connecting structure that realizes a clean room by connecting panels. The technology described in Patent Document 2 relates to a partition mechanism that forms compartments within a clean room.
It is common to conduct air leak inspections to ensure the airtightness of the target space, and one method is to use a thermograph that displays heat distribution as an image.Specific inspection methods are as follows.
(1) Create a negative pressure inside the clean room and allow air to flow from the outside.
(2) The temperature of the room outside the clean room is adjusted by the main air conditioning system.
(3) If there is an air leak, air of different temperatures will flow into the clean room.
(4) Use thermography to obtain an image of the heat distribution and determine the location of the air leak from the image.

JP 2009-155944 A Japanese Patent Application Publication No. 10-245919

However, conventional air leak testing using thermography was not always easy to perform, as it could only be performed after the installation of the main air conditioning system and it was difficult to determine whether there was an air leak.
For example, while temporary equipment can be used to adjust the room pressure in a clean room, air conditioning equipment is required to adjust the air temperature, so leak testing can only be performed after the permanent air conditioning equipment is operational. Because the air conditioning equipment installation process occurs later in the overall construction period, it is difficult to conduct leak testing at an early stage. The most ideal time to conduct a leak test is once the walls and ceiling are completed. Furthermore, when corrective work is required, if the workers involved in the construction of the clean room have been transferred to another site, it takes time to recall them. Furthermore, if the scaffolding used during the construction of the clean room has been dismantled, it takes time to reconstruct the scaffolding, making it difficult to carry out corrective work in a timely manner.
In addition, thermography images are taken to determine whether the air leak test has passed or failed, but this requires skill and expertise, so only certain workers can make the determination. For example, if a heat bridge occurs in the ceiling, the thermography image may appear to show a leak, which can confuse workers.
From this perspective, the present invention provides an air leak detection method that can detect air leaks more easily than conventional methods.

The air leak detection method according to the present invention is a method for detecting air leaks in a room. This air leak detection method includes an indoor sound measurement step of measuring indoor sound in the room, and an air leak determination step of determining the presence or absence of air leaks from the indoor sound. In the indoor sound measurement step, a first indoor sound is measured in a state where no pressure difference is generated between the inside and outside of the room, and a second indoor sound is measured in a state where a pressure difference is generated, using a microphone array consisting of a plurality of microphones. In the air leak determination step, the presence or absence of air leaks is determined by comparing the first indoor sound with the second indoor sound.
The air leakage determination step includes an air leakage sound component identification step and an air leakage sound source estimation step. In the air leakage sound component identification step, the frequency band of the air leakage sound generated by air leakage is identified by comparing the components of the first indoor sound and the components of the second indoor sound. In the air leakage sound source estimation step, the frequency band identified in the air leakage sound component identification step is analyzed, signals of the second indoor sound are received from the multiple microphones, and the arrival direction of the air leakage sound is estimated using the MUSIC algorithm .
The air leak detection method according to the present invention does not require air temperature adjustment, so it can be performed even before an air conditioner is installed. Therefore, there are few limitations on the time when the inspection can be performed. Furthermore, the presence or absence of an air leak sound can be clearly determined by comparing the first indoor sound with the second indoor sound. Therefore, it is possible to make a judgment without requiring the skill or technique required for judgment using a thermographic image. Furthermore, it is possible to identify the location of the air leak.

The air leak detection method according to the present invention is a method for detecting air leaks in a room. This air leak detection method includes an indoor sound measurement step of measuring indoor sound in the room, and an air leak determination step of determining the presence or absence of air leaks from the indoor sound. In the indoor sound measurement step, a first indoor sound is measured without generating a pressure difference between the inside and outside of the room, and a second indoor sound is measured with a pressure difference generated. In the air leak determination step, the presence or absence of air leaks is determined by comparing the first indoor sound with the second indoor sound.
The air leakage determination step includes an air leakage sound component identification step, an analysis time zone determination step, and an air leakage sound source estimation step. In the air leakage sound component identification step, the frequency band of the air leakage sound generated by air leakage is identified by comparing the components of the first indoor sound and the components of the second indoor sound. In the analysis time zone determination step, a time history of sound pressure levels is created for the frequency band identified in the air leakage sound component identification step, and a time zone for analyzing the air leakage sound is determined based on this time history. In the air leakage sound source estimation step, the frequency band identified in the air leakage sound component identification step and the time zone determined in the analysis time zone determination step are analyzed, and the arrival direction of the air leakage sound is estimated from the second indoor sound.
In the analysis time period determination step, the air leakage sound start time when the air leakage sound begins is calculated using displacement point detection from the time history of sound pressure levels, and a predetermined time period from the air leakage sound start time when there is no influence of reflected sound is set as the time period during which the air leakage sound is analyzed.
The air leak detection method according to the present invention does not require air temperature adjustment, so it can be performed even before an air conditioner is installed. Therefore, there are no restrictions on the time when the inspection can be performed. Furthermore, the presence or absence of an air leak sound can be clearly determined by comparing the first indoor sound with the second indoor sound. Therefore, a judgment can be made without the need for skill or technique, as is required when using a thermographic image. Furthermore, the influence of reflected sound (echoes from the room) generated in the room can be suppressed.

This invention makes it easier than ever to detect air leaks.

1 is a configuration diagram of an air leak detection system according to an embodiment of the present invention. FIG. 1 is a configuration diagram of a sound source tracking system. FIG. 2 is a block diagram of an air leakage sound source estimation unit. 1 is an example of a flowchart illustrating the processing of an air leak detection system. 10 is an example of a flowchart illustrating an analysis time period determination step. FIG. 1 is a diagram illustrating an environment in which an experiment was conducted. 1 is a graph showing 1/3 octave sound pressure levels of background noise (first room sound) and room sound including air leakage sound (second room sound) recorded in a verification experiment. 1 is a graph showing the time history of noise levels for each band (three types: "250 Hz," "1600 Hz," and "2000 Hz"). This is the result of detecting a change point in the "250 Hz" band. This is the result of detecting a change point in the "1600 Hz" band. This is the result of detecting change points in the "2000 Hz" band. FIG. 10 is an image diagram of a composite image in which a MUSIC spectrum is superimposed on a spherical image.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings. Each drawing is merely a schematic illustration to allow a sufficient understanding of the present invention. Therefore, the present invention is not limited to the illustrated examples. In each drawing, common or similar components are designated by the same reference numerals, and redundant explanations thereof will be omitted.
<Configuration of the air leak detection system according to the embodiment>
The configuration of the air leak detection system 100 will be described with reference to FIG. 1. FIG. 1 is a configuration diagram of the air leak detection system 100 according to an embodiment of the present invention. The air leak detection system 100 is a system for detecting air leaks in a room. The room in which air leaks are detected by the air leak detection system 100 is assumed to be airtight (designed to achieve airtightness), and one example is a clean room. Note that the room in which air leaks are detected does not need to be completely airtight; for example, air conditioning equipment may be installed in the room. Furthermore, it is assumed that the air leak detected by the air leak detection system 100 occurs due to a hole with a small cross-sectional area that connects the inside and outside of the room (penetrating the components of the room). This hole is, for example, a narrow gap that is not easily visible to the human eye.

The air leak detection system 100 creates a pressure difference between the inside and outside of a room, forcing air to flow through the hole causing the air leak. For example, it creates a negative pressure inside the room, creating an environment in which air flows into the room from the outside. As mentioned above, the hole causing the air leak has a small cross-sectional area, so when air passes through it, an air vortex is generated, producing a sound. In this embodiment, the sound produced by air passing through the hole is referred to as "air leak sound." The air leak detection system 100 detects the occurrence of an air leak in a room by recording the air leak sound while a pressure difference is created between the inside and outside of the room. The system also identifies the leak location by analyzing the recorded air leak sound. In other words, if an air leak is occurring in a room, the sound recorded inside the room (indoor sound) will include the air leak sound, but if an air leak is not occurring in a room, the sound recorded inside the room (indoor sound) will not include the air leak sound. Note that if environmental sound is occurring both inside and outside the room, the indoor sound will include the environmental sound.

1, the air leak detection system 100 mainly includes a sound source probing system 1 and a pressure difference generating unit 2. The air leak detection system 100 also includes a differential pressure meter 9. The differential pressure meter 9 is connected to a room by a tube and is capable of measuring the pressure within the room.
The sound source probing system 1 is a system for identifying the location of the source of an observed sound (air leakage sound in this embodiment). The configuration of the sound source probing system 1 is shown in Fig. 2. Fig. 2 is a configuration diagram of the sound source probing system 1. The configuration of the sound source probing system 1 will be described later.
The pressure difference generating unit 2 shown in FIG. 1 is a device that generates a pressure difference between the inside and outside of a room. In this embodiment, the pressure difference generating unit 2 is a blower and is installed on the wall of the room. The pressure difference generating unit 2 creates a negative pressure inside the room by sending air inside the room to the outside. The pressure difference generating unit 2 may also create a positive pressure inside the room by taking in air from outside the room. It is desirable that the operating noise of the pressure difference generating unit 2 be small enough to be negligible in air leak detection, and in this embodiment, the operating noise of the pressure difference generating unit 2 is also small enough to be negligible.

The configuration of the sound source tracking system 1 will be described with reference to Fig. 2. The sound source tracking system 1 includes a microphone array 3, an A/D converter 4, a signal processing unit 5, an image processing unit 6, a celestial sphere camera 7, and a display unit 8. The microphone array 3 and the celestial sphere camera 7 are preferably installed inside a room, while the other components may be installed either inside or outside the room. The signal processing unit 5 and the image processing unit 6 are realized by program execution processing by a CPU (Central Processing Unit), dedicated circuits, etc.
The omnidirectional camera 7 is an example of an imaging unit, and captures an image of the inside of a room where air leak detection is performed (particularly, the area around the microphone array 3). The omnidirectional camera 7 here can capture a 360-degree image in all directions, up and down, left and right.
The display unit 8 is, for example, a display, and can display images captured by the omnidirectional camera 7 .

The microphone array 3 is composed of multiple microphones M arranged three-dimensionally. The microphones M are, for example, omnidirectional microphones. Each microphone M outputs an observation signal to the A/D converter 4. In other words, the microphone array 3 outputs the same number of analog observation signals as the number of microphones M to the A/D converter 4. In this embodiment, two indoor sounds are recorded using the microphone array 3. The first indoor sound is indoor sound generated when no pressure difference is generated between the inside and outside of the room and is referred to as the "first indoor sound." The first indoor sound is, for example, background noise. The second indoor sound is indoor sound generated when a pressure difference is generated between the inside and outside of the room and is referred to as the "second indoor sound." If an air leak occurs in the room, the second indoor sound includes air leakage noise. The first indoor sound and the second indoor sound may include environmental sound, but the environmental sound included in the first indoor sound and the environmental sound included in the second indoor sound are similar.
The A/D converter 4 receives analog observation signals from the microphone array 3 for the number of microphones M, and performs analog-to-digital conversion on the received analog observation signals. The A/D converter 4 then outputs the digital observation signals to the signal processing unit 5.

The signal processing unit 5 (air leakage determination unit) focuses only on the air leakage sound components contained in the second indoor sound and estimates the occurrence of air leakage and the arrival direction of the air leakage sound. The signal processing unit 5 receives digital observation signals of the first indoor sound and the second indoor sound that have been analog-to-digital converted by the A/D converter 4. The signal processing unit 5 includes an air leakage sound component identification unit 51, an analysis time zone determination unit 52, and an air leakage sound source estimation unit 53.
The air leakage sound component identifying unit 51 acquires the first indoor sound and the second indoor sound and determines the presence or absence of air leakage by comparing the first indoor sound and the second indoor sound. For example, the air leakage sound component identifying unit 51 identifies the frequency band of the air leakage sound generated by air leakage by comparing the components of the first indoor sound and the second indoor sound. For example, the air leakage sound component identifying unit 51 identifies, as the frequency band of the air leakage sound, a band in which the difference between the components of the first indoor sound and the components of the second indoor sound is equal to or greater than a threshold. The air leakage sound component identifying unit 51 determines that air leakage sound is occurring (i.e., air leakage is occurring in the room) when there is one or more bands in which the difference between the components of the first indoor sound and the components of the second indoor sound is equal to or greater than a threshold, and determines that air leakage sound is not occurring (i.e., air leakage is not occurring in the room) when there is no band in which the difference is equal to or greater than the threshold. The air leakage sound component identifying unit 51 outputs information about the identified air leakage sound components to the analysis time zone determining unit 52 and the air leakage sound source estimating unit 53.

The analysis time period determination unit 52 determines a time period suitable for analyzing air leakage sounds. As mentioned above, the room in which air leakage is to be detected is airtight, making the room a closed space, and the accuracy of estimating the direction from which air leakage sounds are coming is reduced by, for example, reflected sound (echoes) from the walls. For this reason, the analysis time period determination unit 52 determines a time period when there is no (or little) influence from reflections, and the air leakage sound source estimation unit 53 estimates the air leakage sound based on that time period. For example, the analysis time period determination unit 52 creates a time history of sound pressure levels for the frequency band identified by the air leakage sound component identification unit 51, and determines a time period for analyzing air leakage sounds based on the created time history of sound pressure levels. The analysis time period determination unit 52 calculates the start time of the air leakage sound from the time history of sound pressure levels using displacement point detection, and determines a predetermined time period from the start time of the air leakage sound when there is no influence of reflected sound as the time period for analyzing the air leakage sound. For example, the time it takes for the reflected sound to arrive is calculated in advance, and a shorter time (for example, several milliseconds to several hundred milliseconds) is set as the time period for analyzing the air leakage sound. Methods for detecting change points include, for example, the "k-nearest neighbor method," the "singular spectrum transform method," and the "Changefinder method." Furthermore, time series prediction algorithms are now available as open source software libraries (for example, a tool named "Prophet"), and these publicly available tools may also be used. In other words, there are no particular limitations on the method for detecting change points. The analysis time period determination unit 52 outputs information regarding the time period suitable for analyzing the air leakage sound to the air leakage sound source estimation unit 53.

The air leakage sound source estimation unit 53 analyzes the frequency band identified by the air leakage sound component identification unit 51 and estimates the direction of arrival of the air leakage sound (the position of the air leakage sound source) from the second indoor sound. In other words, only the frequency band that rises from the background noise due to the pressure difference created inside and outside the room is set as the analysis frequency, and the direction of arrival of the air leakage sound (the position of the air leakage sound source) is estimated based on this analysis frequency. It is desirable for the air leakage sound source estimation unit 53 to analyze the air leakage sound in a time period determined by the analysis time period determination unit 52 that is suitable for analyzing the air leakage sound. In this case, the air leakage sound source estimation unit 53 accepts the analysis target frequencies determined by the second indoor sound and the air leakage sound component identification unit 51. In this embodiment, the air leakage sound source estimation unit 53 accepts second indoor sound signals from multiple microphones M and estimates the direction of arrival of the air leakage sound using the MUSIC algorithm. The air leakage sound source estimation unit 53 then outputs the estimated value of the arrival direction of the air leakage sound (horizontal angle φ, elevation angle θ) and the MUSIC spectrum to the image processing unit 6. Note that the information output by the air leakage sound source estimation unit 53 only needs to be capable of identifying the position of the air leakage sound, and the estimated value of the arrival direction of the air leakage sound and the MUSIC spectrum are merely examples. Note that it is also possible to output only either the estimated value of the arrival direction of the air leakage sound (horizontal angle φ, elevation angle θ) or the MUSIC spectrum.

An example of the configuration of the air leakage sound source estimation unit 53 will be described with reference to Fig. 3 (and Fig. 1 and Fig. 2 as appropriate). Fig. 3 is a block diagram of the air leakage sound source estimation unit 53. The air leakage sound source estimation unit 53 may have a general configuration that can estimate the position of the air leakage sound source using the MUSIC algorithm.
The air leakage sound source estimation unit 53 here includes a frame processing unit 53 a, an FFT (Fast Fourier Transformation) 53 b, an observation space correlation matrix calculation unit 53 c, an eigenvalue decomposition unit 53 d, a MUSIC spectrum calculation unit 53 e, an arrival direction estimation unit 53 f, a model space correlation matrix storage unit 53 g, and an arrival direction storage unit 53 h. Note that the configuration of the air leakage sound source estimation unit 53 here is merely an example.
The frame processing unit 53a converts the digital observation signal (second room sound) output from the A/D converter 4 for the number of microphones into frames with a predetermined frame length. For example, the frame processing unit 52a divides the second room sound into split time periods that are obtained by further dividing the analysis time period. The split time periods may, for example, partially overlap with adjacent time periods (for example, "50% overlap," in which half of the split time periods overlap). It is also possible to process the second room sound without dividing the analysis time period into split time periods.
The FFT 53b performs FFT processing (fast Fourier transform processing) to calculate an observed signal vector from each of the framed digital observed signals (test target sounds).

The observation space correlation matrix calculation unit 53c calculates the current observation space correlation matrix based on the observation signal vector obtained from the FFT 53b and the past correlation matrix. At this time, the observation space correlation matrix calculation unit 53c calculates the observation space correlation matrix only at the analysis target frequency calculated by the air leakage sound component identification unit 51.
The eigenvalue decomposition unit 53d performs eigenvalue decomposition on the current observation space correlation matrix, and obtains noise level eigenvectors corresponding to eigenvalues other than the large eigenvalues.
The MUSIC spectrum calculation unit 53e calculates a MUSIC spectrum based on the model space correlation matrix stored in advance in the model space correlation matrix storage unit 53g and the noise level eigenvector calculated by the eigenvalue decomposition unit 53d. The MUSIC spectrum calculation unit 53e calculates a MUSIC spectrum for each divided time period into which the analysis time period is divided. The calculated MUSIC spectrum is output to the direction of arrival estimation unit 53f and the image processing unit 6.
The arrival direction estimation unit 53f averages the estimated directions obtained in the frequency domain to be analyzed, and sets the peak value as the final arrival direction estimate.
The model space correlation matrix storage unit 53g stores a model space correlation matrix, which is a matrix obtained by the phase difference between the outputs of the microphones M with respect to one microphone M as a reference.
The arrival direction storage unit 53h stores the estimated arrival direction values.

The image processing unit 6 shown in FIG. 2 includes a spherical image correction unit 61 and an image synthesis unit 62. The spherical image correction unit 61 corrects the spherical image captured by the spherical camera 7 into a planar image. The image synthesis unit 62 synthesizes an image in which the MUSIC spectrum is displayed as a contour diagram with the corrected spherical image. When a contour diagram is created for each divided time period, the image synthesis unit 62 may display the contour diagrams corresponding to each divided time period as an image arranged in chronological order, or may create and display a new contour diagram by averaging the contour diagrams corresponding to each divided time period. Averaging the contour diagrams is preferable because it can eliminate the effects of noise, etc. An image of the image synthesized by the image synthesis unit 62 is shown in FIG. 12. FIG. 12 is an image of a synthesized image in which the MUSIC spectrum is superimposed on the spherical image. The image processing unit 6 displays the estimated value of the arrival direction of the air leakage sound (horizontal angle φ, elevation angle θ) and the synthesized image on the display unit 8.

<Processing (method) of the air leak detection system according to the embodiment>
The processing of the air leak detection system 100 will be described with reference to FIG. 4 (and also with reference to FIGS. 1 to 3 as appropriate). FIG. 4 is an example of a flowchart showing the processing of the air leak detection system 100. As shown in FIG. 4, the processing steps of the air leak detection system 100 mainly include an "indoor sound measurement step (step S10)" and an "air leak determination step (step S20)." As a preliminary step, a pressure difference generating unit 2 is installed in advance in the room where the air leak test will be performed. It is desirable that the pressure difference generating unit 2 be easily removable after the test is completed, and it is preferable that it be a small fan, for example.
(Indoor sound measurement process (step S10))
First, the air leak detection system 100 measures (records) background noise as the first indoor sound (step S11). The background noise (first indoor sound) is measured without the pressure difference generating unit 2 operating (i.e., without generating a pressure difference between the inside and outside of the room). Next, the air leak detection system 100 measures (records) indoor sound including the air leak sound as the second indoor sound (steps S12 to S16). The indoor sound including the air leak sound (second indoor sound) is measured while the pressure difference generating unit 2 is operating (i.e., while generating a pressure difference between the inside and outside of the room). For example, the air leak detection system 100 starts recording the air leak sound (step S12) and then operates a small fan serving as the pressure difference generating unit 2 (step S13). The air leak detection system 100 operates the small fan for a certain period of time, then stops it (steps S14 and S15), and stops recording the air leak sound again (step S16). This completes the indoor sound measurement process. The reason for operating the small fan after starting to record the air leakage sound is to ensure that recording is performed during the period when no reflected sound of the air leakage sound is generated (the period when the air leakage sound begins to be heard).

(Air leakage determination process (step S20))
The air leak detection system 100 (particularly, the air leak sound component identification unit 51) compares background noise (first indoor sound) recorded without a pressure difference between the inside and outside of the room with a recorded sound (second indoor sound) recorded with a pressure difference between the inside and outside of the room (step S21). If the comparison result in step S21 is less than the threshold, the air leak detection system 100 determines that there is no air leak sound (step S22), and concludes that there is no air leak in the room, thereby ending the air leak test. After the air leak test is completed, the small fan serving as the pressure difference generating unit 2 is removed from the room. If the comparison result in step S21 is equal to or greater than the threshold, the air leak detection system 100 determines that there is an air leak sound and extracts a frequency band equal to or greater than the threshold (i.e., the air leak sound component) (step S23). Multiple frequency bands may be extracted.
Following step S23, the air leak detection system 100 (particularly the analysis time zone determination unit 52) sets a time zone (e.g., start time and end time) for the analysis. For example, the air leak detection system 100 creates a time history of sound pressure levels for the frequency bands identified by the air leak sound component identification unit 51, and sets a time zone for analyzing the air leak sound based on the created time history of sound pressure levels. If multiple bands are extracted in step S23, a different time zone (start time and end time) may be set for each band. Note that the time zone (start time and end time) for the analysis may also be set manually. In this case, for example, the air leak detection system 100 displays the time history of sound pressure levels on a screen and accepts the time zone (start time and end time) set by the person.
Following step S24, the air leak detection system 100 (particularly the air leakage sound source estimating unit 53) performs sound source exploration analysis of the air leakage sound based on the target frequency band and the analysis time period (step S25). For example, the air leakage sound source estimating unit 53 analyzes the frequency band identified by the air leakage sound component identifying unit 51, and estimates the arrival direction of the air leakage sound (the position of the air leakage sound source) from the second indoor sound during the analysis time period.

An example of the processing in step S23 is shown in FIG. 5. FIG. 5 is an exemplary flowchart illustrating the analysis time zone determination process in step S23. As shown in FIG. 5, for example, the analysis time zone determination unit 52 convolves a target frequency band filter with a recorded sound (second indoor sound) recorded while a pressure difference is generated between the inside and outside of the room (step S241). The target frequency band filter is a filter that passes signals in a target band. Next, the analysis time zone determination unit 52 calculates the noise level every 100 ms for the signals in each band that have passed through the target frequency band filter (step S242). Next, the analysis time zone determination unit 52 sets an analysis start time for each band using change point detection (step S243).
Change-point detection is the detection of the time point at which a change occurs in time-series data. It is generally used as a method for detecting anomalies. Time-series analysis methods for change-point detection have been proposed in the past, such as the "k-nearest neighbor method," the "singular spectrum transform method," the "Changefinder method," and the "method using a tool named "Prophet." In this embodiment, it is sufficient to detect the time at which the air leakage sound begins, and the change-point detection method is not particularly limited. For example, the noise level for each band every "100 ms" is treated as time-series data, and the first change-point is detected.

As described above, the air leak detection method realized by the air leak detection system 100 according to the embodiment does not require air temperature adjustment, and can therefore be carried out even before an air conditioner is installed. This means that there are fewer limitations on the time when the inspection can be carried out. Furthermore, the presence or absence of air leak sounds becomes clear by comparing the first indoor sound with the second indoor sound. This makes it possible to make a judgment without the skill or technique required for judgment using thermographic images.

<Verification experiment>
An experiment for verifying the effectiveness of the air leak detection system 100 according to the embodiment will be described. First, the environment in which the verification experiment was conducted will be described with reference to Fig. 6 (and Figs. 1 to 5 as appropriate). Fig. 6 is a diagram for explaining the environment in which the verification experiment was conducted.
As shown in Figure 6, an experiment was conducted using a large room Q1, a small room Q2 adjacent to the large room Q1, and a front room Q3 of the small room Q2. The large room Q1 is an artificial climate chamber (a laboratory where the temperature, etc., can be changed). The large room Q1 has an airtight structure, and when the entrance door R1 is closed, there is no air flow inside or outside the large room Q1. In this verification experiment, a removable panel R3 attached to the wall R2 at the boundary between the large room Q1 and the small room Q2 was loosened to create a narrow gap between the wall R2 and the panel R3.
The sound source detection system 1 of the air leak detection system 100 was installed in the large room Q1, and the small fan serving as the pressure difference generator 2 was installed in a temporary member that blocked the entrance/exit with the door R1. By operating the pressure difference generator 2, the air in the large room Q1 was sent to the outside, and the air pressure in the large room Q1 became 100 Pa lower than the air pressure (atmospheric pressure) in the small room Q2. As a result, the air in the small room Q2 flowed into the large room Q1 through the gap between the wall R2 and the panel R3, as indicated by the symbol P. In other words, an artificial air leak was generated between the large room Q1 and the small room Q2, creating an environment in which air leakage sounds could be heard. The temperature in the large room Q1 was 25°C, and the temperature in the small room Q2 was 30°C.

The background noise (first room sound) and the room sound including air leakage sounds (second room sound) recorded in the verification experiment will be described with reference to Fig. 7. Fig. 7 is a graph showing the 1/3 octave sound pressure levels of the background noise (first room sound) and the room sound including air leakage sounds (second room sound) recorded in the verification experiment. When "10 dB" was set as the threshold for the difference between the first room sound and the second room sound, the bands of "250 Hz,""1600Hz," and "2000 Hz" were identified, as shown by the dashed line areas in Fig. 7.
The determination of the analysis time period in the verification experiment will be described with reference to Figures 8 to 11. In the verification experiment, target frequency band filters that pass the bands of "250 Hz,""1600Hz," and "2000 Hz" were convolved with the second indoor sound, and time-series noise levels were determined every "100 ms" for each band (three types: "250 Hz,""1600Hz," and "2000 Hz") (see Figure 8). Figure 8 is a graph showing the time history of noise levels for each band (three types: "250 Hz,""1600Hz," and "2000 Hz").

As shown in Figure 8, the time at which air leakage noise begins varies depending on the frequency band (the time at which the sound pressure level increases differs for each band). In this verification experiment, it was possible to particularly distinguish the differences between "250 Hz" and "1600 Hz" and "2000 Hz." Therefore, to suppress the influence of reflected sound, it is necessary to set an appropriate analysis start time for each band. In this verification experiment, the time at which air leakage noise begins was calculated using the tool "Prophet." Specifically, the noise level for each band every "100 ms" was treated as time-series data, and the first change point was detected. This time-series data is characterized by being a non-stationary time-series signal. The arrows in Figure 8 show the rough trend of changes in the time-series data. The objective is to detect the time of the first change point K1 in the time series.
The results of change-point detection for each band are shown in Figs. 9 to 11. Fig. 9 shows the results of change-point detection in the "250 Hz" band, Fig. 10 shows the results of change-point detection in the "1600 Hz" band, and Fig. 11 shows the results of change-point detection in the "2000 Hz" band. The black dots in Figs. 9 to 11 represent actual data, and the line graphs (solid lines) are drawn based on this data. The dashed lines running vertically on the paper in Figs. 9 to 11 represent change points K calculated by change-point detection, and of these change points K, the first change point K1 in the time series is set as the analysis start time.

An image of a composite image in which a contour map of the MUSIC spectrum is superimposed on a spherical image in the verification experiment is shown in Fig. 12. In Fig. 12, the removable panel R3 (see Fig. 6), which is the location E where the air leak sound is generated, is shown in the center of the spherical image, and the hatched area indicating the MUSIC spectrum overlaps with the location E. In other words, it can be said that the air leak detection system 100 successfully identified the air leak location.
Although the embodiment of the present invention has been described above, the present invention is not limited to this and can be practiced within the scope of the claims.
For example, in the embodiment, the second indoor sound signals are received from the multiple microphones M, and the arrival direction of the air leakage sound is estimated using the MUSIC algorithm. However, the position of the air leakage sound can also be estimated using a method other than the MUSIC algorithm.
Even if there are multiple air leak locations and each location produces a different air leak sound, the air leak detection system 100 can identify each of the multiple air leak locations.

REFERENCE SIGNS LIST 1 Sound source detection system 2 Pressure difference generating unit 3 Microphone array 4 A/D converter 5 Signal processing unit (air leak determination unit)
6 Image processing unit 7 Spherical camera (photographing unit)
8 Display unit 51 Air leakage sound component identification unit 52 Analysis time period determination unit 53 Air leakage sound source estimation unit 61 Spherical image correction unit 62 Image synthesis unit 100 Air leakage detection system

Claims (3)

An air leak detection method for detecting air leaks in a room, comprising:
an indoor sound measurement step of measuring indoor sound in the room;
an air leakage determination step of determining whether or not there is an air leakage from the indoor sound,
In the indoor sound measuring step, a first indoor sound is measured in a state where no pressure difference is generated between the inside and outside of the room, and a second indoor sound is measured in a state where a pressure difference is generated between the inside and outside of the room using a microphone array consisting of a plurality of microphones,
In the air leakage determination step, the presence or absence of air leakage is determined by comparing the first indoor sound with the second indoor sound ,
The air leak determination step includes:
an air leakage sound component identifying step of identifying a frequency band of an air leakage sound generated by an air leak by comparing the first indoor sound component with the second indoor sound component;
an air leakage sound source estimating step of analyzing the frequency band identified in the air leakage sound component identifying step, receiving signals of the second indoor sound from the plurality of microphones, and estimating the arrival direction of the air leakage sound using a MUSIC algorithm;
A method for detecting an air leak. An air leak detection method for detecting air leaks in a room, comprising:
an indoor sound measurement step of measuring indoor sound in the room;
an air leakage determination step of determining whether or not there is an air leakage from the indoor sound,
In the indoor sound measuring step, a first indoor sound is measured in a state where no pressure difference is generated between the inside and outside of the room, and a second indoor sound is measured in a state where a pressure difference is generated between the inside and outside of the room,
In the air leakage determination step, the presence or absence of air leakage is determined by comparing the first indoor sound with the second indoor sound ,
The air leak determination step includes:
an air leakage sound component identifying step of identifying a frequency band of an air leakage sound generated by an air leak by comparing the first indoor sound component with the second indoor sound component;
an analysis time period determination step of creating a time history of sound pressure levels for the frequency bands identified in the air leakage sound component identification step, and determining a time period in which to analyze the air leakage sound based on the time history;
an air leakage sound source estimating step of estimating the arrival direction of the air leakage sound from the second indoor sound by analyzing the frequency band identified in the air leakage sound component identifying step and the time period determined in the analysis time period determining step,
A method for detecting an air leak. In the analysis time period determination step, the air leakage sound start time is calculated using displacement point detection from the time history of sound pressure levels, and a predetermined time period from the air leakage sound start time when there is no influence of reflected sound is determined as the time period for analyzing the air leakage sound.
3. The method for detecting an air leak according to claim 2 .