A Fault Diagnosis Method and System for Multicolor Infrared Detectors

Abstract

This application relates to the technical field of data calibration for detector testing, and specifically relates to a fault diagnosis method and system for multi-color infrared detectors. The method includes: obtaining the I-V characteristic curves of the multi-color infrared detector at each sampling moment; dividing the piecewise straight line of the structural damage degree - time; removing the growth trend of the I-V characteristic curves at each sampling moment; using the piecewise straight line of the structural damage degree - time, performing frequency domain conversion on the dark current densities divided into corresponding regions at all sampling moments, screening out the noise dark current density intervals and denoising them; using the ratio difference of the number of dark current densities in the noise dark current density intervals between each region and its adjacent regions before and after, to judge the fault condition of the structure of the multi-color infrared detector. This application aims to improve the accuracy of the diagnosis results by analyzing the interference of noise data points caused by the growth trend on the analysis of the structure faults of multi-color infrared detectors.

Description

Technical Field

[0001] The present application relates to the technical field of data calibration for detector testing, and in particular to a fault diagnosis method and system for multi-color infrared detectors. Background Art

[0002] At present, infrared detector technology has entered the third generation development stage. Antimonide type II superlattice (T2SL) has the advantages of adjustable energy band, low Auger recombination, large effective mass of electrons and good material uniformity, which meets the requirements of high performance, large array, multi-color detection and low cost of the third generation detector. Multi-color detection can obtain spectral information of different bands at the same time, improve the recognition and tracking of targets, and reduce the false alarm rate. Multi-color detectors enhance the recognition ability of targets by comparing the spectral information of targets in different bands. Fault diagnosis is to monitor and isolate faults according to fault phenomena, reason and analyze abnormalities, and obtain fault location.

[0003] Material structure is a key part of the performance of multi-color infrared detectors. The current method for diagnosing material structure faults is to determine whether there is a material structure fault by measuring the dark current. Dark current affects the performance of multi-color infrared detectors, that is, the detection rate, and the existence of dark current is directly related to the integrity of the material structure of the detector. Therefore, accurate measurement of dark current is very important, but because the dark current is very small and the noise will gradually increase over time, it is difficult to accurately evaluate the performance. Summary of the invention

[0004] In order to solve the above technical problems, the present application provides a fault diagnosis method and system for multi-color infrared detectors, and the technical solutions adopted are as follows:

[0005] In a first aspect, an embodiment of the present application provides a fault diagnosis method for a multi-color infrared detector, the method comprising the following steps:

[0006] Obtaining an IV characteristic curve of the multi-color infrared detector at each sampling moment; the IV characteristic curve is composed of dark current densities under different bias voltages;

[0007] According to the distribution of dark current density at all sampling times, the noise is determined and denoised; specifically:

[0008] A1, according to the detection rate and quantum efficiency of all bias voltages at any sampling time, determine the degree of structural damage at any sampling time, so as to construct a scatter plot of structural damage degree-time, and divide the piecewise straight line of structural damage degree-time;

[0009] A2, according to the growth trend of the dark current density with zero bias voltage at all sampling moments, the growth trend of the IV characteristic curve at each sampling moment is removed;

[0010] A3, using the piecewise straight line of structural damage degree-time, the dark current density at all sampling moments is divided into corresponding regions; the dark current density in each region is converted into frequency domain and divided into dark current density intervals; based on the frequency domain information difference of the same dark current density interval in all regions, the noise possibility of each dark current density interval is calculated, so as to screen out the noisy dark current density interval and perform denoising on it;

[0011] By using the proportion of dark current density in the noise dark current density range in each area, the difference between the adjacent areas before and after is analyzed, the degree of structural damage in each area is determined, and the fault condition of the multi-color infrared detector structure is judged.

[0012] Preferably, the method for determining the degree of structural damage comprises:

[0013] Obtaining an average level of detection rate at 50% cutoff wavelength corresponding to all bias voltages at the arbitrary sampling time;

[0014] Obtaining the average level of the maximum values ​​of quantum efficiencies corresponding to all bias voltages at any sampling time;

[0015] The results of the positive phase fusion of the two average levels are subjected to anti-correlation mapping to determine the degree of structural damage at the arbitrary sampling moment.

[0016] Preferably, the segmentation method of the piecewise straight line of structural damage degree-time is:

[0017] A region growing algorithm is used for all data points in the scatter plot. The condition for region growing is that the difference between the slope of the line connecting adjacent data points and the slope of the line connecting the previous adjacent data points is less than a preset growth threshold.

[0018] A straight line is fitted to the data points in each growth area to obtain a piecewise straight line of structural damage degree-time.

[0019] Preferably, the method for removing the growth trend is:

[0020] ;

[0021] in, It represents the IV characteristic curve after the growth trend is removed at sampling time t. To adjust the preset coefficients for dark current data stability, It represents the degree of structural damage on the piecewise straight line of structural damage degree-time at sampling time t, The IV characteristic curve at sampling time t is shown.

[0022] Preferably, the selection condition of the preset coefficient for adjusting the smoothness of the dark current data is: after fitting the dark current density when the bias voltage is 0 in the IV characteristic curve after removing the growth trend at all sampling moments into a straight line, the slope of the straight line falls within a preset range.

[0023] Preferably, the dark current density interval is divided by: dark current densities of the same order of magnitude after frequency domain conversion are grouped into one dark current density interval.

[0024] Preferably, the calculation expression of the noise possibility is:

[0025] ;

[0026] Where P represents the noise probability of the dark current density interval, C represents the mean of the dark current density interval, It represents the average level of the mean of all regions in this dark current density range, I represents the number of regions, It represents the distance between the occurrence frequency of the dark current density in the dark current density interval of the ith region and the fitting straight line, and norm() is the normalization function.

[0027] Preferably, the fitting straight line is obtained by performing straight line fitting on the occurrence frequencies of dark current densities in all regions in the same dark current density interval.

[0028] Preferably, the determination expression of the degree of structural damage is:

[0029] ;

[0030] in, represents the degree of structural damage in the sth region, , , are the noise point proportions of the s-1th, sth, and s+1th regions respectively, and norm() represents a normalization function; wherein the noise point proportion is the proportion of the number of dark current densities in the noise dark current density interval in each region to the total number of dark current densities in the region.

[0031] In the second aspect, an embodiment of the present application also provides a fault diagnosis system for a multi-color infrared detector, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, wherein when the processor executes the computer program, the steps of any one of the above-mentioned fault diagnosis methods for a multi-color infrared detector are implemented.

[0032] This application has at least the following beneficial effects:

[0033] Aiming at the problem that the detection rate of a multi-color infrared detector decreases with use, resulting in gradually more noise in the dark current data, and the structural fault of the multi-color infrared detector cannot be accurately diagnosed, the present application divides the structural damage degree-time segmented straight line according to the detection rate and quantum efficiency reflected by the multi-color infrared detector at each bias, and analyzes the damage of the multi-color infrared detector; then, the growth trend of the dark current density with zero bias at all sampling moments is analyzed, the trend of the dark current data growing over time is removed, and the problem of inaccurate identification of noise data points caused by the growth trend is eliminated; finally, the distribution of the sampling moments in the growth area on the segmented straight line is analyzed, the area of ​​all sampling moments is divided, and the distribution of the frequency of occurrence of the same dark current density in all areas of the same order of magnitude after frequency domain conversion using the IV characteristic curve is calculated, and the noise possibility of the same dark current density is calculated, so as to screen out the noise dark current density interval and perform denoising processing, and at the same time, the correlation between the number of noise points and the detection effect of the multi-color infrared detector between adjacent areas is combined to further quantify the degree of structural damage of the multi-color infrared detector, and judge the structural fault of the multi-color infrared detector, so that the diagnosis result is more accurate. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present application or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0035] Figure 1 A flowchart of a fault diagnosis method for a multi-color infrared detector provided in one embodiment of the present application;

[0036] Figure 2 A schematic diagram of an IV characteristic curve provided for an embodiment of the present application;

[0037] Figure 3 A flowchart of a process for denoising dark current data provided by one embodiment of the present application;

[0038] Figure 4 A schematic diagram of the trend of a first dark current variation curve provided by an embodiment of the present application. DETAILED DESCRIPTION

[0039] In order to further explain the technical means and effects adopted by the present application to achieve the predetermined invention purpose, the following is a detailed description of the fault diagnosis method and system for multi-color infrared detectors proposed in the present application, its specific implementation, structure, features and effects, in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0040] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

[0041] The following is a detailed description of a fault diagnosis method and system for multi-color infrared detectors provided by the present application in conjunction with the accompanying drawings.

[0042] An embodiment of the present application provides a fault diagnosis method and system for a multi-color infrared detector.

[0043] When diagnosing structural faults of the focal plane array of a multi-color infrared detector, dark current data is often used as a reference. As the detector is used, the dark current data will gradually become larger and contain more and more noise. Therefore, it is necessary to perform noise reduction based on the characteristics of dark current changes, thereby reducing the situation in which the multi-color infrared detector becomes increasingly noisy due to use time, making the dark current detection effect worse.

[0044] Specifically, a fault diagnosis method for multi-color infrared detectors is provided as follows. Figure 1 , the method comprises the following steps:

[0045] The first step is to obtain the IV characteristic curve of the multi-color infrared detector at each sampling moment.

[0046] Taking 1 day as a sampling period, that is, obtaining the IV characteristic curve (dark current under different bias voltages) of the multi-color infrared detector at 77K (degrees Kelvin) in history (1 year) at a sampling moment.

[0047] IV characteristic test: The structure is a light shield (blocking external light), a current limiting resistor (preventing overload and protecting the detector) and a voltage regulator (providing bias voltage, adjusting the bias voltage to read the corresponding current value, dividing the current value by the table size to get the dark current density, and plotting the dark current density and the corresponding bias voltage curve, recorded as the IV characteristic curve. The schematic diagram of the IV characteristic curve is as shown in the attached Figure 2 as shown).

[0048] exist Figure 2In the figure, the horizontal axis is the adjustment voltage, the unit is V (volt), the vertical axis is the dark current density, the unit is A / m² (ampere per square meter), the adjustment bias voltage is in steps of 1V, and the range is [-4V, 4V].

[0049] At this point, the IV characteristic curve at each sampling moment can be obtained by the above method, and the IV characteristic curve is composed of dark current densities under different bias voltages, that is, dark current densities under different bias voltages at each sampling moment.

[0050] In the second step, the noise is determined and denoised based on the distribution of dark current density at all sampling times.

[0051] Dark current has an absolute impact on the performance of the device (focal plane array of multi-color infrared detector) and is used to measure the performance of the device. The dark current is mainly determined by the growth quality of the material crystal, the structural design of the device, and the process level of device preparation. The structure and quality of the device will gradually decrease with use, which will cause the dark current to increase. At the same time, the reduction in device quality will lead to a lower detection rate and more noise in the detector, and the change in noise will lead to a decrease in the accuracy of the dark current data, and the measurement of device performance will no longer be accurate. Therefore, noise reduction is required to improve the accuracy of device fault diagnosis (structural integrity of the device).

[0052] Traditional filtering algorithms do not consider the noise distribution characteristics of dark current data, and the denoising effect of gradually increasing noise is poor. This application combines the changes in the IV characteristic curve of the multi-color infrared detector and the distribution changes of the dark current data over time to analyze the distribution characteristics of the noise, and combines median filtering for noise reduction.

[0053] Accordingly, in this application, the process flow chart of denoising dark current data is as shown in the attached figure. Figure 3 As shown, specifically:

[0054] A1, according to the detection rate and quantum efficiency of all bias voltages at any sampling time, determine the degree of structural damage at any sampling time, so as to construct a scatter plot of structural damage degree-time, and divide the piecewise straight line of structural damage degree-time;

[0055] A2, according to the growth trend of the dark current density with zero bias voltage at all sampling moments, the growth trend of the IV characteristic curve at each sampling moment is removed;

[0056] A3, using the piecewise straight line of structural damage degree-time, divide the dark current density at all sampling moments into corresponding areas; perform frequency domain conversion on the dark current density in each area and divide it into dark current density intervals; based on the frequency domain information difference of the same dark current density interval in all areas, calculate the noise possibility of each dark current density interval, so as to screen out the noisy dark current density interval and perform denoising on it.

[0057] The details are as follows:

[0058] A1, according to the detection rate and quantum efficiency of all bias voltages at any sampling time, the degree of structural damage at any sampling time is determined to construct a scatter plot of the degree of structural damage-time and divide the piecewise straight line of the degree of structural damage-time.

[0059] The response rate and quantum efficiency characterize the macroscopic and microscopic sensitivities of the multi-color infrared detector respectively, and can be used to show the structural integrity of the detector. They will gradually decrease with the increase of usage. Therefore, the decrease of the response rate and quantum efficiency over time can be used to show the structural damage of the detector.

[0060] A101, obtain the detection rate at 50% cutoff wavelength (50% cutoff wavelength reflects the sensitivity of the detector to infrared radiation of different wavelengths) corresponding to all bias voltages at any sampling time; obtain the maximum value of quantum efficiency (the ratio of the number of photoelectrons generated per second to the number of incident photons at a specific wavelength) corresponding to all bias voltages at any sampling time;

[0061] A102, calculate the response rate at any sampling time:

[0062] ;

[0063] Where D is the response rate at any sampling time, A is the amount of bias voltage adjusted, It represents the detection rate at the 50% cutoff wavelength corresponding to the ath adjusted bias at any sampling time. (The detection rate is represented by the mean of the detection rates at all biases).

[0064] A103, calculate the quantum efficiency at any sampling time:

[0065] ;

[0066] Where QE represents the quantum efficiency at any sampling time, A represents the amount of bias voltage adjusted, It represents the maximum value of the quantum efficiency corresponding to the ath adjustment bias at any sampling time.

[0067] A104, calculate the degree of structural damage at any sampling time:

[0068] ;

[0069] Among them, S represents the degree of structural damage at any sampling time, D represents the response rate at any sampling time, QE represents the quantum efficiency at any sampling time, and exp represents the exponential function with the natural constant e as the base.

[0070] It should be understood that the greater the response rate and the greater the quantum efficiency, the better the detection effect, the more complete the structure, and the less the degree of structural damage.

[0071] A105, for any multi-color infrared detector, a coordinate system is established with time as the horizontal axis and the degree of structural damage as the vertical axis, and a scatter plot of the degree of structural damage-time is drawn.

[0072] Use the region growing algorithm for all data points, record the first data point as the growth seed point, and obtain the slope of the line connecting the growth seed point and the adjacent data points , the slope of the line connecting an adjacent data point and its next adjacent data point is recorded as The condition for region growth is ,when When , the growth stops, and the next data point is used as a new growth seed point, and so on to obtain several growth areas; 0.1 is the preset growth threshold, and is the slope of the line connecting adjacent data points.

[0073] For growth regions where the number of data points is less than the number of biases in the IV characteristic curve (i.e., bias sequence), these data points are merged into the growth region with the closest distance; a straight line is fitted to the data points in each growth region to obtain a piecewise straight line of structural damage degree-time.

[0074] A2, according to the growth trend of the dark current density when the bias voltage is zero in all sampling moments, the growth trend of the IV characteristic curve at each sampling moment is removed.

[0075] As the device structure is damaged more, the dark current will increase accordingly. In order to place the dark current data at the same level for analysis of noise data points, the trend of gradually increasing dark current should be removed. The trend of increasing dark current is related to the integrity of the device structure. Therefore, the dark current data can be adjusted according to the degree of structural damage obtained in step A1.

[0076] A201, establish a coordinate system, with the horizontal axis being time and the vertical axis being dark current density, taking the bias voltage at a sampling moment as a cycle, sequentially obtaining the IV characteristic curve at each sampling moment as a cycle, and forming the first dark current scatter plot of the IV characteristic curves at all sampling moments according to the sampling time.

[0077] Then, adjacent data points are connected, and Chaikin curve smoothing is performed on the data points in each cycle to obtain a first dark current variation curve. The trend diagram of the first dark current variation curve is shown in the attached figure. Figure 4 The process of Chaikin curve smoothing is a well-known technique and will not be described in detail.

[0078] exist Figure 4 In the figure, the minimum dark current density within the period of each sampling moment represents the dark current density when the bias voltage is 0. The dark current density when the bias voltage is 0 at all sampling moments is linearly fitted to obtain the blue straight line in the image.

[0079] A202, calculate the dark current density after removing the dark current growth trend:

[0080] ;

[0081] in, It represents the IV characteristic curve after the growth trend is removed at sampling time t. To adjust the preset coefficients for dark current data stability, It represents the degree of structural damage on the piecewise straight line of structural damage degree-time at sampling time t, The IV characteristic curve at sampling time t is shown.

[0082] The selection condition of the preset coefficient k for adjusting the stability of the dark current data is: in the IV characteristic curve after removing the growth trend at all sampling moments, the dark current density when the bias voltage is 0 is fitted into a straight line, and the slope of the straight line belongs to , that is, to ensure that there is no problem of inaccurate identification of noise data points caused by the growth trend between the IV characteristic curves of all sampling moments after the growth trend is removed.

[0083] A203, for all IV characteristic curves after the growth trend is removed, the horizontal axis is time, the vertical axis is dark current density, a coordinate system is established, and a second dark current scatter plot is drawn. The second dark current scatter plot includes the IV characteristic curves after the growth trend is removed at all sampling moments.

[0084] A3, using the piecewise straight line of structural damage degree-time, divide the dark current density at all sampling moments into corresponding areas; perform frequency domain conversion on the dark current density in each area and divide it into dark current density intervals; based on the frequency domain information difference of the same dark current density interval in all areas, calculate the noise possibility of each dark current density interval, so as to screen out the noisy dark current density interval and perform denoising on it.

[0085] The second dark current scatter plot shows that the dark current density data gradually becomes noisier as time goes by. At the beginning, the dark current density is more consistent with the changing relationship between dark current and bias voltage. As time goes by, more and more noise will be distributed outside the IV characteristic curve, which is manifested as a change in the frequency distribution of dark current density. Therefore, the dark current scatter plot can be segmented Fourier transform, and the frequency change of dark current density can be used to determine which data points are more likely to be noise, thereby filtering out the noise and obtaining accurate dark current data.

[0086] A301, several growth regions are obtained in the process of obtaining the piecewise straight line of structural damage degree-time; all sampling moments contained in the same growth region are combined into one region; all sampling moments are divided into several regions, each region contains several cycles.

[0087] The dark current density data of each area is converted into frequency domain, and the dark current densities of the same order of magnitude after frequency domain conversion are placed in the same dark current density interval. The frequency of dark current density appearing in each dark current density interval is counted, and a dark current density interval-frequency histogram of each area is drawn.

[0088] For the explanation of the same order of magnitude, for example: the same order of magnitude, such as 10 0 ~10 1 is an order of magnitude, 10 -2 ~10 -1 The dark current density of each dark current density interval is obtained. The dark current density interval-frequency histogram is the distribution of the dark current density. Some intervals have more data and some intervals have less data. One interval is represented by an order of magnitude.

[0089] It should be understood that the structural damage of the multi-color infrared detector is not completely linearly related to time, so it is not divided into sections according to time periods. The segmented straight line of structural damage degree-time shows the situation of structural damage, and the slope of each segmented straight line shows the speed of structural damage during this period.

[0090] A302, with area as the horizontal axis and the frequency of occurrence of dark current density as the vertical axis, for one dark current density range, obtain the frequency of occurrence of dark current density in all areas of this dark current density range, and perform straight line fitting. The relationship between the frequency of occurrence of dark current density in this dark current density range and its fitting straight line represents the change of this dark current density range.

[0091] A303, calculate the noise probability for any dark current density interval:

[0092] ;

[0093] Where P represents the noise probability of the dark current density interval, C represents the mean of the dark current density interval, It represents the average level of the mean of all regions in this dark current density range, I represents the number of regions, represents the distance between the occurrence frequency of the dark current density in the dark current density interval of the ith region and the fitting straight line, and norm() is a normalization function. The distance is the shortest distance between a point and a straight line.

[0094] It should be understood that It shows the prominence of the dark current density range. The farther away from the normal range of the dark current density range, the greater the possibility of noise. It shows the degree of discreteness of the dark current density range. The larger it is, the more irregular the change of the dark current density range is, and the greater the possibility of it being noise.

[0095] A304, record the dark current density interval with noise probability greater than 0.6 as the noise dark current density interval.

[0096] A305, median filtering is performed on the noise dark current density to obtain corrected dark current density data. The processing process of median filtering is a well-known technology and will not be described in detail.

[0097] The third step is to use the proportion of dark current density in the noise dark current density range in each area to analyze the differences between the adjacent areas before and after it, determine the degree of structural damage in each area, and judge the fault condition of the multi-color infrared detector structure.

[0098] In the second step, all sampling moments are divided into several regions. The proportion of noise points in each region reflects the accuracy of the detector. The more noise, the lower the accuracy, the higher the degree of structural damage, and the higher the fault level. The specific steps are as follows:

[0099] 1. Calculate the noise ratio in any area:

[0100] ;

[0101] Among them, Y is the proportion of noise points in any area, is the number of dark current densities in the noise dark current density interval in the region, and y is the total number of dark current densities in the region.

[0102] 2. Calculate the degree of structural damage in any area:

[0103] ;

[0104] in, represents the degree of structural damage in the sth region, , , are the noise point proportions of the s-1th, sth, and s+1th regions respectively, and norm() represents a normalization function; wherein the noise point proportion is the proportion of the number of dark current densities in the noise dark current density interval in each region to the total number of dark current densities in the region.

[0105] It should be understood that It shows the change of the proportion of noise points in the sth area. The larger it is, the faster the noise will increase, which means the detector's structure is damaging faster and the fault is more serious.

[0106] 3. Judge the structural failure of the multi-color infrared detector according to the degree of structural damage: No adjustment is made when When performing partial maintenance and algorithm correction, It is considered that the fault is relatively serious. In this embodiment, T1 and T2 are respectively set to 0.3 and 0.7, which can be set by the implementer.

[0107] Based on the same inventive concept as the above method, an embodiment of the present application also provides a fault diagnosis system for a multi-color infrared detector, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, wherein when the processor executes the computer program, the steps of a fault diagnosis method for a multi-color infrared detector described in any one of the above methods are implemented.

[0108] The various embodiments in the present application are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

[0109] It should be noted that, unless otherwise specified and limited, terms such as "include", "comprises" or any other variants thereof are intended to cover non-exclusive inclusion, so that a circuit structure, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such article or device. In the absence of further restrictions, an element defined by the sentence "including one..." does not exclude the existence of other identical elements in the article or device including the element. In addition, the term "and\or" used herein includes any and all combinations of one or more related listed items.

[0110] Those skilled in the art will readily appreciate other embodiments of the present application after considering the specification and practicing the invention herein. The present application is intended to cover any variations, uses or adaptations of the present application, which follow the general principles of the present application and include common knowledge or customary technical means in the art that are not invented by the present application.

[0111] It will be appreciated that the present application is not limited to the exact construction that has been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof.

Claims

1. A fault diagnosis method for a multi-color infrared detector, characterized in that: The method comprises the following steps: Obtaining an IV characteristic curve of the multi-color infrared detector at each sampling moment; the IV characteristic curve is composed of dark current densities under different bias voltages; According to the distribution of dark current density at all sampling times, the noise is determined and denoised; specifically: A1, according to the detection rate and quantum efficiency of all bias voltages at any sampling time, determine the degree of structural damage at any sampling time, so as to construct a scatter plot of structural damage degree-time, and divide the piecewise straight line of structural damage degree-time; A2, according to the growth trend of the dark current density with zero bias voltage at all sampling moments, the growth trend of the IV characteristic curve at each sampling moment is removed; A3, using the piecewise straight line of structural damage degree-time, the dark current density at all sampling moments is divided into corresponding regions; the dark current density in each region is converted into frequency domain and divided into dark current density intervals; based on the frequency domain information difference of the same dark current density interval in all regions, the noise possibility of each dark current density interval is calculated, so as to screen out the noisy dark current density interval and perform denoising on it; By using the proportion of dark current density in the noise dark current density range in each area, the difference between the adjacent areas before and after is analyzed, the degree of structural damage in each area is determined, and the fault condition of the multi-color infrared detector structure is judged.

2. A fault diagnosis method for a multi-color infrared detector as claimed in claim 1, characterized in that: The method for determining the degree of structural damage comprises: Obtaining an average level of detection rate at 50% cutoff wavelength corresponding to all bias voltages at the arbitrary sampling time; Obtaining the average level of the maximum values ​​of quantum efficiencies corresponding to all bias voltages at any sampling time; The results of the positive phase fusion of the two average levels are subjected to anti-correlation mapping to determine the degree of structural damage at the arbitrary sampling moment.

3. A fault diagnosis method for a multi-color infrared detector as claimed in claim 1, characterized in that: The segmentation method of the structural damage degree-time segmented straight line is: A region growing algorithm is used for all data points in the scatter plot. The condition for region growing is that the difference between the slope of the line connecting adjacent data points and the slope of the line connecting the previous adjacent data points is less than a preset growth threshold. A straight line is fitted to the data points in each growth area to obtain a piecewise straight line of structural damage degree-time.

4. A fault diagnosis method for a multi-color infrared detector as claimed in claim 1, characterized in that: The method for removing the growth trend is: ； in, It represents the IV characteristic curve after the growth trend is removed at sampling time t. To adjust the preset coefficients for dark current data stability, It represents the degree of structural damage on the piecewise straight line of structural damage degree-time at sampling time t, The IV characteristic curve at sampling time t is shown.

5. A fault diagnosis method for a multi-color infrared detector as claimed in claim 4, characterized in that: The selection condition of the preset coefficient for adjusting the stability of the dark current data is: after fitting the dark current density when the bias voltage is 0 in the IV characteristic curve after removing the growth trend at all sampling moments into a straight line, the slope of the straight line falls within a preset range.

6. A fault diagnosis method for a multi-color infrared detector as claimed in claim 1, characterized in that: The dark current density interval division method is: dark current densities belonging to the same order of magnitude after frequency domain conversion are grouped into a dark current density interval.

7. A fault diagnosis method for a multi-color infrared detector as claimed in claim 1, characterized in that: The calculation expression of the noise possibility is: ； Where P represents the noise probability of the dark current density interval, C represents the mean of the dark current density interval, It represents the average level of the mean of all regions in this dark current density range, I represents the number of regions, represents the distance between the occurrence frequency of the dark current density in the dark current density interval of the ith region and the fitting straight line, norm() is a normalization function, and the fitting straight line is obtained by linear fitting of the occurrence frequency of the dark current density in all regions of the same dark current density interval.

8. A fault diagnosis method for a multi-color infrared detector as claimed in claim 1, characterized in that: The determination expression of the structural damage degree is: ； in, represents the degree of structural damage in the sth region, , , are the noise point proportions of the s-1th, sth, and s+1th regions respectively, and norm() represents a normalization function; wherein the noise point proportion is the proportion of the number of dark current densities in the noise dark current density interval in each region to the total number of dark current densities in the region.

9. A fault diagnosis system for a multi-color infrared detector, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the computer program, the processor implements the steps of a fault diagnosis method for a multi-color infrared detector as described in any one of claims 1-8.

Images