Insulation pollution developing method and device, terminal and medium

Abstract

The invention discloses an insulation pollution developing method and device, a terminal and a medium, and the method is characterized in that the method comprises the following steps: collecting a plurality of insulation pollution images through a plurality of spectrum channel imaging sensors, and analyzing the dispersion of the gray values of the plurality of insulation pollution images; if the dispersion is lower than a preset threshold, outputting a plurality of insulation pollution images; and if the dispersion is higher than or equal to a preset threshold, dynamically updating the gains of the plurality of spectral channel imaging sensors until the dispersion is lower than the preset threshold, updating the configuration of the sensors by using the gains, and outputting a plurality of insulation pollution images. Through cooperation of a gain iterative optimization algorithm and hardware, light flux compensation can be realized by utilizing gain adjustment of the imaging chip, and the quality of an initial image is remarkably improved.

Description

Technical Field

[0001] The present invention relates to the field of power systems, and more specifically, to an insulation contamination development method and system. Background Art

[0002] Line insulators or power equipment bushings bear the mechanical support and electrical insulation between transmission lines and transmission towers, and between power equipment and processing lines. However, since insulators or bushings work in outdoor atmospheric environments for a long time, dirt will inevitably accumulate on the surface of the insulator to form a dirt layer, which greatly increases the risk of surface flashover of the insulator. Studies have shown that the important factors affecting the flashover voltage of insulator pollution are the degree of dirtiness and the distribution of dirtiness. The former is mainly analyzed by the determination of equivalent salt density and ash density. It is necessary to obtain insulator dirtiness by simulating the tower insulator string or artificial line sampling, and use the laboratory offline method to evaluate its dirtiness value based on the equivalent leakage current value. The latter dirtiness distribution is currently mainly obtained through visible light or infrared images. This method can obtain data online and contactlessly, but when the dirtiness is difficult to distinguish from the color of the insulator body in a wide spectral range or when the boundary is simulated, the dirtiness distribution will be difficult to distinguish.

[0003] The existing non-contact image detection methods for the contamination status of insulators are mainly infrared thermal imaging and ultraviolet solar blind imaging. Infrared thermal imaging uses infrared detectors and optical imaging lenses to collect infrared radiation signals generated by the heat of contaminated insulators under high-voltage environments to establish infrared thermal images of the insulator surface, convert the invisible infrared energy emitted by the object into a visible image, and use the surface temperature distribution characteristics of the insulator to build a surface contamination analysis algorithm to detect the contamination status of the insulator. However, infrared thermal imagers rely on the temperature difference of the target object for imaging. If the overall temperature difference of the insulator is small, the thermal image has poor resolution for its surface details. At the same time, the difference in its own parameters will also lead to an unpredictable deviation between the imaging temperature and the actual temperature, and the heat caused by the aging of the insulator will have a greater impact on the detection results. Solar-blind ultraviolet discharge imaging can capture the contamination discharge spot of the insulator through ultraviolet solar-blind images when the contaminated insulator meets the discharge conditions, thereby reflecting its contamination status. It can effectively and intuitively observe the discharge conditions of contaminated insulators, and provides a powerful diagnostic method for live detection. However, the small amount of information obtained in the narrow ultraviolet solar-blind band is difficult to accurately characterize the surface contamination characteristics of the insulator, and it is impossible to conduct a comprehensive and comprehensive evaluation of the contamination status of the insulator.

[0004] In general, the degree of insulator contamination is unlikely to cause a significant increase in surface leakage current or surface electric field distortion. Severe heating and abnormal corona of insulators often lack sufficient conditions to produce. Therefore, infrared imaging and ultraviolet day-blind imaging are not sensitive to insulator contamination. Multi-band imaging technology is an imaging method that has been widely studied in recent years and widely used in forestry, agriculture, mining, medicine and other fields. At present, the application of multi-band imaging technology in insulator detection is in its initial stage. Its ability to detect insulator contamination has been experimentally confirmed and has been applied on a certain scale. This method has shown outstanding advantages in portability, economy and diagnostic ability. However, its main problem is that the adjustment of spectral channel parameters often depends on field experience. Inappropriate channel sensitivity coordination will lead to failure of imaging of insulator contamination areas. This problem has become the main bottleneck affecting the field application of multi-band imaging.

[0005] In view of the above problems, there is an urgent need for an insulating contamination developing method and device. Summary of the invention

[0006] In order to solve the deficiencies in the prior art, the present invention provides a method and device for developing insulating contamination, which can optimize and adjust the sensitivity of a multi-channel target area to obtain different types of contamination development.

[0007] The present invention adopts the following technical solution.

[0008] A first aspect of the present invention relates to a method for developing insulation contamination, which comprises the following steps: using multiple spectral channel imaging sensors to collect multiple insulation contamination images, analyzing the discreteness of the grayscale values ​​of the multiple insulation contamination images; if the discreteness is lower than a preset threshold, outputting multiple insulation contamination images; if the discreteness is higher than or equal to the preset threshold, dynamically updating the gains of the multiple spectral channel imaging sensors until the discreteness is lower than the preset threshold, and using the gain to update the sensor configuration and output multiple insulation contamination images.

[0009] Preferably, a plurality of insulation contamination images are collected using a plurality of spectral channel imaging sensors, including: each of the plurality of spectral channel imaging sensors uses an optical lens having a different spectral transmission rate from a sensor in the other plurality of spectral channel imaging sensors.

[0010] Preferably, the spectral transmittances of optical lenses with different spectral transmittances are respectively determined by the radiation spectrum bands of iron oxide, calcium sulfate, sodium chloride, kaolin, copper sulfate, silicon dioxide and calcium chloride; and at least one of the optical lenses is not set with a spectral transmittance.

[0011] Preferably, analyzing the discreteness of the grayscale values ​​of multiple insulating contamination images includes: collecting synchronous imaging data of 1 to n spectral channel imaging sensors at the mth time sequence; using a pixel registration method to achieve registration between the synchronous imaging data of multiple spectra passing through the imaging sensor to obtain a registered image; extracting contaminated areas from multiple registered images, calculating the total grayscale of the contaminated area in each image to be registered, and analyzing the discreteness of the total grayscale of the contaminated area in the multiple registered images.

[0012] Preferably, the total grayscale dispersion of the dirty areas in the multiple registered images is L m for:

[0013]

[0014] and, g m,i is the total grayscale of the ith spectral channel imaging sensor among 1 to n spectral channel imaging sensors at the mth time sequence.

[0015] Preferably, the gain is used to update and output multiple insulation pollution images, including: if the discreteness at the mth time sequence is greater than or equal to a preset threshold, dynamically updating the gains of multiple spectral channel imaging sensors; wherein the gain of the i-th spectral channel imaging sensor at the m+1th time sequence is described as and:

[0016]

[0017] g i is the total grayscale of multiple registered images corresponding to the imaging sensor of the i-th spectral channel;

[0018] Continue to determine whether the discreteness at the (m+1)th time sequence is higher than or equal to the preset threshold; if not, continue to cyclically update the gains of the multiple spectral channel imaging sensors until the discreteness is higher than or equal to the preset threshold.

[0019] The second aspect of the present invention relates to an insulating contamination developing device, which is implemented using the method described in the first aspect of the present invention; wherein the device includes a replaceable filter array, an optical lens module array, a spectral imaging array, a photosensitivity controller and an image processing unit connected in sequence; the replaceable filter array uses an ion sputtering coating method to process the surface of a fused quartz glass sheet to form a plurality of different circular filter units, and form a rectangular array; the light transmittance of each lens in the optical lens module array is electrically controlled, and the electrically controlled adjustment method uses the gains of multiple spectral channel imaging sensors calculated in an insulating contamination developing method as an adjustment basis.

[0020] Preferably, the thickness of the fused quartz glass sheet after coating does not exceed 1 mm, and the minimum gap between the sheet and the optical lens module does not exceed 0.3 mm; each circular filter covers the light-incoming area of ​​the optical lens, and the area around the filter is filled with light-absorbing material.

[0021] A third aspect of the present invention relates to a terminal, comprising a processor and a storage medium; the storage medium is used to store instructions; the processor is used to operate according to the instructions to execute the steps of the method described in the first aspect of the present invention.

[0022] A fourth aspect of the present invention relates to a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method in the first aspect of the present invention.

[0023] The beneficial effect of the present invention is that, compared with the prior art, the present invention provides an insulation contamination development method and device, which obtains different types of contamination development by optimizing and adjusting the sensitivity of the multi-channel target area. The insulation contamination development method with optimized and adjusted sensitivity of the multi-channel target area proposed by the present invention optimizes and adjusts the photosensitivity of the photoelectric imaging sensor of each channel according to the grayscale feedback of the contamination area of ​​multiple spectral channels, thereby enhancing the display effect of the contamination area on the surface of the insulator and the quantitative evaluation capability of the contamination based on multi-spectral reconstruction, and improving the efficiency of on-site analysis of insulator contamination on transmission lines and the intuitiveness of contamination detection.

[0024] The beneficial effects of the present invention also include:

[0025] 1. Compared with the multi-spectral pollution imaging method based on fixed gain, the present invention adjusts and optimizes the sensitivity according to the pollution area (rather than the entire imaging target), maximizes the photosensitivity of each channel imaging sensor, and is not affected by the photosensitivity effect of the background area, thereby significantly improving the spectral image contrast of the pollution area;

[0026] 2. Compared with the existing universal multi-spectral camera parameter control method, the present invention uses the cooperation of the photosensitive controller and the image processing unit to iterate feedback so that the grayscale intensity of the contaminated target area of ​​each channel remains consistent, thus providing a guarantee for the quality of spectral image reconstruction;

[0027] 3. Compared with the existing digital image post-processing methods, the gain iteration optimization algorithm and hardware coordination can utilize the gain adjustment of the imaging chip itself to achieve light transmission compensation, and the quality of the initial image is significantly improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 A schematic diagram of a multi-channel spectral imaging device in an insulating contamination developing method of the present invention;

[0029] Figure 2A schematic diagram of a process of photosensitive control and image processing in a method for developing insulating contamination according to the present invention;

[0030] Figure 3 It is a schematic diagram of the fixed gain multi-spectral contamination imaging effect in an insulating contamination development method of the present invention;

[0031] Figure 4 The present invention is a schematic diagram of the multi-spectral contamination imaging effect of iterative gain in an insulating contamination development method. DETAILED DESCRIPTION

[0032] In order to make the purpose, technical scheme and advantages of the present invention clearer, the technical scheme of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. The embodiments described in the present invention are only embodiments of a part of the present invention, not all embodiments. Based on the spirit of the present invention, all other embodiments not recorded in the present invention obtained by ordinary technicians in this field according to the embodiments recorded in the present invention without making creative work should belong to the protection scope of the present invention.

[0033] The main detection objects of infrared temperature imaging and solar-blind ultraviolet imaging are the heating or discharge caused by insulator contamination, not the contamination target itself. It is worth noting that contamination is one of the inducing factors for heating and discharge, and under normal conditions it does not manifest as heating or discharge. Therefore, the above two imaging detection technologies cannot effectively detect the contamination situation in the early stage of insulator heating and discharge failure.

[0034] At the same time, multi-band imaging technology has been experimentally confirmed in insulator detection and has been initially applied. However, its main problem is that the adjustment of spectral channel parameters often relies on on-site experience. Inappropriate channel sensitivity coordination will lead to failure in the development of insulator contaminated areas. In addition, the sensitivity or gain of each channel of existing non-coaxial multi-spectral imaging devices is mostly fixed, and it will not make adaptive adjustments based on the contaminated target area itself, which is not conducive to the subsequent multi-spectral image reconstruction and quantitative evaluation of contaminated areas.

[0035] Figure 1 FIG. 1 is a schematic diagram of a multi-channel spectral imaging device in a method for developing insulating contamination according to the present invention. Figure 1 As shown, the first aspect of the present invention relates to a method for developing insulating contamination, which includes steps 1 and 2.

[0036] Step 1: collect multiple insulation contamination images using multiple spectral channel imaging sensors, and analyze the discreteness of the grayscale values ​​of the multiple insulation contamination images.

[0037] Multiple spectral channel imaging sensors are used to collect multiple insulation pollution images, including: each of the multiple spectral channel imaging sensors uses an optical lens with a different spectral pass rate from one of the other multiple spectral channel imaging sensors.

[0038] The present invention relates to an insulating contamination developing method with optimized sensitivity adjustment of a multi-channel target area, comprising a set of multi-channel spectral imaging devices with adjustable sensitivity and a set of target area sensitivity control logic. The multi-channel spectral imaging device with adjustable sensitivity comprises: a replaceable filter array, a spectral imaging array, a photosensitive controller and an image processing unit.

[0039] The replaceable filter array uses an ion sputtering coating method to process the surface of the fused quartz glass sheet to form a plurality of different circular filter units and form a rectangular array. The optical parameters of the filter are selected according to the reflection spectrum of the shooting target. The thickness of the fused quartz glass sheet after coating does not exceed 1mm, and the minimum gap between the optical lens module does not exceed 0.3mm. Each circular filter should effectively cover the light-incoming area of ​​the optical lens. The filter is filled with light-absorbing material to prevent light interference caused by the overflow of incident light from the filter.

[0040] The spectral transmittances of the optical lenses with different spectral transmittances are respectively determined by the reflection spectral bands of iron oxide, calcium sulfate, sodium chloride, kaolin, copper sulfate, silicon dioxide and calcium chloride; at least one of the optical lenses is not set with a spectral transmittance.

[0041] Optical lens module array. A rectangular array is formed by using multiple optical lenses with different spectral transmittances. The spectral range of each lens should be determined according to the sensitive reflection spectral band of insulating contaminants and should not exceed the range of 300nm to 790nm. The transmittance within the spectral range should be greater than 90%. The light flux F of each lens in the array can be adjusted by electrical control, and the F adjustment range covers 1 / 1.4 to 1 / 22.

[0042] The spectral imaging array is made of imaging sensors with the same technical parameters and forms a coplanar array, with n imaging sensor units. The sensor spectral response range should cover the range of 300nm to 790nm, the light quantum efficiency (QE) should be higher than 30%, the pixel (P) should not be less than 640×480px, the dark noise (DN) should be lower than 5e, and the signal-to-noise ratio (SNR) should not be lower than 40dB. The photosensor controller is controlled by the upper image processing unit and executes the gain adjustment logic flow issued by the image processing unit; its working principle is to convert the gain value sequence issued by the image processing unit into the imaging sensor gain level control signal.

[0043] The discreteness of grayscale values ​​of multiple insulating contaminated images is analyzed, including: collecting synchronous imaging data of 1 to n spectral channel imaging sensors at the mth time sequence; using a pixel registration method to realize the registration between the synchronous imaging data of multiple spectra passing through the imaging sensor to obtain a registered image; extracting contaminated areas from multiple registered images, calculating the total grayscale of the contaminated area in each image to be registered, and analyzing the discreteness of the total grayscale of the contaminated area in the multiple registered images.

[0044] Set the deviation tolerance s, and the image processing unit reads the mth synchronous imaging data from the imaging sensors of each spectral channel from 1 to n. The upper image processing unit performs pixel registration on the image data from 1 to n, and the registration rate should not be less than 95%. The upper image processing unit extracts the dirty area from the images from 1 to n. And calculate the total gray value vector G in the dirty area m .

[0045] G m =[g m,1 ,g m,2 ,…g m,n ]

[0046] Among them, the total gray value g of the dirty area in the i-th image m,i :

[0047]

[0048] The total grayscale dispersion of the dirty area in multiple registered images L m for:

[0049]

[0050] and, g m,i is the total grayscale of the ith spectral channel imaging sensor among 1 to n spectral channel imaging sensors at the mth time sequence.

[0051] Step 2: if the discreteness is lower than a preset threshold, multiple insulation contamination images are output; if the discreteness is higher than or equal to the preset threshold, the gains of multiple spectral channel imaging sensors are dynamically updated until the discreteness is lower than the preset threshold, and the gains are used to update and output multiple insulation contamination images.

[0052] The gain is used to update and output multiple insulation pollution images, including: if the discreteness at the mth time sequence is greater than or equal to a preset threshold, the gain of multiple spectral channel imaging sensors is dynamically updated; wherein the gain of the i-th spectral channel imaging sensor at the m+1th time sequence is described as and:

[0053]

[0054] g i is the total gray value of multiple registered images corresponding to the imaging sensor of the i-th spectral channel;

[0055] Continue to determine whether the dispersion at the (m + 1)-th time sequence is higher than or equal to the preset threshold. If not, continue to loop and update the gains of the multiple spectral channel imaging sensors until the dispersion is higher than or equal to the preset threshold.

[0056] When RSDm < s, retain the image data of each spectral channel from No. 1 to No. n, and end the process; when RSDm ≥ s, update the gain value sequence of the imaging sensors from No. 1 to No. n according to the total gray values of the images from No. 1 to No. n ( i = 1 to n). Update the gain value sequence of the imaging sensors ( i = 1 to n; m = m + 1), and the image processing unit issues this gain value sequence to the photosensitive controller.

[0057] Figure 2 is a schematic diagram of the photosensitive control and image processing process in an insulating contamination development method of the present invention. As Figure 2 shown, the photosensitive controller converts the sensor gain value sequence into an imaging gain level control signal and adjusts the gains of each imaging sensor. Repeat the above optimization iteration loop until RSD m < s.

[0058] Figure 3 is a schematic diagram of the imaging effect of fixed-gain multi-spectral contamination in an insulating contamination development method of the present invention. In the prior art, the fixed-gain multi-spectral contamination imaging method cannot accurately obtain the contamination states of insulators of different materials.

[0059] Figure 4 is a schematic diagram of the imaging effect of iterative-gain multi-spectral contamination in an insulating contamination development method of the present invention. As Figure 4 shown, the number of imaging sensor units n = 7, and the spectral ranges of each lens are respectively: 350nm ± 25nm, 435nm ± 25nm, 485nm ± 25nm, 535nm ± 25nm, 590nm ± 25nm, 645nm ± 25nm, 705nm ± 25nm, and the deviation allowable value s = 2%.

[0060] In the m-th imaging, the contamination image data of the silicone rubber surface in 7 spectral channels can be obtained. Pixel registration is performed on the contamination image data of the 7 spectral channels to ensure that the registration rate is not lower than 95%. If RSD m < 2%, then retain the image data of all spectral channels and end the process. If RSD m ≥ 2%, then update the gain value of each imaging sensor: i = 1 to 7. Among them is the gain value of the i-th imaging sensor in the current m-th imaging. The photosensitive controller converts the gain value sequence into an imaging gain level control signal and adjusts the gain of each imaging sensor. Repeat the above steps until RSD m <2%.

[0061] In this embodiment, in the first imaging (m=1), the following total gray value vector is obtained:

[0062] G1=[150.1,160.3,155.1,145.0,140.2,164.9,150.0]

[0063] Calculate the average:

[0064]

[0065] Calculate Lm:

[0066]

[0067] Update the gain value:

[0068] Issue gain command and adjust gain: Update the gain value sequence Sent to the photosensitive controller.

[0069] Repeat the optimization iteration: Repeat the above steps until RSD m <2%.

[0070] The image processing unit processes and feeds back the image information of the imaging sensor array. The process includes: image registration, calculation of the total gray value of the dirty area, deviation judgment, imaging sensor gain calculation and gain value sequence issuance. The above process adopts a feedback closed loop method until the target value is reached.

[0071] The contrast ratios of various single or mixed contamination areas including Fe2O3, CaSO4, NaCl, Kaolin, CuSO4, SiO2, CaCl2, etc. on the insulator samples obtained by the present invention are significantly improved.

[0072] Compared with the multi-spectral pollution imaging method based on fixed gain, the sensitivity optimization of the present invention does not depend on the entire image, but is determined by the pollution area itself, and can optimize the contrast of the pollution area imaged in each channel, thereby improving the spectral image reconstruction and quantitative evaluation effect of the insulating pollution area; compared with the existing universal multi-spectral camera parameter control method, the present invention ensures that the grayscale intensity of the pollution target area remains consistent through the iterative cooperation of the photosensitive controller and the image processing unit, thereby providing a guarantee for the stability of the spectral image reconstruction quality; compared with the existing digital image post-processing method, the gain iterative optimization algorithm and hardware cooperation can use the gain adjustment of the imaging chip itself to achieve light transmission compensation, and the quality of its initial image is significantly improved.

[0073] The second aspect of the present invention relates to an insulating contamination developing device, which is implemented using the method described in the first aspect of the present invention; wherein the device includes a replaceable filter array, an optical lens module array, a spectral imaging array, a photosensitivity controller and an image processing unit connected in sequence; the replaceable filter array uses an ion sputtering coating method to process the surface of a fused quartz glass sheet to form a plurality of different circular filter units, and form a rectangular array; the light transmittance of each lens in the optical lens module array is electrically controlled, and the electrically controlled adjustment method uses the gains of multiple spectral channel imaging sensors calculated in an insulating contamination developing method as an adjustment basis.

[0074] The thickness of the fused quartz glass sheet after coating does not exceed 1 mm, and the minimum gap between the sheet and the optical lens module does not exceed 0.3 mm; each circular filter covers the light-incoming area of ​​the optical lens, and the area around the filter is filled with light-absorbing material.

[0075] The spectral imaging array is made of imaging sensors with the same technical parameters and forms a coplanar array, with n imaging sensor units. The sensor spectral response range should cover the range of 300nm to 790nm, the light quantum efficiency (QE) should be higher than 30%, the pixel (P) should not be less than 640×480px, the dark noise (DN) should be lower than 5e, and the signal-to-noise ratio (SNR) should not be lower than 40dB.

[0076] A third aspect of the present invention relates to a terminal, comprising a processor and a storage medium; the storage medium is used to store instructions; the processor is used to operate according to the instructions to execute the steps of the method described in the first aspect of the present invention.

[0077] A fourth aspect of the present invention relates to a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method in the first aspect of the present invention.

[0078] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents, and any modifications or equivalent replacements that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A method for developing insulating contamination, characterized in that: The method comprises the following steps: Using multiple spectral channel imaging sensors to collect multiple insulation contamination images, and analyzing the discreteness of the grayscale values ​​of the multiple insulation contamination images; If the discreteness is lower than a preset threshold, a plurality of insulation contamination images are output; If the discreteness is higher than or equal to the preset threshold, the gains of multiple spectral channel imaging sensors are dynamically updated until the discreteness is lower than the preset threshold, and the sensor configuration is updated using the gain to output multiple insulation contamination images.

2. The insulating contamination developing method according to claim 1, characterized in that: The method of collecting multiple insulation pollution images using multiple spectral channel imaging sensors includes: Each of the plurality of spectral channel imaging sensors uses an optical lens having a spectral transmittance different from that of one of the other plurality of spectral channel imaging sensors.

3. The insulating contamination developing method according to claim 2, characterized in that: The spectral transmission rates of the optical lenses with different spectral transmission rates are respectively determined by the radiation spectrum bands of iron oxide, calcium sulfate, sodium chloride, kaolin, copper sulfate, silicon dioxide, and calcium chloride; At least one of the optical lenses is not set with a spectral transmittance.

4. The insulating contamination developing method according to claim 1, characterized in that: The analyzing the discreteness of the grayscale values ​​of the plurality of insulation contamination images includes: Collecting synchronous imaging data of 1 to n spectral channel imaging sensors at the mth time sequence; A pixel registration method is used to realize registration between synchronous imaging data of multiple spectra passing through an imaging sensor to obtain a registered image; The dirty areas are extracted from multiple registered images, the total grayscale of the dirty areas in each image to be registered is calculated, and the discreteness of the total grayscale of the dirty areas in multiple registered images is analyzed.

5. The insulating contamination developing method according to claim 4, characterized in that: The total grayscale dispersion of the dirty area in multiple registered images L m for: and, g m,i is the total grayscale of the i-th spectral channel imaging sensor among 1 to n spectral channel imaging sensors at the m-th time sequence.

6. The insulating contamination developing method according to claim 5, characterized in that: The method of updating and outputting a plurality of insulation pollution images by using the gain includes: If the discreteness at the mth time sequence is higher than or equal to the preset threshold, the gains of the imaging sensors of the multiple spectral channels are dynamically updated; Among them, the gain of the imaging sensor of the i-th spectral channel at the m+1th time sequence is described as and: g i is the total grayscale of multiple registered images corresponding to the imaging sensor of the i-th spectral channel; Continue to determine whether the discreteness at the (m+1)th time sequence is higher than or equal to the preset threshold; if not, continue to cyclically update the gains of the multiple spectral channel imaging sensors until the discreteness is higher than or equal to the preset threshold.

7. An insulating contamination developing device, characterized in that: The device is implemented using the method described in any one of claims 1 to 6; wherein, The device comprises a replaceable filter array, an optical lens module array, a spectral imaging array, a photosensor controller and an image processing unit which are connected in sequence; The replaceable filter array uses an ion sputtering coating method to process the surface of a fused silica glass sheet to form a plurality of different circular filter units and form a rectangular array; The light flux of each lens in the optical lens module array is adjusted by an electronic control method, and the electronic control method uses the gains of multiple spectral channel imaging sensors calculated in an insulating contamination development method as an adjustment basis.

8. The insulating contamination developing device according to claim 7, characterized in that: The thickness of the coated fused quartz glass sheet does not exceed 1 mm, and the minimum gap between the sheet and the optical lens module does not exceed 0.3 mm; Each circular filter covers the light-incoming area of ​​the optical lens, and the area around the filter is filled with light-absorbing material.

9. A terminal comprising a processor and a storage medium; characterized in that: The storage medium is used to store instructions; The processor is configured to operate according to the instructions to execute the steps of the method according to any one of claims 1-6.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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