CN114372230A - Photovoltaic module EL test evaluation system and method based on battery efficiency - Google Patents
Photovoltaic module EL test evaluation system and method based on battery efficiency Download PDFInfo
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Abstract
The invention discloses a photovoltaic module EL test evaluation system and method based on battery efficiency, the system comprises a battery piece parameter acquisition module to be tested, an EL test image problem preprocessing identification module, a defective battery piece EL image performance analysis module, a same batch of battery piece EL image failure reason analysis module and different EL image program control modules, and aims to systematically and accurately identify battery piece EL test images, analyze defect reason types of EL tests in a programmed manner, judge defects of each battery piece for multiple times and improve the detection efficiency of the battery piece EL images.
Description
Technical Field
The invention relates to the field of photovoltaics, in particular to a photovoltaic module EL test evaluation system and method based on battery efficiency.
Background
In recent years, along with the rapid development of photovoltaic occupations, the test method in the quality control link of a photovoltaic module is continuously enhanced, and the original appearance and electric function test is far from satisfying the requirements of the occupations. The existing method for testing potential defects of the silicon solar cell and the silicon solar cell module is widely selected as an EL test in the professional field, and the EL test skill is used by a plurality of manufacturers of the crystalline silicon solar cell and the silicon solar cell module at present and is used for product inspection or online product quality control of the crystalline silicon solar cell and the silicon solar cell module.
In the solar cell, the dispersion length of minority carriers is far greater than the width of the potential barrier, so that the probability of disappearance due to recombination when electrons and holes pass through the potential barrier is small, and the minority carriers are continuously dispersed towards the dispersion difference. Under forward bias voltage, a small amount of carriers are injected into the p-n junction barrier region and the dispersion region, and the nonequilibrium small amount of carriers are continuously compounded with the majority of carriers to emit light, which is the basic principle of the electroluminescence of the solar cell. Luminescence imaging usefully exploits the radiative recombination effect in the solar interband that excites the electron-mediator. Photons joining forward bias at both ends of the solar cell can be acquired by a sensitive ccd camera, i.e. the radiation composite scattering picture of the solar cell is obtained. However, the electroluminescent intensity is very low and the wavelength is in the near infrared region, so that the camera must have very high sensitivity and very low noise at 900-1100 nm.
The process of the EL test is that a forward bias voltage is applied to the crystalline silicon solar cell, a direct-current power supply injects a plurality of unbalanced cut-off photons into the crystalline silicon solar cell, and the solar cell continuously performs compound luminescence by relying on a plurality of unbalanced cut-off photons injected from a dispersion area to emit photons, namely the reverse process of the photovoltaic effect; the photons are captured by the ccd camera, processed by the computer and displayed in a picture mode, and the whole process is carried out in a darkroom.
The brightness of the picture tested by the EL is in direct proportion to the minority carrier lifetime and the current density of the cell, the minority carrier dispersion length is lower in the solar cell with defects, and then the brightness of the displayed picture is darker. Through analysis of EL test pictures, hidden defects of solar cells and components can be clearly found, and the defects comprise silicon data defect dispersion defects, printing defects, sintering defects, cracks in component packaging process and the like.
Common defects of the EL test are broken pieces, hidden cracks, broken grids, sintered defects, black chips and the like, the defects are usually manually identified, the labor cost is high, the defect types of the battery pieces and whether the battery pieces are invalid or not can not be accurately grasped by manual identification, the method aims at systematically identifying the EL test images of the battery pieces accurately, analyzing the defect reason types of the EL test in a programmed mode, judging the defects of each battery piece for multiple times and improving the detection efficiency of the EL images of the battery pieces.
Disclosure of Invention
The invention aims to provide a photovoltaic module EL test evaluation system and method based on battery efficiency, so as to solve the problems in the prior art.
In order to achieve the purpose, the invention provides the following technical scheme:
a photovoltaic module EL test evaluation system based on battery efficiency comprises an EL tester, the system comprises a battery piece parameter acquisition module to be tested, an EL test image problem preprocessing identification module, a defective battery piece EL image performance analysis module, a same batch of battery piece EL image failure reason analysis module and different EL image program control modules, wherein the battery piece parameter acquisition module to be tested, the EL test image problem preprocessing identification module and the defective battery piece EL image performance analysis module are sequentially connected through an intranet and are respectively connected with the different EL image program control modules through the intranet;
the device comprises a battery piece parameter acquisition module to be tested, an EL test image problem preprocessing identification module, a battery piece EL image performance analysis module, a battery piece EL image failure reason analysis module, a battery piece failure reason ratio analysis module, a battery piece parameter acquisition module, an EL image program control module and an EL image program control module, wherein the battery piece parameter acquisition module is used for monitoring characteristic parameters of a battery piece to be tested and an EL tester and judging whether a test environment is proper or not, the EL test image problem preprocessing identification module is used for preprocessing an EL test image of the battery piece, intelligently detecting defects and distortion of each EL image, secondarily testing the EL image of the battery piece with the defects, the defective battery piece EL image performance analysis module is used for judging whether the battery piece fails according to the reasons of the defects of the EL image and analyzing the battery piece battery efficiency of the battery piece without all failures, the battery piece EL image failure reasons of the same batch of the battery piece are used for counting the reasons of the battery pieces in the same batch, analyzing the battery piece failure reason ratio data, the battery piece with the defects are marked and repaired, the different EL image program control modules are used for storing and calling the EL images at different moments in real time, and (5) manual intervention.
Further setting: the battery piece parameter acquisition module to be tested comprises a test piece characteristic parameter marking submodule and an EL tester multi-position parameter marking submodule, wherein the test piece characteristic parameter marking submodule is used for detecting the length, the width and the thickness of a battery piece to be tested, detecting the light intensity of the environment of the battery piece to be tested and counting detection data, the EL tester multi-position parameter marking submodule comprises a main EL tester and a plurality of standby EL testers, a three-dimensional coordinate system is formed by the length, the width and the height of the battery piece to be tested from the EL testers to mark position information parameters of different EL testers, three-dimensional coordinate points of the main EL tester and the plurality of standby EL testers are counted, and the counted data are sent to different EL image program control modules for data backup.
Further setting: the EL test image problem preprocessing and identifying module comprises a battery piece EL test image processing and judging submodule and a standby EL tester secondary test calling submodule, wherein the battery piece EL test image processing and judging submodule is used for preprocessing a battery piece image detected by the EL tester and identifying whether defects exist in different EL images or whether distortion exists in the different EL images, identifying and marking the defects of the EL image, giving real-time early warning to image distortion, calling the secondary test calling submodule of the standby EL tester for carrying out secondary EL test on the battery piece to be identified and marked, retransmitting the tested EL image to the battery piece EL test picture processing and judging submodule for carrying out defect judgment, and when the EL image detected for the second time is inconsistent with the EL image detected for the first time, calling the standby EL tester to perform detection for the third time and then performing defect judgment again.
Further setting: the defective cell EL image performance analysis module comprises a defective cell dark part area ratio analysis submodule and a defective cell efficiency estimation analysis submodule, the defective cell dark part area ratio analysis submodule is used for virtually marking the shadow of each cell EL image, the reason of the shadow of each cell is classified according to the reason of the shadow of the cell judged by the EL test image problem preprocessing identification module, the shadow reason of each cell is rejected, the cell EL test image which is directly judged to be invalid is rejected, the shadow area ratio in the rest cell EL test images is analyzed to determine whether the cell with the shadow EL test image is invalid, and the defective cell efficiency estimation analysis submodule is used for analyzing and estimating the cell efficiency of the cell which is not invalid.
Further setting: the analysis submodule for dark part area ratio of the defective cell judges the shape of the shadow area in the EL test image of the cell, measures the distance from the position of the shadow center point to any three points on the outermost side of the shadow, wherein the angle between the straight line connecting each point and the center point and the straight line connecting the other point and the center point is more than 90 degrees, and sets the distance between the position of the shadow center point and any three points on the outermost side of the shadow as rn-1、rn、rn+1The shadow area inside the marked EL image is estimated according to the formula:
when r isn-1＝rn＝rn+1N is 1, when r isn-1≠rn≠rn+1And n is taken as 2, calculating to obtain the shadow area inside each marked cell EL image, and setting different shadow areas inside the marked cell EL images as S1、S2、S3、...、Sn-1、SnSetting the length and width of the marked cell slice to be ln、lmSetting the shadow area ratio inside the cell EL test image to satisfy the following formula:
when the shadow area inside the battery piece EL test image meets the formula, the current shadow area is judged to have little influence on the power of the battery piece, the battery piece cannot be invalid, and when the shadow area inside the battery piece EL test image does not meet the formula, the current shadow area inside the EL test image is judged to cause the battery piece to be invalid, and the battery piece is subjected to invalidation marking.
Further setting: the method comprises the steps that a defective cell efficiency estimation analysis submodule extracts an EL image of a cell marked to have an EL image shadow but not to be invalid, screens a position structure of a shadow part of the EL image, divides the position structure of the EL image shadow into three types including a position parallel to a main grid line, a position inclined to the main grid line and a position perpendicular to the main grid line, judges that the cell efficiency of the defective cell is 50% of the cell efficiency of a normal cell when the position structure of the shadow part of the EL image of a certain cell is parallel to the main grid line, judges that the cell efficiency of the defective cell is 80% of the cell efficiency of the normal cell when the position structure of the shadow part of the EL image of the certain cell is inclined to the main grid line, and judges that the cell efficiency loss of the cell cannot be caused by the EL image shadow when the position structure of the shadow part of the EL image of the certain cell is perpendicular to the main grid line.
Further setting: the same batch of battery piece failure reason analysis module comprises a defective battery piece failure analysis statistics submodule and a defective battery piece repair marking submodule, wherein the defective battery piece failure analysis statistics submodule is used for summarizing reasons causing battery piece defects in the same batch of battery piece assemblies, analyzing the proportion of the number of battery pieces caused by each defect reason in the total number of the defective battery pieces, marking different reasons causing the defects and feeding back the results to different EL image program control modules, the defective battery piece repair marking submodule is used for carrying out secondary repair marking on the battery pieces with the defects, and the EL test image problem preprocessing and identifying module carries out multiple EL tests on the battery pieces with the secondary repair marks.
Further setting: the different EL image program control modules comprise an EL image storage and collection platform and a manual intervention platform, the EL image storage and collection platform is used for storing images tested by the plurality of EL testers and then calling the images in real time, and the manual intervention platform can perform manual intervention and real-time monitoring on each step of EL testing.
A photovoltaic module EL test evaluation method based on battery efficiency comprises the following steps:
a1: monitoring characteristic parameters of the battery piece to be tested and the EL tester by using a battery piece parameter acquisition module to be tested, and judging whether the environment to be tested is appropriate or not;
a2: the method comprises the following steps of preprocessing an EL test image by utilizing an EL test image problem preprocessing and identifying module, intelligently detecting the defect and distortion of each EL image, and carrying out secondary test on the EL image of the battery with the defect;
a3: judging whether the battery piece fails or not by using a defective battery piece EL image performance analysis module according to the defect reason of the EL image, and analyzing the battery efficiency of the battery piece which does not fail completely;
a4: counting the failure reasons of the battery pieces in the same batch by using an EL image failure reason analysis module of the battery pieces in the same batch, analyzing proportion data of the failure reasons of the battery pieces, and marking and repairing the battery pieces with defects;
a5: and storing the EL images at different moments by using different EL image program control modules, and calling the stored EL images in real time for manual intervention.
Further setting:
a-1, detecting the length, the width and the thickness of a battery piece to be tested by using a test piece characteristic parameter marking submodule, detecting the light intensity of the environment of the battery piece to be tested, counting detection data, wherein the EL tester multi-position parameter marking submodule comprises a main EL tester and a plurality of standby EL testers, marking position information parameters of different EL testers by forming a three-dimensional coordinate system according to the length, the width and the height of the battery piece to be tested from the EL testers, counting three-dimensional coordinate points of the main EL tester and the standby EL testers, and sending the counted data to different EL image program control modules for data backup;
a-2, utilizing a battery piece EL test picture processing and judging submodule to preprocess a battery piece image detected by an EL tester, identifying whether different EL images have defects or distortion, identifying and marking the defects of the EL images, and giving an early warning to the image distortion in real time, using a standby EL tester secondary test calling submodule to call the battery piece with the identified and marked, calling a standby EL tester to carry out secondary EL test on the battery piece, resending the tested EL images to the battery piece EL test picture processing and judging submodule to carry out defect judgment, and calling the standby EL tester to carry out defect judgment again after carrying out three-time detection when the EL images of the secondary detection are inconsistent with the EL images of the primary detection;
a-3, virtually marking the shadow of the EL image of each cell by using a defective cell dark part area ratio analysis submodule, classifying the shadow reason of each cell according to the reason of the generation of the shadow surface of the cell judged by an EL test image problem preprocessing and identifying module, rejecting the EL test image of the cell which is directly judged to be invalid, analyzing the shadow area ratio in the residual EL test image to determine whether the cell with the shadow EL test image is invalid or not, and analyzing and estimating the cell efficiency of the cell which is not invalid by using a defective cell efficiency estimation analysis submodule;
a-4, summarizing the reasons of the battery piece defects in the battery piece assemblies in the same batch by utilizing a defective battery piece failure analysis and statistics submodule, analyzing the proportion of the number of the battery pieces caused by each defect reason in the total number of the defective battery pieces, marking the different causes of the defects and feeding the different causes of the defects back to different EL image program control modules, marking the defective battery piece repairing marking submodule for carrying out secondary repairing marking on the battery piece with the defects, and carrying out multiple EL tests on the battery piece with the secondary repairing marking by utilizing an EL test image problem preprocessing and identifying module;
and A-5, storing and calling the images tested by the plurality of EL testers in real time by using an EL image storage and collection platform, and manually intervening each step of the EL test by using a manual intervening platform to monitor in real time.
Compared with the prior art, the invention has the beneficial effects that: the invention utilizes a battery piece parameter acquisition module to monitor characteristic parameters of a battery piece to be tested and an EL tester, judges whether a testing environment is proper or not, utilizes an EL testing image problem preprocessing identification module to preprocess an EL testing image of the battery piece, intelligently detects the defect and distortion of each EL image, carries out secondary testing on the EL image of the battery piece with the defect, utilizes a defective battery piece EL image performance analysis module to judge whether the battery piece is invalid or not according to the defect reason of the EL image, analyzes the battery efficiency of the battery piece without all failures, utilizes the same batch of battery piece EL image failure reason analysis module to count the failure reason of the battery piece in the same batch, analyzes the proportion data of the failure reason of the battery piece, marks and repairs the battery piece with the defect, utilizes different EL image program control modules to store the EL images at different moments and then calls the EL images in real time, manual intervention;
the method aims to systematically and accurately identify the EL test images of the battery pieces, analyze the defect reason category of the EL test in a programmed manner, judge the defects of each battery piece for many times and improve the detection efficiency of the EL images of the battery pieces.
Drawings
In order that the present invention may be more readily and clearly understood, a more particular description of the invention briefly described above will be rendered by reference to specific embodiments that are illustrated in the appended drawings.
FIG. 1 is a schematic structural diagram of a photovoltaic module EL test evaluation system based on cell efficiency according to the present invention;
FIG. 2 is a schematic diagram illustrating steps of a photovoltaic module EL test evaluation method based on cell efficiency according to the present invention;
FIG. 3 is a schematic diagram illustrating specific steps of a photovoltaic module EL test evaluation method based on cell efficiency according to the present invention;
fig. 4 is a schematic diagram of an implementation process of the photovoltaic module EL test evaluation method based on cell efficiency.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1-4, in an embodiment of the invention, a photovoltaic device EL test evaluation system based on battery efficiency includes an EL tester, the system comprises a battery piece parameter acquisition module to be tested, an EL test image problem preprocessing and identifying module, a defective battery piece EL image performance analysis module, a same batch battery piece EL image failure reason analysis module and different EL image program control modules, wherein, the battery piece parameter acquisition module to be tested, the EL test image problem preprocessing and identifying module and the defect battery piece EL image performance analysis module are connected in turn by an intranet, the EL test image problem preprocessing and identifying module, the defective cell EL image performance analyzing module and the different EL image program control modules are respectively connected with the same batch of cell EL image failure reason analyzing modules through an intranet;
the device comprises a battery piece parameter acquisition module to be tested, an EL test image problem preprocessing identification module, a battery piece EL image performance analysis module, a battery piece EL image failure reason analysis module, a battery piece failure reason ratio analysis module, a battery piece parameter acquisition module, an EL image program control module and an EL image program control module, wherein the battery piece parameter acquisition module is used for monitoring characteristic parameters of a battery piece to be tested and an EL tester and judging whether a test environment is proper or not, the EL test image problem preprocessing identification module is used for preprocessing an EL test image of the battery piece, intelligently detecting defects and distortion of each EL image, secondarily testing the EL image of the battery piece with the defects, the defective battery piece EL image performance analysis module is used for judging whether the battery piece fails according to the reasons of the defects of the EL image and analyzing the battery piece battery efficiency of the battery piece without all failures, the battery piece EL image failure reasons of the same batch of the battery piece are used for counting the reasons of the battery pieces in the same batch, analyzing the battery piece failure reason ratio data, the battery piece with the defects are marked and repaired, the different EL image program control modules are used for storing and calling the EL images at different moments in real time, and (5) manual intervention.
Further setting: the battery piece parameter acquisition module to be tested comprises a test piece characteristic parameter marking submodule and an EL tester multi-position parameter marking submodule, wherein the test piece characteristic parameter marking submodule is used for detecting the length, the width and the thickness of a battery piece to be tested, detecting the light intensity of the environment of the battery piece to be tested and counting detection data, the EL tester multi-position parameter marking submodule comprises a main EL tester and a plurality of standby EL testers, a three-dimensional coordinate system is formed by the length, the width and the height of the battery piece to be tested from the EL testers to mark position information parameters of different EL testers, three-dimensional coordinate points of the main EL tester and the plurality of standby EL testers are counted, and the counted data are sent to different EL image program control modules for data backup.
Further setting: the EL test image problem preprocessing and identifying module comprises a battery piece EL test image processing and judging submodule and a standby EL tester secondary test calling submodule, wherein the battery piece EL test image processing and judging submodule is used for preprocessing a battery piece image detected by the EL tester and identifying whether defects exist in different EL images or whether distortion exists in the different EL images, identifying and marking the defects of the EL image, giving real-time early warning to image distortion, calling the secondary test calling submodule of the standby EL tester for carrying out secondary EL test on the battery piece to be identified and marked, retransmitting the tested EL image to the battery piece EL test picture processing and judging submodule for carrying out defect judgment, and when the EL image detected for the second time is inconsistent with the EL image detected for the first time, calling the standby EL tester to perform detection for the third time and then performing defect judgment again.
Further setting: the defective cell EL image performance analysis module comprises a defective cell dark part area ratio analysis submodule and a defective cell efficiency estimation analysis submodule, the defective cell dark part area ratio analysis submodule is used for virtually marking the shadow of each cell EL image, the reason of the shadow of each cell is classified according to the reason of the shadow of the cell judged by the EL test image problem preprocessing identification module, the shadow reason of each cell is rejected, the cell EL test image which is directly judged to be invalid is rejected, the shadow area ratio in the rest cell EL test images is analyzed to determine whether the cell with the shadow EL test image is invalid, and the defective cell efficiency estimation analysis submodule is used for analyzing and estimating the cell efficiency of the cell which is not invalid.
The analysis submodule for dark part area ratio of the defective cell judges the shape of the shadow area in the EL test image of the cell, measures the distance from the position of the shadow center point to any three points on the outermost side of the shadow, wherein the angle between the straight line connecting each point and the center point and the straight line connecting the other point and the center point is more than 90 degrees, and sets the distance between the position of the shadow center point and any three points on the outermost side of the shadow as rn-1、rn、rn+1The shadow area inside the marked EL image is estimated according to the formula:
when r isn-1＝rn＝rn+1N is 1, when r isn-1≠rn≠rn+1And n is taken as 2, calculating to obtain the shadow area inside each marked cell EL image, and setting different shadow areas inside the marked cell EL images as S1、S2、S3、...、Sn-1、SnSetting the length and width of the marked cell slice to be ln、lmSetting the shadow area ratio inside the cell EL test image to satisfy the following formula:
when the shadow area inside the battery piece EL test image meets the formula, the current shadow area is judged to have little influence on the power of the battery piece, the battery piece cannot be invalid, and when the shadow area inside the battery piece EL test image does not meet the formula, the current shadow area inside the EL test image is judged to cause the battery piece to be invalid, and the battery piece is subjected to invalidation marking.
The method comprises the steps that a defective cell efficiency estimation analysis submodule extracts an EL image of a cell marked to have an EL image shadow but not to be invalid, screens a position structure of a shadow part of the EL image, divides the position structure of the EL image shadow into three types including a position parallel to a main grid line, a position inclined to the main grid line and a position perpendicular to the main grid line, judges that the cell efficiency of the defective cell is 50% of the cell efficiency of a normal cell when the position structure of the shadow part of the EL image of a certain cell is parallel to the main grid line, judges that the cell efficiency of the defective cell is 80% of the cell efficiency of the normal cell when the position structure of the shadow part of the EL image of the certain cell is inclined to the main grid line, and judges that the cell efficiency loss of the cell cannot be caused by the EL image shadow when the position structure of the shadow part of the EL image of the certain cell is perpendicular to the main grid line.
Further setting: the same batch of battery piece failure reason analysis module comprises a defective battery piece failure analysis statistics submodule and a defective battery piece repair marking submodule, wherein the defective battery piece failure analysis statistics submodule is used for summarizing reasons causing battery piece defects in the same batch of battery piece assemblies, analyzing the proportion of the number of battery pieces caused by each defect reason in the total number of the defective battery pieces, marking different reasons causing the defects and feeding back the results to different EL image program control modules, the defective battery piece repair marking submodule is used for carrying out secondary repair marking on the battery pieces with the defects, and the EL test image problem preprocessing and identifying module carries out multiple EL tests on the battery pieces with the secondary repair marks.
Further setting: the different EL image program control modules comprise an EL image storage and collection platform and a manual intervention platform, the EL image storage and collection platform is used for storing images tested by the plurality of EL testers and then calling the images in real time, and the manual intervention platform can perform manual intervention and real-time monitoring on each step of EL testing.
A photovoltaic module EL test evaluation method based on battery efficiency comprises the following steps:
a1: monitoring characteristic parameters of the battery piece to be tested and the EL tester by using a battery piece parameter acquisition module to be tested, and judging whether the environment to be tested is appropriate or not;
a2: the method comprises the following steps of preprocessing an EL test image by utilizing an EL test image problem preprocessing and identifying module, intelligently detecting the defect and distortion of each EL image, and carrying out secondary test on the EL image of the battery with the defect;
a3: judging whether the battery piece fails or not by using a defective battery piece EL image performance analysis module according to the defect reason of the EL image, and analyzing the battery efficiency of the battery piece which does not fail completely;
a4: counting the failure reasons of the battery pieces in the same batch by using an EL image failure reason analysis module of the battery pieces in the same batch, analyzing proportion data of the failure reasons of the battery pieces, and marking and repairing the battery pieces with defects;
a5: and storing the EL images at different moments by using different EL image program control modules, and calling the stored EL images in real time for manual intervention.
Further setting:
a-1, detecting the length, the width and the thickness of a battery piece to be tested by using a test piece characteristic parameter marking submodule, detecting the light intensity of the environment of the battery piece to be tested, counting detection data, wherein the EL tester multi-position parameter marking submodule comprises a main EL tester and a plurality of standby EL testers, marking position information parameters of different EL testers by forming a three-dimensional coordinate system according to the length, the width and the height of the battery piece to be tested from the EL testers, counting three-dimensional coordinate points of the main EL tester and the standby EL testers, and sending the counted data to different EL image program control modules for data backup;
a-2, utilizing a battery piece EL test picture processing and judging submodule to preprocess a battery piece image detected by an EL tester, identifying whether different EL images have defects or distortion, identifying and marking the defects of the EL images, and giving an early warning to the image distortion in real time, using a standby EL tester secondary test calling submodule to call the battery piece with the identified and marked, calling a standby EL tester to carry out secondary EL test on the battery piece, resending the tested EL images to the battery piece EL test picture processing and judging submodule to carry out defect judgment, and calling the standby EL tester to carry out defect judgment again after carrying out three-time detection when the EL images of the secondary detection are inconsistent with the EL images of the primary detection;
a-3, virtually marking the shadow of the EL image of each cell by using a defective cell dark part area ratio analysis submodule, classifying the shadow reason of each cell according to the reason of the generation of the shadow surface of the cell judged by an EL test image problem preprocessing and identifying module, rejecting the EL test image of the cell which is directly judged to be invalid, analyzing the shadow area ratio in the residual EL test image to determine whether the cell with the shadow EL test image is invalid or not, and analyzing and estimating the cell efficiency of the cell which is not invalid by using a defective cell efficiency estimation analysis submodule;
a-4, summarizing the reasons of the battery piece defects in the battery piece assemblies in the same batch by utilizing a defective battery piece failure analysis and statistics submodule, analyzing the proportion of the number of the battery pieces caused by each defect reason in the total number of the defective battery pieces, marking the different causes of the defects and feeding the different causes of the defects back to different EL image program control modules, marking the defective battery piece repairing marking submodule for carrying out secondary repairing marking on the battery piece with the defects, and carrying out multiple EL tests on the battery piece with the secondary repairing marking by utilizing an EL test image problem preprocessing and identifying module;
and A-5, storing and calling the images tested by the plurality of EL testers in real time by using an EL image storage and collection platform, and manually intervening each step of the EL test by using a manual intervening platform to monitor in real time.
Example 1: defining conditions, setting the distance between the central point of the shadow and any three points at the outermost side of the shadow to be 12mm, 7mm and 11mm, and when r isn-1≠rn≠rn+1And the value of n is 2, and the shadow area inside the marked EL image is estimated according to a formula:
Calculating to obtain the shadow area of 50 pi mm inside each marked cell EL image2。
Example 2: defining conditions, setting the distance between the central point of the shadow and any three points at the outermost side of the shadow to be 3.11mm, 3.11mm and 3.11mm, and when r isn-1＝rn＝rn+1And the value of n is 1, and the shadow area inside the marked EL image is estimated according to a formula:
Sn＝π[3.11]2about 9.7 pi (unit: mm)2)
Calculating to obtain the shadow area of 9.7 pi mm inside each marked cell EL image2。
Example 3: defining conditions, setting different shadow areas in the EL image of the marked cell to be 9.7 pi, 6.1 pi, 11 pi and 17 pi (unit: mm)2) Setting the length and width of the marked cell to be 100mm and 120mm respectively, and setting the shadow area ratio inside the EL test image of the cell to satisfy the following formula:
when the shadow area inside the battery piece EL test image meets the formula, the current shadow area is judged to have little influence on the power of the battery piece, and the battery piece cannot be invalid.
Example 4: defining conditions for setting different shaded areas of 41.7 pi, 53.31 pi, 27 pi and 31.1 pi (unit: mm) in the EL image of the marking cell2) Setting the length and width of the marked cell to be 50mm and 90mm respectively, and setting the shadow area ratio inside the EL test image of the cell to satisfy the following formula:
and when the shadow area inside the EL test image of the battery piece does not satisfy the formula, judging that the shadow area inside the current EL test image can cause the failure of the battery piece, and marking the failure of the battery piece.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned.
Claims (10)
1. A photovoltaic module EL test evaluation system based on battery efficiency comprises an EL tester and is characterized in that: the system comprises a to-be-tested battery piece parameter acquisition module, an EL test image problem preprocessing identification module, a defective battery piece EL image performance analysis module, a same batch of battery piece EL image failure reason analysis module and different EL image program control modules, wherein the to-be-tested battery piece parameter acquisition module, the EL test image problem preprocessing identification module and the defective battery piece EL image performance analysis module are sequentially connected through an intranet and are respectively connected with the different EL image program control modules through the intranet, and the EL test image problem preprocessing identification module, the defective battery piece EL image performance analysis module and the different EL image program control modules are respectively connected with the same batch of battery piece EL image failure reason analysis module through the intranet.
2. The photovoltaic module EL test evaluation system based on battery efficiency as claimed in claim 1, wherein the battery piece parameter acquisition module to be tested is used for monitoring the characteristic parameters of the battery piece to be tested and the EL tester and determining whether the testing environment is suitable or not, the battery piece parameter acquisition module to be tested comprises a test piece characteristic parameter marking submodule and an EL tester multi-position parameter marking submodule, the test piece characteristic parameter marking submodule is used for detecting the length, the width and the thickness of the battery piece to be tested, detecting the light intensity of the battery piece to be tested environment and counting the detection data, the EL tester multi-position parameter marking submodule comprises a main EL tester and a plurality of standby EL testers, and the length, the width and the height of the battery piece to be tested from the EL testers form a three-dimensional coordinate system to mark the position information parameters of different EL testers, and counting the three-dimensional coordinate points of the main EL tester and the plurality of standby EL testers, and sending the counted data to different EL image program control modules for data backup.
3. The photovoltaic module EL test evaluation system based on battery efficiency as claimed in claim 1, wherein the EL test image problem preprocessing identification module is used for preprocessing the EL test images of the battery pieces, intelligently detecting the defects and distortion of each EL image, and secondarily testing the EL images of the battery pieces with defects, the EL test image problem preprocessing identification module comprises a battery piece EL test picture processing judgment submodule and a standby EL tester secondary test calling submodule, the battery piece EL test picture processing judgment submodule is used for preprocessing the battery piece images detected by the EL tester, identifying whether the defects or the distortions exist in different EL images, identifying and marking the defects existing in the EL images, giving real-time early warning on image distortion, and the standby EL tester secondary test calling submodule is used for identifying and marking the battery pieces with marks, calling a standby EL tester to carry out secondary EL test on the battery piece, resending the tested EL image to the battery piece EL test image processing and judging submodule to carry out defect judgment, and calling the standby EL tester to carry out defect judgment again after carrying out tertiary detection when the EL image of the secondary detection is inconsistent with the EL image of the primary detection.
4. The system of claim 1, wherein the defective cell EL image performance analysis module determines whether the cell fails according to the reason for the defect in the EL image and analyzes the cell efficiency of the cell which does not fail completely, the defective cell EL image performance analysis module comprises a defective cell dark area ratio analysis submodule and a defective cell efficiency estimation analysis submodule, the defective cell dark area ratio analysis submodule is used for virtually marking the shadow of each cell EL image, the reason for the shadow of each cell determined by the EL test image problem preprocessing and identification module is used for classifying the shadow reason of each cell, rejecting the EL test image which is determined to fail directly, and analyzing the shadow area ratio in the residual cell EL test images to determine whether the cell which has the shadow EL test image fails, and the defective cell efficiency estimation and analysis submodule is used for analyzing and estimating the cell efficiency of the non-failed cell.
5. The system of claim 4, wherein the analysis submodule determines the shape of the shadow area in the test image of the cell EL, measures the distance from the center point of the shadow to any three points on the outermost side of the shadow, wherein the angle between the straight line connecting each point and the center point and the straight line connecting the other point and the center point is greater than 90 degrees, and sets the distance between the center point of the shadow and any three points on the outermost side of the shadow to rn-1、rn、rn+1The shadow area inside the marked EL image is estimated according to the formula:
when r isn-1＝rn＝rn+1N is 1, when r isn-1≠rn≠rn+1And n is taken as 2, calculating to obtain the shadow area inside each marked cell EL image, and setting different shadow areas inside the marked cell EL images as S1、S2、S3、...、Sn-1、SnSetting the length and width of the marked cell slice to be ln、lmSetting the shadow area ratio inside the cell EL test image to satisfy the following formula:
when the shadow area inside the battery piece EL test image meets the formula, the current shadow area is judged to have little influence on the power of the battery piece, the battery piece cannot be invalid, and when the shadow area inside the battery piece EL test image does not meet the formula, the current shadow area inside the EL test image is judged to cause the battery piece to be invalid, and the battery piece is subjected to invalidation marking.
6. The system of claim 4, wherein the sub-module for estimating and analyzing the cell efficiency of the defective cell performs EL image extraction on the cells marked to have EL image shadow but not to fail, screens the position structure of the shadow part of the EL image, divides the position structure of the shadow part of the EL image into three types, i.e. the position parallel to the main grid line, the position inclined to the main grid line, and the position perpendicular to the main grid line, determines that the cell efficiency of the defective cell is 50% of the cell efficiency of the normal cell when the position structure of the shadow part of the EL image of a certain cell is parallel to the main grid line, determines that the cell efficiency of the defective cell is 80% of the cell efficiency of the normal cell when the position structure of the shadow part of the EL image of a certain cell is perpendicular to the main grid line, it was determined that the EL image shading did not cause cell efficiency loss.
7. The photovoltaic module EL test evaluation system based on battery efficiency as claimed in claim 1, wherein the same batch of battery piece EL image failure reason analysis module is used for counting the failure reasons of the same batch of battery pieces, analyzing the ratio data of the failure reasons of the battery pieces and marking and repairing the defective battery pieces, the same batch of battery piece failure reason analysis module comprises a defective battery piece failure analysis and statistics submodule and a defective battery piece repair marking submodule, the defective battery piece failure analysis and statistics submodule is used for summarizing the reasons causing the battery piece defects in the same batch of battery piece assemblies, analyzing the ratio of the number of the battery pieces caused by each defect reason in the total number of the defective battery pieces, marking different causes of the defects and feeding back the results to different EL image program control modules, the defective battery piece repair marking submodule is used for carrying out secondary repair marking on the defective battery pieces, the EL test image problem preprocessing and identifying module carries out multiple times of EL tests on the battery piece with the secondary repair mark.
8. The photovoltaic module EL test evaluation system based on battery efficiency as claimed in claim 1, wherein the different EL image program control modules are used for storing and then calling EL images at different times in real time for manual intervention, the different EL image program control modules comprise an EL image storage and collection platform and a manual intervention platform, the EL image storage and collection platform is used for storing and then calling images tested by a plurality of EL testers in real time, and the manual intervention platform can perform manual intervention and real-time monitoring on each step of the EL test.
9. A photovoltaic module EL test evaluation method based on battery efficiency is characterized in that:
a1: monitoring characteristic parameters of the battery piece to be tested and the EL tester by using a battery piece parameter acquisition module to be tested, and judging whether the environment to be tested is appropriate or not;
a2: the method comprises the following steps of preprocessing an EL test image by utilizing an EL test image problem preprocessing and identifying module, intelligently detecting the defect and distortion of each EL image, and carrying out secondary test on the EL image of the battery with the defect;
a3: judging whether the battery piece fails or not by using a defective battery piece EL image performance analysis module according to the defect reason of the EL image, and analyzing the battery efficiency of the battery piece which does not fail completely;
a4: counting the failure reasons of the battery pieces in the same batch by using an EL image failure reason analysis module of the battery pieces in the same batch, analyzing proportion data of the failure reasons of the battery pieces, and marking and repairing the battery pieces with defects;
a5: and storing the EL images at different moments by using different EL image program control modules, and calling the stored EL images in real time for manual intervention.
10. The method of claim 9 for evaluating a photovoltaic module EL test based on cell efficiency, wherein:
a-1, detecting the length, the width and the thickness of a battery piece to be tested by using a test piece characteristic parameter marking submodule, detecting the light intensity of the environment of the battery piece to be tested, counting detection data, wherein the EL tester multi-position parameter marking submodule comprises a main EL tester and a plurality of standby EL testers, marking position information parameters of different EL testers by forming a three-dimensional coordinate system according to the length, the width and the height of the battery piece to be tested from the EL testers, counting three-dimensional coordinate points of the main EL tester and the standby EL testers, and sending the counted data to different EL image program control modules for data backup;
a-2, utilizing a battery piece EL test picture processing and judging submodule to preprocess a battery piece image detected by an EL tester, identifying whether different EL images have defects or distortion, identifying and marking the defects of the EL images, and giving an early warning to the image distortion in real time, using a standby EL tester secondary test calling submodule to call the battery piece with the identified and marked, calling a standby EL tester to carry out secondary EL test on the battery piece, resending the tested EL images to the battery piece EL test picture processing and judging submodule to carry out defect judgment, and calling the standby EL tester to carry out defect judgment again after carrying out three-time detection when the EL images of the secondary detection are inconsistent with the EL images of the primary detection;
a-3, virtually marking the shadow of the EL image of each cell by using a defective cell dark part area ratio analysis submodule, classifying the shadow reason of each cell according to the reason of the generation of the shadow surface of the cell judged by an EL test image problem preprocessing and identifying module, rejecting the EL test image of the cell which is directly judged to be invalid, analyzing the shadow area ratio in the residual EL test image to determine whether the cell with the shadow EL test image is invalid or not, and analyzing and estimating the cell efficiency of the cell which is not invalid by using a defective cell efficiency estimation analysis submodule;
a-4, summarizing the reasons of the battery piece defects in the battery piece assemblies in the same batch by utilizing a defective battery piece failure analysis and statistics submodule, analyzing the proportion of the number of the battery pieces caused by each defect reason in the total number of the defective battery pieces, marking the different causes of the defects and feeding the different causes of the defects back to different EL image program control modules, marking the defective battery piece repairing marking submodule for carrying out secondary repairing marking on the battery piece with the defects, and carrying out multiple EL tests on the battery piece with the secondary repairing marking by utilizing an EL test image problem preprocessing and identifying module;
and A-5, storing and calling the images tested by the plurality of EL testers in real time by using an EL image storage and collection platform, and manually intervening each step of the EL test by using a manual intervening platform to monitor in real time.
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