Online monitoring method for photovoltaic slice circulating liquid

Abstract

The invention relates to the technical field of intelligent monitoring, and particularly discloses an online monitoring method for a photovoltaic slice circulating liquid, which comprises the following steps: S1, sampling the circulating liquid, obtaining a first curve according to a sample, and grouping the first curve; s2, determining a second curve, and obtaining a fitting curve according to the second curve; cutting parameters of the silicon rod are obtained, a cutting effect score is calculated, and an abnormal score is determined; determining an abnormal curve according to the abnormal score, and recording the spectral signal intensity of the abnormal curve on each wave band; s3, collecting a real-time sample, and judging whether the sample is in an abnormal state; and calculating a replacement proportion, calculating a supplement amount, discharging the circulating liquid according to the supplement amount, and supplementing new circulating liquid. The replacement amount of the circulating liquid can be accurately judged, and cost rise caused by resource waste is avoided.

Description

Technical Field

[0001] The invention relates to the technical field of intelligent monitoring, and in particular to an online monitoring method for photovoltaic slice circulating fluid. Background Art

[0002] Photovoltaic slicing is achieved by rubbing the silicon rod with a diamond wire at high speed. In this process, a coolant is usually needed, also known as a slicing circulating fluid. It is composed of an aqueous solution of organic substances such as alcohols and ethers. During the cutting process, it mainly plays the role of lubrication, cooling, and removal of debris.

[0003] After recycling, the physical and chemical properties of the cutting fluid will decline, affecting the quality of the slices. At this time, part of the circulating fluid will be discharged during the process and fresh cutting fluid will be added. Although discharging a large amount of circulating fluid can more effectively ensure the slicing effect, the cost of the cutting fluid is very high, which will result in a great cost waste. Summary of the invention

[0004] The purpose of the present invention is to provide an online monitoring method for photovoltaic slice circulating fluid to solve the following technical problems: After recycling, the physical and chemical properties of the cutting fluid will decline, affecting the quality of the slices. At this time, part of the circulating fluid will be discharged during the process and fresh cutting fluid will be added. Although discharging a large amount of circulating fluid can more effectively ensure the slicing effect, the cost of the cutting fluid is very high, which will result in a great cost waste.

[0005] The purpose of the present invention can be achieved through the following technical solutions: An online monitoring method for photovoltaic slice circulating fluid comprises the following steps: S1: sampling the circulating fluid m times, where m is a preset number, obtaining spectral information based on spectral technology, obtaining spectral signal intensities of chemical functional groups in different bands, drawing spectral curves, wherein the spectral lines include absorption curves, scattering curves and transmission curves, taking the spectral curves as first curves, grouping the first curves, and the similarity between any two first curves in the same group is greater than a preset similarity threshold; S2: Take the first curve in the same group as the second curve, obtain the spectral signal intensity of the single second curve corresponding to band i, and calculate the mean value Y of the spectral signal intensity i , generate coordinate points (i, Y i ), fitting the coordinate points to obtain a fitting curve f(x), where x represents a band; Obtaining the cutting effect parameters of the silicon rod, wherein the cutting effect parameters include the first-time qualified rate of slicing, the short line rate, and the A-grade silicon wafer yield rate, and calculating the cutting effect score based on the good and bad solution distance method. When the cutting effect score is less than or equal to a preset cutting effect score threshold, it is regarded as an abnormal score; Determine the proportion C of the cutting effect score corresponding to the second curve as the abnormal score. When the proportion C is greater than or equal to the preset proportion threshold, use the corresponding fitting curve f(x) as the abnormal curve F(x), and record the spectral signal intensity YC of the abnormal curve F(x) on band a. a ; S3: Periodically sample the circulating fluid and use it as a real-time sample to obtain the spectral information of the real-time sample. When the spectral signal intensity S of the real-time sample in band a is a ≤YC a When , it is marked as abnormal state; Calculate the replacement ratio P = (Yys + YC a -S a ) / S a , Yys represents the preset spectral signal intensity correction value, the supplement amount L=P*Lys is calculated, Lys represents the preset total amount of circulating fluid, and the circulating fluid is discharged and supplemented with new circulating fluid according to the supplement amount.

[0006] As a further solution of the present invention: the step S3 further includes the following steps: After replenishing the new circulating fluid, the spectrum signal intensity SSa of the real-time sample in band a is obtained again. When the spectrum signal intensity SS a >YC a When the supplement effect is good, When the spectral signal intensity SS a ≤YC a When the replenishment effect is determined to be poor, step S3 is executed again to discharge and replenish the circulating fluid.

[0007] As a further solution of the present invention: in the step S2, the process of obtaining the similarity of the first curve specifically includes: The first curve f 1 (x) and the second first curve f 2 The similarity between (x) ; Among them, XSys represents the preset similarity benchmark value, [x sta , x end ] represents the domain of the first curve.

[0008] As a further solution of the present invention: the step S2 further includes the following steps: The first curve corresponding to the cutting effect score that is not an abnormal score is taken as a normal curve. When the spectral signal intensity ZC of the normal curve in band a is a Less than or equal to the spectral signal intensity YC a When the spectral signal intensity ZC a As the strength to be determined; The proportion of the normal curve corresponding to the undetermined intensity to the normal curve is counted. When the proportion is greater than the proportion threshold, the judgment condition of the abnormal state is modified to: the spectral signal intensity S of the real-time sample in band a a >YC a , and let the replacement ratio P = (S a -Yys-YC a ) / (Yys+YC a ).

[0009] As a further solution of the present invention: in the step S3, the interval t∈[0.1s, 10s] for sampling the circulating fluid.

[0010] As a further solution of the present invention: in the step S1, the light source used to obtain the spectral information is white light or a laser of a specific wavelength band.

[0011] As a further solution of the present invention: in the step S1, the sample of the circulating fluid is stored in a sample pool, the light source and the sample pool are softly connected through a total reflection optical fiber, the sample pool and the signal detector are also connected through an optical fiber, an anti-ultraviolet coating is added inside the optical fiber, and the signal detector is used to obtain spectral information.

[0012] As a further solution of the present invention: in the step S1, the spectral technology includes one or more of infrared absorption spectroscopy technology, ultraviolet visible light absorption spectroscopy technology, Raman scattering spectroscopy technology, surface enhanced Raman spectroscopy technology, and fluorescence spectroscopy technology.

[0013] Beneficial effects of the present invention: In this scheme, firstly, the circulating fluid is sampled multiple times, and the spectral signal intensity information in different bands is collected by spectral technology to draw an absorption spectrum curve, and then the spectral curves are grouped according to the similarity of the spectral curves to ensure that the spectral curves in each group have a high degree of similarity; the purpose of this process is to obtain the spectral data of the circulating fluid under different operating conditions, to provide original data support for subsequent spectral analysis, to ensure the reliability and accuracy of the model, and to provide necessary data input for accurate judgment of subsequent steps; then, the spectral curves after the first step of grouping are averaged to generate a fitting curve, combined with the cutting parameter scoring of the silicon rod, the samples with abnormal cutting effect scores are analyzed, the abnormal curves are extracted, and a benchmark abnormal spectrum library is constructed. It is worth noting that by establishing a correlation model between the cutting effect and the spectral characteristics, the abnormal spectrum and the poor cutting are clearly identified. Through this process, complex spectral data can be converted into evaluation standards for process control, so that subsequent real-time detection can quickly and accurately identify the deterioration of the circulating fluid performance, avoiding cost waste caused by premature replacement or reduced cutting quality; finally, through periodic sampling, the real-time spectral information of the circulating fluid is obtained, and it is compared with the characteristic curve in the abnormal spectrum library. When the spectral signal intensity of the real-time sample is lower than the characteristic value in the abnormal spectrum, it is marked as an abnormal state, and the proportion and replenishment amount of the circulating fluid that need to be replaced are calculated, thereby realizing real-time monitoring and dynamic management of the circulating fluid, ensuring that the performance of the circulating fluid is always maintained within the effective range. By accurately calculating the replenishment amount, the ineffective discharge of the circulating fluid can be minimized, the service life of the fluid can be extended, resource consumption and production costs can be reduced, and the dual optimization of economic and process benefits can be achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] The present invention will be further described below in conjunction with the accompanying drawings.

[0015] Figure 1 The present invention is a schematic flow chart of an online monitoring method for photovoltaic slice circulating fluid. DETAILED DESCRIPTION

[0016] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0017] See also Figure 1 As shown, the present invention is an online monitoring method for photovoltaic slice circulating fluid, comprising the following steps: S1: sampling the circulating fluid m times, where m is a preset number, obtaining spectral information based on spectral technology, obtaining spectral signal intensities of chemical functional groups in different bands, and drawing spectral curves, wherein the spectral lines include absorption curves, scattering curves, and transmission curves, taking the spectral curves as first curves, grouping the first curves, and the similarity between any two first curves in the same group is greater than a preset similarity threshold; S2: Take the first curve in the same group as the second curve, obtain the spectral signal intensity of the single second curve corresponding to band i, and calculate the mean value Y of the spectral signal intensity i , generate coordinate points (i, Y i ), fitting the coordinate points to obtain a fitting curve f(x), where x represents a band; Obtaining the cutting effect parameters of the silicon rod, wherein the cutting effect parameters include the first-time qualified rate of slicing, the short line rate, and the A-grade silicon wafer yield rate, and calculating the cutting effect score based on the good and bad solution distance method. When the cutting effect score is less than or equal to a preset cutting effect score threshold, it is regarded as an abnormal score; Determine the proportion C of the cutting effect score corresponding to the second curve as the abnormal score. When the proportion C is greater than or equal to the preset proportion threshold, use the corresponding fitting curve f(x) as the abnormal curve F(x), and record the spectral signal intensity YC of the abnormal curve F(x) on band a. a ; S3: Periodically sample the circulating fluid and use it as a real-time sample to obtain the spectral information of the real-time sample. When the spectral signal intensity S of the real-time sample in band a is a ≤YC a When , it is marked as abnormal state; Calculate the replacement ratio P = (Yys + YC a -S a ) / S a , Yys represents the preset spectral signal intensity correction value, the supplement amount L=P*Lys is calculated, Lys represents the preset total amount of circulating fluid, and the circulating fluid is discharged and supplemented with new circulating fluid according to the supplement amount.

[0018] It should be noted that, firstly, the circulating fluid is sampled multiple times, and the spectral signal intensity information in different bands is collected by spectral technology to draw the absorption spectrum curve, and then the spectral curves are grouped according to the similarity of the spectral curves to ensure that the spectral curves in each group are highly similar; the purpose of this process is to obtain the spectral data of the circulating fluid under different operating conditions, to provide original data support for the subsequent spectral analysis, to ensure the reliability and accuracy of the model, and to provide the necessary data input for the precise judgment of the subsequent steps; then, the spectral curves after the first step of grouping are averaged to generate a fitting curve, combined with the cutting parameter score of the silicon rod, the samples with abnormal cutting effect scores are analyzed, the abnormal curves are extracted, and the benchmark abnormal spectrum library is constructed. It is worth noting that by establishing a correlation model between the cutting effect and the spectral characteristics, the abnormal spectrum and the poor cutting quality are clearly related. Through this process, complex spectral data can be converted into evaluation standards for process control, so that subsequent real-time detection can quickly and accurately identify the deterioration of the circulating fluid performance, avoiding cost waste caused by premature replacement or reduced cutting quality; finally, through periodic sampling, the real-time spectral information of the circulating fluid is obtained, and it is compared with the characteristic curve in the abnormal spectrum library. When the spectral signal intensity of the real-time sample is lower than the characteristic value in the abnormal spectrum, it is marked as an abnormal state, and the proportion and replenishment amount of the circulating fluid that need to be replaced are calculated, thereby realizing real-time monitoring and dynamic management of the circulating fluid, ensuring that the performance of the circulating fluid is always maintained within the effective range. By accurately calculating the replenishment amount, the ineffective discharge of the circulating fluid can be minimized, the service life of the liquid can be extended, resource consumption and production costs can be reduced, and the dual optimization of economic and process benefits can be achieved.

[0019] It is worth noting that the scheme is based on the same spectral curve.

[0020] In another preferred embodiment of the present invention, the step S3 further includes the following steps: After replenishing the new circulating fluid, the spectrum signal intensity SSa of the real-time sample in band a is obtained again. When the spectrum signal intensity SS a >YC a When the supplement effect is good, When the spectral signal intensity SS a ≤YC a When the replenishment effect is determined to be poor, step S3 is executed again to discharge and replenish the circulating fluid.

[0021] It is worth noting that by obtaining the spectral signal intensity SS of the real-time sample in band a again after replenishing the new circulating fluid, a , and the abnormal spectrum signal intensity threshold YC a Compare and judge the effect of supplementation; when SS a>YC a When SS a <YC a When the replenishment effect is not ideal, the circulating fluid performance has not returned to normal levels, and the discharge and replenishment steps need to be performed again; by introducing a feedback mechanism for the replenishment effect, a closed-loop control system is formed to avoid the problem of continuous deterioration caused by insufficient replenishment or operational errors. Its purpose is to improve the accuracy and reliability of circulating fluid management, ensure that the replenishment process can be corrected in a timely manner, and always maintain the optimal performance of the circulating fluid.

[0022] In another preferred embodiment of the present invention, in step S2, the process of obtaining the similarity of the first curve specifically includes: The first curve f 1 (x) and the second first curve f 2 The similarity between (x) ; Among them, XSys represents the preset similarity benchmark value, [x sta , x end ] represents the domain of the first curve.

[0023] In another preferred embodiment of the present invention, the step S2 further includes the following steps: The first curve corresponding to the cutting effect score that is not an abnormal score is taken as a normal curve. When the spectral signal intensity ZC of the normal curve in band a is a Less than or equal to the spectral signal intensity YC a When the spectral signal intensity ZC a As the strength to be determined; The proportion of the normal curve corresponding to the undetermined intensity to the normal curve is counted. When the proportion is greater than the proportion threshold, the judgment condition of the abnormal state is modified to: the spectral signal intensity S of the real-time sample in band a a >YC a , and let the replacement ratio P = (S a -Yys-YC a ) / (Yys+YC a ).

[0024] It should be noted that by analyzing the spectral curve with normal cutting effect score, the spectral signal intensity ZC in band a is identified. a Less than or equal to abnormal intensity YC aThe situation is considered as the undetermined intensity, and the proportion of this intensity in the normal spectrum curve is counted. When this proportion exceeds the preset proportion threshold, it means that the high spectral signal intensity at this band may come from the by-products (such as debris) generated during the cutting process. The accumulation of these substances will reduce the cutting effect. To adapt to this phenomenon, the judgment condition of the abnormal state is modified to S a >YC a , redefine the replacement ratio formula to more accurately reflect the actual abnormal situation in the circulating fluid; by dynamically adjusting the judgment criteria, it is possible to identify and correct the spectral abnormalities caused by cutting by-products, avoid misjudging the normal state as abnormal, and reduce unnecessary circulating fluid replacement operations; it is understandable that in the above case, when judging whether the supplementation effect is good, the judgment basis is also modified to: spectral signal intensity SS a ≤YC a .

[0025] In another preferred embodiment of the present invention, in step S3, the interval t∈[0.1s, 10s] for sampling the circulating fluid is.

[0026] In another preferred embodiment of the present invention, in step S1, the light source used to obtain the spectral information is white light or a laser of a specific wavelength band.

[0027] In another preferred embodiment of the present invention, in the step S1, the sample of the circulating fluid is stored in a sample pool, the light source and the sample pool are softly connected through a total reflection optical fiber, the sample pool and the signal detector are also connected through an optical fiber, an anti-ultraviolet coating is added inside the optical fiber, and the signal detector is used to obtain spectral information.

[0028] In another preferred embodiment of the present invention, in step S1, the spectroscopy technique includes one or more of infrared absorption spectroscopy technique, ultraviolet-visible absorption spectroscopy technique, Raman scattering spectroscopy technique, surface enhanced Raman spectroscopy technique, and fluorescence spectroscopy technique.

[0029] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A method for online monitoring of photovoltaic slice circulating fluid, characterized in that: The following steps are involved: S1: sampling the circulating fluid m times, where m is a preset number, obtaining spectral information based on spectral technology, obtaining spectral signal intensities of chemical functional groups in different bands, and drawing spectral curves, wherein the spectral lines include absorption curves, scattering curves, and transmission curves, taking the spectral curves as first curves, grouping the first curves, and the similarity between any two first curves in the same group is greater than a preset similarity threshold; S2: Take the first curve in the same group as the second curve, obtain the spectral signal intensity of the single second curve corresponding to band i, and calculate the mean value Y of the spectral signal intensity i , generate coordinate points (i, Y i ), fitting the coordinate points to obtain a fitting curve f(x), where x represents a band; Obtaining the cutting effect parameters of the silicon rod, wherein the cutting effect parameters include the first-time qualified rate of slicing, the wire breakage rate, and the yield rate of grade A silicon wafers, and calculating the cutting effect score based on the good and bad solution distance method. When the cutting effect score is less than or equal to a preset cutting effect score threshold, it is regarded as an abnormal score; Determine the proportion C of the cutting effect score corresponding to the second curve as the abnormal score. When the proportion C is greater than or equal to the preset proportion threshold, use the corresponding fitting curve f(x) as the abnormal curve F(x), and record the spectral signal intensity YC of the abnormal curve F(x) on band a. a ; S3: Periodically sample the circulating fluid and use it as a real-time sample to obtain the spectral information of the real-time sample. When the spectral signal intensity S of the real-time sample in band a is a ≤YC a When , it is marked as abnormal state; Calculate the replacement ratio P = (Yys + YC a -S a ) / S a , Yys represents the preset spectral signal intensity correction value, the supplement amount L=P*Lys is calculated, Lys represents the preset total amount of circulating fluid, and the circulating fluid is discharged and supplemented with new circulating fluid according to the supplement amount.

2. The online monitoring method of photovoltaic slice circulating fluid according to claim 1, characterized in that: The step S3 further includes the following steps: After replenishing the new circulating fluid, the spectrum signal intensity SSa of the real-time sample in band a is obtained again. When the spectrum signal intensity SS a >YC a When the supplement effect is good, When the spectral signal intensity SS a ≤YC a When the replenishment effect is determined to be poor, step S3 is executed again to discharge and replenish the circulating fluid.

3. The online monitoring method of photovoltaic slice circulating fluid according to claim 1 is characterized in that: In the step S2, the process of obtaining the similarity of the first curve specifically includes: The similarity between the first first curve f1(x) and the second first curve f2(x) ; Among them, XSys represents the preset similarity benchmark value, [x sta , x end ] represents the domain of the first curve.

4. The online monitoring method of photovoltaic slice circulating fluid according to claim 1, characterized in that: The step S2 further includes the following steps: The first curve corresponding to the cutting effect score that is not an abnormal score is taken as a normal curve. When the spectral signal intensity ZC of the normal curve in band a is a Less than or equal to the spectral signal intensity YC a When the spectral signal intensity ZC a As the strength to be determined; The proportion of the normal curve corresponding to the undetermined intensity to the normal curve is counted. When the proportion is greater than the proportion threshold, the judgment condition of the abnormal state is modified to: the spectral signal intensity S of the real-time sample in band a a >YC a , and let the replacement ratio P = (S a -Yys-YC a ) / (Yys+YC a ).

5. The online monitoring method of photovoltaic slice circulating fluid according to claim 1, characterized in that: In the step S3, the interval t∈[0.1s, 10s] for sampling the circulating fluid is.

6. The online monitoring method of photovoltaic slice circulating fluid according to claim 1, characterized in that: In the step S1, the light source used to obtain the spectrum information is white light or a laser of a specific wavelength band.

7. The online monitoring method of photovoltaic slice circulating fluid according to claim 6, characterized in that: In step S1, the sample of the circulating fluid is stored in a sample pool, the light source and the sample pool are softly connected via a fully reflective optical fiber, the sample pool and the signal detector are also connected via an optical fiber, an anti-ultraviolet coating is added inside the optical fiber, and the signal detector is used to obtain spectral information.

8. The online monitoring method of photovoltaic slice circulating fluid according to claim 1, characterized in that: In the step S1, the spectroscopy technique includes one or more of infrared absorption spectroscopy technique, ultraviolet-visible light absorption spectroscopy technique, Raman scattering spectroscopy technique, surface enhanced Raman spectroscopy technique, and fluorescence spectroscopy technique.

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