A defect early warning method for oil-immersed power transformer

Abstract

The invention discloses a defect early warning method for an oil-immersed power transformer, relates to the technical field of cooling control, and is used to improve the problem of acid value surge and deterioration of insulating oil caused by cooling time in a forced circulation cooling process, comprising obtaining heat records of various parts of a power transformer to screen and mark the heating parts of the power transformer, collecting the size of the marked parts and detecting the amount of charge passing through the marked parts when working, calculating the heat score of each marked part according to the size and the amount of charge of each marked part, calculating the main temperature index of the power transformer by using a hierarchical analysis method according to the heat score of each marked part and the real-time temperature of each marked part, selecting different cooling methods according to the main temperature index to cool the power transformer using insulating oil, detecting the acidity of the insulating oil and the number of impurity particles when using a forced circulation cooling method, calculating the execution time of the forced circulation cooling method by using a polynomial regression algorithm, and giving an early warning prompt.

Description

Technical Field

[0001] The present invention relates to the technical field of cooling control, and more specifically, to a defect early warning method for an oil-immersed power transformer. Background Art

[0002] Cooling control technology refers to the control and management of temperature through a series of means and methods to ensure that the equipment or system is in an efficient working state under the environment. Applying cooling control technology to defect warning of oil-immersed power transformers can improve the working state of power transformers and improve operating efficiency.

[0003] The prior art has the following deficiencies:

[0004] In the past, when insulating oil was used to cool power transformers, the insulating oil was only adjusted and replaced according to the working status of the power transformer. It was not considered that the long cooling time of the insulating oil during the forced circulation cooling process would lead to a surge in impurities, and the rapid increase in the acidity of the insulating oil would lead to accelerated deterioration, which seriously reduced the cooling utilization rate of the insulating oil. Summary of the invention

[0005] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides a defect warning method for an oil-immersed power transformer, which scores the heat generation of the power transformer by analyzing the working status of each part of the power transformer, performs a test after each use of forced circulation cooling, selects an insulating oil control method based on the heat generation score of the power transformer, calculates the cooling time of the next forced circulation cooling, and issues a warning prompt to replace the insulating oil based on the cooling time to solve the problems raised in the above-mentioned background technology.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] A defect early warning method for an oil-immersed power transformer comprises the following steps:

[0008] Step S1: obtaining heat records of various parts of the power transformer, screening and marking the heating parts of the power transformer according to the heat records of various parts; collecting the part dimensions of the marked parts, detecting the current passing through the marked parts when the power transformer is working, and calculating the charge;

[0009] Step S2: Calculate the size expansion amount of the marked part according to the size of the marked part, calculate the heat score of the corresponding part by using the hierarchical analysis method through the size expansion amount and the charge amount of each marked part, detect the real-time temperature of each marked part and calculate the main temperature index of the power transformer;

[0010] Step S3: according to the main temperature index, a natural convection cooling method or a forced circulation cooling method is selected to cool the power transformer using insulating oil, and after each cooling treatment using the forced circulation cooling method, the acid value of the insulating oil is measured and the acid value change is calculated, and the number of particles in the insulating oil is collected to obtain the impurity particle count and record it;

[0011] Step S4: Calculate the acid coefficient of the current insulating oil based on the change in the acid value of the insulating oil and the count of the impurity particles, calculate the cooling time of the forced circulation cooling treatment based on the acid coefficient, and issue an early warning prompt.

[0012] In a preferred embodiment, in step S1, the heat records of various parts of the power transformer are called through the historical database, the heat records of various parts are the temperatures of various parts under normal operation of the power transformer in the historical data, the temperatures of various parts under normal operation of the power transformer are used as the regional temperatures of various parts, the regional temperatures of all parts in the power transformer are recorded and the temperature average value is calculated as the temperature screening threshold, and the parts exceeding the temperature screening threshold are screened out and marked.

[0013] In a preferred embodiment, in step S1, a period of time is selected as the analysis time when the power transformer is working, and the current sensor is used to detect the current passing through each marked part when the power transformer is working during the analysis time, and the charge amount of each marked part is calculated according to the analysis time and the current of each marked part: , where I is the current passing through the marked part when the power transformer is working, t is the analysis time interval, and Q is the charge amount at the corresponding marked part;

[0014] Two time points were randomly selected during the analysis time to detect the site size of each marked site.

[0015] In a preferred embodiment, in step S2, the size of the part detected at a later time point is subtracted from the size of the mark detected at a previous time point during the analysis time to obtain the size expansion of the marked part, and the thermal acceleration coefficient of each marked part is calculated according to the size expansion and charge of the marked part and used as the thermal score of each marked part;

[0016] Calculate the thermal acceleration coefficient of the marked area: ,in, is the size expansion of the marked part, is the charge at the marked site, is the thermal acceleration coefficient of the corresponding mark, and i is the serial number of each marked part.

[0017] The real-time temperature of each marked part is detected by a temperature sensor, and the thermal acceleration coefficient of each marked part is used as the thermal score. The thermal scores are sorted from small to large, and the thermal weight is set for each marked part after sorting using the hierarchical analysis method.

[0018] In a preferred embodiment, in step S2, the heat weight is set by using the hierarchical analysis method and the main temperature index of the entire power transformer is calculated in combination with the real-time temperature of each marked part. The specific steps are as follows:

[0019] Constructing a scoring matrix: Constructing a scoring matrix based on the heat scores of each marked part to compare the relative importance of each part;

[0020] Standardization: Standardize each column of the scoring matrix so that the sum of each column is equal to 1;

[0021] Calculate eigenvalues: Calculate the eigenvalue of each factor. The eigenvalue is the weighted average of each column of the scoring matrix. The eigenvalue of each part is used as the quantitative value of the importance of each part.

[0022] The characteristic value of each part is used as the heat weight of the corresponding marked part, and the heat weight of each marked part and the real-time temperature of the corresponding marked part are weighted and summed to obtain the main temperature index of the entire power transformer.

[0023] In a preferred embodiment, in step S3, when the main temperature index of the power transformer is lower than the temperature index threshold, the insulating oil is controlled by natural convection cooling to cool the power transformer; when the main temperature index of the power transformer exceeds the temperature index threshold, the insulating oil is controlled by forced circulation cooling to cool the power transformer.

[0024] In a preferred embodiment, in step S3, after each cooling process is completed, the acid value of the insulating oil is measured and recorded using a pH meter, and the acid value of the insulating oil measured this time is subtracted from the acid value of the insulating oil recorded last time to obtain the change in the acid value of the insulating oil; the insulating oil is collected according to a set fixed collection volume, and particles exceeding a preset size are obtained and their number is counted to obtain the impurity particle count and record it.

[0025] In a preferred embodiment, in step S4, the acid value change of the insulating oil and the impurity particle count are comprehensively considered to calculate the acid coefficient of the current insulating oil using a polynomial regression algorithm: ,in is the acidity coefficient of the current insulating oil, is the change in the acid value of the insulating oil after the cooling adjustment. is the impurity particle count after cooling adjustment. and are the influence weights of the two parameters respectively, is the modulation constant;

[0026] The reciprocal of the current acid coefficient of the insulating oil is taken as the cooling adjustment ratio of the next forced circulation cooling method, and the product of the cooling time of the current forced circulation cooling method and the cooling adjustment ratio is taken as the cooling time of the next forced circulation cooling method.

[0027] In a preferred embodiment, in step S4, each time the forced circulation cooling method is used to control the cooling of the insulating oil, the cooling time is recorded in real time, and when the processing time reaches the cooling time of the current time, the natural convection cooling method is switched to cool the power transformer;

[0028] If the cooling time of the next forced circulation cooling method calculated from the cooling time of the current forced circulation cooling method is lower than the preset processing time threshold, an early warning is issued and a prompt is given to replace the insulating oil.

[0029] The technical effects and advantages of the oil-immersed power transformer defect early warning method of the present invention are as follows:

[0030] The present invention screens and marks the heating parts of the power transformer by obtaining the heat records of each part of the power transformer, collects the size of the marked part and detects the amount of charge passing through the marked part when it is working, calculates the heat score of each marked part according to the size and charge of each marked part, calculates the main temperature index of the power transformer according to the heat score of each marked part and the real-time temperature of each marked part, and calculates the main temperature index of the power transformer as a whole by splitting and summing, thereby reducing the detection cost and improving the temperature measurement accuracy. The relative importance of each part is analyzed to facilitate subsequent management and call, and different cooling methods are selected according to the main temperature index to cool the power transformer using insulating oil. When using the forced circulation cooling method, the acidity of the insulating oil and the number of impurity particles are detected to calculate the execution time of the forced circulation cooling method and provide early warning prompts, thereby improving the cooling safety of the oil-immersed current transformer. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 It is a schematic diagram of a defect early warning method for an oil-immersed power transformer according to the present invention. DETAILED DESCRIPTION

[0032] 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.

[0033] The present invention screens and marks the heating parts of the power transformer by acquiring the heat records of various parts of the power transformer, collects the size of the marked part and detects the amount of charge passing through the marked part when it is working, calculates the heat score of each marked part according to the size and the amount of charge of each marked part, calculates the main temperature index of the power transformer according to the heat score of each marked part and the real-time temperature of each marked part, selects different cooling methods according to the main temperature index to cool the power transformer using insulating oil, detects the acidity of the insulating oil and the number of impurity particles when using the forced circulation cooling method, calculates the execution time of the forced circulation cooling method, and issues early warning prompts, thereby improving the cooling safety of the oil-immersed current transformer.

[0034] Embodiment, a method for early warning of defects of oil-immersed power transformer, such as Figure 1 As shown, the following steps are included:

[0035] Step S1: obtaining heat records of various parts of the power transformer, screening and marking the heating parts of the power transformer according to the heat records of various parts; collecting the part dimensions of the marked parts, detecting the current passing through the marked parts when the power transformer is working, and calculating the charge;

[0036] Step S2: Calculate the size expansion amount of the marked part according to the size of the marked part, calculate the heat score of the corresponding part by using the hierarchical analysis method through the size expansion amount and the charge amount of each marked part, detect the real-time temperature of each marked part and calculate the main temperature index of the power transformer;

[0037] Step S3: according to the main temperature index, a natural convection cooling method or a forced circulation cooling method is selected to cool the power transformer using insulating oil, and after each cooling treatment using the forced circulation cooling method, the acid value of the insulating oil is measured and the acid value change is calculated, and the number of particles in the insulating oil is collected to obtain the impurity particle count and record it;

[0038] Step S4: Calculate the acid coefficient of the current insulating oil based on the change in the acid value of the insulating oil and the count of the impurity particles, calculate the cooling time of the forced circulation cooling treatment based on the acid coefficient, and issue an early warning prompt.

[0039] The specific implementation is as follows:

[0040] In step S1, the heat records of various parts of the power transformer are called through the historical database. The heat records of various parts are the temperatures of various parts of the power transformer under normal operation in the historical data. The temperatures of various parts of the power transformer under normal operation are used as the regional temperatures of various parts. The regional temperatures of all parts of the power transformer are recorded and the temperature average is calculated as the temperature screening threshold. Parts exceeding the temperature screening threshold are screened out and marked.

[0041] When the power transformer is working, a period of time is selected as the analysis time. During the analysis time, the current sensor is used to detect the current passing through each marked part when the power transformer is working. The charge amount of each marked part is calculated according to the analysis time and the current of each marked part: , where I is the current passing through the marked part when the power transformer is working, t is the analysis time interval, and Q is the charge at the corresponding marked part.

[0042] The dimensions of each marked part are collected in real time using a non-contact three-dimensional measuring instrument. As the insulating oil cools the power transformer for a long time, impurities in the insulating oil accumulate. Some impurities are adsorbed on the surface of various parts of the power transformer, increasing the size of the part. The more impurities adsorbed on the marked part, the larger the size of the marked part, and the increased internal resistance of the marked part leads to heat rise.

[0043] Two time points are randomly selected during the analysis time to detect the size of each marked part, and the size of the part detected at the previous time point is marked as a, and the size of the part detected at the next time point is marked as b.

[0044] It should be noted that the historical database is a system for storing and managing historical data, which contains the heat records of various parts of the voltage transformer in the past; the current sensor is a device for measuring current, which is used to detect the current passing through each marked part when the power transformer is working; the non-contact three-dimensional measuring instrument is a device that uses optical laser technology to perform three-dimensional space measurement, and in this example it is used to collect the part dimensions of different marked parts.

[0045] In step S2, the size expansion amount of the marked part is calculated according to the size of the marked part, and the size expansion amount of the marked part is obtained by subtracting the part size detected at the latter time point from the marked size detected at the previous time point during the analysis time. The thermal growth rate coefficient of each marked part is calculated according to the size expansion amount and the charge amount of the marked part and used as the thermal score of each marked part. It should be explained that the larger the size expansion amount of the marked part or the larger the charge amount, the faster the thermal growth rate of the marked part and the higher the thermal score;

[0046] Calculate the thermal acceleration coefficient of the marked area: ,in, is the size expansion of the marked part, is the charge at the marked site, is the thermal acceleration coefficient of the corresponding mark, and i is the serial number of each marked part.

[0047] The temperature sensor is used to detect the real-time temperature of each marked part, and the heat growth coefficient of each marked part is used as the heat score. The heat scores are sorted from small to large. The heat weight of each marked part after sorting is set by the hierarchical analysis method, and the main temperature index of the entire power transformer is calculated in combination with the real-time temperature of each marked part. The specific steps are as follows:

[0048] Constructing a scoring matrix: The relative importance of each part is compared by constructing a scoring matrix based on the heat score of each marked part. A 3-point scale of 1 to 3 is used, where 1 indicates the same importance, 2 indicates a slight difference in importance, and 3 indicates a severe difference in importance.

[0049] Standardization: Standardize each column of the rating matrix so that the sum of each column is equal to 1. For the above rating matrix, the standardized matrix is ​​as follows:

[0050] Calculate eigenvalues: Calculate the eigenvalue of each factor. The eigenvalue is the weighted average of each column of the scoring matrix. The eigenvalue of each part is used as the quantitative value of the importance of each part. The calculation is as follows:

[0051] Importance of part A = (0.1111 + 0.1429 + 0.1816) / 3 = 0.1452

[0052] Importance of part B = (0.3333 + 0.2857 + 0.2728) / 3 = 0.2973

[0053] Importance of part C = (0.5000 + 0.5714 + 0.5454) / 3 = 0.5389

[0054] The characteristic value of each part is used as the heat weight of the corresponding marked part, and the heat weight of each marked part and the real-time temperature of the corresponding marked part are weighted and summed to obtain the main temperature index of the entire power transformer.

[0055] It should be noted that in the above-mentioned hierarchical analysis method, this example takes three parts as an example. In actual application, it is determined according to the number of marked parts screened out. In addition, the order of parts A, B, and C is consistent with the order of the heat scores of each marked part from small to large.

[0056] In step S3, the main temperature index of the power transformer in the current power supply system is calculated and compared with a preset temperature index threshold. When the main temperature index of the power transformer is lower than the temperature index threshold, the natural convection cooling method is used to control the insulating oil to cool the power transformer; when the main temperature index of the power transformer exceeds the temperature index threshold, the forced circulation cooling method is used to control the insulating oil to cool the power transformer.

[0057] It should be noted that if the number of power transformers in the power supply system is not unique, the average value of the main stability index of each power transformer is compared with the temperature index threshold. The temperature index threshold is set by professionals in this field according to actual conditions and will not be elaborated here.

[0058] Natural convection cooling is a technology that uses the principle of natural convection to dissipate heat and cool the transformer. When the power transformer is in operation, heat is generated due to the passage of electric current. In the natural convection cooling method, the power transformer is immersed in insulating oil. When the insulating oil is heated, the density decreases, the oil moves upward, and the cold oil with a lower temperature is replenished from below, forming a natural convection cycle. The natural convection cooling method can increase the available time of the insulating oil, but the cooling effect is general.

[0059] Forced circulation cooling is a cooling technology that promotes the flow of cooling medium through mechanical means. In power transformers, the insulating oil is forced to circulate through a pump or fan, allowing it to flow quickly between the internal and external cooling systems of the power transformer, thereby improving the heat dissipation effect. However, it will accelerate the deterioration of the insulating oil and reduce the usable time of the insulating oil.

[0060] In order to increase the usable time of insulating oil, the next cooling time is calculated after each cooling process of the power transformer using the forced circulation cooling method to control the insulating oil;

[0061] After the cooling process is completed, the acid value of the insulating oil is measured and recorded using a pH meter, and the acid value of the insulating oil measured this time is subtracted from the acid value of the insulating oil recorded last time to obtain the change in the acid value of the insulating oil;

[0062] After the cooling process is completed, the insulating oil is collected according to the set fixed collection volume, and particles exceeding the preset size are obtained and their number is counted to obtain the impurity particle count and record it.

[0063] It should be noted that the pH meter is an instrument for measuring the acidity and alkalinity of a solution. The higher the acid value of the insulating oil or the more impurities it contains, the greater the degree of deterioration of the insulating oil, and the more it needs to adjust the cooling time of the forced circulation cooling method.

[0064] In step S4, the acid coefficient of the current insulating oil is calculated by using a polynomial regression algorithm based on the change in the acid value of the insulating oil and the count of impurity particles: ,in is the acidity coefficient of the current insulating oil, is the change in the acid value of the insulating oil after the cooling adjustment. is the impurity particle count after cooling adjustment. and are the influence weights of the two parameters respectively, is a modulation constant used to compress the acid coefficient to a suitable range for calculating the control ratio of the cooling time.

[0065] The greater the change in the acid value of the insulating oil after the first cooling modulation or the greater the impurity particle count, the higher the acid coefficient of the current insulating oil is, and the more it is necessary to reduce the cooling time of the next forced circulation cooling method.

[0066] The reciprocal of the acid coefficient of the current insulating oil is taken as the cooling adjustment ratio of the next forced circulation cooling method, and the product of the cooling time of the current forced circulation cooling method and the cooling adjustment ratio is taken as the cooling time of the next forced circulation cooling method;

[0067] Each time the forced circulation cooling method is used to control the cooling of the insulating oil, the cooling time is recorded in real time. When the processing time reaches the cooling time of that time, the natural convection cooling method is switched to cool the power transformer. If the cooling time of the next forced circulation cooling method calculated from the cooling time of the current forced circulation cooling method is lower than the preset processing time threshold, an early warning is issued and a prompt is given to replace the insulating oil.

[0068] It should be noted that the setting of influence weight is not unique and can be set according to actual conditions. For example, and They are set to 0.4 and 0.6 respectively. In addition, the cooling time when the forced circulation cooling method is used for the first time is set by professionals and will not be analyzed in detail here.

[0069] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented by software, the above embodiments may be implemented in whole or in part in the form of a computer program product.

[0070] Those of ordinary skill in the art will appreciate that the modules and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application of the technical solution and the invention constraints. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0071] In addition, each functional module in each embodiment of the present application may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.

[0072] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0073] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A defect early warning method for an oil-immersed power transformer, characterized in that: The following steps are included: Step S1: obtaining heat records of various parts of the power transformer, screening and marking the heating parts of the power transformer according to the heat records of various parts; collecting the part dimensions of the marked parts, detecting the current passing through the marked parts when the power transformer is working, and calculating the charge; Step S2: Calculate the thermal acceleration coefficient of each marked part as a thermal score according to the size expansion amount and charge amount of the marked part; detect the real-time temperature of each marked part, use the hierarchical analysis method to determine the thermal weight of each marked part according to the thermal score, and calculate the main temperature index of the power transformer in combination with the real-time temperature of the corresponding marked part; Step S3: according to the main temperature index, a natural convection cooling method or a forced circulation cooling method is selected to cool the power transformer using insulating oil, and after each cooling treatment using the forced circulation cooling method, the acid value of the insulating oil is measured and the acid value change is calculated, and the number of particles in the insulating oil is collected to obtain the impurity particle count and record it; Step S4: Calculate the acid coefficient of the current insulating oil based on the change in the acid value of the insulating oil and the count of impurity particles, and calculate the cooling time of the forced circulation cooling treatment based on the acid coefficient. If the adjusted cooling time of the forced circulation cooling treatment is lower than the preset treatment time threshold, issue an early warning to replace the insulating oil.

2. The oil-immersed power transformer defect early warning method according to claim 1 is characterized in that: In step S1, the heat records of various parts of the power transformer are called through the historical database. The heat records of various parts are the temperatures of various parts under normal operation of the power transformer in the historical data. The temperatures of various parts under normal operation of the power transformer are used as the regional temperatures of various parts. The regional temperatures of all parts in the power transformer are recorded and the temperature average is calculated as the temperature screening threshold. Parts exceeding the temperature screening threshold are screened out and marked. The historical database is a system for storing and managing historical data, which contains the thermal records of various parts of the power transformer in the past.

3. The oil-immersed power transformer defect early warning method according to claim 1 is characterized in that: In step S1, a period of time is selected as the analysis time when the power transformer is working. During the analysis time, the current passing through each marked part when the power transformer is working is detected by using a current sensor. The charge amount of each marked part is calculated according to the analysis time and the current of each marked part: , where I is the current passing through the marked part when the power transformer is working, t is the analysis time interval, and Q is the charge amount at the corresponding marked part; Two time points were randomly selected during the analysis time to detect the site size of each marked site.

4. The oil-immersed power transformer defect early warning method according to claim 3 is characterized in that: In step S2, the size of the part detected at the next time point is subtracted from the size of the mark detected at the previous time point during the analysis time to obtain the size expansion of the marked part, and the thermal acceleration coefficient of each marked part is calculated according to the size expansion and charge of the marked part and used as the thermal score of each marked part; Calculate the thermal acceleration coefficient of the marked area: ,in, is the size expansion of the marked part, is the charge at the marked site, is the thermal acceleration coefficient of the corresponding marked part, and i is the serial number of each marked part; The real-time temperature of each marked part is detected by a temperature sensor, and the thermal acceleration coefficient of each marked part is used as a heat score. The heat scores are sorted from small to large, and the heat weight of each marked part after sorting is set using the hierarchical analysis method. The temperature sensor is a device for detecting temperature, which is used to detect the real-time temperature of each marked part.

5. The oil-immersed power transformer defect early warning method according to claim 4 is characterized in that: In step S2, the heat weight is set by using the hierarchical analysis method and the main temperature index of the entire power transformer is calculated in combination with the real-time temperature of each marked part. The specific steps are as follows: Constructing a scoring matrix: Constructing a scoring matrix based on the heat scores of each marked part to compare the relative importance of each part; Standardization: Standardize each column of the scoring matrix so that the sum of each column is equal to 1; Calculate eigenvalues: Calculate the eigenvalue of each factor. The eigenvalue is the weighted average of each column of the scoring matrix. The eigenvalue of each part is used as the quantitative value of the importance of each part. The characteristic value of each part is used as the heat weight of the corresponding marked part, and the heat weight of each marked part and the real-time temperature of the corresponding marked part are weighted and summed to obtain the main temperature index of the entire power transformer.

6. The oil-immersed power transformer defect early warning method according to claim 5 is characterized in that: In step S3, when the main temperature index of the power transformer is lower than the temperature index threshold, the insulating oil is controlled by the natural convection cooling method to cool the power transformer; when the main temperature index of the power transformer exceeds the temperature index threshold, the insulating oil is controlled by the forced circulation cooling method to cool the power transformer; In the natural convection cooling method, when the insulating oil is heated, the density decreases, the oil moves upward, and the oil below is replenished, forming a natural convection cycle; The forced circulation cooling method uses a pump or fan to force the insulating oil to circulate quickly between the inside of the power transformer and the external cooling system.

7. The oil-immersed power transformer defect early warning method according to claim 1 is characterized in that: In step S3, after each cooling process using the forced circulation cooling method is completed, the acid value of the insulating oil is measured and recorded using a pH meter, and the acid value of the insulating oil measured this time is subtracted from the acid value of the insulating oil recorded last time to obtain the acid value change of the insulating oil; the insulating oil is collected according to the set fixed collection volume, and particles exceeding a preset size are obtained and their number is counted to obtain the impurity particle count and record it; A pH meter is an instrument for measuring the acidity or alkalinity of a solution and is used to detect the acid value of insulating oil.

8. The oil-immersed power transformer defect early warning method according to claim 7 is characterized in that: In step S4, the acid coefficient of the current insulating oil is calculated by using a polynomial regression algorithm based on the change in the acid value of the insulating oil and the count of impurity particles: ,in is the acidity coefficient of the current insulating oil, is the change in the acid value of the insulating oil after the cooling adjustment. is the impurity particle count after cooling adjustment. and are the influence weights of the two parameters respectively, is the modulation constant; The reciprocal of the current acid coefficient of the insulating oil is taken as the cooling adjustment ratio of the next forced circulation cooling method, and the product of the cooling time of the current forced circulation cooling method and the cooling adjustment ratio is taken as the cooling time of the next forced circulation cooling method.

9. The oil-immersed power transformer defect early warning method according to claim 8, characterized in that: In step S4, each time the forced circulation cooling method is used to control the insulating oil to perform cooling treatment, the processing time is recorded in real time. When the processing time reaches the cooling time of the current time, the natural convection cooling method is switched to perform cooling treatment on the power transformer; If the cooling time of the next forced circulation cooling method calculated from the cooling time of the current forced circulation cooling method is lower than the preset processing time threshold, an early warning is issued and a prompt is given to replace the insulating oil.

Images