Generator stator winding end portion corona assessment method and device, medium and equipment

Abstract

The invention discloses a generator stator winding end portion corona assessment method and device, a medium and equipment. The method comprises the following steps: determining a relational expression between characteristic parameters and discharge capacity according to characteristic parameter data and discharge capacity data generated in a corona discharge process of the end part of a stator winding; wherein the characteristic parameters include but are not limited to ultrasonic signals, ultrahigh frequency signals, ultraviolet light pulses and ozone concentration; according to parameter data of the corona discharge process of the end part of the stator winding, determining a weight coefficient corresponding to the characteristic parameter; and determining a first target discharge amount according to a weight coefficient corresponding to the characteristic parameter and a relational expression. According to a plurality of characteristic parameters generated in the corona discharge process of the end part of the stator winding, the corona discharge capacity of the end part of the stator winding is jointly determined, and the determination accuracy of the discharge capacity is improved.

Description

Technical Field

[0001] The present application relates to the field of corona discharge technology, and in particular to a method, device, medium and equipment for evaluating corona at the end of a generator stator winding. Background Art

[0002] Large high-voltage generators are important equipment in the power system that is responsible for the task of outputting electric energy. Power outages caused by failures of large high-voltage generators will not only cause direct paralysis of the entire social industrial system, but will also affect other equipment in the entire power system and endanger the safety of their equipment.

[0003] The safety hazards of large high-voltage generators mainly come from their stator windings, and most of the operating accidents of large high-voltage generators are caused by abnormalities in the stator winding insulation system. Therefore, in the relevant technology, the insulation of the stator winding is evaluated by performing a corona discharge test on the end of the generator stator winding.

[0004] Among them, the discharge amount obtained by the corona discharge test is the most direct and reliable characteristic quantity for evaluating the insulation of the electrode winding, but the measurement of the discharge amount is easily affected by on-site electromagnetic interference, and the error is large in practical applications. In addition, among the related technologies for determining the amount of corona discharge, most of them only stay at the level of qualitative analysis, and the few studies on quantitative monitoring of corona discharge also have shortcomings, such as low sensitivity, difficulty in capturing the optical signal in the initial stage of corona discharge, or high performance requirements of the detection equipment, limited practicality, and poor monitoring effect of the decomposition gas analysis method on the initial stage of corona discharge. Summary of the invention

[0005] In view of this, the present application provides a method, device, medium and equipment for evaluating corona at the end of a generator stator winding. The corona discharge amount at the end of the stator winding is jointly determined based on multiple characteristic parameters generated during the corona discharge process at the end of the stator winding, thereby improving the accuracy of determining the discharge amount.

[0006] According to one aspect of the present application, a method for evaluating the corona at the end of a generator stator winding is provided, comprising: determining a relationship expression between the characteristic parameter and the discharge amount based on characteristic parameter data and discharge amount data generated during a corona discharge process at the end of the stator winding; determining a weight coefficient corresponding to the characteristic parameter based on the parameter data of the corona discharge process at the end of the stator winding; and determining a first target discharge amount based on the weight coefficient corresponding to the characteristic parameter and the relationship expression.

[0007] Optionally, the method of determining a relationship expression between the characteristic parameter and the discharge amount based on the characteristic parameter data and the discharge amount data generated during the corona discharge process at the end of the stator winding comprises: determining a scatter plot between the characteristic parameter and the discharge amount based on the characteristic parameter data and the discharge amount data; fitting the scatter plot, and determining a relationship expression between the characteristic parameter and the discharge amount based on a curve obtained by fitting.

[0008] Optionally, determining the first target discharge amount according to the weight coefficient corresponding to the characteristic parameter and the relationship expression includes: determining the second target discharge amount corresponding to the characteristic parameter according to the characteristic parameter data and the relationship expression; and performing weighted processing on the second target discharge amount corresponding to the characteristic parameter according to the weight coefficient corresponding to the characteristic parameter to determine the first target discharge amount.

[0009] Optionally, determining the weight coefficient corresponding to the characteristic parameter based on the parameter data of the corona discharge process at the stator winding end includes: comparing the parameter data with multiple preset parameter ranges; and determining the weight coefficient corresponding to the characteristic parameter based on the preset weight coefficient corresponding to the target preset parameter range that matches the parameter data.

[0010] Optionally, the corona assessment method for the end of the stator winding of a generator also includes: obtaining first historical characteristic parameter data, first historical discharge quantity data and second historical discharge quantity data of the corona discharge process corresponding to the preset parameter range; determining a historical relationship expression between the characteristic parameter and the discharge quantity based on the first historical characteristic parameter data and the first historical discharge quantity data; taking the sum of the preset weight coefficients corresponding to the characteristic parameter as 1 as a constraint condition, determining an objective function of the preset weight coefficient corresponding to the characteristic parameter based on the second historical discharge quantity data, the first historical characteristic reference data and the historical relationship expression; if the value of the objective function is less than a first preset threshold value, determining the value of the preset weight coefficient corresponding to the preset parameter range.

[0011] Optionally, the corona assessment method for the end of a generator stator winding also includes: before corona discharge occurs at the end of the stator winding, obtaining initial characteristic parameter data in the corona discharge environment of the end of the stator winding; if the initial characteristic parameter data is less than a second preset threshold, obtaining the characteristic parameter data and the discharge amount data generated by the corona discharge process at the end of the stator winding.

[0012] Optionally, the corona assessment method for the end of the generator stator winding also includes: comparing the first target discharge amount with multiple preset discharge amount ranges; determining the risk level of the first target discharge amount according to a preset level corresponding to a target preset discharge amount range that matches the first target discharge amount.

[0013] According to another aspect of the present application, a corona assessment device for a generator stator winding end is provided, comprising: a determination module for determining a relationship expression between a characteristic parameter and a discharge amount based on characteristic parameter data and discharge amount data generated during a corona discharge process at the stator winding end; and, based on the parameter data of the corona discharge process at the stator winding end, determining a weight coefficient corresponding to the characteristic parameter; and, based on the weight coefficient corresponding to the characteristic parameter and the relationship expression, determining a first target discharge amount.

[0014] Optionally, the determination module is specifically used to determine a scatter plot between the characteristic parameter and the discharge amount based on the characteristic parameter data and the discharge amount data; fit the scatter plot, and determine a relationship expression between the characteristic parameter and the discharge amount based on a curve obtained by fitting.

[0015] Optionally, the determination module is specifically used to determine the second target discharge amount corresponding to the characteristic parameter according to the characteristic parameter data and the relationship expression; and to perform weighted processing on the second target discharge amount corresponding to the characteristic parameter according to the weight coefficient corresponding to the characteristic parameter to determine the first target discharge amount.

[0016] Optionally, the determination module is specifically used to compare the parameter data with multiple preset parameter ranges; and determine the weight coefficient corresponding to the characteristic parameter according to the preset weight coefficient corresponding to the target preset parameter range matched by the parameter data.

[0017] Optionally, the generator stator winding end corona assessment device further comprises:

[0018] An extreme value module is used to obtain the first historical characteristic parameter data, the first historical discharge amount data and the second historical discharge amount data of the corona discharge process corresponding to the preset parameter range; determine the historical relationship expression between the characteristic parameter and the discharge amount according to the first historical characteristic parameter data and the first historical discharge amount data; take the sum of the preset weight coefficients corresponding to the characteristic parameter as 1 as a constraint condition, determine the objective function of the preset weight coefficient corresponding to the characteristic parameter according to the second historical discharge amount data, the first historical characteristic reference data and the historical relationship expression; if the value of the objective function is less than the first preset threshold value, determine the value of the preset weight coefficient corresponding to the preset parameter range.

[0019] Optionally, the generator stator winding end corona assessment device further comprises:

[0020] An acquisition module is used to acquire initial characteristic parameter data in the corona discharge environment of the stator winding end before corona discharge is performed at the stator winding end; if the initial characteristic parameter data is less than a second preset threshold, the characteristic parameter data and the discharge amount data generated by the corona discharge process of the stator winding end are acquired.

[0021] Optionally, the generator stator winding end corona assessment device further comprises:

[0022] A comparison module, used for comparing the first target discharge amount with a plurality of preset discharge amount ranges;

[0023] The risk level of the first target discharge amount is determined according to a preset level corresponding to a target preset discharge amount range that matches the first target discharge amount.

[0024] According to another aspect of the present application, a readable storage medium is provided, on which a program or instruction is stored. When the program or instruction is executed by a processor, the steps of the above-mentioned method for evaluating corona at the end of a generator stator winding are implemented.

[0025] According to another aspect of the present application, a computer device is provided, including a storage medium, a processor, and a computer program stored on the storage medium and executable on the processor, and the processor implements the steps of the above-mentioned method for evaluating corona at the end of a generator stator winding when executing the program.

[0026] By means of the above technical scheme, the present application provides a method, device, medium and equipment for evaluating the corona at the end of the stator winding of a generator. According to the characteristic parameter data and discharge amount data generated by the corona discharge at the end of the stator winding, the relationship expression between the characteristic parameter and the discharge amount is determined, and the correlation between each characteristic parameter and the discharge amount is independently analyzed. And according to the weight coefficient corresponding to the characteristic parameter, the importance of different characteristic parameters in determining the discharge amount is reflected, so as to determine the first target discharge amount according to the weight coefficient corresponding to the characteristic parameter and the relationship expression, so that the obtained first target discharge amount can more comprehensively characterize the actual situation of the corona discharge at the end of the stator winding of the generator, improve the accuracy of the determination of the discharge amount, and then improve the accuracy of the corona discharge severity assessment, which effectively solves the inaccuracy and limitation of evaluating the severity of corona discharge with a single characteristic parameter.

[0027] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0029] Figure 1 A schematic flow chart of a method for evaluating corona at the end of a generator stator winding provided in an embodiment of the present application is shown;

[0030] Figure 2 The structural block diagram of the corona assessment device for the stator winding end of a generator provided in an embodiment of the present application is shown. DETAILED DESCRIPTION

[0031] The present application will be described in detail below with reference to the accompanying drawings and in combination with embodiments. It should be noted that the embodiments and features in the embodiments of the present application can be combined with each other without conflict.

[0032] The embodiments of the present application are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present application, and cannot be interpreted as limiting the present application.

[0033] Those skilled in the art will appreciate that, unless expressly stated, the singular forms "a", "an", "said" and "the" used herein may also include plural forms. It should be further understood that the term "comprising" used in the specification of the present application refers to the presence of the features, integers, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or groups thereof. It should be understood that when we refer to an element as being "connected" or "connected" to another element, it may be directly connected or connected to the other element, or there may be intermediate elements. In addition, the "connection" or "connection" used herein may include wireless connection or wireless fusion. The term "and / or" used herein includes all or any unit and all combinations of one or more associated listed items.

[0034] Now, exemplary embodiments according to the present application will be described in more detail with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in a variety of different forms and should not be interpreted as being limited to the embodiments set forth herein. It should be understood that these embodiments are provided to make the disclosure of the present application thorough and complete, and to fully convey the concepts of these exemplary embodiments to those of ordinary skill in the art.

[0035] The corona assessment method for the end of the generator stator winding provided in the embodiment of the present application can be applied to the terminal, can also be applied to the server, and can also be software running in the terminal or the server. In some embodiments, the terminal can be a smart phone, a tablet computer, a laptop computer, a desktop computer, etc.; the server side can be configured as an independent physical server, or a server cluster or distributed system composed of multiple physical servers, and can also be configured as a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms; the software can be an application that implements the corona assessment method for the end of the generator stator winding, etc., but is not limited to the above forms.

[0036] In this embodiment, a method for evaluating corona at the end of a generator stator winding is provided. Figure 1 As shown, the method includes:

[0037] Step 101, determining a relational expression between the characteristic parameter and the discharge amount according to the characteristic parameter data and the discharge amount data generated during the corona discharge process at the stator winding end.

[0038] In this example, corona discharge is analyzed from multiple dimensions, and the influence of each characteristic parameter on the discharge amount during the corona discharge process is independently evaluated, providing a reliable basis for accurately evaluating the severity of corona discharge at the end of the generator stator winding.

[0039] Further, as a refinement and expansion of the specific implementation method of the above-mentioned embodiment, in order to fully illustrate the specific implementation process of this embodiment, step 101, that is, determining the relationship expression between the characteristic parameter and the discharge amount based on the characteristic parameter data and the discharge amount data generated by the corona discharge process at the end of the stator winding, specifically includes: determining a scatter plot between the characteristic parameter and the discharge amount based on the characteristic parameter data and the discharge amount data; fitting the scatter plot, and determining the relationship expression between the characteristic parameter and the discharge amount based on the curve obtained by fitting.

[0040] In this embodiment, characteristic information of corona discharge is obtained from multiple angles, and the originally relatively abstract corona discharge phenomenon is converted into a specific mathematical expression by determining the mathematical relationship between the discharge amount and various characteristic parameters generated during the corona discharge process. This allows the discharge amount to be quantitatively calculated by measuring the characteristic parameters that are relatively easy to obtain, which is conducive to more accurately determining the discharge amount of the corona discharge.

[0041] Exemplarily, a corona discharge test is performed on the stator winding end of an air-cooled generator. The stator winding of the air-cooled generator is placed in a sealed container filled with air, and the required sensors and partial discharge measuring instruments are installed. Different types of sensors and partial discharge measuring instruments are used to measure different characteristic parameters and the change of discharge amount with discharge time at a target test voltage, so as to obtain characteristic parameter data and discharge amount data generated by the corona discharge process at the stator winding end at the target test voltage.

[0042] The characteristic parameters include but are not limited to ultrasonic signals, ultra-high frequency signals, ultraviolet light pulses, and ozone concentration.

[0043] Furthermore, the mathematical relationship between the discharge amount and each characteristic parameter is determined respectively. Exemplarily, for any characteristic parameter, a scatter plot between the discharge amount and the characteristic parameter is determined based on the discharge amount data and the characteristic parameter data, and the scatter plot is fitted with a curve to determine the relationship expression between the characteristic parameter and the discharge amount at the target test voltage. Generally, after fitting the scatter plot, a straight line is obtained, thereby determining the linear relationship between the characteristic parameter and the discharge amount.

[0044] Among them, the target test voltage can be the rated phase voltage of the generator, the maximum operating voltage, or any voltage between the rated phase voltage and the maximum operating voltage. It can be set specifically according to the actual application scenario to evaluate the performance of the generator under normal operating voltage conditions, thereby checking whether there are defects in the stator winding and ensuring the safety and reliability of the generator during normal operation.

[0045] Step 102: Determine the weight coefficient corresponding to the characteristic parameter according to the parameter data of the corona discharge process at the stator winding end.

[0046] In this embodiment, the specific working condition of the current corona discharge process is determined based on the parameter data of the corona discharge process at the stator winding end, so as to specifically determine the importance of each characteristic parameter in the current working condition, so that the first target discharge amount determined by weight in the subsequent steps is more accurate and reliable.

[0047] It should be noted that the parameter data of the corona discharge process of the stator winding end includes but is not limited to the capacity of the generator, the structural design of the generator stator winding connection, and the test voltage of the corona discharge process. For example, the parameter data under one working condition is: 300MW unit 3Y connection 1.1U n Voltage, the parameter data under another working condition is: 200MW unit 2Y connection Voltage is lower, among which, U n is the rated voltage of the generator.

[0048] Further, as a refinement and expansion of the specific implementation methods of the above-mentioned embodiment, in order to fully illustrate the specific implementation process of this embodiment, step 102, that is, determining the weight coefficient corresponding to the characteristic parameter based on the parameter data of the corona discharge process at the end of the stator winding, specifically includes: comparing the parameter data with multiple preset parameter ranges; determining the weight coefficient corresponding to the characteristic parameter based on the preset weight coefficient corresponding to the target preset parameter range matching the parameter data.

[0049] Specifically, the influence degree of each characteristic parameter on the discharge amount under different parameter ranges corresponding to different working conditions is predetermined, that is, the preset weight coefficient corresponding to each characteristic parameter under different preset parameter ranges is predetermined.

[0050] In this embodiment, by comparing the parameter data of the current corona discharge process at the end of the stator winding with multiple preset parameter ranges, the operating condition closest to the current operating condition is determined, and then the weight coefficients corresponding to the various characteristic parameters under the current operating condition are determined according to the preset weight coefficients corresponding to the closest operating condition, so as to reflect the actual influence of the characteristic parameters on the discharge amount in the current corona discharge process at the end of the stator winding, so that the first target discharge amount calculated according to the weight coefficients in the subsequent steps is more in line with the actual situation.

[0051] Exemplarily, a preset weight coefficient corresponding to a target preset parameter range matched by the parameter data is used as a weight coefficient corresponding to a characteristic parameter in the current corona discharge test.

[0052] Step 103: determining a first target discharge capacity according to the weight coefficient and the relationship expression corresponding to the characteristic parameter.

[0053] In this embodiment, various characteristic parameters are comprehensively considered to calculate the first target discharge capacity, thereby improving the accuracy and reliability of the discharge capacity determination.

[0054] Furthermore, as a refinement and extension of the specific implementation methods of the above-mentioned embodiment, in order to fully illustrate the specific implementation process of this embodiment, the second target discharge amount corresponding to the characteristic parameter is determined according to the characteristic parameter data and the relationship expression; according to the weight coefficient corresponding to the characteristic parameter, the second target discharge amount corresponding to the characteristic parameter is weighted to determine the first target discharge amount.

[0055] In this embodiment, the second target discharge amount represented by each characteristic parameter in the corona discharge process is calculated according to the relational expression, reflecting the corona discharge situation from different angles, and the second target discharge amount represented by the characteristic parameter is weighted according to the weight coefficient corresponding to the characteristic parameter, and the information of multiple characteristic parameters is integrated to determine a more comprehensive and accurate corona discharge amount at the stator winding end.

[0056] Exemplarily, in step 101, the relationship expression between the characteristic parameter and the discharge amount under the target test voltage has been determined based on the characteristic parameter data and the discharge amount data generated by the stator winding end of the air-cooled generator during the corona discharge process. Furthermore, the characteristic parameter data generated by the corona discharge process of the stator winding end under the same test voltage as the target test voltage can be substituted into the relationship expression to calculate the second target discharge amount corresponding to the characteristic parameter. For example, if the relationship expression is based on 1.1U n The characteristic parameter data generated under the test voltage and the discharge capacity data are determined, then the characteristic parameter data of the second target discharge capacity is substituted into the relationship expression, which also needs to be 1.1U n Characteristic parameter data generated under the test voltage.

[0057] Furthermore, according to the calculated second target discharge amounts represented by the characteristic parameters, a first target discharge amount of corona discharge at the end of the stator winding of the generator is determined by weighted summation.

[0058] Exemplarily, the first target discharge amount is expressed as:

[0059] Q=k1f(x1)+k2f(x2)+k3f(x3)+k4f(x4)...+k m f(x m ). (1)

[0060] Among them, x a (a=1...m) is the characteristic parameter, m is the total number of characteristic parameters, k a (a=1...m) is the characteristic parameter x a The corresponding preset weight coefficient, f(x a ) is the characteristic parameter x a The relationship expression between it and the discharge capacity.

[0061] It is worth mentioning that, unlike the preset weight coefficients corresponding to the characteristic parameters under different working conditions, the relationship expression determined by using the characteristic parameter data generated by the current stator winding end corona discharge process and the discharge amount data can capture the influence of unique factors such as specific equipment, environment, and operating conditions on corona discharge in the current corona discharge test. The relationship expression determined by the current data can take these unique factors into consideration, thereby improving the accuracy of the discharge amount calculation.

[0062] In one embodiment, the corona assessment method for the end of a generator stator winding also includes: comparing a first target discharge amount with a plurality of preset discharge amount ranges; and determining a risk level of the first target discharge amount according to a preset level corresponding to a target preset discharge amount range that matches the first target discharge amount.

[0063] In this embodiment, according to the determined first target discharge amount, the severity of corona discharge at the stator winding end is quickly and accurately evaluated to determine the risk level, which has important practical application significance for insulation aging evaluation and life evaluation of the generator stator winding end.

[0064] Exemplarily, a large amount of historical first target discharge data is obtained, and the severity of corona discharge at the end of the stator winding is evaluated accordingly according to the insulation condition of the stator winding corresponding to the historical first target discharge data, so as to determine the risk level, such as slight, medium, severe, etc., and the historical first target discharge data is classified and sorted according to the risk level. A statistical distribution diagram of the risk level is established based on the sorted historical first target discharge data. The correspondence between the preset discharge range and the risk level is divided according to the statistical distribution curve, for example, based on the shape of the statistical distribution curve and the data distribution, a natural dividing point is identified, such as an obvious fault or a distribution tail.

[0065] In one embodiment, the corona assessment method for the end of the stator winding of a generator also includes: obtaining first historical characteristic parameter data, first historical discharge quantity data and second historical discharge quantity data of the corona discharge process corresponding to a preset parameter range; determining a historical relationship expression between the characteristic parameter and the discharge quantity based on the first historical characteristic parameter data and the first historical discharge quantity data; taking the sum of the preset weight coefficients corresponding to the characteristic parameters as 1 as a constraint condition, determining an objective function of the preset weight coefficient corresponding to the characteristic parameter based on the second historical discharge quantity data, the first historical characteristic reference data and the historical relationship expression; if the value of the objective function is less than the first preset threshold value, determining the value of the preset weight coefficient corresponding to the preset parameter range.

[0066] In this embodiment, based on historical data obtained from historical experiments, preset weight coefficients of characteristic parameters under different operating conditions are predetermined so that the preset weight coefficients can cover more operating conditions, thereby being able to quickly match the preset weight coefficients corresponding to the current operating conditions in actual application scenarios, thereby improving the efficiency of determining the first target discharge amount.

[0067] Specifically, according to the needs of the actual application scenario, determine which working conditions the weight coefficients need to be predetermined. For example, according to the common generator capacity, the structural design of the generator stator winding connection, and the test voltage of the corona discharge process in the actual application scenario, determine the preset parameter ranges corresponding to multiple different target working conditions.

[0068] For any target operating condition, multiple groups of historical tests are carried out in the laboratory and in the actual operating environment according to the preset parameter range corresponding to the target operating condition, so as to obtain the accurate second historical discharge data measured in the laboratory, as well as the first historical characteristic parameter data and the first historical discharge data measured in the actual operating environment.

[0069] Furthermore, according to the first historical characteristic parameter data and the first historical discharge quantity data, step 101 is used to determine the historical relationship expression between the characteristic parameter and the discharge quantity under the actual operating environment, and the discharge quantity calculation value (historical second target discharge quantity) corresponding to the characteristic parameter is determined according to the historical relationship expression. Then, according to the difference between the accurate second historical discharge quantity data in the laboratory and the discharge quantity calculation value multiplied by the preset weight coefficient, the objective function of the preset weight coefficient corresponding to the characteristic parameter is determined. Using the conditional extreme value method in higher mathematics, with the sum of the preset weight coefficients corresponding to the characteristic parameter being 1 as a constraint condition, if the value of the objective function is the smallest (less than the first preset threshold), the value of the preset weight coefficient corresponding to the characteristic parameter is determined. Among them, the first preset threshold is used to control the calculation accuracy of the conditional extreme value, which is specifically determined according to the actual application scenario, and this application does not limit it here.

[0070] Exemplarily, the objective function is expressed as:

[0071]

[0072] Where n is the number of data sets (number of historical test sets) substituted into formula (2), f i (x a )' is the characteristic parameter x in the i-th historical test under the actual operating environment a The historical relationship expression between Q and discharge capacity; i ' is the second historical discharge data measured by the i-th group of historical tests in the laboratory; k1+k2+k3+k4...+k n =1.

[0073] In this embodiment, the constructed objective function S is the second historical discharge data measured in the laboratory, minus four discharge calculation values ​​multiplied by preset weight coefficients, and the values ​​of k1, k2, k3, and k4 sought should minimize S. Substituting the second historical discharge data and the first historical characteristic parameter data measured in each group of historical tests in the laboratory and the actual operating environment into formula (2), and applying the conditional extreme value method in higher mathematics, the values ​​of each preset weight coefficient, i.e., k1, k2, k3, and k4, can be obtained.

[0074] In this embodiment, by constructing the objective function S to minimize the value of S, the optimal combination of preset weight coefficients is determined, so that the discharge amount obtained according to the method of this embodiment can be as close as possible to the accurate discharge amount measured in the laboratory (the second historical discharge amount data), thereby ensuring the accuracy of the preset weight coefficients and improving the accuracy of the evaluation of the corona discharge amount at the end of the stator winding.

[0075] In one embodiment, the corona assessment method for the stator winding end of a generator further includes: before corona discharge occurs at the stator winding end, obtaining initial characteristic parameter data in the corona discharge environment at the stator winding end; if the initial characteristic parameter data is less than a second preset threshold, obtaining characteristic parameter data and discharge amount data generated by the corona discharge process at the stator winding end.

[0076] In this embodiment, before the corona discharge test is performed on the stator winding, the values ​​measured by various sensors in the environmental background are detected when the stator winding is not powered, thereby reducing the influence of external environmental factors and errors of the instrument itself.

[0077] For example, before the corona discharge test, the initial characteristic parameter data measured by each sensor in the environmental background when the stator winding is not powered is used as the background partial discharge level to evaluate the purity of the corona discharge test environment and ensure the accuracy of the data. By determining the background partial discharge level, the minimum detectable signal level generated by each sensor itself in the absence of partial discharge can be determined, reflecting the sensitivity and resolution of the sensor. If the background noise value is too high, it may mask the partial discharge signal, resulting in the inability to accurately detect the partial discharge inside the stator winding, thereby affecting the judgment of the insulation state of the stator winding.

[0078] Furthermore, if the initial characteristic parameter data is less than the second preset threshold, the characteristic parameter data and discharge amount data generated by the corona discharge process at the stator winding end are obtained to ensure the accuracy and reliability of the measurement data. In addition, determining the background partial discharge level helps to identify and eliminate signal interference caused by non-partial discharge factors, further improving the accuracy and credibility of the measurement data. By comparing the initial characteristic parameter data with the actual measured signal level, it is possible to more accurately determine whether there is a partial discharge phenomenon and the severity of the discharge, providing an important basis for the maintenance and overhaul of the equipment.

[0079] In one embodiment, the corona assessment method for the end of a generator stator winding also includes: before conducting a corona discharge test on the end of the stator winding, conducting a corona discharge pre-test on the stator winding of the generator to determine its corona discharge starting voltage and the discharge amount measured by a local discharge measuring instrument at this voltage, and using this as a reference local discharge level to clarify the voltage range that needs to be controlled during the corona discharge process at the end of the stator winding, which helps to reasonably set the gradient of the target test voltage and make the corona discharge process at the end of the stator winding more efficient.

[0080] The present application provides a method, device, medium and equipment for evaluating corona at the end of a generator stator winding. The method has strong operability and effectively solves the inaccuracy and limitation of determining the amount of corona discharge by a single characteristic parameter. Multiple parameters are introduced to jointly determine the amount of corona discharge, and then the severity of the discharge is evaluated based on the amount of corona discharge jointly determined by the multiple parameters, thereby ensuring the accuracy and authenticity of the results. The method has important practical application significance for the insulation aging evaluation and life evaluation of the generator stator winding.

[0081] It should be noted that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0082] Furthermore, if Figure 2 As shown, as a specific implementation of the above-mentioned generator stator winding end corona assessment method, an embodiment of the present application provides a generator stator winding end corona assessment device 200, and the generator stator winding end corona assessment device 200 includes: a determination module 201.

[0083] Among them, the determination module 201 is used to determine the relationship expression between the characteristic parameter and the discharge amount according to the characteristic parameter data and the discharge amount data generated by the corona discharge process at the end of the stator winding; and, according to the parameter data of the corona discharge process at the end of the stator winding, determine the weight coefficient corresponding to the characteristic parameter; and, according to the weight coefficient corresponding to the characteristic parameter and the relationship expression, determine the first target discharge amount.

[0084] In one embodiment, the determination module 201 is specifically used to determine a scatter plot between the characteristic parameter and the discharge amount based on the characteristic parameter data and the discharge amount data; fit the scatter plot, and determine a relationship expression between the characteristic parameter and the discharge amount based on a curve obtained by fitting.

[0085] In one embodiment, the determination module 201 is specifically used to determine the second target discharge amount corresponding to the characteristic parameter according to the characteristic parameter data and the relationship expression; and to perform weighted processing on the second target discharge amount corresponding to the characteristic parameter according to the weight coefficient corresponding to the characteristic parameter to determine the first target discharge amount.

[0086] In one embodiment, the determination module 201 is specifically used to compare the parameter data with a plurality of preset parameter ranges; and determine the weight coefficient corresponding to the characteristic parameter according to the preset weight coefficient corresponding to the target preset parameter range matched by the parameter data.

[0087] In one embodiment, the generator stator winding end corona assessment device further comprises:

[0088] An extreme value module is used to obtain the first historical characteristic parameter data, the first historical discharge amount data and the second historical discharge amount data of the corona discharge process corresponding to the preset parameter range; determine the historical relationship expression between the characteristic parameter and the discharge amount according to the first historical characteristic parameter data and the first historical discharge amount data; with the sum of the preset weight coefficients corresponding to the characteristic parameters being 1 as a constraint condition, determine the objective function of the preset weight coefficient corresponding to the characteristic parameter according to the second historical discharge amount data, the first historical characteristic reference data and the historical relationship expression; if the value of the objective function is less than the first preset threshold value, determine the value of the preset weight coefficient corresponding to the preset parameter range.

[0089] In one embodiment, the generator stator winding end corona assessment device further comprises:

[0090] The acquisition module is used to acquire the initial characteristic parameter data in the corona discharge environment of the stator winding end before corona discharge is performed at the stator winding end; if the initial characteristic parameter data is less than the second preset threshold, the characteristic parameter data and discharge amount data generated by the corona discharge process of the stator winding end are acquired.

[0091] In one embodiment, the generator stator winding end corona assessment device further comprises:

[0092] The comparison module is used to compare the first target discharge amount with a plurality of preset discharge amount ranges; and determine the risk level of the first target discharge amount according to the preset level corresponding to the target preset discharge amount range that matches the first target discharge amount.

[0093] The specific definition of the corona evaluation device for the end of the generator stator winding can be found in the definition of the corona evaluation method for the end of the generator stator winding above, which will not be repeated here. Each module in the above-mentioned corona evaluation device for the end of the generator stator winding can be implemented in whole or in part by software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0094] Based on the above Figure 1 The method shown in the embodiment of the present application accordingly provides a readable storage medium on which a computer program is stored, and when the program is executed by a processor, the above-mentioned Figure 1 The corona assessment method for generator stator winding ends is shown.

[0095] Based on this understanding, the technical solution of the present application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.), and includes a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each implementation scenario of the present application.

[0096] Based on the above Figure 1 The method shown, and Figure 2 In order to achieve the above-mentioned purpose, the embodiment of the present application further provides a computer device, which can be a personal computer, a server, a network device, etc. The computer device includes a storage medium and a processor; the storage medium is used to store a computer program; the processor is used to execute the computer program to achieve the above-mentioned Figure 1 The corona assessment method for generator stator winding ends is shown.

[0097] Optionally, the computer device may further include a user interface, a network interface, a camera, a radio frequency (RF) circuit, a sensor, an audio circuit, a WI-FI module, etc. The user interface may include a display, an input unit such as a keyboard, etc., and the optional user interface may also include a USB interface, a card reader interface, etc. The network interface may optionally include a standard wired interface, a wireless interface (such as a Bluetooth interface, a WI-FI interface), etc.

[0098] Those skilled in the art will appreciate that the computer device structure provided in this embodiment does not limit the computer device, and may include more or fewer components, or a combination of certain components, or different component arrangements.

[0099] The storage medium may also include an operating system and a network communication module. The operating system is a program that manages and saves the hardware and software resources of the computer device, and supports the operation of information processing programs and other software and / or programs. The network communication module is used to realize communication between the components inside the storage medium, and communication with other hardware and software in the physical device.

[0100] Through the description of the above implementation methods, those skilled in the art can clearly understand that the present application can be implemented by means of software plus a necessary general hardware platform, or the embodiments of the present application can be implemented by hardware.

[0101] Those skilled in the art will appreciate that the accompanying drawings are only schematic diagrams of a preferred implementation scenario, and the modules or processes in the accompanying drawings are not necessarily necessary for implementing the present application. Those skilled in the art will appreciate that the modules in the devices in the implementation scenario can be distributed in the devices of the implementation scenario according to the description of the implementation scenario, or can be changed accordingly and located in one or more devices different from the present implementation scenario. The modules of the above-mentioned implementation scenario can be combined into one module, or can be further split into multiple submodules.

[0102] The above serial numbers of this application are only for description and do not represent the advantages and disadvantages of the implementation scenarios. The above disclosure is only a few specific implementation scenarios of this application, but this application is not limited to them, and any changes that can be thought of by technicians in this field should fall within the scope of protection of this application.

Claims

1. A method for evaluating corona at the end of a generator stator winding, characterized in that: The method comprises: According to the characteristic parameter data and discharge quantity data generated in the corona discharge process of the stator winding end, the relationship expression between the characteristic parameter and the discharge quantity is determined; Determining a weight coefficient corresponding to the characteristic parameter according to parameter data of the corona discharge process of the stator winding end; A first target discharge amount is determined according to the weight coefficient corresponding to the characteristic parameter and the relationship expression.

2. The corona evaluation method for the stator winding end of a generator according to claim 1, characterized in that: The method of determining the relationship between the characteristic parameter and the discharge amount according to the characteristic parameter data and the discharge amount data generated during the corona discharge process at the stator winding end includes: Determining a scatter plot between the characteristic parameter and the discharge amount according to the characteristic parameter data and the discharge amount data; The scatter plot is fitted, and a relationship expression between the characteristic parameter and the discharge amount is determined based on a curve obtained by fitting.

3. The corona evaluation method for the stator winding end of a generator according to claim 1, characterized in that: The determining of the first target discharge amount according to the weight coefficient corresponding to the characteristic parameter and the relational expression includes: Determining a second target discharge amount corresponding to the characteristic parameter according to the characteristic parameter data and the relational expression; According to the weight coefficient corresponding to the characteristic parameter, the second target discharge amount corresponding to the characteristic parameter is weighted to determine the first target discharge amount.

4. The corona evaluation method for the stator winding end of a generator according to claim 1, characterized in that: Determining the weight coefficient corresponding to the characteristic parameter according to the parameter data of the corona discharge process of the stator winding end includes: comparing the parameter data with a plurality of preset parameter ranges; The weight coefficient corresponding to the characteristic parameter is determined according to the preset weight coefficient corresponding to the target preset parameter range matched by the parameter data.

5. The corona evaluation method for the stator winding end of a generator according to claim 4, characterized in that: The method further comprises: Acquire first historical characteristic parameter data, first historical discharge quantity data and second historical discharge quantity data of the corona discharge process corresponding to the preset parameter range; Determining a historical relationship expression between the characteristic parameter and the discharge amount according to the first historical characteristic parameter data and the first historical discharge amount data; Taking the sum of the preset weight coefficients corresponding to the characteristic parameters as 1 as a constraint condition, determining the objective function of the preset weight coefficients corresponding to the characteristic parameters according to the second historical discharge amount data, the first historical characteristic reference data and the historical relationship expression; If the value of the objective function is less than the first preset threshold, the value of the preset weight coefficient corresponding to the preset parameter range is determined.

6. The corona evaluation method for the stator winding end of a generator according to claim 1, characterized in that: The method further comprises: Before corona discharge is performed at the stator winding end, initial characteristic parameter data in the corona discharge environment of the stator winding end is obtained; If the initial characteristic parameter data is less than a second preset threshold, the characteristic parameter data and the discharge amount data generated during the corona discharge process at the stator winding end are obtained.

7. The corona evaluation method for the stator winding end of a generator according to claim 1, characterized in that: The method further comprises: comparing the first target discharge amount with a plurality of preset discharge amount ranges; The risk level of the first target discharge amount is determined according to a preset level corresponding to a target preset discharge amount range that matches the first target discharge amount.

8. A corona evaluation device for generator stator winding ends, characterized in that: The device comprises: A determination module, for determining a relational expression between characteristic parameters and discharge amount according to characteristic parameter data and discharge amount data generated during the corona discharge process of the stator winding end; and Determining a weight coefficient corresponding to the characteristic parameter according to parameter data of the corona discharge process of the stator winding end; and A first target discharge amount is determined according to the weight coefficient corresponding to the characteristic parameter and the relationship expression.

9. A readable storage medium having a program or instruction stored thereon, characterized in that: When the program or instruction is executed by a processor, the steps of the method for evaluating corona at the end of a stator winding of a generator according to any one of claims 1 to 7 are implemented.

10. A computer device comprising a storage medium, a processor, and a computer program stored in the storage medium and executable on the processor, characterized in that: When the processor executes the program, the corona evaluation method for the stator winding end of a generator according to any one of claims 1 to 7 is implemented.

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