Generator health degree assessment method, system, device, equipment and medium
By acquiring the real-time data and test data of the generator, using non-contact electric field sensors and a centralized stator bar model, combined with a mapping relationship library, real-time diagnosis and health assessment of the generator stator bars are achieved, solving the problems of insufficient accuracy and real-time performance in traditional assessment methods and improving the reliability and safety of generator operation.
Patent Information
- Application Number
- CN202510898756.0
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-06-30
- Publication Date
- 2025-10-10
AI Technical Summary
Traditional generator stator bar health assessment methods have difficulty in real-time monitoring of complex wide-band overvoltages, lack a systematic understanding of the threats of temporary overvoltages and transient overvoltage intrusions, lack assessment accuracy, and lack real-time and detailed diagnostic warnings, making it difficult to achieve stator bar-level diagnosis.
By acquiring real-time data and test data from the generator, using non-contact electric field sensors to measure the electric field distribution, and combining the stator bar centralized model and mapping relationship library, real-time diagnosis and health assessment of the stator bars can be achieved, including comprehensive monitoring and assessment of temperature, vibration, and partial discharge characteristics.
The accuracy and real-time performance of the generator stator bar health assessment are improved, real-time monitoring of complex wide-band overvoltages is achieved, and the reliability and safety of the generator operation are enhanced.
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Figure CN120761847A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the technical field of generators, and in particular to a generator health assessment method, system, device, equipment and medium. Background Art
[0002] As the penetration rate of new energy continues to increase, generator stator bars will face more severe and complex broadband overvoltage (temporary overvoltage and transient overvoltage intrusion threats). Their main insulation and inter-turn insulation will be subjected to high-intensity superimposed impacts, and their insulation aging process will be further accelerated, which may even cause catastrophic accidents.
[0003] Traditional monitoring technologies struggle to achieve real-time monitoring of complex, wide-band overvoltages and lack a systematic understanding of the threats posed by temporary and transient overvoltage intrusions. Consequently, existing assessment methods fail to incorporate the impact of complex, wide-band overvoltage intrusions into stator bar health assessments, resulting in low assessment accuracy. Second, existing assessments primarily rely on offline data, lacking real-time performance. Third, existing assessments often focus on post-event evaluations, lacking real-time, in-process assessments of units and proactive early warning. Fourth, existing assessment technologies primarily focus on macroscopic assessments of the generator stator, failing to provide detailed diagnostic and early warning capabilities at the stator bar level. Summary of the Invention
[0004] In view of this, the present application provides a generator health assessment method, device, equipment and medium to improve the accuracy of stator bar diagnosis. The technical solution is as follows.
[0005] In a first aspect, a method for evaluating the health of a generator is provided, the method comprising:
[0006] Acquiring real-time data of the target generator; the real-time data includes temperature data, vibration data, partial discharge characteristics, and potential and electric field distribution at various positions of the stator bars of the target generator;
[0007] Acquiring test data of the target generator; the test data including stator bar insulation resistance, absorption ratio, polarization index, and stator winding leakage current;
[0008] According to the real-time data of the target generator, a real-time diagnostic result of the stator bars of the target generator is obtained through a mapping relationship library; the mapping relationship library includes mapping relationships between a plurality of levels for indicating the health of the generator and the real-time data;
[0009] An evaluation result of the health of the target generator is obtained based on the test data of the target generator and the real-time diagnosis result of the stator bars of the target generator.
[0010] In an alternative embodiment, the method further comprises:
[0011] acquiring a concentrated model of the stator bars of the target generator;
[0012] acquiring the potential and electric field distribution of each position of the stator bars based on the concentrated model of the stator bars and the calculated voltage value at the generator end of the target generator.
[0013] In an alternative embodiment, before acquiring the potential distribution of each position of the stator bars, the method further comprises:
[0014] acquiring a real-time light intensity signal sent by a non-contact electric field sensor under the electric field of the stator bars; the non-contact electric field sensor is arranged on the three-phase closed busbar shell at the generator end of the target generator;
[0015] calculating the calculated voltage value according to the real-time light intensity signal.
[0016] In an alternative embodiment, the method further comprises:
[0017] acquiring the potential distribution of each position of the stator bars based on the concentrated model of the stator bars and the calculated voltage value at the generator end of the target generator;
[0018] inverting the potential along the stator bars into the electric field distribution.
[0019] In an alternative embodiment, the method further comprises:
[0020] acquiring physical data of the stator bars with different degrees of insulation degradation under the target environment; the physical data includes the potential and electric field distribution of each position of the stator bars, temperature data, partial discharge characteristic quantity and vibration data;
[0021] constructing the mapping relationship library according to the physical data of the stator bars with different degrees of insulation degradation.
[0022] In an alternative embodiment, the method further comprises:
[0023] if the health degree of the target generator is the first level, issuing a warning to indicate that the target generator is to be overhauled;
[0024] if the health degree of the target generator is the second level, setting the monitoring frequency of the target generator to a first frequency and indicating that the target generator is to be overhauled within a first time period;
[0025] if the health degree of the target generator is the third level, set the monitoring frequency of the target generator to a second frequency; the second frequency is less than the first frequency;
[0026] if the health degree of the target generator is the fourth level, keep normal monitoring of the target generator.
[0027] In a second aspect, a generator health degree evaluation system is provided, and the system comprises: an online evaluation and early warning device, an online partial discharge monitoring device, an online temperature monitoring device, an online vibration monitoring device, an online overvoltage monitoring device, and a test data input device.
[0028] The online partial discharge monitoring device is configured to detect the discharge state of the target generator stator in real time; the online temperature monitoring device is configured to detect the temperature of the target generator stator in real time; the online vibration monitoring device is configured to detect the vibration data of the generator stator in real time; the online overvoltage monitoring device is configured to monitor the overvoltage state of the target generator stator in real time; the test data input device is configured to obtain the test data in the electrical detection report or the test data uploaded by the user; and the online evaluation and early warning device is configured to execute the above generator health degree evaluation method.
[0029] In a third aspect, a generator health degree evaluation device is provided, and the device comprises:
[0030] A first data acquisition module is configured to acquire real-time data of a target generator; the real-time data comprises temperature data, vibration data, partial discharge characteristic quantities, and the potential and electric field distribution of each position of the stator bar of the target generator;
[0031] A second data acquisition module is configured to acquire test data of the target generator; the test data comprises the stator bar insulation resistance, absorption ratio, polarization index, and stator winding leakage current;
[0032] A stator diagnosis module is configured to acquire real-time diagnosis results of the stator bar of the target generator through a mapping relationship library according to the real-time data of the target generator; the mapping relationship library comprises the mapping relationship between a plurality of levels for indicating the health degree of the generator and the real-time data;
[0033] A health evaluation module is configured to acquire an evaluation result of the health degree of the generator based on the test data of the target generator and the real-time diagnosis results of the stator bar of the target generator.
[0034] In a fourth aspect, an electronic device is provided, and the electronic device comprises a processor and a storage medium; the storage medium stores program instructions executable by the processor; and the processor executes the program instructions to execute the above generator health degree evaluation method.
[0035] In a fifth aspect, a computer-readable storage medium is provided, wherein the storage medium stores at least one instruction, which is loaded by a processor to execute the generator health degree evaluation method.
[0036] The technical scheme provided in the application can have the following beneficial effects.
[0037] In the application, real-time data of the target generator is first acquired, including temperature data, vibration data, partial discharge characteristic quantity, and potential and electric field distribution of each position of the stator bar of the target generator. Then, test data of the target generator is acquired as prior data, that is, stator bar insulation resistance, absorption ratio, polarization index, and stator winding leakage current of the target generator obtained in the test process. According to the real-time data of the target generator, the real-time diagnosis result of the stator bar of the target generator can be determined through a preset mapping relationship library. Then, based on the real-time diagnosis result and the prior data of the target generator, the evaluation result of the generator health degree can be obtained. The above scheme can accurately evaluate the generator health degree based on the prior data of the generator and the real-time data of the generator, thereby improving the reliability of the generator operation. BRIEF DESCRIPTION OF DRAWINGS
[0038] In order to more clearly illustrate the technical scheme in the specific embodiments or prior art of the application, the drawings needed in the description of the specific embodiments or prior art will be briefly introduced. Obviously, the drawings in the following description are some embodiments of the application, and other drawings can be obtained by those skilled in the art without creative labor.
[0039] Figure 1 FIG. 1 is a flowchart of a method for evaluating the health degree of a generator according to an example embodiment.
[0040] Figure 2 FIG. 1 is a flowchart of a method for evaluating the health degree of a generator according to an example embodiment.
[0041] Figure 3 FIG. 1 is a flowchart of a method for evaluating the health degree of a generator according to an example embodiment.
[0042] Figure 4 FIG. 1 is a flowchart of a method for evaluating the health degree of a generator according to an example embodiment.
[0043] Figure 5 FIG. 1 is a flowchart of a method for evaluating the health degree of a generator according to an example embodiment. DETAILED DESCRIPTION
[0044] With the further improvement of new energy penetration rate, the generator stator bar will face more severe complex broadband overvoltage (temporary overvoltage and transient overvoltage intrusion threat), the main insulation and turn-to-turn insulation will withstand high-intensity superposition impact, and the insulation aging process will further accelerate, and even may cause catastrophic accidents. The existing generator stator bar health assessment method mainly relies on the generator periodic test to obtain the stator insulation resistance, absorption ratio or polarization index data, and realizes the comprehensive evaluation of the health of the stator bar through the real-time stator temperature and partial discharge data obtained by online monitoring. The traditional monitoring technology is difficult to realize the real-time monitoring of the complex broadband overvoltage, and lacks systematic understanding of the temporary overvoltage and transient overvoltage intrusion threat, so that the existing evaluation method does not include the complex broadband overvoltage intrusion into the stator bar health evaluation system, and thus the accuracy of the evaluation. Two is that the existing evaluation mainly uses offline data as the evaluation basis, and the real-time evaluation is insufficient. Three is that the existing evaluation mainly stays in the post-evaluation, and lacks the real-time evaluation of the unit in the middle, the early warning, four is that the existing evaluation technology route mainly stays in the macro evaluation of the generator stator, and it is difficult to refine to the stator bar level diagnosis and early warning.
[0045] To solve the above problems, an embodiment of the present application provides a generator health assessment method. Figure 1 It is a method flow chart of generator health assessment according to an exemplary embodiment. The method is applied to an electronic device, and the method comprises:
[0046] Step 101, acquiring real-time data of the target generator; the real-time data includes temperature data, vibration data, partial discharge characteristic quantity and potential and electric field distribution of each position of the stator bar of the target generator.
[0047] In the embodiment of the present application, the thermocouple or infrared temperature measuring device can be arranged on the surface of the stator winding and the bar to collect the temperature data of the target generator; the acceleration sensor can be arranged at the bar support to collect the vibration data; and the charge sensitive probe can be arranged around the generator to collect the partial discharge characteristic quantity of the target generator.
[0048] In addition, in the embodiment of the present application, in order to measure the potential and electric field distribution of each position of the stator bar of the target generator, a high-precision, large-range non-contact electric field sensor array can be installed on the generator end three-phase closed bus shell opening; the electric field change caused by the temporary overvoltage and transient overvoltage invading the stator bar of the generator is converted into real-time light intensity change through the non-contact electric field sensor array, then the real-time light intensity signal sensed by the non-contact electric field sensor array is converted into a calculated voltage value, finally the generator stator bar lumped model is established, and the calculated voltage value is recursively propagated from the generator end to the stator bar of the generator relying on the generator stator bar lumped model, forming the potential distribution of the overvoltage along the stator bar, so as to inverse the potential along the stator bar into the electric field distribution.
[0049] In step 102, test data of the target generator is obtained; the test data includes the insulation resistance, absorption ratio, polarization index and stator winding leakage current of the stator bar.
[0050] In the embodiment of the present application, during the maintenance or intermittent operation, the insulation resistance, absorption ratio / polarization index and winding leakage current test can be completed according to the specified test standard, so as to obtain the insulation resistance, absorption ratio, polarization index and stator winding leakage current of the stator bar.
[0051] In step 103, the real-time diagnosis result of the stator bar of the target generator is obtained through the mapping relationship library according to the real-time data of the target generator; the mapping relationship library includes the mapping relationship between the several levels for indicating the generator health degree and the real-time data.
[0052] Since the mapping relationship library in the embodiment of the present application can be used to indicate the mapping relationship between the several levels for indicating the generator health degree and the real-time data, the diagnosis level of the generator health degree of the stator bar of the target generator can be obtained according to the real-time data of the target generator.
[0053] In the embodiment of the present application, the mapping relationship library also includes the test data of the target generator, that is, the prior data. That is, in an optional implementation, the mapping relationship library can determine the several levels for indicating the generator health degree according to the prior data of the target generator and the real-time data collected during the working process.
[0054] In step 104, the evaluation result of the generator health degree is obtained based on the test data of the target generator and the real-time diagnosis result of the stator bar of the target generator.
[0055] In the embodiment of the present application, the test data of the target generator is obtained during the maintenance or intermittent operation, and the test data is obtained according to the specified test standard, so that the test data can be used as the prior data of the target generator, and the real-time diagnosis result of the stator bar of the target generator can be used as the in-process evaluation of the target generator during operation, so that the complete evaluation of the safety state of the target generator can be realized according to the prior data of the target generator and the in-process evaluation result of the target generator during operation.
[0056] In summary, in the present application, the real-time data of the target generator is first obtained, including temperature data, vibration data, partial discharge characteristic quantity, and potential and electric field distribution of each position of the stator bar of the target generator, and the test data of the target generator is obtained as prior data, that is, the stator bar insulation resistance, absorption ratio, polarization index, and stator winding leakage current of the target generator obtained during the test process, according to the real-time data of the target generator, the real-time diagnosis result of the stator bar of the target generator can be determined through the preset mapping relationship library, and then based on the real-time diagnosis result and the prior data of the target generator, the evaluation result of the generator health degree can be obtained. The above-mentioned scheme can accurately realize the evaluation of the generator health degree based on the prior data of the generator and the real-time data of the generator, thereby improving the reliability of the generator operation.
[0057] Figure 2 is a flow chart of a method for evaluating the health degree of a generator according to an exemplary embodiment. The method is applied to an electronic device, and the method comprises:
[0058] In step 201, a real-time light intensity signal transmitted by a non-contact electric field sensor under the electric field of the stator bar is obtained; the non-contact electric field sensor is arranged on the terminal three-phase closed busbar shell of the target generator.
[0059] In step 202, the calculated voltage value is calculated according to the real-time light intensity signal.
[0060] In the embodiment of the present application, the non-contact electric field sensor can be an electric field sensor based on Pockels effect. The principle is that when a polarized light passes through some asymmetric electro-optic crystal, an external electric field will change the phase or polarization state of the crystal to the light beam, so that the electric field strength applied to the electric field sensor can be calculated by measuring the change of light intensity. In the embodiment of the present application, the non-contact electric field sensors on the busbar shell of the target generator are arranged in an array, so that the calculated voltage value of the generator end can be calculated according to the electric field strength of each position.
[0061] In step 203, real-time data of the target generator is acquired; the real-time data includes temperature data, vibration data, partial discharge characteristic quantity, and potential and electric field distribution of each position of the stator bar of the target generator.
[0062] Optionally, the partial discharge characteristic quantity can include collected partial discharge spectrum and amplitude-frequency characteristic.
[0063] In step 204, a concentrated model of the stator bar of the target generator is acquired.
[0064] Since the structure of the stator bar is relatively complex, the actual distribution of the stator bar along the path is continuous resistance, inductance, and capacitance (including turn-to-turn capacitance and ground capacitance), if the distributed transmission line equation is used to accurately describe, the model is very complex, and real-time online calculation is difficult to realize. Therefore, the distributed parameters along the path can be “equivalent” to several concentrated elements, thereby obtaining a concentrated parameter model which is approximate to the real one and is convenient for real-time calculation. The concentrated model of the stator bar can be obtained based on the real three-dimensional model of the stator bar through finite element electromagnetic simulation calculation.
[0065] In step 205, potential and electric field distribution of each position of the stator bar is acquired based on the concentrated model of the stator bar and the calculated voltage value at the machine end of the target generator.
[0066] In the embodiment of the present application, the potential distribution of each position of the stator bar is acquired based on the concentrated model of the stator bar and the calculated voltage value at the machine end of the target generator; the potential along the path of the stator bar is inversed into electric field distribution.
[0067] Since the calculated voltage value at the machine end of the target generator has been obtained, and the concentrated model of the stator bar can also reflect the capacitance, inductance, and electronic condition along the path of the stator bar, that is, the potential distribution of each position of the stator bar can be calculated according to the two; and the electric field along the path of the stator bar can be acquired by differentiating the potential distribution.
[0068] In the embodiment of the present application, when acquiring the real-time data of the target generator, in addition to acquiring the potential and electric field distribution of each position of the stator bar through the above process, real-time data including temperature data, vibration data, and partial discharge characteristic quantity can also be collected through the sensors arranged on the target generator.
[0069] In step 206, test data of the target generator is acquired; the test data includes stator bar insulation resistance, absorption ratio, polarization index, and stator winding leakage current.
[0070] In the embodiment of the present application, the test data can be used as a “health degree diagnosis starting point” to calibrate the concentrated parameter model and the threshold library, so as to ensure the sensitivity and accuracy of the early warning.
[0071] It should be particularly pointed out that in the embodiments of the present application, the test data can be other types of data in addition to the stator bar insulation resistance, absorption ratio, polarization index and stator winding leakage current described above, and the specific data type can be determined according to the actual test project required by the target generator.
[0072] In step 207, the real-time diagnosis result of the stator bar of the target generator is obtained from the mapping relationship library according to the real-time data of the target generator; the mapping relationship library includes the mapping relationship between the several levels indicating the health degree of the generator and the real-time data.
[0073] Optionally, in the embodiments of the present application, the physical data of the stator bars in different insulation deterioration degrees is obtained under the target environment; the physical data includes the potential and electric field distribution of each position of the stator bar, temperature data, partial discharge condition and vibration data; the mapping relationship library is constructed according to the physical data of the stator bars in different insulation deterioration degrees.
[0074] That is, before the real-time diagnosis of the stator bar is performed through the mapping relationship library, the stator bars in different insulation deterioration degrees can be tested first to obtain their physical data under different working environments, such as the potential and electric field distribution of each position of the stator bar, temperature data, partial discharge characteristic quantity and vibration data, so as to construct the mapping relationship library according to the corresponding relationship between the physical data and the insulation deterioration degree.
[0075] In step 208, the evaluation result of the health degree of the generator is obtained based on the test data of the target generator and the real-time diagnosis result of the stator bar of the target generator.
[0076] Further, if the health degree of the target generator is the first level, a warning is issued to indicate that the target generator is to be overhauled;
[0077] If the health degree of the target generator is the second level, the monitoring frequency of the target generator is set to the first frequency, and the target generator is indicated to be overhauled within the first time period;
[0078] If the health degree of the target generator is the third level, the monitoring frequency of the target generator is set to the second frequency; the second frequency is less than the first frequency;
[0079] If the health degree of the target generator is the fourth level, the normal monitoring of the target generator is maintained.
[0080] Specifically, in the embodiments of the present application, the generator health degree can be evaluated in real time according to the diagnosis result of the stator bar. When the stator bar is in the first level, the generator health degree is evaluated as the normal state of the D level; when there is one state quantity of the stator bar in the second level of degradation exceeding the standard limit value, the generator health degree is evaluated as the attention state of the C level; when there is at least one state quantity of the third level or multiple state quantities of the second level of degradation exceeding the standard limit value, the generator health degree is evaluated as the abnormal state of the B level; and when there is at least one state quantity of the fourth level of degradation exceeding the standard limit value, the generator health degree is evaluated as the serious state of the A level.
[0081] In addition, when the generator health degree is evaluated as the A level, it indicates that the equipment is in high-risk operation, and the risk source is excluded by arranging maintenance immediately; when the generator health degree is evaluated as the B level, it indicates that the risk is moderate, and the maintenance is arranged as soon as possible by increasing the tracking monitoring frequency; when the generator health degree is evaluated as the C level, it indicates that the equipment is in low-risk operation, and the maintenance cycle is shortened and the risk factors are reduced by appropriately strengthening the monitoring; and when the generator health degree is evaluated as the D level, it indicates that the risk is small, and the equipment can be continuously operated by maintaining normal monitoring.
[0082] Correspondingly, refer to Figure 3 which shows a generator health degree evaluation system according to an embodiment of the present application. The system is used to execute the generator health degree evaluation method as shown in Figure 2 . As shown in Figure 3 , the system includes an online evaluation and early warning device, a partial discharge online monitoring device, a temperature online monitoring device, a vibration online monitoring device, an overvoltage online monitoring device, and a test data input device.
[0083] The partial discharge online monitoring device is used to detect the discharge state of the target generator stator in real time; the temperature online monitoring device is used to detect the temperature of the target generator stator in real time; the vibration online monitoring device is used to detect the vibration data of the generator stator in real time; the overvoltage online monitoring device is used to monitor the overvoltage state of the target generator stator in real time; and the test data input device is used to obtain the test data in the electrical detection report or the test data uploaded by the user.
[0084] Specifically, the system also integrates the first, second, third and fourth level mapping relationship library of the stator bar insulation degradation and physical quantities such as electric field, temperature, vibration and partial discharge, and accepts the generator regular electrical test data input device to form the generator health degree evaluation and correction starting point; accepts the data from the generator stator bar temperature online monitoring device, the generator stator bar temperature online monitoring device, the stator bar vibration online monitoring device, the generator stator temporary overvoltage and transient overvoltage online monitoring device, uses the relational database and the evaluation starting point to form the generator health degree evaluation result and the early warning result and outputs. The generator stator partial discharge online monitoring device monitors the stator state in real time, and uploads the partial discharge data once detected. The generator stator temperature online monitoring device obtains the generator stator bar temperature in real time and uploads it. The generator stator vibration online monitoring device obtains the generator stator vibration data in real time and uploads it. The generator stator temporary overvoltage and transient overvoltage online monitoring device obtains the generator stator overvoltage state in real time, and uploads the temporary overvoltage and transient overvoltage data once detected. The generator regular electrical test data input device has automatic recognition of the data confidence in the generator regular electrical monitoring report, and supports manual input of test data and uploading.
[0085] Therefore, the scheme shown in the embodiment of the present application comprehensively considers the test data obtained by the test process before the operation of the target generator and the real-time data collected during the operation of the target generator, judges the diagnosis result of the stator bar of the target generator through the two, and generates the evaluation result of the health degree of the target generator based on the diagnosis result, so as to execute the corresponding early warning operation according to the evaluation result, that is, the embodiment of the present application constitutes a complete detection scheme of diagnosing, evaluating and warning the target generator by comprehensively considering the pre-event and in-process data, and improves the reliability of the operation of the generator.
[0086] In summary, the real-time data of the target generator are first obtained in the present application, including temperature data, vibration data, partial discharge characteristic quantity and potential and electric field distribution of each position of the stator bar of the target generator, and the test data of the target generator are obtained as pre-event data, that is, the stator bar insulation resistance, absorption ratio, polarization index and stator winding leakage current of the target generator obtained during the test process. According to the real-time data of the target generator, the real-time diagnosis result of the stator bar of the target generator can be determined through the preset mapping relationship library, and the evaluation result of the health degree of the generator can be obtained based on the real-time diagnosis result and the pre-event data of the target generator. The above scheme can accurately realize the evaluation of the health degree of the generator based on the pre-event data of the generator and the real-time data of the generator, thereby improving the reliability of the operation of the generator.
[0087] A generator health degree evaluation device is also provided in the embodiments of the present application, which is used to implement the above-mentioned embodiments and preferred embodiments, and will not be described herein again. As used below, the term "module" can be a combination of software and / or hardware that implements a predetermined function. Although the device described in the following embodiments is preferably implemented in software, implementation of hardware, or a combination of software and hardware, is also possible and contemplated.
[0088] The embodiments of the present application provide a generator health degree evaluation device, Figure 4 is a structural schematic diagram of a generator health degree evaluation device provided by the embodiments of the present application, which comprises:
[0089] A first data acquisition module 401 is configured to acquire real-time data of a target generator; the real-time data comprises temperature data, vibration data, partial discharge characteristic quantity, and potential and electric field distribution of each position of a stator bar of the target generator;
[0090] A second data acquisition module 402 is configured to acquire test data of the target generator; the test data comprises stator bar insulation resistance, absorption ratio, polarization index, and stator winding leakage current;
[0091] A stator diagnosis module 403 is configured to acquire real-time diagnosis results of the stator bar of the target generator according to the real-time data of the target generator through a mapping relationship library; the mapping relationship library comprises mapping relationships between a plurality of levels for indicating generator health degree and real-time data;
[0092] A health evaluation module 404 is configured to acquire an evaluation result of the generator health degree based on the test data of the target generator and the real-time diagnosis results of the stator bar of the target generator.
[0093] In summary, in the present application, real-time data of a target generator is first acquired, which comprises temperature data, vibration data, partial discharge characteristic quantity, and potential and electric field distribution of each position of a stator bar of the target generator. Meanwhile, test data of the target generator is also acquired as prior data, that is, stator bar insulation resistance, absorption ratio, polarization index, and stator winding leakage current obtained in a test process of the target generator. According to the real-time data of the target generator, real-time diagnosis results of the stator bar of the target generator can be determined through a preset mapping relationship library. Then, based on the real-time diagnosis results and the prior data of the target generator, an evaluation result of the generator health degree can be acquired. The above-mentioned scheme can accurately implement evaluation of the generator health degree based on prior data of the generator and real-time data of the generator, thereby improving the reliability of generator operation.
[0094] Further function description of each module and unit is the same as the above corresponding embodiment, and will not be repeated here.
[0095] The above apparatus is presented in the form of functional units, where the units refer to an ASIC (Application Specific Integrated Circuit) circuit, a processor and a memory executing one or more software or fixed programs, and / or other devices that can provide the above functions.
[0096] Please refer to Figure 5 , Figure 5 is a structural schematic diagram of an electronic device provided by an optional embodiment of the application. The electronic device can be a computer device, such as Figure 5 As shown, the electronic device includes one or more processors 10, a memory 20, and interfaces for connecting components, including high-speed interfaces and low-speed interfaces. Each component is communicatively connected with different buses, and can be installed on a common motherboard or in other ways as needed. The processor can process instructions executed within the electronic device, including instructions stored in the memory or on the memory to display graphical information of a GUI on an external input / output device, such as a display device coupled to the interface.
[0097] The processor 10 can further include a hardware chip. The hardware chip can be an application specific integrated circuit, a programmable logic device, or a combination thereof. The programmable logic device can be a complex programmable logic device, a field programmable logic gate array, a generic array logic, or any combination thereof.
[0098] The memory 20 stores instructions executable by the at least one processor 10, so that the at least one processor 10 executes the method shown in the above embodiments.
[0099] The memory 20 can include a program storage area and a data storage area, where the program storage area can store an operating system and application programs required by at least one function; the data storage area can store data created by use of the electronic device according to the display of a small program landing page, and the like. In addition, the memory 20 can include a high-speed random access memory, and can also include a non-transitory memory, such as at least one magnetic disk storage device, a flash memory device, or other non-transitory solid-state memory device. The memory 20 can include a volatile memory, such as a random access memory; the memory can also include a non-volatile memory, such as a flash memory, a hard disk, or a solid state disk; and the memory 20 can also include a combination of the above kinds of memories.
[0100] The electronic device further includes a communication interface 30 for communication between the electronic device and other devices or communication networks.
[0101] The embodiments of the present application further provide a computer readable storage medium, and the method according to the embodiments of the present application can be implemented in hardware, firmware, or recorded in a storage medium, or be implemented as computer codes stored in a remote storage medium or a non-transitory machine readable storage medium and stored in a local storage medium to be downloaded through a network, so that the method described herein can be processed by such software on a storage medium using a general computer, a special processor, or programmable or special hardware. The storage medium can be a magnetic disk, an optical disk, a read-only memory, a random access memory, a flash memory, a hard disk, or a solid state disk, etc. Further, the storage medium can also include a combination of the above-mentioned memories. It can be understood that the computer, the processor, the microprocessor controller, or the programmable hardware includes a storage component that can store or receive software or computer codes, and when the software or computer codes are accessed and executed by the computer, the processor, or the hardware, the method shown in the above embodiments is implemented.
[0102] Although the embodiments of the present application are described in conjunction with the accompanying drawings, various modifications and changes can be made by those skilled in the art without departing from the spirit and scope of the present application, and such modifications and changes fall within the scope defined by the appended claims.
Claims
1. A method for evaluating the health of a generator, characterized in that: The method comprises: Acquiring real-time data of the target generator; the real-time data includes temperature data, vibration data, partial discharge characteristics, and potential and electric field distribution at various positions of the stator bars of the target generator; Acquiring test data of the target generator; the test data including stator bar insulation resistance, absorption ratio, polarization index, and stator winding leakage current; According to the real-time data of the target generator, a real-time diagnostic result of the stator bars of the target generator is obtained through a mapping relationship library; the mapping relationship library includes mapping relationships between a plurality of levels for indicating the health of the generator and the real-time data; An evaluation result of the health of the target generator is obtained based on the test data of the target generator and the real-time diagnosis result of the stator bars of the target generator.
2. The method according to claim 1, characterized in that The obtaining of the electric potential and electric field distribution at various positions of the stator bar of the target generator includes: Obtaining a stator bar concentrated model of a target generator; Based on the stator bar lumped model and the calculated voltage value of the target generator at the generator end, the electric potential and electric field distribution at each position of the stator bar are obtained.
3. The method according to claim 2, characterized in that Before obtaining the potential distribution at each position of the stator bar, the method further includes: Acquire a real-time light intensity signal sent by a non-contact electric field sensor under the electric field of the stator bar; the non-contact electric field sensor is arranged on the three-phase enclosed busbar housing at the end of the target generator; The calculated voltage value is obtained by calculation according to the real-time light intensity signal.
4. The method according to claim 2, characterized in that The obtaining of the electric potential and electric field distribution at each position of the stator bar includes: Based on the stator bar lumped model and the calculated voltage value of the target generator at the generator end, obtaining the potential distribution at each position of the stator bar; The electric potential along the stator bar is inverted into an electric field distribution.
5. The method according to any one of claims 1 to 4, characterized in that: The method further comprises: Acquiring physical data of stator bars at different degrees of insulation degradation in a target environment; the physical data includes potential and electric field distribution at various locations of the stator bars, temperature data, partial discharge characteristics, and vibration data; The mapping relationship library is constructed according to the physical data of the stator bars with different insulation degradation degrees.
6. The method according to any one of claims 1 to 4, characterized in that: The method further comprises: If the health of the target generator is at the first level, issuing an early warning to instruct the target generator to be repaired; If the health of the target generator is at the second level, setting the monitoring frequency of the target generator to the first frequency and instructing to perform maintenance on the target generator within a first time period; If the health of the target generator is at the third level, setting the monitoring frequency of the target generator to a second frequency; the second frequency is less than the first frequency; If the health of the target generator is at the fourth level, the target generator is kept under normal monitoring.
7. A generator health assessment system, characterized in that: The system includes: an online assessment and early warning device, a partial discharge online monitoring device, a temperature online monitoring device, a vibration online monitoring device, an overvoltage online monitoring device and a test data entry device; The partial discharge online monitoring device is used to detect the discharge status of the target engine stator in real time; the temperature online monitoring device is used to detect the temperature of the target engine stator in real time; the vibration online monitoring device is used to detect the vibration data of the generator stator in real time; the overvoltage online monitoring device is used to monitor the overvoltage status of the target generator stator in real time; the test data entry device is used to obtain test data in the electrical inspection report or obtain test data uploaded by the user; the online evaluation and early warning device is used to execute the generator health assessment method as described in any one of claims 1 to 6.
8. A generator health assessment device, characterized in that: The device comprises: A first data acquisition module is configured to acquire real-time data of the target generator; the real-time data includes temperature data, vibration data, partial discharge characteristics, and potential and electric field distribution at various locations of the stator bars of the target generator; A second data acquisition module is used to acquire test data of the target generator; the test data includes stator bar insulation resistance, absorption ratio, polarization index and stator winding leakage current; a stator diagnostic module, configured to obtain real-time diagnostic results of the stator bars of the target generator based on the real-time data of the target generator through a mapping relationship library; the mapping relationship library includes mapping relationships between several levels indicating the health of the generator and the real-time data; A health assessment module is used to obtain an assessment result of the health of the generator based on the test data of the target generator and the real-time diagnosis result of the stator bars of the target generator.
9. An electronic device, characterized in that: The electronic device includes a processor and a storage medium, wherein the storage medium stores program instructions executable by the processor, and the processor executes the program instructions to perform the generator health assessment method according to any one of claims 1 to 6.
10. A computer-readable storage medium, characterized in that The storage medium stores at least one instruction, and the at least one instruction is loaded by the processor to execute the generator health assessment method according to any one of claims 1 to 6.