Knowledge base evaluation method and system for intelligent operation and maintenance of wind power system, terminal and medium

Abstract

The embodiment of the invention relates to the technical field of data processing, and provides a knowledge base evaluation method and system for intelligent operation and maintenance of a wind power system, a terminal and a medium, and the method comprises the steps: obtaining wind power parameters of a wind power station, obtaining power generation information of the wind power station, according to the wind power parameters and the first power generation information, a knowledge base of intelligent operation and maintenance of the wind power system is used for evaluating the wind power station to obtain first evaluation information, and a wind power station test platform is used for testing and evaluating the wind power station to obtain second evaluation information; according to the first evaluation information and the second evaluation information, evaluating the knowledge base of the intelligent operation and maintenance of the wind power system to obtain third evaluation information which is used for representing whether the knowledge base of the intelligent operation and maintenance of the wind power system is abnormal or not; and the accuracy of evaluating the knowledge base for intelligent operation and maintenance of the wind power system is improved.

Description

Technical Field

[0001] The present application relates to the technical field of data processing, and particularly to a knowledge base evaluation method, system, terminal and medium for intelligent operation and maintenance of a wind power system. Background Art

[0002] With the rapid development of wind power technology, new equipment and technologies are constantly emerging, and it may be difficult for the knowledge base to cover all relevant knowledge in a timely manner. The correlation between knowledge is not sorted out enough, and it is often a fragmented list of knowledge, lacking the construction of the knowledge chain in the overall operation and maintenance scenario, resulting in insufficient accuracy in evaluating the knowledge base for intelligent operation and maintenance of the wind power system. Summary of the Invention

[0003] Embodiments of the present application provide a knowledge base evaluation method, system, terminal and medium for intelligent operation and maintenance of a wind power system, which can evaluate the knowledge base for intelligent operation and maintenance of the wind power system by combining the wind power parameters of a wind power station and the power generation information of the wind power station, and improve the accuracy in evaluating the knowledge base for intelligent operation and maintenance of the wind power system.

[0004] The first aspect of the embodiments of the present application provides a knowledge base evaluation method for intelligent operation and maintenance of a wind power system, and the method includes:

[0005] Obtain the wind power parameters of a wind power station, where the wind power parameters include wind power level, temperature parameter and humidity parameter;

[0006] Obtain the power generation information of the wind power station to obtain the first power generation information;

[0007] Evaluate the wind power station using the knowledge base for intelligent operation and maintenance of the wind power system according to the wind power parameters and the first power generation information to obtain the first evaluation information;

[0008] Use a wind power station test platform to test and evaluate the wind power station to obtain the second evaluation information;

[0009] Evaluate the knowledge base for intelligent operation and maintenance of the wind power system according to the first evaluation information and the second evaluation information to obtain the third evaluation information.

[0010] In this example, by obtaining the wind power parameters of a wind power station, where the wind power parameters include wind power level, temperature parameter, humidity parameter, etc., obtaining the power generation information of the wind power station to get the first power generation information, evaluating the wind power station using the knowledge base of intelligent operation and maintenance of the wind power system according to the wind power parameters and the first power generation information to get the first evaluation information, testing and evaluating the wind power station using the wind power station test platform to get the second evaluation information, and evaluating the knowledge base of intelligent operation and maintenance of the wind power system according to the first evaluation information and the second evaluation information to get the third evaluation information, it is possible to combine the wind power parameters of the wind power station and the power generation information of the wind power station to evaluate the knowledge base of intelligent operation and maintenance of the wind power system, improving the accuracy of evaluating the knowledge base of intelligent operation and maintenance of the wind power system.

[0011] In a possible implementation manner, the evaluating the wind power station using the knowledge base of intelligent operation and maintenance of the wind power system according to the wind power parameters and the first power generation information to get the first evaluation information includes:

[0012] Performing initialization processing on the knowledge base of intelligent operation and maintenance of the wind power system to obtain a target knowledge base;

[0013] Inputting the wind power parameters into the target knowledge base for matching to obtain a target triple set;

[0014] Obtaining the tail entities in the target triple set to obtain a target entity set;

[0015] Performing normalization processing on the target entities in the target entity set to obtain the second power generation information;

[0016] Evaluating the wind power station according to the first power generation information and the second power generation information to obtain the first evaluation information.

[0017] In a possible implementation manner, the testing and evaluating the wind power station using the wind power station test platform to get the second evaluation information includes:

[0018] Performing functional testing and evaluation on the wind power station using the wind power station test platform to obtain functional evaluation information;

[0019] Performing power testing and evaluation on the wind power station using the wind power station test platform to obtain power evaluation information;

[0020] Fusing the functional evaluation information and the power evaluation information to obtain the second evaluation information.

[0021] In a possible implementation manner, the evaluating the knowledge base of intelligent operation and maintenance of the wind power system according to the first evaluation information and the second evaluation information to get the third evaluation information includes:

[0022] Obtain the evaluation bias corresponding to the first evaluation information to obtain a first evaluation bias, and calculate the evaluation bias corresponding to the second evaluation information to obtain a second evaluation bias;

[0023] Determine whether the first evaluation bias and the second evaluation bias are consistent to obtain a determination result;

[0024] Generate evaluation information corresponding to the knowledge base for intelligent operation and maintenance of the wind power system according to the determination result to obtain third evaluation information.

[0025] In a possible implementation manner, before evaluating the wind power station using the knowledge base for intelligent operation and maintenance of the wind power system according to the wind power parameters and the first power generation information, the method further includes:

[0026] Obtain the enterprise internal technical documents of the wind power station to obtain a target document;

[0027] Use a preset triple generation model to disassemble the target document to obtain a set of triples;

[0028] Construct the knowledge base for intelligent operation and maintenance of the wind power system according to the triples in the set of triples to obtain the knowledge base for intelligent operation and maintenance of the wind power system.

[0029] A second aspect of the embodiments of the present application provides a knowledge base evaluation system for intelligent operation and maintenance of a wind power system, and the system includes:

[0030] A first acquisition unit, configured to acquire wind power parameters of a wind power station, where the wind power parameters include wind power level, temperature parameter, and humidity parameter;

[0031] A second acquisition unit, configured to acquire power generation information of the wind power station to obtain first power generation information;

[0032] A first evaluation unit, configured to evaluate the wind power station using the knowledge base for intelligent operation and maintenance of the wind power system according to the wind power parameters and the first power generation information to obtain first evaluation information;

[0033] A second evaluation unit, configured to perform a test evaluation on the wind power station using a wind power station test platform to obtain second evaluation information;

[0034] A third evaluation unit, configured to evaluate the knowledge base for intelligent operation and maintenance of the wind power system according to the first evaluation information and the second evaluation information to obtain third evaluation information.

[0035] In a possible implementation manner, the first evaluation unit is specifically configured to:

[0036] Initialize the knowledge base for the intelligent operation and maintenance of the wind power system to obtain the target knowledge base;

[0037] Input the wind power parameters into the target knowledge base for matching to obtain the target triple set;

[0038] Obtain the tail entities in the target triple set to obtain the target entity set;

[0039] Normalize the target entities in the target entity set to obtain the second power generation information;

[0040] Evaluate the wind power station based on the first power generation information and the second power generation information to obtain the first evaluation information.

[0041] In a possible implementation, the second evaluation unit is specifically configured to:

[0042] Use the wind power station test platform to conduct a functional test evaluation on the wind power station to obtain the functional evaluation information;

[0043] Use the wind power station test platform to conduct a power test evaluation on the wind power station to obtain the power evaluation information;

[0044] Fuse the functional evaluation information and the power evaluation information to obtain the second evaluation information.

[0045] In a possible implementation, the third evaluation unit is specifically configured to:

[0046] Obtain the evaluation bias corresponding to the first evaluation information to obtain the first evaluation bias, and calculate the evaluation bias corresponding to the second evaluation information to obtain the second evaluation bias;

[0047] Judge whether the first evaluation bias and the second evaluation bias are consistent to obtain the judgment result;

[0048] Generate the evaluation information corresponding to the knowledge base for the intelligent operation and maintenance of the wind power system according to the judgment result to obtain the third evaluation information.

[0049] In a possible implementation, before evaluating the wind power station using the knowledge base for the intelligent operation and maintenance of the wind power system based on the wind power parameters and the first power generation information to obtain the first evaluation information, the first evaluation unit is specifically further configured to:

[0050] Obtain the enterprise internal technical documents of the wind power station to obtain the target documents;

[0051] Use the preset triple generation model to disassemble the target documents to obtain the triple set;

[0052] Construct a knowledge base for intelligent operation and maintenance of the wind power system according to the triples in the triple set, and obtain the knowledge base for intelligent operation and maintenance of the wind power system.

[0053] The third aspect of the embodiments of the present application provides a terminal, including a processor, an input device, an output device, and a memory. The processor, the input device, the output device, and the memory are interconnected. Among them, the memory is used to store a computer program, the computer program includes program instructions, and the processor is configured to call the program instructions to execute the step instructions in the first aspect of the embodiments of the present application.

[0054] The fourth aspect of the embodiments of the present application provides a computer-readable storage medium. Among them, the computer-readable storage medium stores a computer program for electronic data exchange. Among them, the computer program enables a computer to execute some or all of the steps described in the first aspect of the embodiments of the present application.

[0055] The fifth aspect of the embodiments of the present application provides a computer program product. Among them, the computer program product includes a non-transitory computer-readable storage medium storing a computer program. The computer program is operable to enable a computer to execute some or all of the steps described in the first aspect of the embodiments of the present application. This computer program product can be a software installation package. Description of the Drawings

[0056] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0057] Figure 1 It is a schematic flowchart of a method for evaluating a knowledge base for intelligent operation and maintenance of a wind power system provided by an embodiment of the present application;

[0058] Figure 2 It is a schematic structural diagram of a terminal provided by an embodiment of the present application;

[0059] Figure 3 It is a schematic structural diagram of a knowledge base evaluation system for intelligent operation and maintenance of a wind power system provided by an embodiment of the present application.

[0060] Specific implementation method

[0061] The following will clearly and completely describe the technical solutions in the embodiments of the present application with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in the present application without creative efforts belong to the scope of protection of the present application.

[0062] The terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned accompanying drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally further includes steps or units not listed, or optionally further includes other steps or units inherent to these processes, methods, products or devices.

[0063] Referring to "embodiments" in the present application means that specific features, structures or characteristics described in connection with the embodiments can be included in at least one embodiment of the present application. The appearance of this phrase in various positions in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment mutually exclusive with other embodiments. Those skilled in the art explicitly and implicitly understand that the embodiments described in the present application can be combined with other embodiments.

[0064] To better understand a knowledge base evaluation method for intelligent operation and maintenance of a wind power system provided by an embodiment of the present application, a brief introduction to the knowledge base evaluation method for intelligent operation and maintenance of a wind power system in the existing solution will be given first. In the existing solution, data is usually collected through various channels for the evaluation of the knowledge base for intelligent operation and maintenance of a wind power system. For example, for knowledge accuracy, the differences between the data in the knowledge base and authoritative materials (such as manufacturer's technical manuals, industry standard documents, etc.) are manually checked and scored; for integrity, the comparison results between the content directory of the knowledge base and an ideal full-functional coverage list are analyzed for scoring. During the manual checking process, misdetection or missed detection often occurs due to the carelessness of the checking personnel, resulting in insufficient accuracy in the evaluation of the knowledge base for intelligent operation and maintenance of a wind power system.

[0065] Aiming at solving the above technical problems, an embodiment of the present application provides a knowledge base evaluation method for intelligent operation and maintenance of a wind power system, which can evaluate the knowledge base for intelligent operation and maintenance of a wind power system by combining the wind power parameters of a wind power station and the power generation information of the wind power station, improving the accuracy in the evaluation of the knowledge base for intelligent operation and maintenance of a wind power system.

[0066] Please refer to Figure 1 , Figure 1This application provides a schematic flow diagram of a knowledge base evaluation method for intelligent operation and maintenance of a wind power system. As Figure 1 shown, the method includes:

[0067] 101. Obtain the wind power parameters of the wind power station, where the wind power parameters include wind power level, temperature parameter, and humidity parameter.

[0068] It can be to obtain the real-time wind power parameters of the wind power station through the meteorological collection device of the wind power station, or to obtain the wind power parameters of the wind power station through the local meteorological bureau. Specifically, it can be to collect the wind power level, temperature parameter, humidity parameter, etc. of the wind power station by setting up meteorological collection devices such as temperature collection devices, wind power collection devices, and humidity collection devices near the wind power station, so as to obtain the wind power parameters of the wind power station.

[0069] 102. Obtain the power generation information of the wind power station to obtain the first power generation information.

[0070] It can be to obtain the real-time power generation power data, etc. transmitted back by the wind power station through a wireless transmission device or a wired transmission device to obtain the first power generation information. Specifically, the wind power station can transmit the power generation power data, etc. of the current day back to the server through, but not limited to, 4G / 5G wireless networks or optical fiber wired transmission networks, etc., so as to obtain the first power generation information.

[0071] 103. Evaluate the wind power station using the knowledge base of the intelligent operation and maintenance of the wind power system according to the wind power parameters and the first power generation information to obtain the first evaluation information.

[0072] It can be to input the wind power parameters into the knowledge base of the intelligent operation and maintenance of the wind power system for matching to obtain a target entity set, perform normalization processing on the target entity set to obtain the second power generation information, and then evaluate the power generation power data, etc. of the wind power station according to the first power generation information and the second power generation information, so as to obtain the first evaluation information.

[0073] 104. Use the wind power station test platform to test and evaluate the wind power station to obtain the second evaluation information.

[0074] It can be to test and evaluate the functions and power of the wind power station through the wind power station test platform to obtain function evaluation information and power evaluation information, and then fuse the function evaluation information and the power evaluation information to obtain the second evaluation information.

[0075] 105. Evaluate the knowledge base of the intelligent operation and maintenance of the wind power system according to the first evaluation information and the second evaluation information to obtain the third evaluation information.

[0076] It can be to obtain the evaluation bias corresponding to the first evaluation information and the evaluation bias corresponding to the second evaluation information, obtain the first evaluation bias and the second evaluation bias, determine whether the first evaluation bias and the second evaluation bias are consistent, obtain a judgment result, and generate evaluation information corresponding to the knowledge base for intelligent operation and maintenance of the wind power system according to the judgment result, so as to obtain the third evaluation information.

[0077] In this example, by obtaining the wind power parameters of the wind power station, where the wind power parameters include wind power level, temperature parameter, humidity parameter, etc., obtaining the power generation information of the wind power station to obtain the first power generation information, and evaluating the wind power station using the knowledge base for intelligent operation and maintenance of the wind power system according to the wind power parameters and the first power generation information to obtain the first evaluation information, where the first evaluation information is used to indicate whether the wind power station is operating normally, using the wind power station test platform to test and evaluate the wind power station to obtain the second evaluation information, where the second evaluation information is used to indicate whether the wind power station is operating normally, and evaluating the knowledge base for intelligent operation and maintenance of the wind power system according to the first evaluation information and the second evaluation information to obtain the third evaluation information, where the third evaluation information is used to indicate whether there is an abnormality in the knowledge base for intelligent operation and maintenance of the wind power system, which can combine the wind power parameters of the wind power station and the power generation information of the wind power station to evaluate the knowledge base for intelligent operation and maintenance of the wind power system, improving the accuracy when evaluating the knowledge base for intelligent operation and maintenance of the wind power system.

[0078] In a possible implementation manner, a method for evaluating a wind power station using the knowledge base for intelligent operation and maintenance of the wind power system according to the wind power parameters and the first power generation information to obtain the first evaluation information includes:

[0079] A1. Perform an initialization process on the knowledge base for intelligent operation and maintenance of the wind power system to obtain a target knowledge base;

[0080] A2. Input the wind power parameters into the target knowledge base for matching to obtain a target triple set;

[0081] A3. Obtain the tail entities in the target triple set to obtain a target entity set;

[0082] A4. Perform a normalization process on the target entities in the target entity set to obtain the second power generation information;

[0083] A5. Evaluate the wind power station according to the first power generation information and the second power generation information to obtain the first evaluation information.

[0084] Specifically, it can be achieved by selecting appropriate model capabilities of the knowledge base for intelligent operation and maintenance of the wind power system on the user operation interface of the knowledge base for intelligent operation and maintenance of the wind power system, thereby completing the initialization process of the knowledge base for intelligent operation and maintenance of the wind power system and obtaining the target knowledge base.

[0085] After obtaining the target knowledge base, specifically, wind power parameters can be input on the user operation interface of the knowledge base for intelligent operation and maintenance of the wind power system. The knowledge base for intelligent operation and maintenance of the wind power system can use the wind power parameters input by the user as the reference head entity, and match triples with the same reference head entity in the knowledge base to obtain multiple target triples, thereby obtaining a target triple set.

[0086] After obtaining the target triple set, the tail entities in the target triples in the target triple set can be extracted by a general tail entity extraction method to obtain a target entity set. Among them, the tail entities in the target entity set can be the power generation data of a wind power station operating normally under the wind power parameters input by the user, etc.

[0087] After obtaining the target entity set, the target entities in the target entity set can be normalized by a general normalization processing method to obtain a normalized target entity set, and then the average value corresponding to the target entities in the normalized target entity set can be calculated by a general average value calculation method, and the average value corresponding to the target entities in the target entity set is determined as the second power generation information.

[0088] After obtaining the second power generation information, it can be determined whether the difference between the first power generation information and the second power generation information is less than a preset power generation information difference threshold. If it is less, it means that the power generation data of the wind power station meets the expectations, indicating that the wind power station is operating normally, and a first evaluation information is generated. The first evaluation information can be, for example: the wind power station is operating normally. This is only an example for illustration and does not limit the content of the first evaluation information.

[0089] In this example, by matching according to the wind power parameters of the wind power station in the knowledge base for intelligent operation and maintenance of the wind power system, a target entity set is obtained, and then the target entities in the target entity set are normalized to obtain the second power generation information, realizing the prediction of the power generation data of the wind power station, etc. according to the wind power parameters through the knowledge base for intelligent operation and maintenance of the wind power system, thereby improving the efficiency in evaluating the knowledge base for intelligent operation and maintenance of the wind power system.

[0090] In a possible implementation manner, a method for testing and evaluating a wind power station using a wind power station test platform to obtain second evaluation information includes:

[0091] B1. Use a wind power station test platform to conduct a functional test and evaluation on the wind power station to obtain functional evaluation information;

[0092] B2. Use a wind power station test platform to conduct a power test and evaluation on the wind power station to obtain power evaluation information;

[0093] B3. Integrate the functional evaluation information and the power evaluation information to obtain second evaluation information.

[0094] Among them, it can be to adjust the test mode to the functional test on the operation interface of the wind power station test platform, and check the connection status between the wind power station test platform and the wind power station. When the connection status between the wind power station test platform and the wind power station is good, input the pre-set test parameters to conduct a preliminary test on the functions of the wind power station, and view the output voltage, current output waveform, etc. of the wind power station on the oscilloscope to obtain preliminary test results. Judge whether the preliminary test results meet the expected test results. When the preliminary test results do not meet the expected test results, it indicates that the functions of the wind power station are abnormal, and generate functional evaluation information; when the preliminary test results meet the expected test results, adjust the pre-set test parameters to conduct a secondary test on the functions of the wind power station, and view the output voltage, current output waveform, etc. of the wind power station on the oscilloscope to obtain secondary test results. When the secondary test results do not meet the expected test results, it indicates that the functions of the wind power station are abnormal, and generate functional evaluation information (the functional evaluation information indicates functional abnormality), when the secondary test results meet the expected test results, it indicates that the functions of the wind power station are normal, and generate functional evaluation information (the functional evaluation information indicates functional normality). Among them, the functional evaluation information can be used to describe whether the control functions of the wind power station are normal, and the functional evaluation information includes the score of the server for the wind power station in terms of functional testing; the content of the functional evaluation information can be, for example: the control functions of the wind power station are normal, and the score is 9, or it can be, for example: the control functions of the wind power station are abnormal, and the score is 3; only for example here, the content of the functional evaluation information is not limited.

[0095] After obtaining the function evaluation information, the test mode can be adjusted to power test on the operation interface of the wind power station test platform. Control the circuit breaker of the main incoming line of the wind power station through the wind power station test platform, then close the contactor, and input the preset power generation control data. The power generation control data includes voltage control data, current control data, current output waveform control data, etc. Then, do not perform any operation on the wind power station test platform and wait for 1 minute. After waiting for 1 minute, check the voltage value, current output waveform, etc. transmitted back by the power unit of the wind power station on the oscilloscope. Determine whether the voltage value, current value, and current output waveform transmitted back by the power unit of the wind power station are consistent with the power generation control data. If they are not consistent, it indicates that the power output function of the wind power station is abnormal, and power evaluation information is generated; if they are consistent, then cancel the preset power generation control data, so that the wind power station test platform controls the wind power station to perform a full-power test, and check the voltage value and current value transmitted back by the power unit of the wind power generation on the oscilloscope. Determine whether the voltage value and current value transmitted back by the power unit of the wind power station are consistent with the rated output voltage and rated output current of the power unit of the wind power station. If they are not consistent, it indicates that the power output capacity of the wind power station is abnormal, and power evaluation information is generated; if they are consistent, it indicates that the power output capacity of the wind power station is normal, and power evaluation information is generated. The power evaluation information can be used to describe whether the power output capacity of the wind power station is normal. The function evaluation information includes the score given by the server for the wind power station in terms of power test; the power evaluation information includes the score given by the server for the wind power station in terms of power test; the content of the power evaluation information can be, for example: the power output function of the wind power station is normal, and the score is 8, or it can be, for example: the power output capacity of the wind power station is abnormal, and the score is 2; only examples are given here, and the content of the power evaluation information is not limited.

[0096] After obtaining the power evaluation information, since both the function evaluation information and the power evaluation information can be used as important indicators to represent whether the wind power station is operating normally, therefore, the function evaluation information and the power evaluation information can be weighted and averaged through the first preset weight information corresponding to the function evaluation information and the second preset weight information corresponding to the power evaluation information, so as to complete the fusion between the function evaluation information and the power evaluation information and obtain the second evaluation information.

[0097] In this example, the wind power station test platform conducts function tests and power tests on the wind power station respectively to obtain function evaluation information and power evaluation information, and then fuses the function evaluation information and the power evaluation information through a weighted average method to obtain the second evaluation information, thereby improving the accuracy in evaluating the knowledge base of intelligent operation and maintenance of the wind power system.

[0098] In a possible implementation, a method for evaluating a knowledge base for intelligent operation and maintenance of a wind power system based on the first evaluation information and the second evaluation information to obtain third evaluation information, where the third evaluation information is used to indicate whether there is an abnormality in the knowledge base for intelligent operation and maintenance of the wind power system, includes:

[0099] C1. Obtain the evaluation bias corresponding to the first evaluation information to obtain a first evaluation bias, and calculate the evaluation bias corresponding to the second evaluation information to obtain a second evaluation bias;

[0100] C2. Determine whether the first evaluation bias and the second evaluation bias are consistent to obtain a judgment result;

[0101] C3. Generate evaluation information corresponding to the knowledge base for intelligent operation and maintenance of the wind power system according to the judgment result to obtain third evaluation information.

[0102] Among them, the first evaluation bias corresponding to the first evaluation information and the second evaluation bias corresponding to the second evaluation information can be obtained by using a look-up table method from a preset mapping table.

[0103] After obtaining the first evaluation bias and the second evaluation bias, the target deflection value can be obtained by calculating the deflection value between the first evaluation bias and the second evaluation bias, and then the judgment result can be obtained by determining whether the target deflection value is less than a preset deflection value threshold. Specifically, the deflection value between the first evaluation bias and the second evaluation bias can be calculated by the method shown in the following formula to obtain the target deflection value:

[0104]

[0105] In the formula, S represents the target deflection value; tan represents the tangent operation symbol in trigonometric functions; e is the natural exponential term; n represents the number of feature vectors corresponding to the feature vectors extracted when performing feature extraction on the vectorized first evaluation bias; β represents a preset deflection coefficient, which can be determined by user input or system default; u represents the vectorized second evaluation bias; r represents the vectorized first evaluation bias; d represents the projection coefficient of the vectorized first evaluation bias in the direction of the vectorized second evaluation bias, which can be determined by the dot product method; k represents a deflection constant, which can be determined by user settings or system default; q represents a random number randomly selected by the system.

[0106] After obtaining the judgment result, if the judgment result is that the target deflection value is less than the preset deflection value threshold, it indicates that the evaluation biases expressed by the first evaluation bias and the second evaluation bias are the same. Further, it indicates that the first evaluation information and the second evaluation information are consistent in evaluating the working state of the wind power station, indicating that the knowledge base function of the intelligent operation and maintenance of the wind power system is normal. Thus, the evaluation information corresponding to the knowledge base of the intelligent operation and maintenance of the wind power system is generated to obtain the third evaluation information (the third evaluation information is used to indicate that the knowledge base is normal); if the judgment result is that the target deflection value is greater than or equal to the preset deflection value threshold, it indicates that the evaluation biases expressed by the first evaluation bias and the second evaluation bias are different. Further, it indicates that the first evaluation information and the second evaluation information are inconsistent in evaluating the working state of the wind power station, indicating that the knowledge base function of the intelligent operation and maintenance of the wind power system is abnormal. Thus, the evaluation information corresponding to the knowledge base of the intelligent operation and maintenance of the wind power system is generated to obtain the third evaluation information (the third evaluation information is used to indicate that the knowledge base is abnormal).

[0107] In this example, by obtaining the evaluation biases corresponding to the first evaluation information and the second evaluation information, the first evaluation bias and the second evaluation bias are obtained. By calculating the deflection value between the first evaluation bias and the second evaluation bias, the target deflection value is obtained. Then, by judging the magnitude relationship between the target deflection value and the preset deflection value threshold, the judgment result is obtained, and according to the judgment result, the evaluation information corresponding to the knowledge base of the intelligent operation and maintenance of the wind power system is generated to obtain the third evaluation information, which improves the accuracy in evaluating the knowledge base of the intelligent operation and maintenance of the wind power system.

[0108] In a possible implementation manner, before evaluating the wind power station using the knowledge base of the intelligent operation and maintenance of the wind power system according to the wind power parameters and the first power generation information, and the first evaluation information is used to indicate whether the wind power station is operating normally, the method further includes:

[0109] D1. Obtain the enterprise internal technical documents of the wind power station to obtain the target documents;

[0110] D2. Use a preset triple generation model to disassemble the target documents to obtain a triple set;

[0111] D3. Construct the knowledge base of the intelligent operation and maintenance of the wind power system according to the triples in the triple set to obtain the knowledge base of the intelligent operation and maintenance of the wind power system.

[0112] Among them, it is possible to obtain the technical documents related to wind power generation within the enterprise as the target documents.

[0113] After obtaining the target file, the preset triple generation model can be trained in the general training manner of the triple generation model, and then the target file is input into the preset triple generation model for disassembly to obtain a triple set.

[0114] After obtaining the triple set, the triples in the triple set can be associated and stored according to the preset knowledge base construction rules, so as to construct a knowledge base for intelligent operation and maintenance of the wind power system.

[0115] In this example, the target file is disassembled by the preset triple generation model to obtain a triple set, and then the triples in the triple set are associated and stored according to the preset knowledge base construction rules, so as to construct a knowledge base for intelligent operation and maintenance of the wind power system, improving the efficiency in evaluating the knowledge base for intelligent operation and maintenance of the wind power system.

[0116] Consistent with the above embodiments, please refer to Figure 2 , Figure 2 which is a schematic structural diagram of a terminal provided by an embodiment of the present application. As Figure 2 shown, it includes a processor, an input device, an output device, and a memory. The processor, input device, output device, and memory are interconnected. Among them, the memory is used to store a computer program, the computer program includes program instructions, and the processor is configured to call the program instructions. The above program includes instructions for performing the following steps;

[0117] Obtain the wind power parameters of the wind power station, where the wind power parameters include wind power level, temperature parameter, and humidity parameter;

[0118] Obtain the power generation information of the wind power station to obtain the first power generation information;

[0119] Evaluate the wind power station according to the wind power parameters and the first power generation information using the knowledge base for intelligent operation and maintenance of the wind power system to obtain the first evaluation information, and the first evaluation information is used to indicate whether the wind power station is operating normally;

[0120] Use the wind power station test platform to test and evaluate the wind power station to obtain the second evaluation information, and the second evaluation information is used to indicate whether the wind power station is operating normally;

[0121] Evaluate the knowledge base for intelligent operation and maintenance of the wind power system according to the first evaluation information and the second evaluation information to obtain the third evaluation information, and the third evaluation information is used to indicate whether there is an abnormality in the knowledge base for intelligent operation and maintenance of the wind power system.

[0122] The above mainly introduced the solution of the embodiment of the present application from the perspective of the execution process on the method side. It can be understood that in order for the terminal to implement the above functions, it includes the corresponding hardware structure and / or software module for executing each function. Those skilled in the art should easily realize that, combining the units and algorithm steps of each example described in the embodiments provided in this article, the present application can be implemented in the form of hardware or a combination of hardware and computer software. Whether a certain function is executed in the way of hardware or computer software driving hardware depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present application.

[0123] The embodiment of the present application can divide the functions of the terminal according to the above method examples. For example, each function unit can be divided corresponding to each function, or two or more functions can be integrated into one processing unit. The above integrated unit can be implemented in the form of hardware or in the form of a software function unit. It should be noted that the division of units in the embodiment of the present application is illustrative, only a logical function division, and there can be other division methods in actual implementation.

[0124] Consistent with the above, please refer to Figure 3 , Figure 3 which is a schematic structural diagram of a knowledge base evaluation system for intelligent operation and maintenance of a wind power system provided by an embodiment of the present application. As Figure 3 shown, the system includes:

[0125] A first acquisition unit 301, configured to acquire wind power parameters of a wind power station, where the wind power parameters include wind power level, temperature parameter, and humidity parameter;

[0126] A second acquisition unit 302, configured to acquire power generation information of the wind power station to obtain first power generation information;

[0127] A first evaluation unit 303, configured to evaluate the wind power station according to the wind power parameters and the first power generation information using a knowledge base for intelligent operation and maintenance of a wind power system to obtain first evaluation information;

[0128] A second evaluation unit 304, configured to perform a test evaluation on the wind power station using a wind power station test platform to obtain second evaluation information;

[0129] A third evaluation unit 305, configured to evaluate the knowledge base for intelligent operation and maintenance of the wind power system according to the first evaluation information and the second evaluation information to obtain third evaluation information.

[0130] In a possible implementation manner, the first evaluation unit 303 is specifically configured to:

[0131] Initialize the knowledge base for the intelligent operation and maintenance of the wind power system to obtain a target knowledge base;

[0132] Input the wind power parameters into the target knowledge base for matching to obtain a target triple set;

[0133] Obtain the tail entities in the target triple set to obtain a target entity set;

[0134] Normalize the target entities in the target entity set to obtain second power generation information;

[0135] Evaluate the wind power station according to the first power generation information and the second power generation information to obtain first evaluation information.

[0136] In a possible implementation manner, the second evaluation unit 304 is specifically configured to:

[0137] Use a wind power station test platform to conduct a functional test evaluation on the wind power station to obtain functional evaluation information;

[0138] Use a wind power station test platform to conduct a power test evaluation on the wind power station to obtain power evaluation information;

[0139] Fuse the functional evaluation information and the power evaluation information to obtain second evaluation information.

[0140] In a possible implementation manner, the third evaluation unit 305 is specifically configured to:

[0141] Obtain the evaluation bias corresponding to the first evaluation information to obtain a first evaluation bias, and calculate the evaluation bias corresponding to the second evaluation information to obtain a second evaluation bias;

[0142] Judge whether the first evaluation bias and the second evaluation bias are consistent to obtain a judgment result;

[0143] Generate evaluation information corresponding to the knowledge base for the intelligent operation and maintenance of the wind power system according to the judgment result to obtain third evaluation information.

[0144] In a possible implementation manner, before evaluating the wind power station using the knowledge base for the intelligent operation and maintenance of the wind power system according to the wind power parameters and the first power generation information, and the first evaluation information is used to indicate whether the wind power station is operating normally, the first evaluation unit 303 is further configured to:

[0145] Obtain the enterprise internal technical documents of the wind power station to obtain target documents;

[0146] Decompose the target file using a preset triple generation model to obtain a set of triples;

[0147] Construct a knowledge base for intelligent operation and maintenance of the wind power system according to the triples in the set of triples, to obtain a knowledge base for intelligent operation and maintenance of the wind power system.

[0148] An embodiment of the present application also provides a computer storage medium, wherein the computer storage medium stores a computer program for electronic data exchange, and the computer program causes a computer to execute some or all of the steps of any one of the knowledge base evaluation methods for intelligent operation and maintenance of a wind power system as described in the above method embodiments.

[0149] An embodiment of the present application also provides a computer program product, the computer program product includes a non-transitory computer-readable storage medium storing a computer program, and the computer program causes a computer to execute some or all of the steps of any one of the knowledge base evaluation methods for intelligent operation and maintenance of a wind power system as described in the above method embodiments.

[0150] It should be noted that, for the foregoing method embodiments, for the sake of simple description, they are all expressed as a series of action combinations. However, those skilled in the art should know that the present application is not limited by the described action sequence, because according to the present application, certain steps can be performed in other sequences or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily essential to the present application.

[0151] In the above embodiments, the descriptions of the respective embodiments have their own emphases. For the parts not detailed in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0152] In several embodiments provided by the present application, it should be understood that the disclosed device can be implemented in other ways. For example, the device embodiments described above are only illustrative. For example, the division of the units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point, the displayed or discussed mutual coupling or direct coupling or communication connection can be through some interfaces. The indirect coupling or communication connection of the device or unit can be in an electrical or other form.

[0153] The unit described as a separation component may or may not be physically separated. The component displayed as a unit may or may not be a physical unit, that is, it may be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0154] In addition, in each embodiment of the application, each functional unit can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above integrated unit can be implemented in the form of hardware or in the form of a software program module.

[0155] If the integrated unit is implemented in the form of a software program module and sold or used as an independent product, it can be stored in a computer-readable memory. Based on such an understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in each embodiment of this application. And the aforementioned memory includes: USB flash drives, read-only memory (ROM), random access memory (RAM), mobile hard disks, magnetic disks, or optical discs and other media that can store program codes.

[0156] Those of ordinary skill in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing relevant hardware through a program. This program can be stored in a computer-readable memory, and the memory can include: flash drives, read-only memories, random access memories, magnetic disks, or optical discs, etc.

[0157] The above has introduced the embodiments of this application in detail. Specific examples are used in this article to elaborate on the principle and implementation manner of this application. The description of the above embodiments is only used to help understand the method and its core idea of this application; at the same time, for those of ordinary skill in the art, according to the idea of this application, there will be changes in the specific implementation manner and application scope. In summary, the content of this specification should not be construed as a limitation to this application.

Claims

1. A knowledge base evaluation method for intelligent operation and maintenance of wind power systems, characterized in that: The method comprises: Obtaining wind parameters of the wind power station, wherein the wind parameters include wind force level, temperature parameters and humidity parameters; Acquire power generation information of the wind power station to obtain first power generation information; According to the wind power parameter and the first power generation information, the wind power station is evaluated using a knowledge base of wind power system intelligent operation and maintenance to obtain first evaluation information; Using the wind power station test platform to test and evaluate the wind power station to obtain second evaluation information; The knowledge base of intelligent operation and maintenance of the wind power system is evaluated according to the first evaluation information and the second evaluation information to obtain third evaluation information.

2. The knowledge base evaluation method for intelligent operation and maintenance of wind power system according to claim 1 is characterized in that: The step of evaluating the wind power station using the knowledge base of wind power system intelligent operation and maintenance according to the wind power parameter and the first power generation information to obtain first evaluation information includes: Initializing the knowledge base of the wind power system intelligent operation and maintenance to obtain a target knowledge base; Inputting the wind force parameters into a target knowledge base for matching to obtain a target triple set; Obtaining the tail entity in the target triple set to obtain a target entity set; Normalizing the target entities in the target entity set to obtain second power generation information; The wind power station is evaluated according to the first power generation information and the second power generation information to obtain first evaluation information.

3. The knowledge base evaluation method for intelligent operation and maintenance of wind power system according to claim 2 is characterized in that: The method of using the wind power station test platform to test and evaluate the wind power station to obtain second evaluation information includes: Use the wind power station test platform to perform functional test and evaluation on the wind power station to obtain functional evaluation information; Use the wind power station test platform to perform power test and evaluation on the wind power station to obtain power evaluation information; The function evaluation information and the power evaluation information are merged to obtain second evaluation information.

4. The knowledge base evaluation method for intelligent operation and maintenance of wind power system according to claim 3 is characterized in that: The step of evaluating the knowledge base of wind power system intelligent operation and maintenance according to the first evaluation information and the second evaluation information to obtain third evaluation information includes: Obtaining the evaluation bias corresponding to the first evaluation information to obtain a first evaluation bias, and calculating the evaluation bias corresponding to the second evaluation information to obtain a second evaluation bias; Determine whether the first evaluation bias is consistent with the second evaluation bias, and obtain a determination result; Evaluation information corresponding to the knowledge base of intelligent operation and maintenance of the wind power system is generated according to the judgment result to obtain third evaluation information.

5. The knowledge base evaluation method for intelligent operation and maintenance of wind power system according to claim 4 is characterized in that: Before evaluating the wind power station using the knowledge base of wind power system intelligent operation and maintenance according to the wind power parameter and the first power generation information to obtain the first evaluation information, the method further includes: Obtain the internal technical documents of the wind power station and obtain the target documents; Using a preset triple generation model to disassemble the target file to obtain a triple set; The knowledge base of the intelligent operation and maintenance of the wind power system is constructed according to the triples in the triple set to obtain the knowledge base of the intelligent operation and maintenance of the wind power system.

6. A knowledge base evaluation system for intelligent operation and maintenance of wind power systems, characterized in that: The system comprises: A first acquisition unit is used to acquire wind parameters of the wind power station, wherein the wind parameters include wind force level, temperature parameters and humidity parameters; A second acquisition unit is used to acquire power generation information of the wind power station to obtain first power generation information; A first evaluation unit is used to evaluate the wind power station using a knowledge base of wind power system intelligent operation and maintenance according to the wind power parameter and the first power generation information to obtain first evaluation information; A second evaluation unit is used to test and evaluate the wind power station using the wind power station test platform to obtain second evaluation information; The third evaluation unit is used to evaluate the knowledge base of wind power system intelligent operation and maintenance according to the first evaluation information and the second evaluation information to obtain third evaluation information.

7. The knowledge base evaluation method for intelligent operation and maintenance of wind power system according to claim 6 is characterized in that: The first evaluation unit is specifically used for: Initializing the knowledge base of the wind power system intelligent operation and maintenance to obtain a target knowledge base; Inputting the wind force parameters into a target knowledge base for matching to obtain a target triple set; Obtaining the tail entity in the target triple set to obtain a target entity set; Normalizing the target entities in the target entity set to obtain second power generation information; The wind power station is evaluated according to the first power generation information and the second power generation information to obtain first evaluation information.

8. The knowledge base evaluation method for intelligent operation and maintenance of wind power systems according to claim 7 is characterized in that: The second evaluation unit is specifically used for: Use the wind power station test platform to perform functional test and evaluation on the wind power station to obtain functional evaluation information; Use the wind power station test platform to perform power test and evaluation on the wind power station to obtain power evaluation information; The function evaluation information and the power evaluation information are merged to obtain second evaluation information.

9. A terminal, characterized in that: The method comprises a processor, an input device, an output device and a memory, wherein the processor, the input device, the output device and the memory are interconnected, wherein the memory is used to store a computer program, the computer program comprises program instructions, and the processor is configured to call the program instructions to execute the method according to any one of claims 1 to 5.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, wherein the computer program includes program instructions, and when the program instructions are executed by a processor, the processor is caused to perform the method according to any one of claims 1 to 5.

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