Method and system for monitoring displacement of generator in wind turbine generator

Abstract

The invention provides a method and a system for monitoring displacement of generators in a wind turbine generator set. The method comprises the following steps: determining first displacement data of each generator base in the generator set; extracting abnormal features in the first displacement data, and establishing a feature data set; preprocessing the feature data set to obtain to-be-analyzed data; based on the feature data set and the to-be-analyzed data, the displacement state of each generator base in the generator set is analyzed, and state analysis data is obtained; and generating a monitoring early warning instruction based on the feature data set, the to-be-analyzed data and the state analysis data. According to the scheme provided by the invention, the data processing link adopts the modes of feature extraction, preprocessing and state analysis to carry out anomaly detection on the first displacement data of the generator base, and anomaly early warning is carried out in time by generating the monitoring early warning instruction, so that effective monitoring of the displacement of the generator in the wind turbine generator can be accurately and reliably realized; and safe and stable operation of the wind turbine generator is ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of wind power generation, and in particular to a method and system for monitoring the displacement of a generator in a wind turbine. Background Art

[0002] During the operation of wind turbines, the generator is affected by the long-term vibration of the nacelle, which may cause large vibrations in the front and rear bearings of the generator, causing the generator base to shift, thus affecting the normal operation of the wind turbine. In order to detect the hidden dangers of wind turbines in advance, it is very important to monitor the operating status of the generator in real time.

[0003] In the related technology, relevant sensors are usually installed on the generator base to detect the displacement status of the generator base. Due to the subsequent data processing link, whether the generator base is seriously offset is manually judged based on whether the acquired displacement data exceeds the safety upper limit. The accuracy and reliability of the displacement monitoring link are insufficient, and it is difficult to ensure the safe and stable operation of the wind turbine.

[0004] Therefore, traditional displacement monitoring solutions lack accuracy and reliability, making it difficult to ensure the safe and stable operation of wind turbines. Summary of the invention

[0005] The present invention provides a method and system for monitoring the displacement of a generator in a wind turbine generator set, which are used to solve the defects that the traditional displacement monitoring scheme is insufficient in accuracy and reliability and is difficult to ensure the safe and stable operation of the wind turbine generator set.

[0006] In one aspect, the present invention provides a method for monitoring the displacement of a generator in a wind turbine generator set, comprising: Determine first displacement data of each generator base in the generator set; Extracting abnormal features from the first displacement data and establishing a feature data set; Preprocessing the feature data set to obtain data to be analyzed; Based on the characteristic data set and the data to be analyzed, the displacement state of each generator base in the generator set is analyzed to obtain state analysis data; A monitoring and early warning instruction is generated based on the feature data set, the data to be analyzed, and the status analysis data.

[0007] According to the method for monitoring the displacement of a generator in a wind turbine provided by the present invention, determining first displacement data of each generator base in the generator set includes: Determine the displacement monitoring equipment corresponding to each generator base in the generator set; Obtaining installation location information and device attribute information of each of the displacement monitoring devices; Establishing a monitoring device array based on the installation location information and the device attribute information; Obtaining the measured displacement value of the generator base collected by the monitoring device array; The displacement measured values ​​are summarized to obtain first displacement data of each generator base in the generator set.

[0008] According to the method for monitoring the displacement of a generator in a wind turbine provided by the present invention, the displacement monitoring device corresponding to each generator base in the generator set is determined, including: Obtain demand information of generator sets; Extracting target requirements related to the generator base from the requirement information; Retrieving a target monitoring device matching the target demand from a preset demand-device database; The target monitoring device is used as a displacement monitoring device corresponding to each generator base in the generator set.

[0009] According to the method for monitoring the displacement of a generator in a wind turbine provided by the present invention, the characteristic data set is preprocessed to obtain data to be analyzed, including: Retrieving a target preprocessing strategy matching the feature data set from a preset feature-method database; The characteristic data set is preprocessed according to the target preprocessing strategy to obtain data to be analyzed.

[0010] According to the method for monitoring the displacement of a generator in a wind turbine provided by the present invention, based on the characteristic data set and the data to be analyzed, the displacement state of each generator base in the generator set is analyzed to obtain state analysis data, including: Extracting a target screening factor corresponding to the feature data set from a preset feature-factor comparison table; Retrieving a state analysis strategy matching the target screening factor from a preset factor-method database; Based on the data to be analyzed, the displacement state of each generator base in the generator set is analyzed according to the state analysis strategy to obtain a state analysis result; The displacement state matching the state analysis result is extracted from a preset result-state comparison table to obtain state analysis data.

[0011] According to the method for monitoring the displacement of a generator in a wind turbine provided by the present invention, a monitoring and early warning instruction is generated based on the characteristic data set, the data to be analyzed and the state analysis data, including: Retrieving a target prediction model matching the feature data set from a preset feature-model database; Inputting the data to be analyzed into the target prediction model to obtain displacement prediction data output by the target prediction model; Determining a displacement prediction state corresponding to the displacement prediction data; Inputting the displacement prediction data, displacement prediction state and state analysis data into a preset early warning database for data matching to obtain an early warning matching result; Extracting the target instruction corresponding to the warning matching result from a preset result-instruction comparison table; The target instruction is used as a monitoring and early warning instruction.

[0012] According to the method for monitoring the displacement of a generator in a wind turbine provided by the present invention, after generating a monitoring warning instruction, the method further includes: Based on the monitoring and early warning instructions, the position of each generator base in the generator set is adjusted.

[0013] According to the method for monitoring the displacement of a generator in a wind turbine provided by the present invention, based on the monitoring and early warning instructions, the position of each generator base in the generator set is adjusted, including: Parsing the monitoring and early warning instructions to obtain an instruction parsing package; Performing factor matching on the parsed content in the instruction parsing package to obtain a matching factor corresponding to each parsed content in the instruction parsing package, and constructing a matching factor set; Extracting a device adjustment strategy corresponding to the matching factor set from a preset factor-strategy comparison table; The position of each generator base in the generator set is adjusted according to the equipment adjustment strategy.

[0014] According to the method for monitoring the displacement of a generator in a wind turbine provided by the present invention, after adjusting the position of each generator base in the generator set, the method further comprises: Determine the second displacement data of each generator base in the generator set after adjustment; Determine the standard position data of each generator base in the generator set; Comparing the standard position data with the second displacement data to obtain position difference data; Based on the position difference data, the position of each generator base in the adjusted generator set is calibrated.

[0015] On the other hand, the present invention also provides a monitoring system for generator displacement in a wind turbine generator set, comprising: A data acquisition module, used to determine first displacement data of each generator base in the generator set; A feature extraction module, used to extract abnormal features in the first displacement data and establish a feature data set; A preprocessing module, used to preprocess the feature data set to obtain data to be analyzed; A state analysis module, used to analyze the displacement state of each generator base in the generator set based on the characteristic data set and the data to be analyzed, so as to obtain state analysis data; The monitoring and early warning module is used to generate monitoring and early warning instructions based on the feature data set, the data to be analyzed and the status analysis data.

[0016] The method and system for monitoring the displacement of a generator in a wind turbine provided by the present invention determine the first displacement data of each generator base in the generator set; extract the abnormal features in the first displacement data to establish a feature data set; pre-process the feature data set to obtain data to be analyzed; analyze the displacement state of each generator base in the generator set based on the feature data set and the data to be analyzed to obtain state analysis data; and generate monitoring and early warning instructions based on the feature data set, the data to be analyzed, and the state analysis data. Since the data processing link uses feature extraction, pre-processing, and state analysis to detect abnormalities in the first displacement data of the generator base, and generates abnormal warnings in a timely manner by generating monitoring and early warning instructions, it is possible to accurately and reliably realize effective monitoring of the displacement of the generator in the wind turbine, solve the problem of insufficient accuracy and reliability of traditional displacement monitoring solutions, and ensure the safe and stable operation of the wind turbine. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0018] Figure 1 It is a flow chart of a method for monitoring displacement of a generator in a wind turbine provided by an embodiment of the present invention; Figure 2 is a schematic structural diagram of a monitoring system for generator displacement in a wind turbine provided by an embodiment of the present invention; Figure 3 It is a schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0019] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0020] Combine the following Figures 1 to 3 The detailed scheme of the method and system for monitoring the displacement of a generator in a wind turbine set provided by an embodiment of the present invention is described.

[0021] Figure 1 It is a flow chart of a method for monitoring displacement of a generator in a wind turbine provided by an embodiment of the present invention.

[0022] like Figure 1 As shown, the monitoring method of the displacement of the generator in the wind turbine provided by the embodiment of the present invention can be performed by a computer or server with data receiving and data processing capabilities. The above method mainly includes the following steps: Step 110: Determine first displacement data of each generator base in the generator set.

[0023] In this embodiment, the first displacement data can be collected by a displacement monitoring device pre-installed at a preset position point in the generator set.

[0024] Step 120: extract abnormal features from the first displacement data and establish a feature data set.

[0025] It can be understood that the abnormal features are mainly used to characterize data features in the first displacement data that obviously deviate from the normal range. After all the abnormal features are aggregated, a feature data set can be obtained.

[0026] In practical applications, a feature database storing various abnormal features and their meanings can be pre-established, so that each data feature in the first displacement data can be matched with the abnormal features in the feature database, thereby accurately extracting the abnormal features in the first displacement data.

[0027] Step 130: pre-process the feature data set to obtain data to be analyzed.

[0028] In practical applications, the preprocessing stage is mainly used to improve the data quality of the data in the feature data set, so as to provide accurate and reliable data basis for the subsequent data analysis stage.

[0029] Step 140: Based on the characteristic data set and the data to be analyzed, the displacement state of each generator base in the generator set is analyzed to obtain state analysis data.

[0030] In this embodiment, the state analysis link mainly analyzes the displacement state of each generator base in the generator set, and the state analysis data can represent the position deviation of the generator base.

[0031] Step 150: Generate monitoring and early warning instructions based on the feature data set, the data to be analyzed, and the status analysis data.

[0032] It is understandable that the monitoring and early warning instructions can present the displacement status of the generator base to the user in the form of early warning information, thereby promptly reminding the user to adjust or maintain the generator base to ensure stable and safe operation of the wind turbine.

[0033] The solution provided by the embodiment of the present invention can monitor the displacement of the generator base in real time, promptly discover abnormal displacement of the generator base, and at the same time generate monitoring and early warning instructions according to the abnormal displacement to ensure the normal operation of the generator set, which helps to improve the power generation efficiency and system stability of the entire wind power generation system.

[0034] In one embodiment, determining first displacement data of each generator base in the generator set includes: The first step is to determine the displacement monitoring equipment corresponding to each generator base in the generator set.

[0035] In a specific implementation, determining the displacement monitoring device corresponding to each generator base in the generator set specifically includes: First, obtain the demand information of the generator set.

[0036] It can be understood that the demand information specifically refers to the demand information of the generator set or the power generation system. In this embodiment, the demand information may specifically include the generator base condition monitoring requirements, system operation status monitoring requirements, and early warning and alarm requirements.

[0037] Then, the target requirements related to the generator base in the requirement information are extracted.

[0038] In this embodiment, the target requirements include but are not limited to requirements on generator displacement, temperature, vibration, etc.

[0039] Next, the target monitoring equipment matching the target demand is retrieved from the preset demand-equipment database.

[0040] In this embodiment, the demand-equipment database is a pre-built database storing the corresponding relationship between the demands related to the generator base and the displacement monitoring equipment.

[0041] Finally, the target monitoring device is used as the displacement monitoring device corresponding to each generator base in the generator set.

[0042] In this embodiment, the displacement monitoring device can be a slip distance sensor installed on the generator base. The slip distance sensor uses laser distance measurement and is installed on the X-axis, Y-axis, and Z-axis of the generator base, respectively. There are two position points on the X-axis, two position points on the Y-axis, and one position point on the Z-axis, so that 5-point measurement of the slip amount can be achieved.

[0043] It is not difficult to find that by obtaining the demand information of the generator set, parsing the target demand related to the generator base, and then selecting the matching target monitoring equipment in the preset demand-equipment database, the target monitoring equipment can be accurately matched according to the demand information of the generator set and the target demand of the generator base to ensure the accuracy of the monitoring data. At the same time, by matching the demand with the equipment, the displacement monitoring equipment can be ensured to be consistent with the demand, reducing the problem of low monitoring accuracy due to information mismatch.

[0044] The second step is to obtain the installation location information and device attribute information of each displacement monitoring device.

[0045] In this embodiment, the installation location information refers to the information of the location point of the displacement monitoring device, and the device attribute information includes device identification such as device model, manufacturer, installation date, etc., which is used to identify and manage the displacement monitoring device.

[0046] The third step is to establish a monitoring device array based on the installation location information and device attribute information.

[0047] The monitoring device array specifically refers to a data matrix constructed based on the installation location information and device attribute information of each displacement monitoring device, which is used to monitor the displacement status of each generator base in the generator set in real time.

[0048] The fourth step is to obtain the actual displacement value of the generator base collected by the monitoring equipment array.

[0049] In this embodiment, the measured displacement value refers to the actual value of each generator base during operation obtained by real-time collection through the monitoring device array, including but not limited to the displacement degree, temperature, vibration and other information of the generator.

[0050] The fifth step is to summarize the measured displacement values ​​to obtain the first displacement data of each generator base in the generator set.

[0051] In actual applications, the measurement results of the slip distance sensor will be collected in real time to the controller in the cabin of the generator set. The controller will sample and filter the measurement results in the form of analog input point signals, and output them to the data analysis software in the central control room. The data analysis software will display the actual displacement value in real time, and support functions such as historical displacement data viewing and abnormal parameter alarm, thereby realizing maintenance and inspection based on the operating status of the wind turbine.

[0052] In one embodiment, preprocessing the feature data set to obtain the data to be analyzed specifically includes: First, the target preprocessing strategy matching the feature data set is retrieved from the preset feature-method database.

[0053] In this embodiment, various abnormal features and corresponding preprocessing strategies are pre-stored in the feature-method database. In practical applications, the preprocessing strategy may be a preprocessing scheme such as data cleaning and data normalization.

[0054] Then, the feature data set is preprocessed according to the target preprocessing strategy to obtain the data to be analyzed.

[0055] Through feature extraction, preprocessing and state analysis, an automated data analysis process is realized, which can accurately analyze the displacement data and determine the displacement state of the generator base, timely discover problems and facilitate subsequent corresponding measures, reduce errors caused by human intervention, and improve data analysis efficiency.

[0056] In one embodiment, based on the characteristic data set and the data to be analyzed, the displacement state of each generator base in the generator set is analyzed to obtain state analysis data, which specifically includes: The first step is to extract the target screening factors corresponding to the feature data set from the preset feature-factor comparison table.

[0057] In this embodiment, the feature-factor comparison table stores the corresponding relationship between each screening factor and the abnormal feature, thereby providing an effective data basis for the conversion process from the abnormal feature to the screening factor.

[0058] The second step is to retrieve the state analysis strategy that matches the target screening factor from the preset factor-method database.

[0059] In this embodiment, the matching relationship between each screening factor and the state analysis strategy is pre-stored in the factor-method database.

[0060] The third step is to analyze the displacement state of each generator base in the generator set based on the data to be analyzed according to the state analysis strategy to obtain the state analysis results.

[0061] It can be understood that the state analysis result can represent the displacement of the generator base, that is, the specific value of the displacement deviation.

[0062] The fourth step is to extract the displacement state matching the state analysis result from the preset result-state comparison table to obtain the state analysis data.

[0063] It can be understood that the result-state comparison table stores the correspondence between different state analysis results and displacement states. Specifically, multiple displacement states can be defined according to the numerical range of the state analysis results, and the correspondence between the state analysis results and the displacement states in different ranges can be established.

[0064] In this embodiment, the displacement state may represent the displacement degree and state of the generator base, and may specifically include multiple levels such as normal, slight displacement, and severe displacement.

[0065] Through the steps of factor acquisition, method matching and state analysis, the present invention can convert abnormal features into screening factors, thereby selecting a suitable analysis method and finally converting the analysis results into specific displacement states. Through factor acquisition and method matching, accurate analysis of the data to be analyzed is achieved, the possibility of misjudgment is reduced, and it is convenient for operation and maintenance personnel to understand and take corresponding measures.

[0066] In one embodiment, based on the feature data set, the data to be analyzed, and the status analysis data, a monitoring and early warning instruction is generated, specifically including: The first step is to retrieve the target prediction model that matches the feature data set from the preset feature-model database.

[0067] In this embodiment, the matching relationship between abnormal features and prediction models is pre-stored in the feature-model database.

[0068] In practical applications, the prediction model can be a deep learning model that is pre-trained with sample data, such as a neural network model.

[0069] The second step is to input the data to be analyzed into the target prediction model to obtain the displacement prediction data output by the target prediction model.

[0070] It is understandable that, since the target prediction model has been trained with sample data in advance, the actual application link can directly input the data to be analyzed into the target prediction model, thereby directly outputting the displacement prediction data through the target prediction model. In this embodiment, the displacement prediction data is similar to the above-mentioned state analysis results, and both are specific values ​​that can characterize the displacement status.

[0071] The third step is to determine the displacement prediction state corresponding to the displacement prediction data.

[0072] In this embodiment, in order to facilitate the staff to view, the present invention converts the displacement prediction data into corresponding displacement prediction states, such as normal, slight displacement, need to be processed and other states.

[0073] The fourth step is to input the displacement prediction data, displacement prediction status and status analysis data into the preset early warning database for data matching to obtain the early warning matching result.

[0074] In this embodiment, the early warning database pre-stores the displacement prediction data, displacement prediction status, and matching relationship between status analysis data and early warning matching results. The early warning matching results can represent different early warning levels, such as low-level warning, intermediate warning, high-level warning and other levels.

[0075] The fifth step is to extract the target instruction corresponding to the warning matching result from the preset result-instruction comparison table.

[0076] In this embodiment, the result-instruction comparison table pre-stores the corresponding relationship between different warning matching results and warning instructions, and the warning instruction is the specific warning content corresponding to the warning matching result.

[0077] Step 6: Use the target instructions as monitoring and early warning instructions.

[0078] It can be seen that the present invention can monitor the displacement of the generator base in real time, discover problems in time, and generate monitoring and early warning instructions according to the displacement prediction and status analysis, reminding the user to take corresponding measures, thereby ensuring the safe and stable operation of the generator set.

[0079] In one embodiment, after generating the monitoring and early warning instruction, the above method may further include: Based on the monitoring and early warning instructions, the position of each generator base in the generator set is adjusted.

[0080] In a specific implementation, based on the monitoring and early warning instructions, the position of each generator base in the generator set is adjusted, specifically including: The first step is to parse the monitoring and early warning instructions to obtain the instruction parsing package.

[0081] It can be understood that the instruction parsing package is a parsed data packet corresponding to the monitoring and early warning instruction after parsing, which includes the instruction content after the instruction is parsed and can be used for subsequent processing.

[0082] The second step is to perform factor matching on the parsed content in the instruction parsing package, obtain the matching factor corresponding to each parsed content in the instruction parsing package, and construct a matching factor set.

[0083] In this embodiment, the factor matching link is mainly used to simplify the parsed content in the instruction parsing package and determine the warning root cause, that is, the matching factor is mainly used to characterize the root cause information related to the parsed content.

[0084] The third step is to extract the device adjustment strategy corresponding to the matching factor set from the preset factor-strategy comparison table.

[0085] It can be understood that the factor-root cause comparison table pre-stores the corresponding relationship between the matching factor and the equipment adjustment strategy.

[0086] The fourth step is to adjust the position of each generator base in the generator set according to the equipment adjustment strategy.

[0087] After the adjustment, the position of each generator base in the generator set was restored to a near normal state, thereby alleviating the generator displacement problem in the generator set through timely intervention, which is conducive to the stable and safe operation of the generator set.

[0088] In one embodiment, after adjusting the position of each generator base in the generator set, the method may further include: The first step is to determine the second displacement data of each generator base in the generator set after adjustment.

[0089] It should be noted that the method for determining the second displacement data in this embodiment is substantially the same as the method for determining the first displacement data, and will not be repeated herein.

[0090] The second step is to determine the standard position data of each generator base in the generator set.

[0091] In this embodiment, the device attribute information of the displacement monitoring device on the adjusted generator base is first obtained, and the braking requirement information of the generator is obtained, and then the standard position data of the matching generator base is retrieved from the standard database based on the device attribute information and the braking requirement information.

[0092] It can be understood that the standard database pre-stores the corresponding relationship between the equipment attribute information and the braking requirement information and the standard position data of the generator base.

[0093] The third step is to compare the standard position data with the second displacement data to obtain position difference data.

[0094] It can be understood that the position difference data can represent the deviation between the second displacement data and the standard position data.

[0095] The fourth step is to calibrate the position of each generator base in the adjusted generator set based on the position difference data.

[0096] In this embodiment, based on the position difference data, the position of each generator base in the adjusted generator set is calibrated, specifically including: The position difference data is input into a preset correction analysis model for correction analysis, and based on the correction analysis results, the corresponding target calibration strategy is obtained from a preset result-calibration strategy comparison table; The position of the adjusted generator base is calibrated based on the target calibration strategy, and calibration position data is generated.

[0097] In a specific implementation, the position difference data is input into a preset correction analysis model for correction analysis, and based on the correction analysis result, the corresponding target calibration strategy is obtained from a preset result-calibration strategy comparison table, specifically including: The first step is to analyze the position difference data to obtain the position change data of the generator base at multiple preset position points after adjustment.

[0098] The second step is to extract features from the position change data and construct a key feature set.

[0099] The third step is to select the correction analysis model that matches the key feature set in the model database.

[0100] The fourth step is to obtain the format information of the correction analysis model, and convert the format of the position change data based on the format information to obtain format conversion data.

[0101] The position data after format conversion, i.e. format conversion data, is more in line with the data format requirements of the subsequent correction analysis model, thereby providing an effective data basis for inputting the data into the correction analysis model in the next step.

[0102] The fifth step is to input the format conversion data into the correction analysis model for correction analysis, and obtain the axial offset analysis results and radial offset analysis results of the generator base respectively.

[0103] In this embodiment, the axial offset analysis result includes the axial offset coefficients corresponding to the preset position points in each row on the generator base, and the radial offset analysis result includes the radial offset coefficients corresponding to the preset position points in each column on the generator base.

[0104] Specifically, the first The axial offset coefficient corresponding to the preset position point and the The radial offset coefficient corresponding to the preset position points can be expressed as follows: (1) in, Indicates the first The axial offset coefficient corresponding to the preset position point; Indicates the first The radial offset coefficients corresponding to the preset position points; Indicates the first The number of preset position points of the row; Indicates the first The number of preset position points; Indicates the first Line The measured displacement value corresponding to each preset position point; Indicates the first Line The standard position value corresponding to the preset position point; Indicates the first Line Deviation calculation weight coefficient corresponding to the preset position points; Indicates the first Line The displacement deviation adjustment coefficient corresponding to the preset position point; Indicates the first Ledi The measured displacement value at the preset position point; Indicates the first Ledi The standard position value corresponding to the preset position point; Indicates the first Ledi Deviation calculation weight coefficient corresponding to the preset position points; Indicates the first Ledi The displacement deviation adjustment coefficient corresponding to the preset position point.

[0105] The sixth step is to comprehensively analyze the axial offset analysis results and the radial offset analysis results to obtain the correction analysis results.

[0106] It can be understood that the correction analysis results are mainly used to characterize the post-processing results of the axial offset analysis results and the radial offset analysis results. Furthermore, the correction analysis results can be obtained after data preprocessing and data aggregation of the axial offset analysis results and the radial offset analysis results.

[0107] The seventh step is to obtain the corresponding target calibration strategy from the preset result-calibration strategy comparison table based on the correction analysis results.

[0108] In some embodiments, in order to ensure the effectiveness of the calibration process, the calibration results can be further verified after the position calibration. Specifically, the calibration position data can be compared and analyzed with the standard position data, and the comparison and analysis results that meet the preset threshold conditions are determined to be in a verified qualified state, thereby ending the calibration process of the generator base.

[0109] The monitoring method for the displacement of the generator in the wind turbine provided by the embodiment of the present invention monitors the displacement data of the generator base, analyzes the displacement state of the generator and generates a monitoring and early warning instruction, and then selects a suitable generator maintenance strategy according to the monitoring and early warning instruction, thereby ensuring the normal and stable operation of the wind turbine. At the same time, the present invention can not only accurately analyze the position change of the generator base, but also match the corresponding calibration strategy according to the correction analysis result, realize the calibration and optimization of the generator, improve the accuracy and efficiency of the calibration, ensure that the position of the generator base after adjustment meets the requirements, and further improve the performance and reliability of the generator.

[0110] Based on the same general inventive concept, the present invention also protects a monitoring system for the displacement of a generator in a wind turbine. The monitoring system for the displacement of a generator in a wind turbine provided by the present invention is described below. The monitoring system for the displacement of a generator in a wind turbine described below and the monitoring method for the displacement of a generator in a wind turbine described above can be referenced to each other.

[0111] like Figure 2 As shown, the monitoring system for generator displacement in a wind turbine provided by an embodiment of the present invention specifically includes: The data acquisition module 210 is used to determine the first displacement data of each generator base in the generator set.

[0112] The feature extraction module 220 is used to extract abnormal features in the first displacement data and establish a feature data set.

[0113] The preprocessing module 230 is used to preprocess the feature data set to obtain data to be analyzed.

[0114] The state analysis module 240 is used to analyze the displacement state of each generator base in the generator set based on the characteristic data set and the data to be analyzed to obtain state analysis data.

[0115] The monitoring and early warning module 250 is used to generate monitoring and early warning instructions based on the feature data set, the data to be analyzed and the status analysis data.

[0116] The monitoring system for the displacement of a generator in a wind turbine provided by an embodiment of the present invention can perform abnormality detection on the first displacement data of the generator base by means of feature extraction, preprocessing and state analysis through the cooperation of a feature extraction module, a preprocessing module, a state analysis module and a monitoring and early warning module, and can timely issue an abnormality warning by generating a monitoring and early warning instruction, thereby being able to accurately and reliably realize effective monitoring of the displacement of the generator in the wind turbine, solving the problem of insufficient accuracy and reliability of traditional displacement monitoring solutions, and ensuring safe and stable operation of the wind turbine.

[0117] Regarding the system in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated again here.

[0118] Figure 3 It is a schematic diagram of the structure of an electronic device provided by an embodiment of the present invention.

[0119] like Figure 3 As shown, the electronic device may include: a processor 310, a communication interface 320, a memory 330 and a communication bus 340, wherein the processor 310, the communication interface 320 and the memory 330 communicate with each other through the communication bus 340. The processor 310 may call the logic instructions in the memory 330 to execute the monitoring method of the displacement of the generator in the wind turbine provided by the above embodiments, the method comprising: determining the first displacement data of each generator base in the generator set; extracting the abnormal features in the first displacement data and establishing a feature data set; preprocessing the feature data set to obtain data to be analyzed; based on the feature data set and the data to be analyzed, analyzing the displacement state of each generator base in the generator set to obtain state analysis data; based on the feature data set, the data to be analyzed and the state analysis data, generating a monitoring and early warning instruction.

[0120] In addition, the logic instructions in the above-mentioned memory 330 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0121] On the other hand, the present invention also provides a computer program product, which includes a computer program. The computer program can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the monitoring method for the displacement of the generator in the wind turbine provided by the above-mentioned embodiments, the method including: determining the first displacement data of each generator base in the generator set; extracting abnormal features in the first displacement data and establishing a feature data set; preprocessing the feature data set to obtain data to be analyzed; based on the feature data set and the data to be analyzed, analyzing the displacement state of each generator base in the generator set to obtain state analysis data; based on the feature data set, the data to be analyzed and the state analysis data, generating a monitoring and early warning instruction.

[0122] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, it is implemented to execute the method for monitoring the displacement of a generator in a wind turbine provided in the above-mentioned embodiments, the method comprising: determining first displacement data of each generator base in the generator set; extracting abnormal features in the first displacement data and establishing a feature data set; preprocessing the feature data set to obtain data to be analyzed; based on the feature data set and the data to be analyzed, analyzing the displacement state of each generator base in the generator set to obtain state analysis data; and generating monitoring and early warning instructions based on the feature data set, the data to be analyzed and the state analysis data.

[0123] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0124] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0125] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for monitoring the displacement of a generator in a wind turbine, characterized in that: include: Determine first displacement data of each generator base in the generator set; Extract the abnormal features in the first displacement data and establish Feature dataset; Preprocessing the feature data set to obtain data to be analyzed; Based on the characteristic data set and the data to be analyzed, the displacement state of each generator base in the generator set is analyzed to obtain state analysis data; A monitoring and early warning instruction is generated based on the feature data set, the data to be analyzed, and the status analysis data.

2. The method for monitoring the displacement of a generator in a wind turbine according to claim 1, characterized in that: Determine the first displacement data of each generator base in the generator set, including: Determine the displacement monitoring equipment corresponding to each generator base in the generator set; Obtaining installation location information and device attribute information of each of the displacement monitoring devices; Establishing a monitoring device array based on the installation location information and the device attribute information; Obtaining the measured displacement value of the generator base collected by the monitoring device array; The displacement measured values ​​are summarized to obtain first displacement data of each generator base in the generator set.

3. The method for monitoring the displacement of a generator in a wind turbine according to claim 2, characterized in that: Determine the displacement monitoring equipment corresponding to each generator base in the generator set, including: Obtain demand information of generator sets; Extracting target requirements related to the generator base from the requirement information; Retrieving a target monitoring device matching the target demand from a preset demand-device database; The target monitoring device is used as a displacement monitoring device corresponding to each generator base in the generator set.

4. The method for monitoring the displacement of a generator in a wind turbine according to claim 1, characterized in that: Preprocessing the feature data set to obtain data to be analyzed includes: Retrieving a target preprocessing strategy matching the feature data set from a preset feature-method database; The characteristic data set is preprocessed according to the target preprocessing strategy to obtain data to be analyzed.

5. The method for monitoring the displacement of a generator in a wind turbine according to claim 1, characterized in that: Based on the characteristic data set and the data to be analyzed, the displacement state of each generator base in the generator set is analyzed to obtain state analysis data, including: Extracting a target screening factor corresponding to the feature data set from a preset feature-factor comparison table; Retrieving a state analysis strategy matching the target screening factor from a preset factor-method database; Based on the data to be analyzed, the displacement state of each generator base in the generator set is analyzed according to the state analysis strategy to obtain a state analysis result; The displacement state matching the state analysis result is extracted from a preset result-state comparison table to obtain state analysis data.

6. The method for monitoring the displacement of a generator in a wind turbine according to claim 1, characterized in that: Generating a monitoring and early warning instruction based on the feature data set, the data to be analyzed, and the status analysis data includes: Retrieving a target prediction model matching the feature data set from a preset feature-model database; Inputting the data to be analyzed into the target prediction model to obtain displacement prediction data output by the target prediction model; Determining a displacement prediction state corresponding to the displacement prediction data; Inputting the displacement prediction data, displacement prediction state and state analysis data into a preset early warning database for data matching to obtain an early warning matching result; Extracting the target instruction corresponding to the warning matching result from a preset result-instruction comparison table; The target instruction is used as a monitoring and early warning instruction.

7. The method for monitoring the displacement of a generator in a wind turbine according to claim 1, characterized in that: After generating the monitoring and early warning instruction, the method further includes: Based on the monitoring and early warning instructions, the position of each generator base in the generator set is adjusted.

8. The method for monitoring the displacement of a generator in a wind turbine according to claim 7, characterized in that: Based on the monitoring and early warning instructions, the position of each generator base in the generator set is adjusted, including: Parsing the monitoring and early warning instructions to obtain an instruction parsing package; Performing factor matching on the parsed content in the instruction parsing package to obtain a matching factor corresponding to each parsed content in the instruction parsing package, and constructing a matching factor set; Extracting a device adjustment strategy corresponding to the matching factor set from a preset factor-strategy comparison table; The position of each generator base in the generator set is adjusted according to the equipment adjustment strategy.

9. The method for monitoring the displacement of a generator in a wind turbine according to claim 7, characterized in that: After adjusting the position of each generator base in the generator set, the method further includes: Determine the second displacement data of each generator base in the generator set after adjustment; Determine the standard position data of each generator base in the generator set; Comparing the standard position data with the second displacement data to obtain position difference data; Based on the position difference data, the position of each generator base in the adjusted generator set is calibrated.

10. A monitoring system for generator displacement in a wind turbine, characterized in that: include: A data acquisition module, used to determine first displacement data of each generator base in the generator set; A feature extraction module, used to extract abnormal features in the first displacement data and establish a feature data set; A preprocessing module, used to preprocess the feature data set to obtain data to be analyzed; A state analysis module, used to analyze the displacement state of each generator base in the generator set based on the characteristic data set and the data to be analyzed, so as to obtain state analysis data; The monitoring and early warning module is used to generate monitoring and early warning instructions based on the feature data set, the data to be analyzed and the status analysis data.

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