A fan failure guidance system and a fan failure guidance method

Abstract

This application discloses a wind turbine fault guidance system and method, relating to the field of wind turbine operation and maintenance technology. It can automatically identify target wind turbines and associate them with equipment files, reducing manual query and matching time, shortening fault handling cycles, and generating preventative maintenance work orders to reduce the risk of sudden downtime. The system includes: a fault analysis module, used to determine the equipment file corresponding to the target wind turbine based on the pending fault work orders uploaded by the operation and maintenance terminal; query the fault guidance manual corresponding to the equipment file in the fault guidance database; send the fault guidance manual to the operation and maintenance terminal; add the pending fault work orders and work tickets and operation tickets generated during the fault handling process to the equipment file; and add the target wind turbine to the health assessment queue; a health assessment module, used to continuously select wind turbine identifiers from the health assessment queue, perform health assessments on the target wind turbines corresponding to the identified identifiers, and generate maintenance work orders based on the health assessment results.

Description

Technical Field

[0001] This application relates to the field of wind turbine operation and maintenance technology, and in particular to a wind turbine fault guidance system and a wind turbine fault guidance method. Background Technology

[0002] With the rapid development of the new energy industry, the large-scale construction of offshore wind farms is accelerating, and wind turbine equipment is showing a trend towards higher power and more complex structures. The types of equipment failures and the complexity of operation and maintenance are increasing exponentially. As the distance from shore to offshore wind farms continues to extend (some sites are over 100 kilometers away), coupled with the highly corrosive effects of the harsh marine environment, the failure rate of wind turbines is significantly higher than in onshore scenarios. This places higher demands on the speed of fault diagnosis response and the accuracy of maintenance guidance.

[0003] In related technologies, maintenance personnel carry paper-based fault code manuals, equipment maintenance guides, and other materials to the site for troubleshooting. However, this approach suffers from problems such as delayed data updates, susceptibility to weather-related damage or loss of manuals during maritime transport, and the need to consult multiple manuals for complex faults, resulting in low equipment handling efficiency and a high risk of misoperation. Summary of the Invention

[0004] In view of this, this application provides a wind turbine fault guidance system and a wind turbine fault guidance method. The main purpose is to solve the problems of outdated paper-based fault code manuals, equipment maintenance guides and other information, damage or loss of manuals due to weather conditions during maritime transportation, and the need to consult multiple manuals for complex faults, which leads to low equipment handling efficiency and high risk of misoperation.

[0005] According to the first aspect of this application, a wind turbine fault guidance system is provided, which includes: a fault analysis module, a file management module, and a health assessment module;

[0006] The fault analysis module is used to determine the target wind turbine based on the pending fault work order uploaded by the operation and maintenance terminal, initiate a data acquisition request to the file query module based on the wind turbine identifier corresponding to the target wind turbine, receive the equipment file sent by the file query module, query the fault guidance manual corresponding to the equipment file in the fault guidance library, send the fault guidance manual to the operation and maintenance terminal, add the pending fault work order and the work tickets and operation tickets generated during the fault handling process to the equipment file, and add the wind turbine identifier of the target wind turbine to the health assessment queue, waiting for the health assessment module to select the target wind turbine from the health assessment queue for health assessment.

[0007] The file management module is used to receive data acquisition requests initiated by the fault analysis module, query the corresponding equipment file according to the wind turbine identifier in the data acquisition request, and send the equipment file to the fault analysis module.

[0008] The health assessment module is used to continuously select wind turbine identifiers from the health assessment queue, perform health assessments on the target wind turbines corresponding to the wind turbine identifiers, and generate maintenance work orders based on the health assessment results.

[0009] According to a second aspect of this application, a wind turbine fault guidance method is provided, the method comprising:

[0010] The fault analysis module determines the target wind turbine based on the pending fault work order uploaded by the operation and maintenance terminal, and sends a data acquisition request to the file query module based on the wind turbine identifier corresponding to the target wind turbine.

[0011] The file management module receives the data acquisition request, queries the corresponding equipment file based on the wind turbine identifier in the data acquisition request, and sends the equipment file to the fault analysis module;

[0012] The fault analysis module receives the equipment file sent by the file query module, queries the fault guidance manual corresponding to the equipment file in the fault guidance library, sends the fault guidance manual to the operation and maintenance terminal, adds the pending fault work order and the work ticket and operation ticket generated during the fault handling process to the equipment file, and adds the wind turbine identifier of the target wind turbine to the health assessment queue.

[0013] The health assessment module continuously selects wind turbine identifiers from the health assessment queue, performs health assessments on the target wind turbines corresponding to the wind turbine identifiers, and generates maintenance work orders based on the health assessment results.

[0014] According to a third aspect of this application, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the method described in any of the first aspects above.

[0015] According to a fourth aspect of this application, a computer-readable storage medium is provided, on which a computer program is stored, wherein the computer program, when executed by a processor, implements the steps of the method described in any one of the first aspects above.

[0016] By employing the above technical solution, this application provides a wind turbine fault guidance system and method. The fault analysis module determines the target wind turbine based on the pending fault work order uploaded by the maintenance terminal, and initiates a data acquisition request to the file query module based on the wind turbine identifier corresponding to the target wind turbine. The file management module receives the data acquisition request and queries the corresponding equipment file based on the wind turbine identifier in the data acquisition request, then sends the equipment file to the fault analysis module. The fault analysis module receives the equipment file sent by the file query module, queries the fault guidance database for the corresponding fault guidance manual, sends the fault guidance manual to the maintenance terminal, and adds the pending fault work order and work tickets and operation tickets generated during the fault handling process to the equipment file. It also adds the wind turbine identifier of the target wind turbine to the health assessment queue. The health assessment module continuously selects wind turbine identifiers from the health assessment queue, performs health assessments on the target wind turbine corresponding to the wind turbine identifier, and generates a maintenance work order based on the health assessment results. This embodiment of the application automatically identifies the target wind turbine and associates it with the equipment file through the fault analysis module, reducing manual query and matching time and shortening the fault handling cycle. The health assessment module continuously monitors the wind turbine identifiers in the queue, predicts potential risks based on equipment status data (such as historical faults and maintenance records), generates preventive maintenance work orders, and reduces the risk of sudden failures and downtime.

[0017] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, the following are specific embodiments of this application. Attached Figure Description

[0018] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the scope of this application. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings:

[0019] Figure 1 This paper shows a schematic diagram of the structure of a wind turbine fault guidance system provided in an embodiment of this application;

[0020] Figure 2 This illustration shows a fault guidance manual maintenance page of a wind turbine fault guidance system provided in an embodiment of this application;

[0021] Figure 3 This illustration shows a schematic diagram of a fault guidance manual page of a wind turbine fault guidance system provided in an embodiment of this application;

[0022] Figure 4This illustration shows a quick search page of a wind turbine fault guidance system provided in an embodiment of this application;

[0023] Figure 5 This illustration shows a quick search page of a wind turbine fault guidance system provided in an embodiment of this application;

[0024] Figure 6 This illustration shows a quick search page of a wind turbine fault guidance system provided in an embodiment of this application;

[0025] Figure 7 This document shows a schematic diagram of a drawing link page for a wind turbine fault guidance system provided in an embodiment of this application;

[0026] Figure 8 This paper shows a schematic diagram of the homepage map of a wind turbine fault guidance system provided in an embodiment of this application;

[0027] Figure 9 This illustration shows a schematic diagram of the wind turbine query function on the homepage map of a wind turbine fault guidance system provided in an embodiment of this application;

[0028] Figure 10 This illustration shows a health trend dashboard of a wind turbine fault guidance system provided in an embodiment of this application.

[0029] Figure 11 This paper illustrates a schematic flowchart of a wind turbine fault guidance method provided in an embodiment of this application.

[0030] Figure 12 A schematic diagram of the device structure of a computer device provided in an embodiment of this application is shown. Detailed Implementation

[0031] The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain this application, and should not be construed as limiting this application.

[0032] Those skilled in the art will understand that, unless specifically stated otherwise, the singular forms “a,” “an,” “the,” and “the” used herein may also include the plural forms. It should be further understood that the word “comprising” as used in the specification of this application means the presence of the stated features, integers, steps, operations, elements, and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof.

[0033] It will be understood by those skilled in the art that, unless otherwise defined, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains. It should also be understood that terms such as those defined in general dictionaries should be understood to have the same meaning as in the context of the prior art, and should not be interpreted in an idealized or overly formal sense unless specifically defined as herein.

[0034] Those skilled in the art will understand that the term "terminal" as used herein includes both devices that are wireless signal receivers, devices that are wireless signal receivers without transmitting capability, and devices with receiving and transmitting hardware, having receiving and transmitting hardware capable of performing bidirectional communication on a bidirectional communication link. Such devices may include: cellular or other communication devices having a single-line display, a multi-line display, or a cellular or other communication device without a multi-line display; PCS (Personal Communications Service) that can combine voice, data processing, fax, and / or data communication capabilities; PDA (Personal Digital Assistant) that may include a radio frequency receiver, pager, Internet / intranet access, web browser, notepad, calendar, and / or GPS (Global Positioning System) receiver; and conventional laptop and / or handheld computers or other devices that have and / or include a radio frequency receiver. As used herein, "terminal" can be portable, transportable, installed in a means of transportation (air, sea, and / or land), or suitable and / or configured to operate locally, and / or in a distributed manner, operating in any other location on Earth and / or in space. "Terminal" as used herein can also be a communication terminal, an internet access terminal, or a music / video playback terminal, such as a PDA, a MID (Mobile Internet Device), and / or a mobile phone with music / video playback capabilities, or a smart TV, set-top box, etc.

[0035] This application provides a wind turbine fault guidance system. The system uses natural language processing technology to analyze historical fault work orders, wind turbine work tickets, and wind turbine standard fault code database data from the power production management system. It extracts semantic features related to fault analysis and handling to generate a structured fault guidance manual. Furthermore, the fault work orders, inspection work orders, defect work orders, early warning work orders, and other data from the power production management system record detailed processes and information such as equipment operation and maintenance details, covering operation time, operators, operation content, and equipment status changes. This data is a true record of the wind turbine operation and maintenance process, concealing key information such as equipment operating patterns and potential factors leading to faults. By analyzing this data, the frequency and focus of daily wind turbine maintenance operations can be understood, and changes in equipment operating status after different operations can be determined, providing fundamental data support for wind turbine health status analysis and assessment and fault prediction.

[0036] The current wind turbine fault guidance system adopts the Spring Cloud technology framework, leveraging its mature distributed system solution to achieve complete autonomy and controllability. The lightweight open-source web server nginx is introduced as a page resource forwarding service, implementing static and dynamic content separation: static resources are handled by nginx, while dynamic resources are handled by the backend server.

[0037] The system supports access via both PC and mobile app, with all functions synchronized and compatible between the two platforms. The app also features offline viewing capabilities to address situations where mobile phones have no signal while performing maintenance at sea.

[0038] like Figure 1 As shown in the embodiment of this application, a wind turbine fault guidance system includes: a fault analysis module 11, a file management module 12, and a health assessment module 13.

[0039] The fault analysis module 11 is used to determine the target wind turbine based on the pending fault work order uploaded by the operation and maintenance terminal, initiate a data acquisition request to the file query module 12 based on the wind turbine identifier corresponding to the target wind turbine, and receive the equipment file sent by the file query module 12. In the fault guidance library, it queries the fault guidance manual corresponding to the equipment file, sends the fault guidance manual to the operation and maintenance terminal, adds the pending fault work order and the work tickets and operation tickets generated during the fault handling process to the equipment file, and adds the wind turbine identifier of the target wind turbine to the health assessment queue, waiting for the health assessment module 13 to select the target wind turbine from the health assessment queue for health assessment.

[0040] The file management module 12 is used to receive data acquisition requests initiated by the fault analysis module 11, query the corresponding equipment file according to the wind turbine identifier in the data acquisition request, and send the equipment file to the fault analysis module 11.

[0041] The health assessment module 13 is used to continuously select wind turbine identifiers from the health assessment queue, perform health assessments on the target wind turbines corresponding to the wind turbine identifiers, and generate maintenance work orders based on the health assessment results.

[0042] Furthermore, in order to more effectively provide fault guidance, facilitate efficient knowledge retrieval and reasoning during fault diagnosis and troubleshooting, and enhance the system's intelligent support capability for fault handling, the wind turbine fault guidance system provided in this application embodiment also includes a construction module.

[0043] In this embodiment, the construction module is used to build a fault guidance library. The fault guidance library can consist of multiple fault guidance manuals. A complete structured fault guidance manual should at least include basic fault handling principles (including instructional videos on the safe operation of key equipment), fault codes, fault names, turbine series, applicable wind turbine models, fault descriptions, fault causes, maintenance materials (tool list, material preparation), safety measures, maintenance steps, maintenance instructions, and corresponding pictures, multimedia information, and drawings. The pictures, multimedia information, and drawings can vividly and intuitively assist in guiding fault diagnosis and troubleshooting. In this embodiment, the construction module generates structured fault guidance manuals by integrating historical data from fault work orders and wind turbine work tickets in the power production management system, ensuring that each manual is detailed and the steps are clear, facilitating maintenance personnel to quickly locate and efficiently resolve problems.

[0044] In actual operation, the module needs to obtain operation and maintenance data from the power production management system. It should be noted that this operation and maintenance data includes historical structured data of fault work orders and wind turbine work tickets from all power plants within the power production management system, as well as structured data from the fault code library. Fault work orders record the fault code, fault cause, faulty equipment name, wind turbine model, and handling method (maintenance steps). Wind turbine work tickets record the work location, work content, fault phenomenon description, fault cause, and handling method. The wind turbine standard fault code library records the equipment manufacturer name, model series, equipment model, fault code, fault name, fault category, and fault description. Furthermore, the module compares the operation and maintenance data (fault work orders, wind turbine work ticket data, and standard code library data) for the same fault to remove redundant information and correct erroneous entries. Simultaneously, the module standardizes the date and field formats in the operation and maintenance data, ensuring data consistency, for example, by ensuring the consistency of date formats.

[0045] Furthermore, the construction module utilizes NLP (Natural Language Processing) technology to parse the text content of the standardized operation and maintenance data. Specifically, the construction module needs to identify key entities in the text content, such as fault descriptions, fault names, fault causes, safety measures, and maintenance steps. Accurate entity identification provides the basic elements for subsequently determining the relationships between entities and constructing the knowledge graph structure. The relationships between these entities are crucial for the knowledge graph's ability to express knowledge and reason, such as determining that a fault was caused by a specific operation. Next, similar types of faults are grouped together. Further, target fields are extracted from the operation and maintenance data based on semantic similarity algorithms and causal reasoning algorithms. The extracted target fields cover various aspects related to faults, providing rich data support for constructing a comprehensive and accurate knowledge graph. Target fields include, but are not limited to, fault codes, fault names, wind turbine brands, turbine series, applicable wind turbine models, fault descriptions, fault causes, safety measures, tool lists, material preparation, maintenance steps, and maintenance instructions. The extraction logic for key fields is shown in Table 1 below.

[0046] Table 1 Key Field Extraction Logic

[0047]

[0048]

[0049] Furthermore, the construction module defines entity types and relationships between entities based on the extracted target fields. Entity types include faults, equipment, spare parts, operating procedures, safety specifications, etc. Relationships between entities include fault-cause, fault-applicable equipment, tool / spare part-applicable fault, cause-step-associated tool, etc. A knowledge graph model is then constructed based on entity types and relationships. This knowledge graph model, based on the defined entity types and relationships, completes the transformation from data to structured knowledge representation, enabling knowledge to be stored, retrieved, and reasoned about in graph form. Through this transformation, the knowledge graph not only achieves structured data storage but also improves the efficiency and accuracy of fault diagnosis. The complex relationships between entities are clearly displayed, providing precise decision support for maintenance personnel and further optimizing the entire process management of wind turbine operation and maintenance.

[0050] In this embodiment, the construction module provides an active learning mechanism. Specifically, when extracting target fields from the operation and maintenance data, the construction module determines the confidence level of the extraction results and compares the confidence level with a preset confidence threshold. If the confidence level is lower than the preset confidence threshold, a manual review process is generated, allowing reviewers to review the target fields based on the manual review process and upload the review results via the review terminal. Furthermore, the construction module also receives the review results uploaded by the reviewers, deletes or modifies the extracted targets based on the review results, and updates the model parameters to improve extraction accuracy. Through continuous iterative optimization, the system gradually reduces manual intervention, achieving efficient and accurate automated operation and maintenance, ensuring stable and reliable wind turbine operation.

[0051] In this embodiment, the construction module also provides a version control function. Specifically, when the construction module detects that the power production management system has received new work order data, it identifies the fault name corresponding to the work order data, as well as the fault cause and maintenance steps corresponding to the fault name, and queries the fault guidance database for the fault cause set and maintenance step set corresponding to the fault name. If there is no fault cause in the fault cause set, or no maintenance step in the maintenance step set, the fault guidance database is updated, adding the fault cause to the fault cause set or adding the maintenance step to the maintenance step set. Otherwise, there is no need to update the fault guidance database. Through version control, the system can update the fault guidance database in a timely manner, ensuring that maintenance personnel obtain the latest fault handling solutions, further improving the efficiency and reliability of wind turbine operation and maintenance.

[0052] In addition, the building module provides a feedback mechanism that allows users to report inaccurate or missing information, and updates the model and database accordingly to ensure the system's accuracy and usability. Specifically, the building module receives feedback reports uploaded by operations and maintenance personnel and updates the fault guidance library based on the entities and relationships between them recorded in the reports. Furthermore, such as... Figure 2 As shown, administrators can manually create and maintain fault guidance manuals through the fault guidance data maintenance application. The fault code, fault description, turbine brand, model series, and applicable turbine model are directly obtained from the fault code library of the power production management system. Material maintenance (tool list, material preparation) data is selected from the tool management and material management systems of the power production management system, thus ensuring the accuracy, completeness, consistency, and timeliness of the data. Extended data entry includes form text information such as fault causes, fault repair steps, repair materials, and repair instructions, and allows uploading images, multimedia files, and drawings as attachments. The module responds to maintenance requests uploaded by the review terminal. Through manual review process control, it ensures that all newly added or updated manual information is reviewed before updating the fault guidance library based on the entities and relationships between them carried in the maintenance request.

[0053] In this embodiment, the fault analysis module 11 queries the fault guidance manual corresponding to the device file in the fault guidance database and sends the fault guidance manual to the maintenance terminal. It should be noted that maintenance personnel can upload a pending fault work order through the maintenance terminal before actual operation. The fault analysis module 11 queries the corresponding fault guidance manual based on the fault information in the pending fault work order and returns it to the maintenance terminal, such as... Figure 3 As shown, maintenance personnel can view fault descriptions, causes, and handling steps according to the fault guidance manual. They can also view the corresponding wind turbine equipment drawings for the specific wind turbine model through the terminal's drawing viewing function, facilitating maintenance of the target wind turbine. Furthermore, the fault analysis module 11 adds pending fault work orders and work tickets and operation tickets generated during fault handling to the equipment file, and adds the target wind turbine's wind turbine identifier to the health assessment queue, awaiting selection of the target wind turbine by the health assessment module 13 for health assessment. In this embodiment, the fault analysis module 11 is the core application function of the system. On-site maintenance personnel can view the fault manual library by model series and fault type through the APP and PC. Figures 4 to 6 As shown, the system also provides users with a quick search function. The system features an interactive search function that utilizes a search dialog box and search methods such as fault codes and keywords. It uniquely identifies fault guidance based on fault codes and model series, and then quickly locates the required troubleshooting manual in the fault guidance database. When users view fault guidance, such as... Figure 7 As shown, it can quickly link to complete drawings of all parts of the wind turbine currently experiencing a fault, improving the efficiency of viewing manual drawings and handling on-site faults. The app retrieves the fault handler, faulty equipment name, and fault code from unprocessed fault work orders in the power production management system. It then searches for the latitude and longitude, wind turbine manufacturer, and wind turbine model in the physical equipment table of the power production management system by faulty equipment name. The app compares the wind turbine's latitude and longitude in the physical equipment table with the user's current geographic location. Once a match is found, it retrieves the corresponding fault guidance data from the fault guidance database based on the fault code of the fault work order, the wind turbine manufacturer, and the wind turbine model of the physical equipment, and directly pushes it to the user, eliminating the need for the user to search manually.

[0054] In this embodiment, the wind turbine and its associated file are linked, achieving "one turbine, one file," allowing users to view all relevant documents, data, maintenance records, etc., of the wind turbines already in operation. For example... Figure 8 and Figure 9As shown, the document management module 12 marks the wind turbine icons of operational wind turbines on the homepage map according to their corresponding real-time geographical locations. When a wind turbine icon on the homepage map is clicked, the corresponding equipment details page is displayed. The details page displays the operation and maintenance information and equipment drawings of the wind turbine corresponding to the icon. The operation and maintenance information includes, but is not limited to, wind turbine equipment technical parameters, recent work, unit lists, unit test lists, unit pile foundation lists, marine engineering (underwater) lists, work records, work statistics, and fault statistics. The fault statistics include fault work order data based on the power production management system, providing multi-dimensional statistics on the current wind turbine's fault-related situations, and outputting visual charts and health assessment results. It should be noted that the document management module 12 also provides an online document viewing function, allowing on-site operation and maintenance personnel to view ledger information, drawings, reports, and other documents online. Furthermore, due to the high rate of drawing reuse, to avoid duplicate data uploads, the document management module 12 also provides a unified upload and management portal for all wind turbine equipment drawings, which can be accessed and viewed in the equipment archives and fault guidance sections.

[0055] In this embodiment, the health assessment module 13 selects a fan identifier from the health assessment queue, sends a data acquisition request to the file management module 12 based on the fan identifier, and receives work order data sent by the file management module 12. The work order data includes fault work orders, inspection work orders, defect work orders, early warning work orders, operation tickets, and work tickets. Fault work orders record the fault occurrence time, fault end time, equipment name, fault code, and handling method (e.g., component replacement). Key fields include fault type, impact level, and maintenance personnel feedback. Inspection work orders contain regular / temporary inspection records, such as equipment appearance inspection results, vibration test data, and infrared temperature images. Key fields include anomaly markers, detection values, and recommended measures. Defect work orders record non-fault equipment hazards (e.g., loose bolts, coating peeling) and handling priority (high / medium / low). Early warning work orders record automatic alarms from the SCADA system (e.g., temperature exceeding limits, abnormal vibration), including threshold trigger records. Operation tickets record equipment start / stop, operation steps, executor, and timestamp. The work order records the safety measures, tool list, and acceptance results for the maintenance task. Furthermore, to quantitatively predict the health status of the wind turbine, a health assessment model needs to be constructed using a hybrid neural network based on historical work order data. Specifically, the health assessment module 13 needs to align the work order timestamps in the work order data with the SCADA sensor data by device ID to generate a unified time series. For example, for a gearbox failure work order dated 2024-05-16 12:33, the vibration and oil temperature data for the hour before and after that time point should be associated. Further, the health assessment module 13 uses a BERT+BiLSTM-CRF model to extract work order data features and associates the operations in the work order data with the maintenance effects of similar historical failures to construct a knowledge graph. For example, the "filter replacement" operation in the work order is associated with the maintenance effects of similar historical failures to quantify its contribution to the health status. Furthermore, the health assessment module 13 extracts temporal features from the SCADA sensor data. The extracted temporal features are statistical quantities (mean, variance, and FFT spectral peaks) of the SCADA sensor data (vibration, temperature, and power). The health assessment module 13 further employs an LSTM network to process the SCADA temporal features and uses a Sentence-BERT model to encode the work order data features into 768-dimensional text vectors. It also uses a CNN network to process the text vectors, fusing the outputs of the LSTM and CNN networks through a fully connected layer to generate a health feature vector. Based on this health feature vector, it predicts the health score of the wind turbine equipment and generates a health assessment result based on the health score.

[0056] Furthermore, the health assessment module 13 also needs to train and optimize the constructed health assessment model. Specifically, the health assessment module 13 needs to define labels, that is, to define the current health status in reverse based on whether a failure has occurred in the next 30 days (e.g., no failure = 100 points, serious failure = 0 points). It also needs to increase the sample weight of devices that have frequently issued warnings recently (e.g., warning times in the past 7 days × 2). Next, the health assessment module 13 uses LSTM layers pre-trained on a general equipment failure dataset (e.g., NASA turbofan degradation data) to accelerate convergence and adds gradient penalty (WGAN-GP) to improve the model's robustness to noisy work order data (e.g., missing fields). In addition, as... Figure 10 As shown, the health assessment module 13 also provides a health trend dashboard, which displays the wind turbine's real-time health score (in a dashboard format) and historical change curves. The health trend dashboard also links to work order event markers (such as the score rising from 40 to 75 after a maintenance), and displays key factors affecting the health score based on health score analysis.

[0057] In this embodiment, the health assessment module 13 compares the health score in the health assessment result with a first scoring threshold and a second scoring threshold. When the health assessment result is lower than the first scoring threshold but higher than or equal to the second scoring threshold, an inspection work order is generated, highlighting key inspection items. When the health assessment result is lower than the second scoring threshold, a defect work order is generated, requiring processing within 48 hours. It should be noted that the first scoring threshold can be set to 70, and the second scoring threshold can be set to 50. Furthermore, these thresholds can be adjusted according to actual needs. This application does not specifically limit the values ​​of the first and second scoring thresholds. Further, the health assessment module 13 also recommends maintenance time windows based on reinforcement learning (such as DQN) algorithms, considering spare parts inventory, personnel scheduling, and weather forecasts. It then uses these maintenance time windows to optimize the execution time of inspection work orders or defect work orders. For example, it avoids the high wind period of the next three days and selects a low wind speed day for blade maintenance.

[0058] The system provided in this application embodiment determines the target wind turbine based on the pending fault work order uploaded by the maintenance terminal. Based on the wind turbine identifier corresponding to the target wind turbine, it initiates a data acquisition request to the file query module. The file management module receives the data acquisition request and queries the corresponding equipment file based on the wind turbine identifier in the data acquisition request, then sends the equipment file to the fault analysis module. The fault analysis module receives the equipment file sent by the file query module, queries the fault guidance manual corresponding to the equipment file in the fault guidance database, sends the fault guidance manual to the maintenance terminal, adds the pending fault work order and the work tickets and operation tickets generated during the fault handling process to the equipment file, and adds the wind turbine identifier of the target wind turbine to the health assessment queue. The health assessment module continuously selects wind turbine identifiers from the health assessment queue, performs health assessments on the target wind turbine corresponding to the wind turbine identifier, and generates a maintenance work order based on the health assessment results. This application embodiment automatically identifies the target wind turbine and associates it with the equipment file through the fault analysis module, reducing manual query and matching time and shortening the fault handling cycle. The health assessment module continuously monitors the wind turbine identifiers in the queue, predicts potential risks based on equipment status data (such as historical faults and maintenance records), generates preventive maintenance work orders, and reduces the risk of sudden failures and downtime.

[0059] This application provides a method for guiding wind turbine fault diagnosis, such as... Figure 11 As shown, the method includes:

[0060] 201. The fault analysis module determines the target wind turbine based on the pending fault work order uploaded by the operation and maintenance terminal, and sends a data acquisition request to the file query module based on the wind turbine identifier corresponding to the target wind turbine.

[0061] 202. The file management module receives the data acquisition request, queries the corresponding equipment file based on the fan identifier in the data acquisition request, and sends the equipment file to the fault analysis module.

[0062] 203. The fault analysis module receives the equipment file sent by the file query module, queries the fault guidance manual corresponding to the equipment file in the fault guidance library, sends the fault guidance manual to the operation and maintenance terminal, adds the work order to be processed and the work ticket and operation ticket generated during the fault processing to the equipment file, and adds the wind turbine identifier of the target wind turbine to the health assessment queue.

[0063] 204. The health assessment module continuously selects wind turbine identifiers from the health assessment queue, performs health assessments on the target wind turbines corresponding to the wind turbine identifiers, and generates maintenance work orders based on the health assessment results.

[0064] The method provided in this application embodiment involves a fault analysis module determining the target wind turbine based on the pending fault work order uploaded by the maintenance terminal, and initiating a data acquisition request to the file query module based on the wind turbine identifier corresponding to the target wind turbine. The file management module receives the data acquisition request and queries the corresponding equipment file based on the wind turbine identifier in the data acquisition request, then sends the equipment file to the fault analysis module. The fault analysis module receives the equipment file sent by the file query module, queries the fault guidance library for the corresponding fault guidance manual for the equipment file, sends the fault guidance manual to the maintenance terminal, adds the pending fault work order and the work tickets and operation tickets generated during the fault handling process to the equipment file, and adds the wind turbine identifier of the target wind turbine to the health assessment queue. The health assessment module continuously selects wind turbine identifiers from the health assessment queue, performs health assessments on the target wind turbine corresponding to the wind turbine identifier, and generates a maintenance work order based on the health assessment results. This application embodiment automatically identifies the target wind turbine and associates it with the equipment file through the fault analysis module, reducing manual query and matching time and shortening the fault handling cycle. The health assessment module continuously monitors the wind turbine identifiers in the queue, predicts potential risks based on equipment status data (such as historical faults and maintenance records), generates preventive maintenance work orders, and reduces the risk of sudden failures and downtime.

[0065] To address the aforementioned technical problems, embodiments of the present invention also provide a computer device. Please refer to [link / reference needed]. Figure 12 , Figure 12 This is a basic structural block diagram of the computer device in this embodiment.

[0066] like Figure 12 The diagram shows the internal structure of a computer device. The computer device includes a processor, non-volatile storage medium, memory, and a network interface connected via a system bus. The non-volatile storage medium stores the operating system, database, and computer-readable instructions. The database may store control information sequences. When the computer-readable instructions are executed by the processor, they enable the processor to implement a data relationship reconstruction method. The processor provides computing and control capabilities, supporting the operation of the entire computer device. The memory stores computer-readable instructions, which, when executed by the processor, enable the processor to implement a data relationship reconstruction method. The network interface of the computer device is used for communication with a terminal. Those skilled in the art will understand that… Figure 4 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0067] In this embodiment, the memory stores the program code and various types of data required to execute the above modules. The network interface is used for data transmission between the user terminal and the server. In this embodiment, the memory stores the program code and data required to execute all sub-modules in the data relationship reconstruction device, and the server can call the server's program code and data to execute the functions of all sub-modules.

[0068] The present invention also provides a storage medium storing computer-readable instructions, which, when executed by one or more processors, cause the one or more processors to perform the steps of the data relationship reconstruction method of any of the above embodiments.

[0069] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. This computer program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the methods described above. The aforementioned storage medium can be a non-volatile storage medium such as a magnetic disk, optical disk, or read-only memory (ROM), or random access memory (RAM).

[0070] The present invention also provides a storage medium storing computer-readable instructions, which, when executed by one or more processors, cause the one or more processors to perform the steps of the data relationship reconstruction method of any of the above embodiments.

[0071] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. This computer program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the methods described above. The aforementioned storage medium can be a non-volatile storage medium such as a magnetic disk, optical disk, or read-only memory (ROM), or random access memory (RAM).

[0072] Those skilled in the art will understand that the steps, measures, and solutions in the various operations, methods, and processes discussed in this application can be alternated, modified, combined, or deleted. Furthermore, other steps, measures, and solutions in the various operations, methods, and processes discussed in this application can also be alternated, modified, rearranged, decomposed, combined, or deleted. Furthermore, steps, measures, and solutions in the prior art that are similar to those disclosed in this application can also be alternated, modified, rearranged, decomposed, combined, or deleted.

[0073] The above description is only a partial embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A wind turbine fault guidance system, characterized in that, The system includes: a fault analysis module, a file management module, a health assessment module, and a construction module; The fault analysis module is used to determine the target wind turbine based on the pending fault work order uploaded by the operation and maintenance terminal, initiate a data acquisition request to the file management module based on the wind turbine identifier corresponding to the target wind turbine, and receive the equipment file sent by the file management module. It then queries the fault guidance library for the fault guidance manual corresponding to the equipment file, sends the fault guidance manual to the operation and maintenance terminal, adds the pending fault work order and the work tickets and operation tickets generated during the fault handling process to the equipment file, and adds the wind turbine identifier of the target wind turbine to the health assessment queue, waiting for the health assessment module to select the target wind turbine from the health assessment queue for health assessment. The operation and maintenance terminal has an offline viewing function. The fault guidance library is used to compose multiple fault guidance manuals. A complete structured fault guidance manual includes at least the basic principles of fault handling, fault code, fault name, model series, applicable wind turbine model, fault description, fault cause, maintenance materials, safety measures, maintenance steps, maintenance instructions, and corresponding pictures, multimedia information, and drawings. The basic principles of fault handling include basic principles of handling and safety operation teaching videos for key equipment. The file management module is used to receive data acquisition requests initiated by the fault analysis module, query the corresponding equipment file according to the wind turbine identifier in the data acquisition request, and send the equipment file to the fault analysis module. The health assessment module is used to continuously select wind turbine identifiers from the health assessment queue, perform health assessments on the target wind turbines corresponding to the wind turbine identifiers, and generate maintenance work orders based on the health assessment results. The construction module is used to identify the fault name corresponding to the work order data, the fault cause and maintenance steps corresponding to the fault name, when the power production management system detects that a new work order data has been received, and to query the fault cause set and maintenance step set corresponding to the fault name in the fault guidance database. If the fault cause does not exist in the fault cause set or the maintenance step does not exist in the maintenance step set, the fault guidance database is updated, and the fault cause is added to the fault cause set or the maintenance step is added to the maintenance step set.

2. The system according to claim 1, characterized in that, The construction module is used to obtain operation and maintenance data from the power production management system, and to delete redundant information and correct erroneous entries in the operation and maintenance data by comparing the operation and maintenance data of the same fault, and to unify the date and field formats in the operation and maintenance data to complete data standardization. The operation and maintenance data includes, but is not limited to, structured data such as fault work orders, wind turbine generator work tickets and wind turbine standard fault code library. The construction module is also used to parse the standardized operation and maintenance data using natural language processing (NLP) technology, extract target fields from the operation and maintenance data based on semantic similarity algorithms and causal reasoning algorithms, define entity types and relationships between entities based on the extracted target fields, and construct a knowledge graph model based on the entity types and relationships between entities. The target fields include, but are not limited to, fault codes, fault names, wind turbine brands, turbine series, applicable wind turbine models, fault descriptions, fault causes, safety measures, tool lists, material preparation, maintenance steps, and maintenance instructions.

3. The system according to claim 2, characterized in that, The construction module is used to determine the confidence level of the extraction result when extracting the target field from the operation and maintenance data. If the confidence level is lower than the preset confidence threshold, a manual review process is generated so that the reviewers can review the target field based on the manual review process and upload the review result based on the review terminal. The construction module is used to receive the review results uploaded by the reviewers and delete or modify the target field according to the review results.

4. The system according to claim 3, characterized in that, The construction module is also used to receive feedback reports uploaded by operation and maintenance personnel, update the fault guidance library according to the entities and relationships between entities recorded in the feedback reports, and update the fault guidance library according to the entities and relationships between entities carried in the maintenance requests uploaded by the auditing terminal.

5. The system according to claim 1, characterized in that, The file management module is also used to mark the wind turbine icons of the wind turbines that have been put into operation on the homepage map according to their corresponding real-time geographical locations, and to display the equipment details page corresponding to the wind turbine icon when the wind turbine icon in the homepage map is clicked. The details page is used to display the operation and maintenance information and equipment drawings of the wind turbine corresponding to the wind turbine icon. The operation and maintenance information includes, but is not limited to, wind turbine equipment technical parameters, recent work, unit list, unit test list, unit pile foundation list, marine engineering list, work records, work statistics, and fault statistics. The fault statistics include visual charts and health assessment results.

6. The system according to claim 1, characterized in that, The health assessment module is used to select a wind turbine identifier from the health assessment queue, send a data acquisition request to the file management module based on the wind turbine identifier, and receive work order data sent by the data acquisition request. The work order data includes fault work orders, inspection work orders, defect work orders, early warning work orders, operation tickets, and work tickets. The health assessment module is used to align the work order timestamps in the work order data with the SCADA sensor data by device ID to generate a unified time series, and to extract key entities from the work order data using the BERT+BiLSTM-CRF model, and to construct a knowledge graph to associate the operations in the work order data with the maintenance effects of similar historical faults. The health assessment module is further configured to extract time-series features from the SCADA sensor data, process the SCADA time-series features using an LSTM network, encode the work order data into text vectors using a Sentence-BERT model, process the text vectors using a CNN network, fuse the outputs of the LSTM network and the CNN network through a fully connected layer to generate a health feature vector, predict the health score of the wind turbine equipment based on the health feature vector, and generate the health assessment result based on the health score.

7. The system according to claim 6, characterized in that, The health assessment module is used to compare the health score in the health assessment result with a first scoring threshold and a second scoring threshold respectively. When the health assessment result is lower than the first scoring threshold but higher than or equal to the second scoring threshold, an inspection work order is generated. When the health assessment result is lower than the second scoring threshold, a defect work order is generated. The health assessment module is also used to determine the maintenance time window based on the reinforcement learning algorithm, spare parts inventory, personnel scheduling and weather forecast, and to optimize the execution time of the inspection work order or the defect work order using the maintenance time window.

8. A method for guiding wind turbine faults in a wind turbine fault guidance system, characterized in that, include: The fault analysis module determines the target wind turbine based on the pending fault work order uploaded by the operation and maintenance terminal, and sends a data acquisition request to the file management module based on the wind turbine identifier corresponding to the target wind turbine. The file management module receives the data acquisition request, queries the corresponding equipment file based on the wind turbine identifier in the data acquisition request, and sends the equipment file to the fault analysis module; The fault analysis module receives the equipment file sent by the file management module, queries the fault guidance manual corresponding to the equipment file in the fault guidance library, sends the fault guidance manual to the operation and maintenance terminal, adds the pending fault work order and the work ticket and operation ticket generated during the fault handling process to the equipment file, and adds the wind turbine identifier of the target wind turbine to the health assessment queue; the operation and maintenance terminal has an offline viewing function; The fault guidance library is used to form multiple fault guidance manuals. A complete structured fault guidance manual includes at least the basic principles of fault handling, fault code, fault name, machine series, applicable fan model, fault description, fault cause, maintenance materials, safety measures, maintenance steps, maintenance instructions, and corresponding pictures, multimedia information and drawings. The basic principles of fault handling include basic principles of handling and safety operation teaching videos for key equipment. The health assessment module continuously selects wind turbine identifiers from the health assessment queue, performs health assessments on the target wind turbines corresponding to the wind turbine identifiers, and generates maintenance work orders based on the health assessment results. When the construction module detects that the power production management system has received new work order data, it identifies the fault name corresponding to the work order data, as well as the fault cause and maintenance steps corresponding to the fault name. It also queries the fault guidance database for the fault cause set and maintenance step set corresponding to the fault name. If the fault cause does not exist in the fault cause set or the maintenance step does not exist in the maintenance step set, the fault guidance database is updated, and the fault cause is added to the fault cause set or the maintenance step is added to the maintenance step set.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method of claim 8.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method of claim 8.

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