Index statistical method and system for fan annual regular inspection quality analysis

Abstract

The invention belongs to the technical field of wind power generation, and particularly relates to an index statistical method and system for annual regular inspection quality analysis of a fan, and the method comprises the steps: obtaining annual operation data of the fan; fault operation duration and fault-free operation duration are calculated according to the annual operation data of the draught fan, and the fault occurrence frequency is counted; and generating a fan regular inspection quality analysis report based on the fault operation duration, the fault-free operation duration and the fault occurrence frequency. According to the method, the maintenance quality and the performance state of the wind power equipment can be evaluated more accurately, and a scientific basis is provided for regular inspection and preventive maintenance of a fan by quantifying the fault operation duration, the fault-free operation duration and the fault frequency. Therefore, the reliability of the wind turbine generator is improved, the non-planned downtime is reduced, the operation and maintenance cost can be effectively reduced, the service life of a fan is prolonged, and the economic benefit and the operation efficiency of a wind power plant are improved on the whole.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of wind power generation, and particularly relates to an index statistical method and system for annual inspection quality analysis of a wind turbine. BACKGROUND

[0002] In the field of wind power generation, regular annual inspection of wind turbines is a key link to ensure their long-term stable operation and improve safety and efficiency. Traditionally, the quality analysis of wind turbine annual inspection highly depends on the experience and intuition of engineers, and this process involves a lot of manual data collection, sorting and analysis work. Although manual analysis can capture the operating conditions of the wind turbine to some extent, this method has significant limitations, mainly in the following aspects: first, manual on-site inspection often fails to obtain all the key parameters of wind turbine operation in real time and comprehensively, which may lead to biased analysis results, thus there is a problem of incompleteness of data collection, second, manually recorded data may have errors, such as inaccurate recording or omission of important information, which affects the accuracy of subsequent analysis, resulting in uncontrollable data quality. Differences in experience and personal judgment of engineers may affect the assessment of the health status of the wind turbine, leading to poor consistency of analysis results, and there is a problem of subjectivity in data analysis. In addition, the traditional method focuses on post-analysis and lacks the ability to provide early warning for future possible faults, which limits the effectiveness of preventive maintenance and results in a lack of fault prediction capability. Manual preparation of maintenance reports is not only time-consuming but also prone to errors, which is not conducive to efficient management and decision-making, and there is a problem of low efficiency in report generation.

[0003] In summary, the existing technology has problems such as low efficiency, insufficient accuracy and lack of foresight in the quality analysis of wind turbine annual inspection, and there is an urgent need for a more systematic and intelligent method and technology to overcome these shortcomings. SUMMARY

[0004] The purpose of the present application is to provide an index statistical method and system for quality analysis of wind turbine annual inspection to solve the problems of low efficiency, insufficient accuracy and lack of foresight in the quality analysis of wind turbine annual inspection in the prior art.

[0005] In order to achieve the above-mentioned purpose, the technical scheme adopted by the present application is as follows: In a first aspect, the present application provides an index statistical method for quality analysis of wind turbine annual inspection, comprising: obtaining wind turbine annual operation data; calculating fault operation duration and fault-free operation duration according to the wind turbine annual operation data, and counting fault occurrence frequency; generating a wind turbine inspection quality analysis report based on the fault operation duration, the fault-free operation duration and the fault occurrence frequency.

[0006] Preferably, the obtaining the annual operation data of the fan specifically comprises: obtaining the number of annual inspection work tickets of the fan, the operation execution time of each annual inspection work ticket, the reemployment time and the fault data.

[0007] Preferably, the fault operation duration and the fault-free operation duration are calculated according to the operation execution time and the reemployment time of each annual inspection work ticket, and the fault occurrence frequency is counted.

[0008] Preferably, the fault operation duration and the fault-free operation duration are calculated according to the operation execution time and the reemployment time of each annual inspection work ticket, and the fault occurrence frequency is counted, specifically comprising: taking the safety measure execution time of the first work ticket as the starting point and the reemployment time of the last work ticket as the ending point to construct an annual inspection time interval; taking the first 1 / 3 month before the regular inspection to the first 1 / 3 month after the regular inspection as a comparison time window; calculating the fault operation duration according to the operation execution time and the reemployment time of each annual inspection work ticket; calculating the fault-free operation duration according to the number of annual inspection work tickets and the fault operation duration; counting the fault frequency in the time window according to the operation execution time of each annual inspection work ticket and the comparison time window.

[0009] Preferably, the fan regular inspection quality analysis report is generated according to the fault operation duration, the fault-free operation duration and the fault frequency.

[0010] In the second aspect of the present application, an index statistical system for annual regular inspection quality analysis of a fan is provided, characterized in that it comprises: a data acquisition unit for acquiring annual operation data of the fan; a calculation unit for calculating fault operation duration and fault-free operation duration according to the annual operation data of the fan and counting fault occurrence frequency; an analysis and display unit for generating a fan regular inspection quality analysis report based on the duration and occurrence frequency of the annual operation data of the fan.

[0011] Preferably, the calculation unit comprises: a time calculation module for calculating fault operation duration and fault-free operation duration according to the annual operation data of the fan; a fault statistical module for counting fault occurrence frequency.

[0012] Preferably, the data acquisition unit acquires the annual operation data of the fan specifically by: obtaining the number of annual inspection work tickets of the fan, the operation execution time of each annual inspection work ticket, the reemployment time and the fault data.

[0013] In a third aspect, the present application provides an electronic device, comprising a processor and a memory, wherein the processor is configured to execute a computer program stored in the memory to implement the index statistical method for annual inspection quality analysis of a fan according to any one of the preceding aspects.

[0014] In a fourth aspect, the present application provides a computer readable storage medium, wherein the computer readable storage medium stores at least one instruction, and the at least one instruction is configured to be executed by a processor to implement the index statistical method for annual inspection quality analysis of a fan according to any one of the preceding aspects.

[0015] Compared with the prior art, the present application has the following advantages: The present application provides an index statistical method for annual inspection quality analysis of a fan, which aims to evaluate the quality and efficiency of fan inspection work by deeply mining the operation data of the fan within a year. In terms of technology, the method first extracts the annual operation data of the fan from the data management system of the wind farm, which includes but is not limited to the working state, maintenance records, fault information, etc. of the fan; in principle, the operation data is converted into quantifiable indexes such as fault operation time, fault-free operation time and fault frequency by using data analysis and statistical principles; in terms of effect, the method generates a fan inspection quality analysis report to intuitively display the operation status and maintenance effect of the fan, helping the wind farm manager to find problems in the maintenance work in a timely manner, optimize the maintenance strategy, and improve the availability and power generation efficiency of the fan. In other embodiments, machine learning algorithms can be introduced to automatically identify the operation mode and fault trend of the fan, further improving the accuracy and predictability of the inspection quality analysis. BRIEF DESCRIPTION OF DRAWINGS

[0016] The accompanying drawings, which form a part of the specification, are included to provide a further understanding of the application and are incorporated herein in conjunction with the description of the application. The embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation of the present application. In the drawings: Figure 1 The method flowchart of the embodiment of the present application is shown in the figure; Figure 2 The system block diagram of the embodiment of the present application is shown in the figure; Figure 3 The structural block diagram of an electronic device according to an embodiment of the present application is shown in the figure. DETAILED DESCRIPTION

[0017] The present application will be described in detail below with reference to the accompanying drawings and in conjunction with the embodiments. It should be noted that the embodiments and features in the embodiments of the present application can be combined with each other without conflict.

[0018] The following detailed description is exemplary in nature and is intended to provide further description of the application. All technical terms employed herein are intended to have the same meaning as commonly understood by one of ordinary skill in the art to which the application pertains unless otherwise defined. The terminology used in the present application is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments in accordance with the present application.

[0019] Referring to Figure 1 The present application discloses an index statistical method for annual inspection quality analysis of wind turbines, comprising: S1: obtaining annual operation data of the wind turbine; S2: calculating the fault operation duration and the fault-free operation duration according to the annual operation data of the wind turbine, and counting the fault occurrence frequency; S3: generating a wind turbine inspection quality analysis report based on the fault operation duration, the fault-free operation duration and the fault occurrence frequency.

[0020] The index statistical method for annual inspection quality analysis of wind turbines proposed in the present application can more accurately evaluate the maintenance quality and performance status of wind power equipment, and provide a scientific basis for periodic inspection and preventive maintenance of wind turbines by quantifying the fault operation duration, fault-free operation duration and fault frequency. This not only helps to improve the reliability of wind turbines and reduce unplanned downtime, but also effectively reduces operation and maintenance costs and prolongs the service life of wind turbines, thereby improving the economic benefits and operational efficiency of wind farms as a whole. In addition, this method can help operation and maintenance personnel to discover potential problems in time and take measures in advance to ensure the safe and stable operation of wind power equipment, which is of great significance to the sustainable development of the wind power industry.

[0021] In some embodiments, the present application provides an index statistical method for annual inspection quality analysis of wind turbines, which aims to evaluate the quality and efficiency of wind turbine inspection work by deeply mining the operation data of wind turbines within a year. Technically, the method first extracts the annual operation data of wind turbines from the data management system of the wind farm, which includes but is not limited to the working status, maintenance records, fault information, etc. of the wind turbine; in principle, data analysis and statistical principles are used to convert the operation data into quantifiable indicators such as fault operation duration, fault-free operation duration and fault frequency; in terms of effect, the method generates a wind turbine inspection quality analysis report to visually display the operation status and maintenance effect of the wind turbine, helping wind farm managers to discover problems in maintenance work in time, optimize maintenance strategies, and improve the availability and power generation efficiency of wind turbines. In other embodiments, machine learning algorithms can be introduced to automatically identify wind turbine operation patterns and fault trends, further improving the accuracy and predictability of inspection quality analysis.

[0022] In some embodiments, the obtaining the annual operation data of the wind turbine specifically includes: obtaining the number of annual inspection work tickets of the wind turbine, the operation error execution time of each annual inspection work ticket, the re-commissioning time, and the fault data. In terms of technology, this step requires the data acquisition system of the wind farm to record and store the maintenance and fault information of the wind turbine in real time, ensuring the completeness and accuracy of the data; in terms of principle, the maintenance cycle and maintenance duration of the wind turbine can be determined through the operation error execution time and the re-commissioning time of each annual inspection work ticket, and then the efficiency and quality of the maintenance work can be evaluated; in terms of effect, the collected fault data can reveal the health status of the wind turbine, providing a basis for the calculation of the fault operation duration and the fault-free operation duration. In other embodiments, additional sensors can also be installed to monitor the status of key components of the wind turbine, collecting more comprehensive operation data to improve the accuracy of fault prediction.

[0023] In some embodiments, the fault operation duration and the fault-free operation duration are calculated according to the operation error execution time and the re-commissioning time of each annual inspection work ticket, and the fault occurrence frequency is counted. In terms of technology, this process involves time series analysis and data cleaning to ensure the reliability and effectiveness of the calculation results; in terms of principle, by comparing the time points before and after the execution of each work ticket, the running state of the wind turbine during and after maintenance can be accurately calculated, and thus the fault operation duration and the fault-free operation duration can be obtained; in terms of effect, the counted fault frequency can reflect the failure rate of the wind turbine, helping the wind farm manager to evaluate the reliability of the wind turbine. In other embodiments, a prediction model of the wind turbine state can also be established to predict possible faults in advance, reduce unplanned downtime, and further optimize the operation efficiency of the wind turbine.

[0024] In some embodiments, the fault operation duration and the fault-free operation duration are calculated according to the operation error execution time and the re-commissioning time of each annual inspection work ticket, specifically including: taking the safety measure execution time of the first work ticket as the starting point and the re-commissioning time of the last work ticket as the ending point to construct the annual inspection time interval; taking the first 1 / 3 month before the regular inspection to the first 1 / 3 month after the regular inspection as the comparison time window. In terms of technology, this implementation utilizes the concept of time window to compare data within a specific time range, improving the relevance and practicality of the analysis; in terms of principle, by calculating the fault operation duration and the fault-free operation duration within the annual inspection time interval, the running performance of the wind turbine during the maintenance cycle can be evaluated; in terms of effect, the setting of the comparison time window helps to analyze the performance recovery of the wind turbine after maintenance, providing a basis for adjusting the maintenance strategy. In other embodiments, the length of the comparison time window can also be dynamically adjusted according to the type of the wind turbine and the operating environment, to adapt to different analysis needs.

[0025] In some embodiments, a wind turbine maintenance quality analysis report is generated based on the duration of failure, the duration of failure-free operation, and the frequency of failure. Technically, this step involves the visual presentation of data analysis results, and a suitable report template and chart display method need to be designed to make the data easy to understand and analyze; in principle, by comprehensively considering the three key indicators of failure duration, failure-free operation duration and failure frequency, the operation quality and maintenance effect of the wind turbine can be comprehensively evaluated; in terms of effect, the generated report can provide decision support for wind farm managers, help them develop effective maintenance plans, reduce operating costs, and improve the economic benefits of wind turbines. In other embodiments, the data in the report can also be updated in real time by integrating a remote monitoring system to achieve dynamic monitoring of the operation of the wind turbine.

[0026] Referring to Figure 2 The present application also discloses an index statistical system for wind turbine annual maintenance quality analysis, comprising: a data acquisition unit for acquiring wind turbine annual operation data; a calculation unit for calculating the duration of failure and the duration of failure-free operation based on the wind turbine annual operation data, and counting the frequency of failure; an analysis and display unit for generating a wind turbine maintenance quality analysis report based on the duration and frequency of wind turbine annual operation data.

[0027] In some embodiments, the calculation unit includes a time calculation module and a failure statistics module. Technically, the time calculation module is responsible for processing time series data and calculating the duration of failure and the duration of failure-free operation, while the failure statistics module focuses on counting the frequency of failure, and the two modules work together to ensure the comprehensiveness and accuracy of data processing; in principle, the time calculation module uses the difference method to calculate the operation duration, while the failure statistics module uses database query technology to count the number of failures; in terms of effect, the efficient operation of these two modules ensures that the system can quickly and accurately generate an analysis report. In other embodiments, parallel computing technology can also be introduced to speed up the data processing process and improve the response speed of the system.

[0028] In some embodiments, the data acquisition unit acquires the annual operation data of the fan, specifically collects the number of annual inspection work tickets of the fan, the operation error execution time, the reemployment time and the fault data of each annual inspection work ticket. In terms of technology, this process is usually completed by data acquisition hardware and software together, the hardware is responsible for real-time data acquisition, and the software is responsible for data transmission and storage; in principle, through the communication protocol between the data acquisition system and the fan control system, the real-time and integrity of the data can be ensured; in terms of effect, the collected data provides a solid foundation for subsequent analysis, and helps to improve the accuracy and reliability of the analysis. In other embodiments, data redundancy backup mechanism can also be added to prevent data loss and ensure data security.

[0029] As shown in Figure 3 The present application also provides an electronic device 100 for implementing the index statistical method for annual inspection quality analysis of the fan. The electronic device 100 comprises a memory 101, at least one processor 102, a computer program 103 stored in the memory 101 and executable on the at least one processor 102, and at least one communication bus 104.

[0030] The memory 101 can be used to store the computer program 103, and the processor 102 can realize the steps of the index statistical method for annual inspection quality analysis of the fan by running or executing the computer program stored in the memory 101 and calling the data stored in the memory 101.

[0031] The memory 101 can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, at least one application required by a function (such as a sound playing function, an image playing function, etc.), etc.; the data storage area can store data (such as audio data) created according to the use of the electronic device 100, etc. In addition, the memory 101 can include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, at least one disk storage device, a flash memory device, or other non-volatile solid-state storage device.

[0032] The at least one processor 102 can be a central processing unit (CPU), and can also be other general-purpose processors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs) or other programmable logic devices, discrete gates or transistor logic, discrete hardware components, etc. The processor 102 can be a microprocessor or the processor 102 can also be any conventional processor. The processor 102 is a control center of the electronic device 100, and is connected with various parts of the electronic device 100 through various interfaces and lines.

[0033] The memory 101 in the electronic device 100 stores a plurality of instructions to implement an index statistical method for annual inspection quality analysis of a fan. The processor 102 can execute the plurality of instructions to implement the following steps. S1: Obtain annual operation data of the fan. S2: Calculate the fault operation time length and the non-fault operation time length according to the annual operation data of the fan, and count the fault occurrence frequency. S3: Generate a fan inspection quality analysis report based on the fault operation time length, the non-fault operation time length and the fault occurrence frequency.

[0034] In some embodiments, if the modules / units integrated in the electronic device 100 are implemented in the form of software function units and sold or used as independent products, they can be stored in a computer readable storage medium. Based on this understanding, all or part of the processes in the above-mentioned embodiment methods can also be completed by a computer program instructing related hardware. The computer program can be stored in a computer readable storage medium. When the computer program is executed by a processor, the steps of the above-mentioned various method embodiments can be implemented. The computer program includes computer program code, which can be in the form of source code, object code, executable files or some intermediate forms, etc. The computer readable medium can include any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, magnetic disk, optical disk, computer memory and read-only memory (ROM).

[0035] Those skilled in the art will appreciate that embodiments of the present application can be devised for a method, a system, or a computer program product. Accordingly, the present application can take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application can take the form of a computer program product on one or more computer readable storage media (including, but not limited to, disk storage, CD-ROMs, optical storage devices, etc.) embodying computer readable program code thereon.

[0036] The present application is described in reference to the drawings, which are as follows. Figure 1 one or more processes and / or blocks Figure 1 means for performing the functions specified in the one or more processes and / or blocks

[0037] These computer program instructions can also be stored in a computer readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer readable memory produce an article of manufacture including instructions which implement the Figure 1 one or more processes and / or blocks Figure 1 means for performing the functions specified in the one or more processes and / or blocks

[0038] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the Figure 1 one or more processes and / or blocks Figure 1 means for performing the functions specified in the one or more processes and / or blocks

[0039] In this description, references to "one embodiment", "an example", "certain examples" etc. mean that the feature being referred to is included in at least one embodiment or example of the present application. Separate references to "one embodiment", "an example", "certain examples" etc. do not necessarily mean that every embodiment or example includes the feature. In addition, descriptions of a particular feature can not imply that the feature is preferred or essential.

[0040] It should be pointed out finally that the above embodiments are only used to illustrate the technical solutions of the present application but not to limit it. Although the present application has been described in detail with reference to the above embodiments, it should be understood by those skilled in the art that the specific embodiments of the present application can be modified or equivalently replaced without departing from the spirit and scope of the present application, and any modification or equivalent replacement should be covered within the protection scope of the claims of the present application.

Claims

1. A statistical method for analyzing the quality of annual scheduled maintenance of wind turbines, characterized in that, include: Obtain annual operating data for wind turbines; Calculate the fault-free operating time and fault-free operating time based on the annual operating data of the wind turbine, and count the frequency of fault occurrence. Based on the fault-free runtime, fault-free runtime, and fault frequency, a wind turbine scheduled maintenance quality analysis report is generated.

2. The statistical method for analyzing the quality of annual scheduled maintenance of wind turbines according to claim 1, characterized in that, The specific steps for obtaining the annual operating data of the wind turbine are as follows: Obtain the number of annual inspection work tickets for the wind turbine, the execution time of each annual inspection work ticket, the decommissioning time, and fault data.

3. The statistical method for analyzing the quality of annual scheduled maintenance of wind turbines according to claim 2, characterized in that, The fault-free runtime and fault-free runtime are calculated based on the error execution time and recovery time of each annual inspection work order, and the frequency of fault occurrence is statistically analyzed.

4. The statistical method for analyzing the quality of annual scheduled maintenance of wind turbines according to claim 3, characterized in that, The fault-free runtime and fault-free runtime are calculated based on the error execution time and recovery time of each annual inspection work order, and the frequency of fault occurrence is statistically analyzed, specifically including: The annual inspection time range is constructed with the implementation time of the safety measures of the first work order as the starting point and the decommissioning time of the last work order as the ending point; the comparison time window is from 1 / 3 month before the scheduled inspection to 1 / 3 month after the scheduled inspection. The downtime is calculated based on the error execution time and recovery time of each annual inspection work order; The fault-free operating time is calculated based on the number of inspection work tickets and the fault operating time throughout the year. Based on the execution time of each annual inspection work order and the comparison time window, the frequency of faults within the time window is statistically analyzed.

5. The statistical method for analyzing the quality of annual scheduled maintenance of wind turbines according to claim 3, characterized in that, A quality analysis report for scheduled maintenance of the fan is generated based on the duration of operation during faults, the duration of operation without faults, and the frequency of faults.

6. A statistical system for analyzing the quality of annual scheduled maintenance of wind turbines, characterized in that, include: The data acquisition unit is used to acquire annual operating data of the wind turbines; The calculation unit is used to calculate the fault-free operation time and fault-free operation time based on the annual operating data of the wind turbine, and to count the frequency of fault occurrence. The analysis and display unit is used to generate a wind turbine scheduled maintenance quality analysis report based on the duration and frequency of annual wind turbine operation data.

7. The index statistical system for annual scheduled inspection quality analysis of wind turbines according to claim 6, characterized in that, The computing unit includes: The time calculation module is used to calculate the fault-free operation time and fault-free operation time based on the annual operating data of the wind turbine; The fault statistics module is used to count the frequency of fault occurrences.

8. The index statistical system for annual scheduled inspection quality analysis of wind turbines according to claim 6, characterized in that, The data acquisition unit acquires the annual operating data of the wind turbine specifically as follows: Obtain the number of annual inspection work tickets for the wind turbine, the execution time of each annual inspection work ticket, the decommissioning time, and fault data.

9. An electronic device, characterized in that, It includes a processor and a memory, the processor being used to execute a computer program stored in the memory to implement the statistical method for the quality analysis of annual maintenance of wind turbines as described in any one of claims 1 to 5.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores at least one instruction, which, when executed by a processor, implements the statistical method for the annual inspection quality analysis of wind turbines as described in any one of claims 1 to 5.

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