Intelligent management system for wind power operation and maintenance

Abstract

The invention belongs to the field of wind power operation and maintenance, relates to a data analysis technology, and is used for solving the problem of low fault processing efficiency caused by the fact that scheduling of operation and maintenance personnel cannot be optimized in combination with an equipment operation state and a risk degree in the prior art. The intelligent management system comprises a wind power operation and maintenance platform, and the wind power operation and maintenance platform is in communication connection with a data acquisition module, an equipment operation evaluation module, an equipment risk evaluation module, an operation and maintenance grading module and a task distribution module. The equipment operation assessment module and the equipment risk assessment module assess the operation state and the risk level of the operation and maintenance equipment, and the operation and maintenance grading module and the task allocation module are used for sorting the operation and maintenance priority of the operation and maintenance equipment and the operation and maintenance capability of operation and maintenance personnel and allocating operation and maintenance tasks to the corresponding operation and maintenance personnel; the operation and maintenance task sequence and the operation and maintenance personnel sequence can be combined, scheduling of the operation and maintenance personnel is optimized, and the fault processing efficiency is improved.

Description

Technical Field

[0001] The present invention belongs to the field of wind power operation and maintenance, relates to data analysis technology, and specifically is an intelligent management system for wind power operation and maintenance. Background Art

[0002] With the increasing attention paid to renewable energy, wind power generation has been widely used as a clean and sustainable way of generating energy. With the rapid development of wind power generation, the scale of wind farms has continued to expand, and the number of wind turbines has also increased. The importance of ensuring the stable operation of wind turbines, extending the service life of equipment, and ensuring reliable power supply for wind power projects has also increased.

[0003] Existing wind power operation and maintenance technologies mainly rely on manual regular inspections to detect faults and then perform post-fault repairs. They are unable to fully utilize advanced sensors and communication technologies to timely collect and analyze equipment operation data. Existing technologies are also unable to optimize the scheduling of operation and maintenance personnel based on equipment operating status and risk levels, resulting in inefficient fault handling.

[0004] In view of the above technical problems, this application proposes a solution. Summary of the invention

[0005] The purpose of the present invention is to provide an intelligent management system for wind power operation and maintenance to solve the problem that the prior art cannot optimize the scheduling of operation and maintenance personnel in combination with the equipment operating status and risk level, resulting in low efficiency in fault handling; The technical problem to be solved by the present invention is: how to provide an intelligent management system for wind power operation and maintenance that can optimize the scheduling of operation and maintenance personnel in combination with the equipment operating status and risk level.

[0006] The purpose of the present invention can be achieved by the following technical solutions: An intelligent management system for wind power operation and maintenance, comprising a wind power operation and maintenance platform, wherein the wind power operation and maintenance platform is communicatively connected with a data acquisition module, an equipment operation evaluation module, an equipment risk evaluation module, an operation and maintenance classification module, and a task allocation module; The data acquisition module is used to collect parameters of the wind turbine during operation: the core wind power generation components in the wind turbine are marked as operation and maintenance equipment s, s=1, 2, ..., n, n is a positive integer, a monitoring cycle of a fixed length is generated during the wind turbine power generation period, and the air temperature QW, the surface temperature WDs of the operation and maintenance equipment s, and the vibration frequency ZDs are collected at a fixed frequency; The equipment operation evaluation module is used to evaluate the state of the operation and maintenance equipment s when the wind turbine is running: obtain the temperature change value WBs and the vibration change value ZBs of the operation and maintenance equipment s, and calculate the state coefficient ZTs through the formula, and evaluate the operation state of the operation and maintenance equipment s according to the state coefficient ZTs; The equipment risk assessment module is used to assess the risk level of the operation and maintenance equipment s: the risk coefficient FXs of the operation and maintenance equipment s is calculated through the historical records of equipment maintenance, and the risk level of the operation and maintenance equipment is assessed according to the risk coefficient FXs; The operation and maintenance classification module is used to sort the operation and maintenance priorities of the operation and maintenance equipment s in combination with the operation status and risk level of the operation and maintenance equipment s: at the end of the monitoring period, the evaluation value of the operation and maintenance equipment s is obtained, and a two-dimensional operation and maintenance task sequence is generated according to the evaluation value and the state coefficient ZTs; The task allocation module is used to allocate operation and maintenance tasks to operation and maintenance personnel according to the operation and maintenance task sequence: obtain the operation and maintenance capability coefficient YN of the operation and maintenance personnel, divide the two-dimensional operation and maintenance task sequence into several subsequences and allocate the operation and maintenance tasks according to the principle of sequence number value matching.

[0007] Furthermore, the operation and maintenance equipment s includes a wind turbine, a rotating shaft, a gear box, a generator and a wind power converter; the temperature QW outside the wind turbine is collected by installing a temperature sensor on the tower; the surface temperature WDs and the vibration frequency ZDs of the operation and maintenance equipment s are collected by installing temperature sensors and vibration sensors on the wind turbine, the rotating shaft, the gear box, the generator and the wind power converter; wherein the collection frequency of all collection devices is 30 seconds each time.

[0008] Furthermore, the process of obtaining the state coefficient ZTs of the operation and maintenance equipment s includes: calculating the difference between the surface temperature WDs of the operation and maintenance equipment s and the air temperature QW to obtain the temperature rise value of the operation and maintenance equipment s; obtaining all the temperature rise values ​​of the operation and maintenance equipment s during the monitoring period and summing and averaging them to obtain the temperature change value WBs; marking the minimum value of the vibration frequency ZDs of the operation and maintenance equipment s during the monitoring period as the vibration reference value, and performing a difference calculation between the vibration frequency ZDs and the vibration reference value to obtain the vibration fluctuation value, obtaining all the vibration fluctuation values ​​of the operation and maintenance equipment s during the monitoring period and summing and averaging them to obtain the vibration change value ZBs; performing numerical calculation on the temperature change value WBs and the vibration change value ZBs to obtain the state coefficient ZTs of the operation and maintenance equipment s.

[0009] Furthermore, the status evaluation process of the operation and maintenance equipment s includes: comparing the status coefficient ZTs of the operation and maintenance equipment s with the preset status threshold ZTmax: if the status coefficient ZTs is less than the status threshold ZTmax, it is judged that the operation and maintenance equipment s is operating normally, and its status performance value is set to 0; if the status coefficient ZTs is greater than or equal to the status threshold ZTmax, it is judged that the operation and maintenance equipment s is operating abnormally, and its status performance value is set to 1.

[0010] Furthermore, the process of obtaining the risk coefficient FXs of the operation and maintenance equipment s includes: obtaining the failure frequency GZs of the operation and maintenance equipment s and the average downtime TJs and average maintenance cost WXs when the operation and maintenance equipment s fails through the historical records of equipment maintenance; and performing numerical calculations on the historical failure frequency GZs, the average downtime TJs and the average maintenance cost WXs to obtain the risk coefficient FXs of the operation and maintenance equipment s.

[0011] Furthermore, the risk assessment process of the operation and maintenance equipment s includes: comparing the risk coefficient FXs of the operation and maintenance equipment s with the preset high risk value FXmax and low risk value FXmin: if the risk coefficient FXs is greater than or equal to the high risk value FXmax, then the risk level of the operation and maintenance equipment s is judged to be high, and its risk performance value is set to 2; if the risk coefficient FXs is less than the high risk value FXmax and greater than or equal to the low risk value FXmin, then the risk level of the operation and maintenance equipment s is judged to be medium, and its risk performance value is set to 1; if the risk coefficient FXs is less than the low risk value FXmin, then the risk level of the operation and maintenance equipment s is judged to be low, and its risk performance value is set to 0.

[0012] Furthermore, the specific process of the operation and maintenance grading module sorting the operation and maintenance priority of the operation and maintenance equipment s includes: at the end of the monitoring period, simultaneously obtaining the state performance value and the risk performance value of the operation and maintenance equipment s, and performing a sum calculation to obtain the evaluation value of the operation and maintenance equipment s; if the evaluation value is 0, it is determined that there is no need to perform operation and maintenance work on the operation and maintenance equipment s; if the evaluation value is not 0, the operation and maintenance equipment s is added to the operation and maintenance task sequence, and the operation and maintenance task sequence is sorted; for the operation and maintenance equipment s in the operation and maintenance task sequence, the operation and maintenance equipment s are first sorted in order from large to small in terms of the evaluation value to obtain a first-level operation and maintenance task sequence, and then the operation and maintenance equipment s with the same evaluation value in the first-level operation and maintenance sequence are sorted for a second time in order from large to small in terms of the state coefficient ZTs to obtain a second-level operation and maintenance task sequence.

[0013] Furthermore, the specific process of the task allocation module allocating the operation and maintenance tasks to the operation and maintenance personnel includes: obtaining the working age NL, the last operation and maintenance time SC, and the one-time operation and maintenance completion rate CG of the operation and maintenance personnel; performing numerical calculations on the working age NL, the last operation and maintenance time SC, and the one-time operation and maintenance completion rate CG to obtain the operation and maintenance capability coefficient YN of the operation and maintenance personnel, and generating an operation and maintenance personnel sequence in descending order of the operation and maintenance capability coefficient YN; marking the total number of operation and maintenance personnel as K, and dividing the secondary operation and maintenance task sequence into a number of subsequences, wherein the 1st, K+1th, 2K+1th tasks, etc. in the secondary operation and maintenance task sequence are the first subsequence, and the 2nd task, K+2th task, 2K+2th task, etc. in the two-dimensional operation and maintenance task sequence are the second subsequence, and so on; when allocating tasks, the subsequences of the secondary operation and maintenance task sequence are allocated in sequence according to the principle of matching the serial number values ​​of the subsequences with the operation and maintenance personnel sequence; after each operation and maintenance task is completed and executed, the operation and maintenance personnel sequence is regenerated according to the last operation and maintenance result.

[0014] The present invention has the following beneficial effects: The sensors installed at various parts of the wind turbines collect operating parameters in real time, and the collected data is periodically analyzed to obtain the status coefficient of the operation and maintenance equipment, thereby ensuring that the operating status of the equipment can be evaluated in a timely and effective manner; By obtaining the historical records of equipment maintenance, a comprehensive analysis of the equipment failure frequency, average downtime and average repair cost is performed to obtain the risk factor of the operation and maintenance equipment, and the risk level of the operation and maintenance equipment is evaluated based on the risk factor; By combining the operation status and risk level of the operation and maintenance equipment to generate an operation and maintenance task sequence, the operation and maintenance priorities of the operation and maintenance equipment are ranked, which reasonably reflects the importance of different operation and maintenance tasks; 4. Generate an operation and maintenance personnel sequence through the historical operation and maintenance records of the operation and maintenance personnel, which reflects the operation and maintenance capabilities of the operation and maintenance personnel. Combined with the operation and maintenance task sequence, it optimizes the scheduling of operation and maintenance personnel and improves the efficiency of fault handling. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0016] Figure 1 The figure is a system block diagram of the present invention as a whole. DETAILED DESCRIPTION

[0017] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0018] like Figure 1 As shown, an intelligent management system for wind power operation and maintenance includes a wind power operation and maintenance platform, which is communicatively connected to a data acquisition module, an equipment operation evaluation module, an equipment risk evaluation module, an operation and maintenance classification module, and a task allocation module.

[0019] The data acquisition module is used to collect the parameters of the wind turbine during operation: the core components of the wind turbine in the wind turbine are marked as operation and maintenance equipment s, s=1, 2,…, n, and n is a positive integer; the operation and maintenance equipment s includes a wind turbine, a rotating shaft, a gear box, a generator, and a wind power converter; a fixed-length monitoring cycle is generated during the power generation period of the wind turbine, and the external temperature QW of the wind turbine is collected by installing a temperature sensor on the tower; temperature sensors and vibration sensors are installed on the wind turbine, the rotating shaft, the gear box, the generator, and the wind power converter to collect the surface temperature WDs and the vibration frequency ZDs of the operation and maintenance equipment s; wherein the collection frequency of all collection devices is 30 seconds each time.

[0020] The equipment operation evaluation module is used to evaluate the status of the operation and maintenance equipment s when the wind turbine is running: the surface temperature WDs of the operation and maintenance equipment s is calculated by difference with the air temperature QW to obtain the temperature rise value of the operation and maintenance equipment s; all the temperature rise values ​​of the operation and maintenance equipment s within the monitoring period are obtained and summed and averaged to obtain the temperature change value WBs; the minimum value of the vibration frequency ZDs of the operation and maintenance equipment s within the monitoring period is marked as the vibration reference value, and the vibration frequency ZDs is calculated by difference with the vibration reference value to obtain the vibration fluctuation value, all the vibration fluctuation values ​​of the operation and maintenance equipment s within the monitoring period are obtained and summed and averaged to obtain the vibration change value ZBs; the temperature change value WBs and the vibration change value ZBs are numerically calculated by the formula ZTs=k1*WBs+k2*ZBs to obtain the status coefficient ZTs of the operation and maintenance equipment s, where k1 and k 2 are both proportional coefficients, and k1>k2>1; compare the state coefficient ZTs of the operation and maintenance equipment s with the preset state threshold ZTmax: if the state coefficient ZTs is less than the state threshold ZTmax, it is judged that the operation and maintenance equipment s is operating normally, and its state performance value is set to 0; if the state coefficient ZTs is greater than or equal to the state threshold ZTmax, it is judged that the operation and maintenance equipment s is operating abnormally, and its state performance value is set to 1; the operating parameters are collected in real time by sensors installed at various parts of the wind turbine, and the collected data are analyzed to obtain the state coefficient of the operation and maintenance equipment, thereby ensuring that the operating status of the equipment can be evaluated in a timely and effective manner.

[0021] The equipment risk assessment module is used to assess the risk level of the operation and maintenance equipment s: the failure frequency GZs of the operation and maintenance equipment s, the average downtime TJs when the operation and maintenance equipment s fails, and the average maintenance cost WXs are obtained through the historical records of equipment maintenance; it should be noted that the historical failure frequency GZs is the ratio of the number of failures to the running time of the operation and maintenance equipment s, and the historical failure frequency GZs, the average downtime TJs, and the average maintenance cost WXs will be updated regularly with the operation of the operation and maintenance equipment s; the historical failure frequency GZs, the average downtime TJs, and the average maintenance cost WXs are numerically calculated through the formula FXs=α1*GZs+α2*TJs+α3*WXs to obtain the risk coefficient FXs of the operation and maintenance equipment s, where α1, α2, and α3 are all proportional coefficients, and α1>α2>α3; The risk coefficient FXs of the operation and maintenance equipment s is compared with the preset high risk value FXmax and low risk value FXmin: if the risk coefficient FXs is greater than or equal to the high risk value FXmax, the risk level of the operation and maintenance equipment s is judged to be high, and its risk performance value is set to 2; if the risk coefficient FXs is less than the high risk value FXmax and greater than or equal to the low risk value FXmin, the risk level of the operation and maintenance equipment s is judged to be medium, and its risk performance value is set to 1; if the risk coefficient FXs is less than the low risk value FXmin, the risk level of the operation and maintenance equipment s is judged to be low, and its risk performance value is set to 0; the risk coefficient of the operation and maintenance equipment is obtained by obtaining the historical records of equipment maintenance, comprehensively analyzing the equipment's failure frequency, average downtime and average maintenance cost, and evaluating the risk level of the operation and maintenance equipment through the risk coefficient.

[0022] The operation and maintenance classification module is used to sort the operation and maintenance priority of the operation and maintenance equipment s in combination with the operation status and risk level of the operation and maintenance equipment: at the end of the monitoring period, the state performance value and risk performance value of the operation and maintenance equipment s are obtained at the same time, and the sum is calculated to obtain the evaluation value of the operation and maintenance equipment s; if the evaluation value is 0, it is determined that there is no need to perform operation and maintenance work on the operation and maintenance equipment s; if the evaluation value is not 0, the operation and maintenance equipment s is added to the operation and maintenance task sequence, and the operation and maintenance task sequence is sorted; For the operation and maintenance equipment s in the operation and maintenance task sequence, the operation and maintenance equipment s are first sorted in descending order according to the evaluation value to obtain the first-level operation and maintenance task sequence, and then the operation and maintenance equipment s with the same evaluation value in the first-level operation and maintenance sequence are sorted again according to the state coefficient ZTs in descending order to obtain the second-level operation and maintenance task sequence; the operation and maintenance task sequence is generated by combining the operating status and risk level of the operation and maintenance equipment, and the operation and maintenance priorities of the operation and maintenance equipment are sorted, which reasonably reflects the importance of different operation and maintenance tasks.

[0023] The task allocation module is used to allocate operation and maintenance tasks to operation and maintenance personnel according to the operation and maintenance task sequence: obtain the working age NL of the operation and maintenance personnel, the duration of the last operation and maintenance SC, and the one-time operation and maintenance completion rate CG; it should be noted that the one-time operation and maintenance completion rate CG refers to the percentage of the number of times the operation and maintenance personnel complete the task once after receiving the operation and maintenance task to the total number of operation and maintenance tasks received by the operation and maintenance personnel; through the formula The working age NL, the last operation and maintenance time SC, and the one-time operation and maintenance completion rate CG are numerically calculated to obtain the operation and maintenance capability coefficient YN of the operation and maintenance personnel, where β1, β2, and β3 are all proportional coefficients, and β1>β2>β3, and the operation and maintenance personnel sequence is generated in descending order according to the operation and maintenance capability coefficient YN; The total number of operation and maintenance personnel is marked as K, and the secondary operation and maintenance task sequence is divided into several subsequences, among which the 1st, K+1th, 2K+1th tasks... in the secondary operation and maintenance task sequence are the first subsequence, and the 2nd task, K+2th task, 2K+2th task... in the two-dimensional operation and maintenance task sequence are the second subsequence, and so on; when allocating tasks, the subsequences of the secondary operation and maintenance task sequence are allocated in sequence according to the principle of matching the serial number value of the subsequence with the operation and maintenance personnel sequence; after each operation and maintenance task is completed, the operation and maintenance personnel sequence is regenerated according to the last operation and maintenance result; the operation and maintenance personnel sequence is generated by obtaining the historical operation and maintenance records of the operation and maintenance personnel, which reflects the operation and maintenance capabilities of the operation and maintenance personnel, and combined with the operation and maintenance task sequence, the scheduling of the operation and maintenance personnel is optimized and the efficiency of fault handling is improved.

[0024] An intelligent management system for wind power operation and maintenance, when working, generates a monitoring cycle of fixed length during the power generation period of a wind turbine, collects operating data of operation and maintenance equipment through multiple sensors and evaluates its operating status, obtains fault data of operation and maintenance equipment through historical records of equipment maintenance and evaluates its risk level, sorts the operation and maintenance priorities of operation and maintenance equipment in combination with the operating status and risk level of the operation and maintenance equipment, generates a secondary operation and maintenance task sequence, finally generates an operation and maintenance personnel sequence according to the operation and maintenance capability coefficient of the operation and maintenance personnel, divides the secondary operation and maintenance task sequence, and allocates the divided subsequences to corresponding operation and maintenance personnel in a manner of matching sequence number values.

[0025] The above contents are merely examples and explanations of the structure of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the structure of the invention or exceed the scope defined by the claims, they should all fall within the protection scope of the present invention.

[0026] The above formulas are obtained by collecting a large amount of data for software simulation and selecting a formula close to the real value. The coefficients in the formula are set by technicians in this field according to the actual situation; for example: formula FXs=α1*GZs+α2*TJs+α3*WXs; technicians in this field collect multiple groups of sample data and set corresponding risk coefficients for each group of sample data; substitute the set risk coefficients and the collected sample data into the formula, any three formulas constitute a three-variable linear equation group, screen the calculated coefficients and take the average, and obtain the values ​​of α1, α2 and α3 as 2.53, 2.17 and 1.64 respectively; The size of the coefficient is to quantify each parameter to obtain a specific value for subsequent comparison. The size of the coefficient depends on the amount of sample data and the initial setting of the corresponding risk coefficient for each set of sample data by technical personnel in this field; as long as it does not affect the proportional relationship between the parameter and the quantified value, such as the risk coefficient is proportional to the average downtime value.

[0027] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0028] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. An intelligent management system for wind power operation and maintenance, characterized in that: It includes a wind power operation and maintenance platform, which is communicatively connected with a data acquisition module, an equipment operation evaluation module, an equipment risk evaluation module, an operation and maintenance classification module, and a task allocation module; The data acquisition module is used to collect parameters of the wind turbine during operation: the core wind power generation components in the wind turbine are marked as operation and maintenance equipment s, s=1, 2, ..., n, n is a positive integer, a monitoring cycle of a fixed length is generated during the wind turbine power generation period, and the air temperature QW, the surface temperature WDs of the operation and maintenance equipment s, and the vibration frequency ZDs are collected at a fixed frequency; The equipment operation evaluation module is used to evaluate the state of the operation and maintenance equipment s when the wind turbine is running: obtain the temperature change value WBs and the vibration change value ZBs of the operation and maintenance equipment s, and calculate the state coefficient ZTs through the formula, and evaluate the operation state of the operation and maintenance equipment s according to the state coefficient ZTs; The equipment risk assessment module is used to assess the risk level of the operation and maintenance equipment s: the risk coefficient FXs of the operation and maintenance equipment s is calculated through the historical records of equipment maintenance, and the risk level of the operation and maintenance equipment is assessed according to the risk coefficient FXs; The operation and maintenance classification module is used to sort the operation and maintenance priorities of the operation and maintenance equipment s in combination with the operation status and risk level of the operation and maintenance equipment: at the end of the monitoring period, the evaluation value of the operation and maintenance equipment s is obtained, and a two-dimensional operation and maintenance task sequence is generated according to the evaluation value and the state coefficient ZTs; The task allocation module is used to allocate operation and maintenance tasks to operation and maintenance personnel according to the operation and maintenance task sequence: obtain the operation and maintenance capability coefficient YN of the operation and maintenance personnel, divide the two-dimensional operation and maintenance task sequence into several subsequences and allocate the operation and maintenance tasks according to the principle of sequence number value matching.

2. The intelligent management system for wind power operation and maintenance according to claim 1, characterized in that: The operation and maintenance equipment s includes a wind turbine, a rotating shaft, a gear box, a generator and a wind power converter; the temperature QW outside the wind turbine is collected by installing a temperature sensor on the tower; the surface temperature WDs and the vibration frequency ZDs of the operation and maintenance equipment s are collected by installing temperature sensors and vibration sensors on the wind turbine, the rotating shaft, the gear box, the generator and the wind power converter; the collection frequency of all collection equipment is 30 seconds each time.

3. The intelligent management system for wind power operation and maintenance according to claim 2, characterized in that: The process of obtaining the state coefficient ZTs of the operation and maintenance equipment s includes: calculating the difference between the surface temperature WDs of the operation and maintenance equipment s and the air temperature QW to obtain the temperature rise value of the operation and maintenance equipment s; obtaining all the temperature rise values ​​of the operation and maintenance equipment s within the monitoring period and summing and averaging them to obtain the temperature change value WBs; marking the minimum value of the vibration frequency ZDs of the operation and maintenance equipment s within the monitoring period as the vibration reference value, and calculating the difference between the vibration frequency ZDs and the vibration reference value to obtain the vibration fluctuation value, obtaining all the vibration fluctuation values ​​of the operation and maintenance equipment s within the monitoring period and summing and averaging them to obtain the vibration change value ZBs; performing numerical calculations on the temperature change value WBs and the vibration change value ZBs to obtain the state coefficient ZTs of the operation and maintenance equipment s.

4. The intelligent management system for wind power operation and maintenance according to claim 3, characterized in that: The status evaluation process of the operation and maintenance equipment s includes: comparing the status coefficient ZTs of the operation and maintenance equipment s with the preset status threshold ZTmax: if the status coefficient ZTs is less than the status threshold ZTmax, it is judged that the operation and maintenance equipment s is operating normally, and its status performance value is set to 0; if the status coefficient ZTs is greater than or equal to the status threshold ZTmax, it is judged that the operation and maintenance equipment s is operating abnormally, and its status performance value is set to 1.

5. The intelligent management system for wind power operation and maintenance according to claim 4, characterized in that: The process of obtaining the risk coefficient FXs of the operation and maintenance equipment s includes: obtaining the failure frequency GZs of the operation and maintenance equipment s, the average downtime TJs when the operation and maintenance equipment s fails, and the average maintenance cost WXs through the historical records of equipment maintenance; performing numerical calculations on the historical failure frequency GZs, the average downtime TJs, and the average maintenance cost WXs to obtain the risk coefficient FXs of the operation and maintenance equipment s.

6. The intelligent management system for wind power operation and maintenance according to claim 5, characterized in that: The risk assessment process of operation and maintenance equipment s includes: comparing the risk coefficient FXs of operation and maintenance equipment s with the preset high risk value FXmax and low risk value FXmin: if the risk coefficient FXs is greater than or equal to the high risk value FXmax, the risk level of the operation and maintenance equipment s is judged to be high, and its risk performance value is set to 2; if the risk coefficient FXs is less than the high risk value FXmax and greater than or equal to the low risk value FXmin, the risk level of the operation and maintenance equipment s is judged to be medium, and its risk performance value is set to 1; if the risk coefficient FXs is less than the low risk value FXmin, the risk level of the operation and maintenance equipment s is judged to be low, and its risk performance value is set to 0.

7. The intelligent management system for wind power operation and maintenance according to claim 6, characterized in that: The specific process of the operation and maintenance grading module to sort the operation and maintenance priority of the operation and maintenance equipment s includes: at the end of the monitoring period, the state performance value and the risk performance value of the operation and maintenance equipment s are obtained at the same time, and the sum is calculated to obtain the evaluation value of the operation and maintenance equipment s; if the evaluation value is 0, it is determined that there is no need to perform operation and maintenance work on the operation and maintenance equipment s; if the evaluation value is not 0, the operation and maintenance equipment s is added to the operation and maintenance task sequence, and the operation and maintenance task sequence is sorted; for the operation and maintenance equipment s in the operation and maintenance task sequence, the operation and maintenance equipment s are first sorted in order from large to small according to the evaluation value to obtain a first-level operation and maintenance task sequence, and then the operation and maintenance equipment s with the same evaluation value in the first-level operation and maintenance sequence are sorted again in order from large to small according to the state coefficient ZTs to obtain a second-level operation and maintenance task sequence.

8. The intelligent management system for wind power operation and maintenance according to claim 7, characterized in that: The specific process of the task allocation module allocating the operation and maintenance tasks to the operation and maintenance personnel includes: obtaining the working age NL, the last operation and maintenance time SC and the one-time operation and maintenance completion rate CG of the operation and maintenance personnel; performing numerical calculations on the working age NL, the last operation and maintenance time SC and the one-time operation and maintenance completion rate CG to obtain the operation and maintenance capability coefficient YN of the operation and maintenance personnel, and generating the operation and maintenance personnel sequence according to the operation and maintenance capability coefficient YN in descending order; marking the total number of operation and maintenance personnel as K, dividing the secondary operation and maintenance task sequence into several subsequences, wherein the 1st, K+1th, 2K+1th tasks in the secondary operation and maintenance task sequence... are the first subsequence, and the 2nd task, K+2th task, 2K+2th task... in the two-dimensional operation and maintenance task sequence are the second subsequence, and so on; when allocating tasks, the subsequences of the secondary operation and maintenance task sequence are allocated in sequence according to the principle of matching the serial number values ​​of the subsequences with the operation and maintenance personnel sequence; after each operation and maintenance task is completed and executed, the operation and maintenance personnel sequence is regenerated according to the last operation and maintenance result.

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