Full-life-cycle management system and method for wind generating set and medium

Abstract

The invention belongs to the field of wind power generation, relates to a generator set management technology, is used for solving the problem that fault monitoring and staged operation supervision analysis cannot be carried out on a wind generator set in the prior art, and particularly relates to a full-life-cycle management system and method for the wind generator set and a medium. The server is in communication connection with an operation monitoring module, a period supervision module, a prediction analysis module and a database; the operation monitoring module is used for monitoring and analyzing the operation state of the wind generating set: marking the wind generating set as a monitoring object, generating a continuous monitoring period, dividing the monitoring period into a plurality of monitoring time periods, and obtaining a monitoring coefficient of the monitoring object at the end time of the monitoring time periods; the operation state of the wind generating set can be monitored and analyzed, the operation state of the wind generating set is fed back according to the monitoring coefficient, an alarm is given in time when an operation fault occurs, and the fault processing efficiency of the wind generating set is improved.

Description

Technical Field

[0001] The present invention belongs to the field of wind power generation and relates to generator set management technology, specifically a wind generator set full life cycle management system, method and medium. Background Art

[0002] The working principle of a wind turbine is to convert wind energy into mechanical energy, and then convert the mechanical energy into electrical energy through a generator. When the wind blows through the wind rotor blades, the blades rotate due to the wind force, converting the wind energy into mechanical energy. The rotating wind rotor is accelerated by the main shaft drive chain and the gear box, driving the generator to generate electricity, and finally converting the mechanical energy into electrical energy.

[0003] The invention patent with announcement number CN113204886A discloses a method for evaluating the power generation performance of a wind turbine. The method can accurately calculate the changing trend of the actual power generation performance compared with the designed power generation performance, as well as specific quantitative data, providing reliable data for wind farm management decisions and improving management efficiency; however, the method cannot perform fault monitoring and periodic operation supervision analysis on the wind turbine generator set, resulting in the inability to timely inspect and maintain the wind turbine generator set, and the operating status cannot be guaranteed.

[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 a wind turbine generator set full life cycle management system, method and medium, which are used to solve the problem that the prior art cannot perform fault monitoring and phased operation supervision and analysis on wind turbine generator sets;

[0006] The technical problem to be solved by the present invention is: how to provide a wind turbine generator set full life cycle management system, method and medium that can perform fault monitoring and phased operation supervision analysis on the wind turbine generator set.

[0007] The purpose of the present invention can be achieved through the following technical solutions:

[0008] A wind turbine generator set full life cycle management system, comprising a server, wherein the server is communicatively connected to an operation monitoring module, a cycle supervision module, a prediction analysis module and a database;

[0009] The operation monitoring module is used to monitor and analyze the operation status of the wind turbine generator set: mark the wind turbine generator set as a monitoring object, generate a continuous monitoring cycle, divide the monitoring cycle into a number of monitoring time periods, obtain the temperature meter data WB, vibration data ZD and noise data ZS of the monitoring object at the end of the monitoring time period, and perform numerical calculations to obtain the monitoring coefficient JC of the monitoring object in the monitoring time period; determine whether the operation status of the monitoring object in the monitoring time period meets the requirements through the monitoring coefficient JC;

[0010] The periodic supervision module is used to perform periodic operation supervision analysis on the wind turbine generator set: at the end of the monitoring period, the fault data GZ, interval data JG and operation data YX of the monitored object are obtained and numerical calculation is performed to obtain the evaluation coefficient PG of the monitored object during the monitoring period, and the evaluation coefficient PG is used to determine whether the supervision status of the monitored object during the monitoring period meets the requirements;

[0011] The prediction and analysis module is used to perform prediction and analysis on the operating status of the wind turbine generator set.

[0012] Furthermore, the temperature meter data WB is the maximum value of the surface temperature of the internal heat sink of the monitored object during the monitoring period, the vibration data ZD is the maximum value of the vibration amplitude of the gearbox base plate of the monitored object during the monitoring period, and the noise data ZS is the maximum value of the noise decibel value of the generator of the monitored object during the monitoring period.

[0013] Furthermore, the specific process of determining whether the operating status of the monitored object during the monitoring period meets the requirements includes: obtaining the monitoring threshold JCmax through the database, and comparing the monitoring coefficient JC of the monitored object during the monitoring period with the monitoring threshold JCmax: if the monitoring coefficient JC is less than the monitoring threshold JCmax, it is determined that the operating status of the monitored object during the monitoring period meets the requirements; if the monitoring coefficient JC is greater than or equal to the monitoring threshold JCmax, it is determined that the operating status of the monitored object during the monitoring period does not meet the requirements, and an equipment maintenance signal is generated and sent to the mobile phone terminal of the manager through the server.

[0014] Furthermore, the process of acquiring the fault data GZ includes: marking the monitoring period in which the operating status of the monitored object does not meet the requirements as an abnormal period, and marking the number of abnormal periods as the fault data GZ; the process of acquiring the interval data JG includes: sorting and numbering the monitoring periods within the monitoring cycle, marking the absolute value of the difference between the serial numbers of two adjacent abnormal periods as the interval value, and marking the minimum value of the interval value as the interval data JG; the operating data YX is the average value of the monitoring coefficient JC of all monitoring periods within the monitoring cycle.

[0015] Furthermore, the specific process of determining whether the supervision status of the monitored object during the monitoring period meets the requirements includes: retrieving the evaluation threshold PGmax through the database, and comparing the evaluation coefficient PG of the monitoring period with the evaluation threshold PGmax: if the evaluation coefficient PG is less than the evaluation threshold PGmax, then it is determined that the supervision status of the monitored object during the monitoring period meets the requirements, and a prediction analysis signal is generated and sent to the prediction analysis module through the server; if the evaluation coefficient PG is greater than or equal to the evaluation threshold PGmax, then it is determined that the supervision status of the monitored object during the monitoring period does not meet the requirements, and a device maintenance signal is generated and sent to the mobile phone terminal of the manager through the server.

[0016] Furthermore, the specific process of the prediction and analysis module predicting and analyzing the operating status of the wind turbine generator set includes: at the end of the monitoring cycle, a rectangular coordinate system is established with the execution time of the monitoring cycle as the X-axis and the monitoring coefficient JC as the Y-axis, and a number of monitoring points are marked in the rectangular coordinate system with the middle time of the monitoring period as the horizontal coordinate and the monitoring coefficient JC of the monitoring period as the vertical coordinate, and the monitoring points are connected from left to right in sequence to obtain a monitoring polyline, and the monitoring polyline is smoothed to obtain a monitoring curve; the monitoring curves of all wind turbine generator sets that have completed the monitoring cycle are retrieved through the database and marked as comparison curves, and all comparison curves are compared and analyzed with the monitoring curve of the current monitoring cycle in turn.

[0017] Furthermore, the specific process of comparing and analyzing the comparison curve with the monitoring curve of the current monitoring cycle includes: translating the comparison curve to the rectangular coordinate system of the current monitoring cycle, connecting the right end point of the comparison curve with the right end point of the monitoring curve to obtain a cutoff line segment, marking the sum of the area values ​​of all closed figures composed of the Y-axis, the monitoring curve, the comparison curve and the cutoff line segment as the overlap value of the comparison curve relative to the monitoring curve, marking the completed monitoring cycle corresponding to the comparison curve with the smallest overlap value as the comparison cycle, and determining whether the supervision status of the wind turbine in the next cycle of the comparison cycle meets the requirements: if so, no processing is performed; if not, a prediction reminder signal is generated and the prediction reminder signal is sent to the mobile phone terminal of the manager through the server.

[0018] A wind turbine generator set full life cycle management method comprises the following steps:

[0019] Step 1: Monitor and analyze the operating status of the wind turbine generator set;

[0020] Step 2: Conduct periodic operation supervision and analysis of wind turbines;

[0021] Step 3: Predict and analyze the operating status of the wind turbine.

[0022] A computer storage medium stores a computer program, which, when executed by a processor, implements a method for managing a wind turbine generator set throughout its life cycle.

[0023] The present invention has the following beneficial effects:

[0024] 1. The operation monitoring module can monitor and analyze the operation status of the wind turbine generator set. At the end of each monitoring period, statistics and analysis are performed on multiple operation parameters of the wind turbine generator set to obtain the monitoring coefficient. Feedback on the operation status of the wind turbine generator set is provided based on the monitoring coefficient. When an operation failure occurs, an alarm is issued in time to improve the fault handling efficiency of the wind turbine generator set.

[0025] 2. The periodic supervision module can be used to conduct periodic operation supervision and analysis on the wind turbine generator set. At the end of the monitoring period, the various fault parameters of the wind turbine generator set are collected and processed to obtain the evaluation coefficient. The overall operation status of the wind turbine generator set during the monitoring period is evaluated through the evaluation coefficient, and then the maintenance and optimization of the wind turbine generator set is carried out according to the evaluation results;

[0026] 3. The prediction and analysis module can be used to predict and analyze the operating status of the wind turbine generator set. The monitoring curve of the current monitoring cycle is compared with the comparison curve of the completed monitoring cycle, and the curve with the highest overlap with the monitoring curve is selected from the comparison curve. Then, the supervision status of the wind turbine generator set is predicted based on the screening results. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] 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.

[0028] Figure 1 is a system block diagram of Embodiment 1 of the present invention;

[0029] Figure 2 This is a flow chart of the method of Embodiment 2 of the present invention. DETAILED DESCRIPTION

[0030] 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.

[0031] Embodiment 1: Figure 1 As shown, a wind turbine generator set full life cycle management system includes a server, and the server is communicatively connected to an operation monitoring module, a cycle supervision module, a prediction and analysis module and a database.

[0032] The operation monitoring module is used to monitor and analyze the operation status of the wind turbine generator set: mark the wind turbine generator set as the monitoring object, generate a continuous monitoring cycle, divide the monitoring cycle into several monitoring periods, and obtain the temperature meter data WB, vibration data ZD and noise data ZS of the monitoring object at the end of the monitoring period. The temperature meter data WB is the maximum value of the surface temperature of the internal heat sink of the monitoring object during the monitoring period, the vibration data ZD is the maximum value of the vibration amplitude of the gear box bottom plate of the monitoring object during the monitoring period, and the noise data ZS is the maximum value of the noise decibel value of the generator of the monitoring object during the monitoring period; through the formula The monitoring coefficient JC of the monitored object in the monitoring period is obtained, wherein c1, c2 and c3 are all proportional coefficients, and c1>c2>c3>1; the monitoring threshold JCmax is obtained through the database, and the monitoring coefficient JC of the monitored object in the monitoring period is compared with the monitoring threshold JCmax: if the monitoring coefficient JC is less than the monitoring threshold JCmax, it is determined that the operating state of the monitored object in the monitoring period meets the requirements; if the monitoring coefficient JC is greater than or equal to the monitoring threshold JCmax, it is determined that the operating state of the monitored object in the monitoring period does not meet the requirements, and an equipment maintenance signal is generated and sent to the mobile phone terminal of the manager through the server; at the end of each monitoring period, statistics and analysis are performed on multiple operating parameters of the wind turbine generator set to obtain the monitoring coefficient, feedback is given on the operating state of the wind turbine generator set according to the monitoring coefficient, and an alarm is given in time when an operating failure occurs, thereby improving the fault handling efficiency of the wind turbine generator set.

[0033] The periodic supervision module is used to perform periodic operation supervision and analysis on the wind turbine generator set: at the end of the monitoring period, the fault data GZ, interval data JG and operation data YX of the monitored object are obtained. The acquisition process of the fault data GZ includes: marking the monitoring period in which the operating status of the monitored object does not meet the requirements as an abnormal period, and marking the number of abnormal periods as the fault data GZ; the acquisition process of the interval data JG includes: sorting and numbering the monitoring periods in the monitoring period, marking the absolute value of the difference between the serial numbers of two adjacent abnormal periods as the interval value, and marking the minimum value of the interval value as the interval data JG; the operation data YX is the average value of the monitoring coefficient JC of all monitoring periods in the monitoring period; through the formula The evaluation coefficient PG of the monitored object during the monitoring period is obtained, wherein m1, m2 and m3 are all proportional coefficients, and m1>m2>m3>1. The evaluation threshold PGmax is retrieved through the database, and the evaluation coefficient PG of the monitoring period is compared with the evaluation threshold PGmax: if the evaluation coefficient PG is less than the evaluation threshold PGmax, it is determined that the supervision status of the monitored object during the monitoring period meets the requirements, a prediction analysis signal is generated and the prediction analysis signal is sent to the prediction analysis module through the server; if the evaluation coefficient PG is greater than or equal to the evaluation threshold PGmax, it is determined that the supervision status of the monitored object during the monitoring period does not meet the requirements, a device maintenance signal is generated and the device maintenance signal is sent to the mobile phone terminal of the manager through the server; at the end of the monitoring period, various fault parameters of the wind turbine are collected and processed to obtain the evaluation coefficient, and the overall operating status of the wind turbine during the monitoring period is evaluated through the evaluation coefficient, and then the wind turbine is maintained and optimized according to the evaluation result.

[0034] The prediction and analysis module is used to perform prediction and analysis on the operating status of wind turbines: at the end of the monitoring cycle, a rectangular coordinate system is established with the execution time of the monitoring cycle as the X-axis and the monitoring coefficient JC as the Y-axis, and several monitoring points are marked in the rectangular coordinate system with the middle time of the monitoring period as the horizontal coordinate and the monitoring coefficient JC of the monitoring period as the vertical coordinate. The monitoring points are connected from left to right in turn to obtain a monitoring polyline, and the monitoring polyline is smoothed to obtain a monitoring curve; the monitoring curves of all wind turbines that have completed the monitoring cycle are retrieved from the database and marked as comparison curves, and all comparison curves are compared and analyzed with the monitoring curve of the current monitoring cycle in turn: the comparison curve is translated to the rectangular coordinate system of the current monitoring cycle, and the right endpoint of the comparison curve is aligned with the monitoring curve The right endpoints of are connected to obtain a cutoff line segment, the sum of the area values ​​of all closed figures composed of the Y axis, the monitoring curve, the comparison curve and the cutoff line segment is marked as the overlap value of the comparison curve relative to the monitoring curve, and the completed monitoring cycle corresponding to the comparison curve with the smallest overlap value is marked as the comparison cycle, and it is determined whether the supervision status of the wind turbine generator set in the next cycle of the comparison cycle meets the requirements: if so, no processing is performed; if not, a prediction reminder signal is generated and sent to the mobile phone terminal of the manager through the server; the monitoring curve of the current monitoring cycle is compared and analyzed with the comparison curve of the completed monitoring cycle, and the curve with the highest overlap with the monitoring curve is screened out from the comparison curve, and then the supervision status of the wind turbine generator set is predicted according to the screening result.

[0035] Embodiment 2: Figure 2 As shown, a wind turbine generator set full life cycle management method includes the following steps:

[0036] Step 1: Monitor and analyze the operating status of the wind turbine generator set: mark the wind turbine generator set as the monitoring object, obtain the temperature meter data WB, vibration data ZD and noise data ZS of the monitoring object at the end of the monitoring period, and perform numerical calculations to obtain the monitoring coefficient JC. The monitoring coefficient JC is used to determine whether the operating status of the monitoring object during the monitoring period meets the requirements;

[0037] Step 2: Perform periodic operation supervision analysis on the wind turbine generator set: At the end of the monitoring period, the fault data GZ, interval data JG and operation data YX of the monitored object are obtained and numerically calculated to obtain the evaluation coefficient PG of the monitoring period. The evaluation coefficient PG is used to determine whether the supervision status of the monitored object during the monitoring period meets the requirements;

[0038] Step 3: Predictive analysis of the operating status of the wind turbine generator set: draw a monitoring curve at the end of the monitoring cycle, retrieve the monitoring curves of all wind turbine generator sets that have completed the monitoring cycle through the database and mark them as comparison curves, compare and analyze all comparison curves with the monitoring curves of the current monitoring cycle in turn, and determine whether the monitored object needs a predictive reminder.

[0039] The present invention also includes a readable storage medium on which a computer program is stored. When the program is executed by a processor, the above-mentioned method for managing the entire life cycle of a wind turbine generator set is implemented. A person of ordinary skill in the art can understand that all or part of the steps of implementing the above-mentioned method embodiments can be completed by hardware related to the computer program. The aforementioned computer program can be stored in a computer-readable storage medium. When the program is executed, the steps of the above-mentioned method embodiments are executed; and the aforementioned storage medium includes: ROM, RAM, magnetic disk or optical disk and other media that can store program codes.

[0040] A wind turbine generator set full life cycle management system, when working, marks the wind turbine generator set as a monitoring object, obtains the temperature meter data WB, vibration data ZD and noise data ZS of the monitoring object at the end of the monitoring period, and performs numerical calculation to obtain the monitoring coefficient JC, and determines whether the operating state of the monitoring object in the monitoring period meets the requirements through the monitoring coefficient JC; obtains the fault data GZ, interval data JG and operation data YX of the monitoring object at the end of the monitoring cycle, and performs numerical calculation to obtain the evaluation coefficient PG of the monitoring cycle, and determines whether the supervision state of the monitoring object in the monitoring cycle meets the requirements through the evaluation coefficient PG; draws a monitoring curve at the end of the monitoring cycle, retrieves the monitoring curves of all wind turbine generator sets that have completed the monitoring cycle through a database and marks them as comparison curves, compares and analyzes all the comparison curves with the monitoring curve of the current monitoring cycle in turn, and determines whether the monitoring object needs to be predicted and reminded.

[0041] 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.

[0042] The above formulas are obtained by collecting a large amount of data and performing software simulation to select a formula close to the actual value. The coefficients in the formula are set by technicians in this field according to actual conditions; for example: Formula ; A technician in this field collects multiple groups of sample data and sets corresponding monitoring coefficients for each group of sample data; Substitute the set monitoring coefficients and the collected sample data into the formula, any three formulas constitute a three-variable linear equation system, screen the calculated coefficients and take the average, and obtain the values ​​of c1, c2 and c3 as 3.52, 2.83 and 2.41 respectively;

[0043] 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 monitoring 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 monitoring coefficient is proportional to the value of the temperature meter data.

[0044] 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.

[0045] 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. A wind turbine generator system full life cycle management system, characterized in that: It includes a server, wherein the server is communicatively connected with an operation monitoring module, a cycle supervision module, a prediction analysis module and a database; The operation monitoring module is used to monitor and analyze the operation status of the wind turbine generator set: mark the wind turbine generator set as a monitoring object, generate a continuous monitoring cycle, divide the monitoring cycle into several monitoring periods, obtain the temperature meter data WB, vibration data ZD and noise data ZS of the monitoring object at the end of the monitoring period, and perform numerical calculations to obtain the monitoring coefficient JC of the monitoring object in the monitoring period; The monitoring coefficient JC is used to determine whether the operating status of the monitored object during the monitoring period meets the requirements; The periodic supervision module is used to perform periodic operation supervision analysis on the wind turbine generator set: at the end of the monitoring period, the fault data GZ, interval data JG and operation data YX of the monitored object are obtained and numerical calculation is performed to obtain the evaluation coefficient PG of the monitored object during the monitoring period, and the evaluation coefficient PG is used to determine whether the supervision status of the monitored object during the monitoring period meets the requirements; The prediction and analysis module is used to perform prediction and analysis on the operating status of the wind turbine generator set.

2. A wind turbine generator system full life cycle management system according to claim 1, characterized in that: The temperature meter data WB is the maximum value of the surface temperature of the internal heat sink of the monitored object during the monitoring period, the vibration data ZD is the maximum value of the vibration amplitude of the gearbox base plate of the monitored object during the monitoring period, and the noise data ZS is the maximum value of the noise decibel value of the generator of the monitored object during the monitoring period.

3. A wind turbine generator system full life cycle management system according to claim 2, characterized in that: The specific process of determining whether the operating status of the monitored object during the monitoring period meets the requirements includes: obtaining the monitoring threshold JCmax through the database, and comparing the monitoring coefficient JC of the monitored object during the monitoring period with the monitoring threshold JCmax: if the monitoring coefficient JC is less than the monitoring threshold JCmax, it is determined that the operating status of the monitored object during the monitoring period meets the requirements; if the monitoring coefficient JC is greater than or equal to the monitoring threshold JCmax, it is determined that the operating status of the monitored object during the monitoring period does not meet the requirements, and an equipment maintenance signal is generated and sent to the mobile phone terminal of the manager through the server.

4. A wind turbine generator system full life cycle management system according to claim 3, characterized in that: The process of acquiring the fault data GZ includes: marking the monitoring period in which the operating status of the monitored object does not meet the requirements as an abnormal period, and marking the number of abnormal periods as the fault data GZ; the process of acquiring the interval data JG includes: sorting and numbering the monitoring periods within the monitoring cycle, marking the absolute value of the difference between the serial numbers of two adjacent abnormal periods as the interval value, and marking the minimum value of the interval value as the interval data JG; the operating data YX is the average value of the monitoring coefficient JC of all monitoring periods within the monitoring cycle.

5. A wind turbine generator system full life cycle management system according to claim 4, characterized in that: The specific process of determining whether the supervision status of the monitored object during the monitoring period meets the requirements includes: retrieving the evaluation threshold PGmax through the database, and comparing the evaluation coefficient PG of the monitoring period with the evaluation threshold PGmax: if the evaluation coefficient PG is less than the evaluation threshold PGmax, it is determined that the supervision status of the monitored object during the monitoring period meets the requirements, and a prediction analysis signal is generated and sent to the prediction analysis module through the server; if the evaluation coefficient PG is greater than or equal to the evaluation threshold PGmax, it is determined that the supervision status of the monitored object during the monitoring period does not meet the requirements, and a device maintenance signal is generated and sent to the mobile phone terminal of the manager through the server.

6. A wind turbine generator system full life cycle management system according to claim 5, characterized in that: The specific process of the prediction and analysis module for predicting and analyzing the operating status of the wind turbine generator set includes: at the end of the monitoring cycle, a rectangular coordinate system is established with the execution time of the monitoring cycle as the X-axis and the monitoring coefficient JC as the Y-axis, and a number of monitoring points are marked in the rectangular coordinate system with the middle time of the monitoring period as the horizontal coordinate and the monitoring coefficient JC of the monitoring period as the vertical coordinate, and the monitoring points are connected from left to right in turn to obtain a monitoring line, and the monitoring line is smoothed to obtain a monitoring curve; the monitoring curves of all wind turbine generator sets that have completed the monitoring cycle are retrieved through the database and marked as comparison curves, and all comparison curves are compared and analyzed with the monitoring curve of the current monitoring cycle in turn.

7. A wind turbine generator system full life cycle management system according to claim 6, characterized in that: The specific process of comparing and analyzing the comparison curve with the monitoring curve of the current monitoring cycle includes: translating the comparison curve to the rectangular coordinate system of the current monitoring cycle, connecting the right end point of the comparison curve with the right end point of the monitoring curve to obtain a cutoff line segment, marking the sum of the area values ​​of all closed figures composed of the Y-axis, the monitoring curve, the comparison curve and the cutoff line segment as the overlap value of the comparison curve relative to the monitoring curve, marking the completed monitoring cycle corresponding to the comparison curve with the smallest overlap value as the comparison cycle, and determining whether the supervision status of the wind turbine generator set in the next cycle of the comparison cycle meets the requirements: if so, no processing is performed; if not, a prediction reminder signal is generated and the prediction reminder signal is sent to the mobile phone terminal of the manager through the server.

8. A wind turbine generator set full life cycle management method, characterized in that: The following steps are involved: Step 1: Monitor and analyze the operating status of the wind turbine generator set; Step 2: Conduct periodic operation supervision and analysis of wind turbines; Step 3: Predict and analyze the operating status of the wind turbine.

9. A computer storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the wind turbine generator set full life cycle management method described in claim 8 is implemented.

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