An operation and maintenance management system for intelligently monitoring mountainous wind power generation equipment

Abstract

The application relates to the technical field of operation and maintenance management, and discloses an operation and maintenance management system for intelligently monitoring mountainous area wind power generation equipment, which comprises a data acquisition module, a sensor unit and a storage unit; the sensor unit comprises a temperature sensor, which is used for acquiring the temperature of a mountainous area environment and the operating temperature of the wind power generation equipment; the storage unit is used for storing various data of the wind power generation equipment and the mountainous area environment; an operation analysis module is used for acquiring the temperature rising rate of the wind power generation equipment according to the various data of the wind power generation equipment and the mountainous area environment; and an early warning triggering module triggers aging early warning according to the acquired temperature rising rate of the wind power generation equipment, and prompts maintenance personnel to perform corresponding maintenance on the wind power generation equipment. By acquiring a temperature smoothing value, the temperature rising rate is calculated according to the temperature smoothing value, temperature fluctuation interference in a high-load period is effectively filtered, and a subtle temperature rising signal caused by equipment aging in a low-load period is amplified.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of operation and maintenance, in particular to an operation and maintenance system for intelligently monitoring mountain wind power generation equipment. BACKGROUND

[0002] Mountain wind power generation equipment refers to a power generation system used for converting wind energy into electric energy in a complex mountain environment, and its design needs to adapt to high altitude, steep terrain and variable climate conditions. The equipment is composed of core components such as blades, towers and generators. The blades convert wind energy into mechanical energy, drive the generator to generate electricity after speed increasing through the gear box, and finally transmit through the control system and grid connection;

[0003] In the operation and health monitoring of wind power generation equipment, temperature monitoring is one of the most direct and key technical means. By obtaining temperature data of the core parts of the wind power generation equipment, data processing is performed to evaluate the operation state of the wind power generation equipment, a threshold model is established to avoid false alarms, and finally maintenance decisions are implemented.

[0004] However, the threshold model is usually established by historical data, which is difficult to track the performance degradation trend of the equipment in real time. For example, when the bearing part of the wind power generation equipment is continuously worn, the initial temperature rise may be smoothed by historical data and missed, so it is ignored until the wear becomes more and more serious and more obvious abnormalities are caused, making the maintenance work more troublesome.

[0005] Therefore, the present application provides an operation and maintenance system for intelligently monitoring mountain wind power generation equipment to solve the problems in the prior art. SUMMARY

[0006] The present application aims to provide an operation and maintenance system for intelligently monitoring mountain wind power generation equipment, which solves the problem that the threshold model is usually established by historical data in the prior art temperature monitoring, which is difficult to track the performance degradation trend of the equipment in real time.

[0007] The purpose of the present application can be achieved by the following technical solutions:

[0008] An operation and maintenance system for intelligently monitoring mountain wind power generation equipment, comprising:

[0009] A data acquisition module comprising a sensor unit and a storage unit;

[0010] The sensor unit comprises a temperature sensor for obtaining the temperature of the mountain environment and the operating temperature of the wind power generation equipment.

[0011] The storage unit is used to store various data of the wind power generation equipment and the mountain environment.

[0012] The operation analysis module is used to obtain the temperature rise rate of the wind power generation equipment based on various data of the wind power generation equipment and the mountainous environment;

[0013] The early warning trigger module triggers an aging warning based on the acquired rate of temperature increase of the wind power generation equipment, prompting maintenance personnel to carry out corresponding maintenance on the wind power generation equipment.

[0014] Preferably, the method for obtaining the temperature rise rate of the wind power generation equipment is... The process is as follows:

[0015] The operating load of the wind power generation equipment is calculated based on the acquired data on the wind power equipment and the mountainous environment. ;

[0016] Based on the operating temperature and operating load of the wind power generation equipment Obtain temperature smoothing value of wind power generation equipment ;

[0017] Based on the temperature smoothing value of wind power generation equipment Calculate and obtain the temperature rise rate of wind power generation equipment .

[0018] Preferably, the wind power generation equipment operates under load Obtained through the following methods:

[0019]

[0020] in, For the first The temperature variation curve of the mountainous environment obtained by Tian To monitor the start time, For the end time of monitoring, The average temperature curve of the mountainous area over the past month. For temperature standard deviation, This is the temperature influence coefficient. For the first The number of times the wind power generation equipment yaws is obtained daily. This represents the average number of yaws by wind turbines over the past month. The standard deviation of the number of yaws of wind power generation equipment. This represents the historical maximum number of yaws for wind power generation equipment. This is the yaw effect coefficient. For the first Wind speed variation curves in mountainous areas obtained by Tian Average wind speed variation curve in mountainous areas over the past month. The standard deviation of wind speed variation This is the wind speed impact index.

[0021] The wind power generation equipment temperature smoothing value is obtained by the following way:

[0022]

[0023] wherein, is the wind power generation equipment operation temperature maximum value obtained on the th day, is the wind power generation equipment operation temperature maximum value obtained on the th day, is the wind power generation equipment operation temperature maximum value obtained on the th day.

[0024] The wind power generation equipment moving average temperature rising rate is obtained by the following way:

[0025]

[0026] wherein, is the wind power generation equipment temperature smoothing value on the th day, is the wind power generation equipment temperature smoothing value on the th day, is the load of the wind power generation equipment on the th day, is the load influence coefficient, is the temperature compensation coefficient.

[0027] The aging early warning is triggered by the following way:

[0028] when and , the wind power generation equipment lubrication system and heat dissipation device are checked;

[0029] when and , the machine is stopped for maintenance, and the transmission connection parts such as gear box and bearing are checked;

[0030] wherein, is the dynamic threshold.

[0031] The dynamic threshold is adjusted in the following way:

[0032] The temperature influence factor , the wind speed influence factor , and the yawing frequency influence factor are obtained.

[0033] when and when When ;

[0034] When or when , .

[0035] Advantages of the present application:

[0036] 1、The present application obtains various data of wind power equipment and mountain environment through the data acquisition module, calculates the wind power equipment operation load by using the environmental temperature, yaw frequency and mountain wind speed through the operation analysis module, and then obtains the temperature smoothing value by comprehensively calculating the wind power equipment operation load and the maximum value of the equipment operation temperature of the adjacent three days, calculates the temperature rising rate according to the temperature smoothing value, and finally triggers the aging warning according to the temperature rising rate trend and the cumulative amount by the early warning trigger module, effectively filters the temperature fluctuation interference of the high load period, and amplifies the subtle temperature rise signal caused by the equipment aging in the low load period.

[0037] Of course, implementing any product of the present application does not necessarily need to achieve all the advantages described above at the same time. BRIEF DESCRIPTION OF DRAWINGS

[0038] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed for the embodiment description will be briefly introduced as follows. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0039] Figure 1 The system module diagram of the present application is a kind of intelligent monitoring mountain wind power equipment operation and maintenance management system. DETAILED DESCRIPTION

[0040] The technical solutions in the embodiments of the present application will be described clearly and completely in combination with the drawings in the embodiments of the present application. Obviously, the described embodiments are only some embodiments of the present application, not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0041] Please refer to Figure 1 The present application is a kind of intelligent monitoring mountain wind power equipment operation and maintenance management system, comprising:

[0042] Data acquisition module, including sensor unit and storage unit;

[0043] The sensor unit comprises a temperature sensor for acquiring the mountain environment temperature and the wind power generation equipment operation temperature;

[0044] The storage unit is used for storing various data of the wind power generation equipment and the mountain environment, and the various data comprises the wind power generation equipment operation temperature, the wind power generation equipment yawing frequency, the environment temperature, and the mountain wind speed;

[0045] The operation analysis module is used for acquiring the wind power generation equipment temperature rising rate according to the various data of the wind power generation equipment and the mountain environment.

[0046] The early warning triggering module triggers the aging early warning according to the acquired wind power generation equipment temperature rising rate, and prompts the maintenance personnel to perform corresponding maintenance on the wind power generation equipment.

[0047] Specifically, the data collection module is composed of the sensor unit and the storage unit, the sensor unit is composed of a plurality of temperature sensors, and is mainly used for collecting the environment temperature of the mountain where the wind power generation equipment is located and the wind power generation equipment operation temperature. The wind power generation equipment operation temperature is mainly the temperature of the planetary gear box, which is one of the most important parts of the wind power generation equipment, and is mainly used for transmitting the rotation of the fan blades of the wind power generation equipment to the generator, so as to realize wind power generation. The temperature in the planetary gear box directly reflects the operation state of the planetary gear, and when the components in the planetary gear box are aged, the temperature will gradually increase with the gradual increase of the operation time, thereby affecting the operation of the wind power generation equipment.

[0048] In the implementation of the sensor unit of the data collection module, the temperature sensor adopts a combination of high-precision thermocouple sensors (precision ±0.5℃) and infrared thermal imagers: the thermocouple sensors are pre-buried in the planetary gear box bearing seat, the generator stator winding, the converter heat dissipation module and other key heating parts of the wind power generation equipment, and real-time single-point temperature data is collected every 10 minutes; the infrared thermal imager is installed in the middle of the equipment tower, and the whole gear box is scanned every hour to obtain the surface temperature field distribution. In view of the complex environment in the mountainous area, the sensors are all configured with IP68 level protective shell to prevent moisture and sand, and data transmission is realized through armored optical fiber to ensure stable work in the temperature range of-40℃~85℃ and 95% humidity environment.

[0049] The storage unit adopts a distributed database architecture, which is divided into a local edge computing node and a cloud server: the local node is deployed in the wind power plant booster station, and uses a solid state disk to store real-time monitoring data for nearly 7 days, and supports offline transmission; the cloud server synchronizes data in real time through 4G / 5G network, and uses a distributed file system to store historical data.

[0050] Acquiring the wind power generation equipment temperature rising rate The process is as follows:

[0051] According to the acquired data of the wind power generation equipment and the mountainous environment, the wind power generation equipment operation load is calculated ;

[0052] According to the wind power generation equipment operation temperature and the wind power generation equipment operation load The wind power generation equipment temperature smoothing value is acquired ;

[0053] According to the wind power generation equipment temperature smoothing value , the wind power generation equipment temperature rising rate is calculated .

[0054] The wind power generation equipment operation load is mainly obtained according to the mountainous environment temperature, the yaw times of the wind power generation equipment, and the mountainous wind speed, specifically, the mountainous environment temperature will directly affect the wind power generation equipment, and the yaw times and the mountainous wind speed are two key factors of the aging of the wind power generation equipment

[0055] Specifically, the wind power generation equipment is equipped with a wind direction instrument, a wind speed instrument, a yaw system, and a brake system, when the mountainous wind speed increases, in order to protect the wind power generation equipment in a normal operating state, the yaw system is controlled to rotate the wind power generation equipment, so that the fan part of the wind power generation equipment can bear appropriate pressure, and in the yaw process, the wind power generation equipment still rotates, so that the wind power generation equipment will bear a larger wind pressure in the yaw process, so that the planetary gear box bears a larger load, so that the wear of the internal components is further increased, thereby affecting the aging of the equipment.

[0056] The wind power generation equipment operation load is obtained by the following method:

[0057]

[0058] Among them, is the change curve of the mountainous environment temperature acquired on the th day, is the monitoring start time, is the monitoring end time, is the average curve of the mountainous environment temperature in the past one month, is the temperature standard deviation, is the temperature influence coefficient, is the yaw times of the wind power generation equipment acquired on the th day, is the average yaw times of the wind power generation equipment in the past one month, is the yaw times standard deviation of the wind power generation equipment, This represents the historical maximum number of yaws for wind power generation equipment. This is the yaw effect coefficient. For the first Wind speed variation curves in mountainous areas obtained by Tian Average wind speed variation curve in mountainous areas over the past month. The standard deviation of wind speed variation This is the wind speed impact index.

[0059] Specifically, wind power operating load The data was obtained by comprehensively calculating the ambient temperature in the main mountainous areas, the yaw rate of wind power generation equipment, and the wind speed in the mountainous areas. First, the ambient temperature in the mountainous areas was collected by temperature sensors, and the ambient temperature change curve in the mountainous areas was calculated. Obtained from the average temperature curve of the mountainous area over the past month The difference was calculated and compared with the temperature standard deviation. Compare and combine weighting coefficients This amplifies the impact of mountain temperatures on wind power generation equipment;

[0060] Curve reflecting the ambient temperature of the day Compared with the average temperature curve of the past 30 days The degree of deviation is determined by the fact that when a cold wave suddenly hits a mountainous area, the viscosity of the equipment lubricating oil increases, causing a surge in gearbox load. At this time, the impact of abnormal temperature on the load is amplified by a weighting coefficient. However, during the high-temperature period in summer, the default setting is used to avoid oversensitivity.

[0061] By using the obtained yaw count Compared with the average The difference is calculated and then compared with the standard deviation of the number of yaws. The impact factor is obtained through comparison. This impact factor is then calculated against the maximum number of yaws. Since the number of yaws significantly affects the internal wear and tear of wind turbine equipment, the calculation result is amplified by squaring and incorporating weighting coefficients. The impact of yaw rate on wind power generation equipment is highlighted.

[0062] By obtaining the wind speed variation curve in mountainous areas Combined with the average curve of wind speed variation in mountainous areas Obtain the difference and compare it with the standard deviation of wind speed change. By comparing and obtaining the influencing factors, the impact of wind speed on wind power generation equipment is further amplified by combining the square method with the weighting coefficients.

[0063] The above three relatively intuitive parameters provide a clear picture of the operating load of wind power equipment, while the monitoring start time... The monitoring ends at midnight every day. For the second day zero, the wind power generation equipment and the mountain environment data are monitored every day with 24 hours as a cycle, and the monitoring data are recorded and stored after the monitoring time ends.

[0064] Temperature influence coefficient Yaw influence coefficient Wind speed influence coefficient are obtained by the following ways respectively:

[0065]

[0066]

[0067]

[0068] wherein, wherein, is the tip vibration amplitude of the wind power generation equipment, is the maximum value of the ambient temperature, is the maximum value of the wind speed in the mountain area, is the rated wind speed variation curve, is the wind speed and rotation factor of the number of rotations, is the maximum single day yaw gear rotation number, is the yaw angle of the wind power generation equipment, is the wind direction in the mountain area, is the first day wind speed variation standard deviation, is the first day wind speed variation average value, is the wind speed variation standard deviation average value, is the output power of the wind power generation equipment, is the ratio of the blade tip linear speed and the wind speed, is the blade diameter of the wind power generation equipment, is the planetary gear transmission ratio, and are weight coefficients.

[0069] Specifically, for the temperature influence coefficient , the greater the deviation of the ambient temperature from the rated value, the more significant the heat dissipation efficiency of the wind power generation equipment, and when the heat dissipation power of the wind power generation equipment decreases, it represents that the temperature of the wind power generation equipment will rise;

[0070] For the yaw influence coefficient When a wind turbine yaws, it is mainly driven by the yaw system. The yaw system controls the rotation of the wind turbine by driving a large gear through multiple small gears. The direction of rotation, number of rotations, and angle of the yaw system are affected by the wind speed and direction in the mountainous area. The greater the wind speed and the more varied the wind speed, the larger the yaw angle will be, and thus the number of rotations of the gears in the yaw system will also increase.

[0071] Regarding the wind speed impact index Specifically, when the wind speed in mountainous areas is high, it has a more direct impact on the vibration amplitude of the blade tip of the wind power generation equipment and the output power of the wind power generation equipment. The output power of the wind power generation equipment is directly affected by the planetary gear transmission ratio and the blade speed. Moreover, when the wind force is greater, the output power of the wind power generation equipment will gradually increase until the rated power stabilizes.

[0072] By dynamically acquiring various impact indices, the operating load of wind power equipment is obtained in a dynamic scenario, thus enabling more flexible acquisition of the operating load of wind power equipment.

[0073] Temperature smoothing value of wind power generation equipment Obtained through the following methods:

[0074]

[0075] in, For the first The maximum operating temperature of wind power equipment obtained from the day For the first The maximum operating temperature of wind power equipment obtained from the day For the first The maximum operating temperature of wind power generation equipment obtained in a day.

[0076] Specifically, the temperature smoothing value of wind power generation equipment The data was obtained by weighting the maximum temperature of wind power equipment over three consecutive days based on load weight. , , For example, divide by the corresponding load respectively. , , The factors that are inversely proportional to the load are obtained, and the average value of the three factors is calculated by summing them. Dividing this average by the corresponding load is primarily to determine that higher loads generally result in higher temperatures, which is normal and is influenced by aging. However, when the load is low but the temperature is high, it indicates equipment aging or malfunction. This is achieved by considering the operating load of the wind power equipment. The temperature data is dynamically weighted to suppress the interference of temperature fluctuations in high load periods on trend analysis, while amplifying the weight of temperature changes in low load periods, so that the smoothed temperature sequence more clearly exposes the aging of the device itself.

[0077] When the wind power generation device is running under heavy load, for example when T = 2, when T = 0.5, the device is continuously yawed by strong wind, and the planetary gear temperature gradually rises, but this temperature rise is mainly caused by short-term overload, and the weight is relatively low;

[0078] When the wind power generation device is running under normal load, for example when T = 1.2, when T = 0.833, the weight is relatively normal;

[0079] And when the wind power generation device is running under low load, when T = 0.6 and the environment is windless, at this time when T = 1.667, the weight is relatively large, which means that the internal temperature of the device is still high, so this high temperature is mainly caused by internal defects of the device.

[0080] For example, on the day when the ambient temperature is 20 degrees Celsius, when T = 55 degrees Celsius, the wind power generation device is running under load when T = 0.6;

[0081] On the day when the ambient temperature is 25 degrees Celsius, when T = 58 degrees Celsius, the wind power generation device is running under load when T = 1.2;

[0082] On the day when the ambient temperature is 30 degrees Celsius, when T = 65 degrees Celsius, the wind power generation device is running under load when T = 2.0, on the day, the temperature smoothing value of the wind power generation device is :

[0083]

[0084] Thus, it can be intuitively seen that from the day to the day to the the temperature of the wind power generation device presents a continuous decline, but is significantly affected by the actual load change.

[0085] And by eliminating the direct impact of load on temperature rise, when When the temperature rise rate is calculated, the value is automatically reduced to avoid misjudging the normal overload temperature rise as equipment aging, and when the amplified temperature rise signal is captured to capture subtle abnormalities, thereby reflecting the temperature rise caused by equipment aging.

[0086] Wind power generation equipment moving average temperature rise rate Obtained by the following way:

[0087]

[0088] Wherein, is the wind power generation equipment temperature smoothing value on the th day, is the wind power generation equipment temperature smoothing value on the th day, is the load of the wind power generation equipment on the th day, is the load influence coefficient, is the temperature compensation coefficient.

[0089] Specifically, the difference between the temperature smoothing values of the adjacent two days , is taken as the original temperature rise rate, divided by the load index on the day to eliminate the direct impact of load on temperature rise, and when the load is higher, the temperature rise rate is further reduced, and then multiplied by the load influence coefficient to adjust the weight under different loads, and the load influence coefficient is related to the wind power generation equipment running load , when the wind power generation equipment running load is large, for example, when the wind power generation equipment running load , , and finally summed with the temperature compensation term to correct the calculation deviation under extreme load;

[0090] The temperature compensation term is related to the mountainous area environment temperature at that time, and is corrected for extreme temperature difference environment. When the temperature difference in the mountainous area is large in winter, the compensation of the sudden drop of the environment temperature on the equipment surface heat dissipation is avoided to avoid misjudgment caused by the change of heat dissipation conditions. When the temperature difference in the mountainous area is small, the compensation is correspondingly reduced, and when , , when , , when , ;

[0091] Through the three ways of wind power generation load, dynamic adjustment of load weight, and temperature compensation, the real temperature rise trend caused by internal defects of the equipment is further highlighted.

[0092] The aging warning is triggered in the following way:

[0093] The aging warning is triggered in the following way:

[0094] When and , the lubrication system and cooling device of the wind power equipment are checked;

[0095] When and , the transmission connection such as the gear box and the bearing is checked and investigated;

[0096] wherein, is a dynamic threshold.

[0097] By obtaining the temperature rising trend and the cumulative temperature rising value of the wind power equipment, a graded judgment of the aging degree of the equipment is realized. Specifically, when the temperature rising rate of the wind power equipment presents an upward trend for 5 consecutive days, and the cumulative temperature rising is greater than , it means that the lubrication system and the cooling fan of the wind power equipment need to be repaired. Further, the deterioration degree of the gear box lubricating oil can be analyzed by the oil online monitoring sensor. If the viscosity change rate exceeds a large value or the iron-based abrasive particle concentration is large, the oil is immediately replaced;

[0098] When the wind power equipment presents an upward trend for three consecutive days, and the average rising temperature of the three days is greater than , it means that the planetary gear box and the bearing connection of the wind power equipment are seriously worn. Further, the acceleration signal of the gear box bearing seat can be collected by the vibration sensor to identify the gear crack or bearing peeling fault. If the characteristic frequency, such as the gear meshing frequency and the bearing fault characteristic frequency, has an amplitude exceeding three times the alarm threshold, the equipment is immediately stopped for inspection. The main shaft torque sensor data can also be checked synchronously. If the torque fluctuation coefficient is large, the problems such as the coupling bolt looseness or the gear box input shaft misalignment are investigated;

[0099] By combining the comprehensive analysis of short-term trend and medium-term trend, both the serious fault of rapid development such as accelerated temperature rise before bearing seizure and the gradual aging fault of cumulative temperature rise caused by slow deterioration of lubricating grease can be identified, providing a more explicit guide for the operation and maintenance personnel, avoiding misjudgment or omission caused by a single threshold, and reducing the risk of unplanned shutdown, thereby improving the safety and economy of the equipment operation in the mountainous wind power plant.

[0100] Dynamic threshold The adjustment method is as follows:

[0101] Obtain the temperature influence factor , and the wind speed influence factor , the yawing frequency influence factor ,

[0102] When and when , ;

[0103] When or when , .

[0104] Specifically, the influence of ambient temperature on the wind power generation equipment is more direct, when the ambient temperature is higher, the corresponding wind power generation equipment is naturally higher, therefore, when the temperature influence factor is greater than the wind speed influence factor and the yawing frequency influence factor, the temperature rise of the equipment is in a more normal condition, the threshold can be appropriately enlarged;

[0105] On the contrary, both the wind speed and the yawing frequency will more directly cause the aging of the wind power generation equipment, the more the yawing frequency, the more the wear and tear of the gear box will be intensified, and the greater the wind speed, the greater the vibration influence on each component of the wind power generation equipment, therefore, when the wind speed influence factor and the yawing influence factor are greater than the temperature influence factor, the threshold needs to be reduced, and the aging condition of the equipment can be more finely found.

[0106] The above is only an example and description of the concept of the present application, and those skilled in the art can make various modifications or supplements to the described specific embodiments or adopt similar ways to replace them, as long as they do not deviate from the concept of the present application or exceed the scope defined by the present claims, which shall belong to the protection scope of the present application.

Claims

1. A smart monitoring and maintenance management system for wind power generation equipment in mountainous areas, characterized in that, include: The data acquisition module includes a sensor unit and a storage unit; The sensor unit includes a temperature sensor for acquiring the ambient temperature in the mountainous area and the operating temperature of the wind power generation equipment. The storage unit is used to store various data related to wind power generation equipment and the mountainous environment; The operation analysis module is used to obtain the temperature rise rate of the wind power generation equipment based on various data of the wind power generation equipment and the mountain environment. It also calculates the wind power generation operating load by comprehensively considering the mountain environment temperature, the number of yaws of the wind power generation equipment, the mountain wind speed, the temperature influence coefficient, the yaw influence coefficient, and the wind speed influence coefficient. The smoothed temperature value of the wind power equipment is calculated based on the temperature of the wind power equipment over three consecutive days. The rate of temperature rise of wind power equipment is calculated by combining the difference between the temperature smoothing value of the current day and the temperature smoothing value of the adjacent day with the overall wind power operation load of the current day. The early warning trigger module triggers an aging warning based on the acquired rate of temperature increase of the wind power generation equipment, prompting maintenance personnel to carry out corresponding maintenance on the wind power generation equipment.

2. The intelligent monitoring and maintenance management system for wind power generation equipment in mountainous areas according to claim 1, characterized in that, The rate of temperature rise of the wind power generation equipment is obtained. The process is as follows: The operating load of the wind power generation equipment is calculated based on the acquired data on the wind power equipment and the mountainous environment. ; Based on the operating temperature and operating load of the wind power generation equipment Obtain temperature smoothing value of wind power generation equipment ; Based on the temperature smoothing value of wind power generation equipment Calculate and obtain the temperature rise rate of wind power generation equipment .

3. The intelligent monitoring and maintenance management system for wind power generation equipment in mountainous areas according to claim 2, characterized in that, The operating load of the wind power generation equipment Obtained through the following methods: ； in, For the first The temperature variation curve of the mountainous environment obtained by Tian To monitor the start time, For the end time of monitoring, The average temperature curve of the mountainous area over the past month. For temperature standard deviation, This is the temperature influence coefficient. For the first The number of times the wind power generation equipment yaws is obtained daily. This represents the average number of yaws by wind turbines over the past month. The standard deviation of the number of yaws of wind power generation equipment. This represents the historical maximum number of yaws for wind power generation equipment. This is the yaw effect coefficient. For the first Wind speed variation curves in mountainous areas obtained by Tian Average wind speed variation curve in mountainous areas over the past month. The standard deviation of wind speed variation This is the wind speed impact index.

4. The intelligent monitoring and maintenance management system for wind power generation equipment in mountainous areas according to claim 2, characterized in that, The temperature smoothing value of the wind power generation equipment Obtained through the following methods: ； in, For the first The maximum operating temperature of wind power equipment obtained from the day For the first The maximum operating temperature of wind power equipment obtained from the day For the first The maximum operating temperature of wind power generation equipment obtained in a day.

5. The intelligent monitoring and maintenance management system for wind power generation equipment in mountainous areas according to claim 2, characterized in that, The sliding average temperature rise rate of the wind power generation equipment Obtained through the following methods: ； in, For the first Temperature smoothing value of wind power generation equipment on a given day. For the first Temperature smoothing value of wind power generation equipment on a given day. For the first The load on the wind power generation equipment of the day, This is the load impact factor. This is the temperature compensation coefficient.

6. The intelligent monitoring and maintenance management system for wind power generation equipment in mountainous areas according to claim 5, characterized in that, The aging warning is triggered in the following ways: when and At the same time, inspect the lubrication system and heat dissipation device of the wind power generation equipment; when and When necessary, stop the machine for maintenance and troubleshoot the gearbox, bearings, and transmission connections. in, , , , , The rate of temperature increase over 5 consecutive days, This is a dynamic threshold.

7. The intelligent monitoring and maintenance management system for wind power generation equipment in mountainous areas according to claim 6, characterized in that, The dynamic threshold The adjustment method is as follows: Obtaining temperature influence factors Wind speed influencing factors Yaw frequency influencing factors , when And when hour, ; when Or when hour, 1.

Images