An Adaptive Condition Monitoring System and Method for Gearboxes of Large Megawatt Wind Turbines

Abstract

This invention belongs to the field of wind power generation, specifically disclosing an adaptive condition monitoring system and method for gearboxes of large-megawatt wind turbines. By monitoring multiple parameters including vibration, oil, temperature, and video, it collects turbine operating condition information and establishes a database corresponding to the operating condition information and vibration and temperature monitoring data. The database is trained using monitoring data obtained during normal turbine operation to determine the normal range of each monitoring data point. Based on the monitoring data collected by the data acquisition system, the data is sent to a monitoring server to determine whether the monitoring data exceeds the normal range, outputs the monitoring results, and sends the results to a remote monitoring center. The monitoring indicators are adjusted and optimized based on the monitoring data obtained by each module and the turbine's SCADA operating data. This allows for comprehensive, accurate, economical, and timely effective monitoring of the gearbox of large-megawatt wind turbines, thereby ensuring the safe and stable operation of the gearbox and greatly improving the accuracy and effectiveness of monitoring.

Description

Technical Field

[0001] This invention belongs to the field of wind power generation, specifically relating to an adaptive state monitoring system and method for gearboxes of large-megawatt wind turbines. Background Technology

[0002] The gearbox is a critical component of any wind turbine. Through the gearbox, the low-speed, high-torque kinetic energy on the turbine rotor side is converted into high-speed, low-torque kinetic energy on the generator side, making it easier for the generator to reach grid-connected speeds. Currently, wind turbines are developing towards larger megawatts, longer blades, and taller towers, increasing the cost per unit. Furthermore, large-megawatt gearboxes, due to their high technological barriers and large demand, account for a more significant proportion of the turbine's price. Moreover, gearbox malfunctions can severely impact the normal operation of the turbine, causing losses in safety and economic aspects. Therefore, accurate, timely, and effective monitoring of large-megawatt gearboxes is becoming increasingly important.

[0003] Currently, there are various monitoring methods for wind turbine gearboxes, such as SCADA data analysis, vibration monitoring, and oil level monitoring. However, the operating environment of wind turbine gearboxes is harsh and the operating conditions are complex, making it difficult to accurately and promptly grasp the gearbox's operating status using only a single monitoring method. Furthermore, wind turbine monitoring needs to be economical; many large-megawatt wind turbines are located in remote mountainous areas or offshore, and the lack of effective monitoring methods significantly increases the operation and maintenance costs of wind farms. Summary of the Invention

[0004] To overcome the shortcomings of existing technologies, the present invention aims to provide an adaptive condition monitoring system and method for gearboxes of large-megawatt wind turbines, in order to solve the problem that existing detection methods are relatively simple and it is difficult to accurately and timely grasp the operating status of gearboxes of large-megawatt wind turbines, thereby increasing the operation and maintenance costs of wind farms.

[0005] To achieve the above objectives, the present invention employs the following technical solution:

[0006] In a first aspect, the present invention provides an adaptive condition monitoring system for a large-megawatt wind turbine gearbox, comprising: a vibration monitoring module, an oil monitoring module, a video monitoring module, a temperature monitoring module, an operating condition information module, a data acquisition system, a monitoring server, and a remote monitoring center; the vibration monitoring module, the oil monitoring module, the video monitoring module, the temperature monitoring module, and the operating condition information module are all connected to the data acquisition system; the data acquisition system is connected to the monitoring server; the monitoring server is bidirectionally connected to the remote control center;

[0007] The vibration monitoring module is used to monitor the vibration of the gearbox and obtain vibration monitoring data;

[0008] The oil monitoring module is used to monitor the oil level in the gearbox and obtain oil monitoring data;

[0009] The video monitoring module is used to perform video monitoring on the gearbox and obtain video monitoring data;

[0010] The temperature monitoring module is used to monitor the temperature of the gearbox and obtain temperature monitoring data;

[0011] The operating condition information module is used to collect SCADA operating data of large-megawatt wind turbine units;

[0012] The data acquisition system is used to collect vibration monitoring data, oil monitoring data, video monitoring data, temperature monitoring data, and SCADA operation data of large-megawatt wind turbines, and to establish a database that establishes a correspondence between the SCADA operation data of large-megawatt wind turbines and the vibration monitoring data and temperature monitoring data; the monitoring server is used to perform analysis and judgment to obtain monitoring results.

[0013] The remote monitoring center is used to receive monitoring results from the monitoring server, understand the status of the wind turbines, inspect and handle the units, and take corresponding actions.

[0014] Furthermore, the vibration monitoring module, oil monitoring module, video monitoring module, temperature monitoring module, and operating condition information module transmit the monitored information to the data acquisition system. The data acquisition system then transmits the acquired data to the monitoring server. The monitoring server analyzes the acquired data to determine if any abnormal indicators are present, obtains the monitoring results, and sends the monitoring results to the remote control center. The remote control center receives the monitoring results from the monitoring server, checks and processes the unit, and takes appropriate actions.

[0015] Furthermore, the vibration monitoring module includes multiple vibration acceleration sensors, which are mounted on the gearbox, and the vibration data collected by the vibration acceleration sensors are sent to the data acquisition system in real time.

[0016] The video monitoring module includes multiple high-definition video monitors, which are mounted on a rack next to the gearbox and are rigidly connected to the rack.

[0017] Furthermore, the operating condition information module utilizes the SCADA operating data of the large-megawatt wind turbine to collect data on wind speed, power, pitch angle, gearbox oil temperature, nacelle ambient temperature, generator speed, and yaw status.

[0018] Furthermore, the data acquisition system collects data from vibration acceleration sensors, oil monitoring modules, high-definition video monitors, and SCADA systems of large-megawatt wind turbines, and transmits the collected data to the monitoring server.

[0019] Secondly, the present invention provides an adaptive state monitoring method for a large-megawatt wind turbine gearbox, and an adaptive state monitoring system for a large-megawatt wind turbine gearbox based on any one of the above-mentioned methods, comprising:

[0020] Vibration monitoring data of the gearbox is obtained by using a vibration monitoring module.

[0021] The gearbox oil level is monitored by an oil level monitoring module to obtain oil level monitoring data;

[0022] The gearbox is monitored via video monitoring module to obtain video monitoring data;

[0023] The temperature of the gearbox is monitored by a temperature monitoring module to obtain temperature monitoring data;

[0024] The unit's SCADA operating data is collected through the operating condition information module;

[0025] A corresponding database is established for the SCADA operation data of large-megawatt wind turbines, along with vibration and temperature monitoring data. The database is trained using monitoring data obtained from the normal operation of large-megawatt wind turbines to determine the normal range of each monitoring data point. Based on the monitoring data collected by the data acquisition system, the monitoring data is sent to the monitoring server. The monitoring server determines whether the monitoring data exceeds the normal range, outputs the monitoring results, and sends the results to the remote monitoring center. Based on the monitoring results, the monitoring indicators of the monitoring data obtained by each module and the SCADA operation data of the large-megawatt wind turbines are adjusted and optimized.

[0026] Furthermore, the vibration monitoring module collects the vibration acceleration of the gearbox through a vibration acceleration sensor, monitors the raw and effective values ​​in real time, and uses spectrum analysis to monitor the frequency characteristics of each fault.

[0027] The raw values ​​are data collected in real time by the vibration acceleration sensor; the effective values ​​are calculated in 10-minute cycles, and the effective vibration value is calculated every 10 minutes. The corresponding range of unit power and effective vibration value is established according to different operating conditions.

[0028] When the effective value exceeds the alarm threshold, the original data is analyzed in detail using spectrum analysis.

[0029] Furthermore, the oil monitoring module is used to analyze the content of ferromagnetic particles in the gearbox lubricating oil for oil monitoring.

[0030] The video monitoring mechanism has two modes: when the vibration acceleration sensor detects a sudden fault or external additional excitation, the video automatically records the data for 10 minutes before and after the vibration impact; or, the data is recorded in a 7-day cycle, with the data recorded in the later cycle overwriting the data recorded in the previous cycle.

[0031] The temperature monitoring data is obtained through a temperature sensor installed in the gearbox. The sampling frequency of the temperature monitoring data is consistent with the setting in SCADA, and the corresponding range of unit power and temperature is established according to different operating conditions.

[0032] Furthermore, the establishment of a corresponding database for the SCADA operation data, vibration monitoring data, and temperature monitoring data of large-megawatt wind turbines specifically includes:

[0033] Establish a database corresponding to the wind speed, power, pitch angle, generator speed, and yaw status recorded in SCADA, and the vibration monitoring and temperature monitoring data.

[0034] The temperature database mainly contains data on wind speed, power, generator speed, and temperature; and establishes the correspondence between wind speed, power, generator speed, and temperature rise.

[0035] The vibration database mainly contains data on wind speed, power, pitch angle, generator speed, and yaw state, and establishes the correspondence between wind speed, power, pitch angle, generator speed, and yaw state and vibration values.

[0036] Furthermore, the adjustment and optimization of monitoring indicators based on the monitoring results obtained from each module and the SCADA operation data of the large-megawatt wind turbine specifically includes:

[0037] The monitoring data obtained from each module and the SCADA operation data of the large-megawatt wind turbine are adaptively corrected and optimized: when abnormal indicators appear, they are checked and confirmed. If the abnormal indicator is a false alarm, the abnormal indicator of the corresponding unit is optimized and adjusted. If the abnormal indicator is a real abnormal situation, the abnormal indicator threshold is continued to be used, and the corresponding unit is checked and processed.

[0038] The present invention has at least the following beneficial effects:

[0039] 1. This invention monitors multiple parameters, including vibration, oil, temperature, and video, and collects unit operating condition information. It establishes a database corresponding to the operating condition information and vibration and temperature monitoring data. The database is trained using monitoring data obtained during normal unit operation to determine the normal range of each monitoring data point. Based on the monitoring data collected by the data acquisition system, the data is sent to a monitoring server. The server determines whether the monitoring data exceeds the normal range, outputs the monitoring results, and sends the results to a remote monitoring center. Based on the monitoring results, the monitoring indicators of each module and the SCADA operation data of the large-megawatt wind turbine are adjusted and optimized. This allows for comprehensive, accurate, economical, and timely effective monitoring of the gearbox of a large-megawatt wind turbine, ensuring the safe and stable operation of the gearbox and significantly improving the accuracy and effectiveness of monitoring.

[0040] 2. This invention sets different monitoring logics for different monitoring methods, which is scientific and reasonable, so that they can better exert their corresponding effects; a new installation logic is set for the video monitoring module, and a reasonable sampling period and data storage logic are set according to the data characteristics of different monitoring methods, which reduces the data storage pressure while ensuring sufficient monitoring data.

[0041] 3. This invention fully utilizes the data already present in the unit's SCADA system, resulting in good economic efficiency; it combines relevant parameters with unit operating condition information to establish corresponding normal operating ranges, making the judgment results more scientific and accurate; considering the operating characteristics of each unit, it adopts an adaptive method to optimize and correct the judgment indicators, reducing the probability of false alarms and increasing the accuracy of monitoring; for abnormal indicators, it performs multi-parameter fusion judgment and qualitative and quantitative analysis, greatly improving the accuracy and effectiveness of monitoring. Attached Figure Description

[0042] The accompanying drawings, which form part of this specification, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an undue limitation of the invention. In the drawings:

[0043] Figure 1 Logic diagram for adaptive adjustment and optimization of unit monitoring indicators;

[0044] Figure 2 Layout diagram of the gearbox vibration acceleration sensor;

[0045] Figure 3 Side view of the installation location of the video surveillance camera;

[0046] Figure 4 Top view of the installation location of the video surveillance system.

[0047] Reference numerals: A, First vibration acceleration sensor; B, Second vibration acceleration sensor; C, Third vibration acceleration sensor; D, Fourth vibration acceleration sensor; E, Fifth vibration acceleration sensor; F, Sixth vibration acceleration sensor; VM1, First high-definition video monitor; VM2, Second high-definition video monitor. Detailed Implementation

[0048] The present invention will now be described in detail with reference to the accompanying drawings and embodiments. It should be noted that, unless otherwise specified, the embodiments and features described herein can be combined with each other.

[0049] The following detailed description is exemplary and intended to provide further detailed explanation of the invention. Unless otherwise specified, all technical terms used in this invention have the same meaning as commonly understood by one of ordinary skill in the art. The terminology used in this invention is for describing particular embodiments only and is not intended to limit the scope of exemplary embodiments according to the invention.

[0050] Example 1

[0051] like Figure 1 As shown, an adaptive condition monitoring system for a large-megawatt wind turbine gearbox includes: a vibration monitoring module, an oil monitoring module, a video monitoring module, a temperature monitoring module, an operating condition information module, a data acquisition system, a monitoring server, and a remote monitoring center. The vibration monitoring module, oil monitoring module, video monitoring module, temperature monitoring module, and operating condition information module are all connected to the data acquisition system, transmitting the monitored information to it. The data acquisition system is connected to the monitoring server, transmitting the collected vibration monitoring data, oil monitoring data, video monitoring data, temperature monitoring data, and large-megawatt wind turbine SCADA operation data to the monitoring server. The monitoring server is bidirectionally connected to the remote control center, analyzing the collected data to determine if any abnormal indicators occur, obtaining monitoring results, and sending the monitoring results to the remote control center. The remote control center receives the monitoring results from the monitoring server, understands the wind turbine status, inspects and handles the unit, and takes appropriate actions.

[0052] Large-megawatt wind turbines are wind turbines with a capacity of 5 megawatts or more.

[0053] The vibration monitoring module includes multiple vibration acceleration sensors. The gearbox typically has 4 to 6 vibration acceleration sensors, depending on the specific internal structure of the gearbox (two-stage or three-stage transmission). Figure 2 As shown, vibration data collected by the vibration acceleration sensor is sent to the data acquisition system in real time.

[0054] The oil monitoring module is used to detect the content of ferromagnetic particles in the oil and send the results to the data acquisition system in real time.

[0055] The video monitoring module includes multiple high-definition video monitors. Two high-definition video monitors are mounted on the rack next to the gearbox: VM1 (first high-definition video monitor) and VM2 (second high-definition video monitor). These are installed on the rack axis (top view) near the impeller and on the rack axis (top view) near the generator, respectively. Figure 3 and Figure 4 As shown. To achieve effective monitoring, the high-definition video monitor must be installed on a rack because the gearbox is directly connected to the rack, and the high-definition video monitor is rigidly connected to the rack. If there is any abnormal relative movement between the two, the high-definition video monitor can record it well. However, if it is installed on the nacelle cover or main bearing, there will be huge monitoring errors, which will affect the monitoring effect.

[0056] The temperature monitoring module uses the SCADA operating data of the large-megawatt wind turbine to monitor two parameters: gearbox oil temperature and nacelle ambient temperature. This reduces the need for sensor placement, prevents redundancy, and directly utilizes the existing equipment of the unit, making it economical and practical.

[0057] The operating condition information module utilizes the SCADA operation data of large-megawatt wind turbines. The large-megawatt wind turbine data that needs to be collected includes wind speed, power, pitch angle, gearbox oil temperature, nacelle ambient temperature, generator speed, and yaw status.

[0058] The data acquisition system collects data from vibration acceleration sensors, oil monitoring modules, high-definition video monitors, and SCADA systems of large-megawatt wind turbines. It establishes a database that correlates the SCADA operation data of large-megawatt wind turbines with vibration monitoring data and temperature monitoring data, and then transmits the collected data to the monitoring server.

[0059] The monitoring server analyzes and judges the overall data, and is the main unit of monitoring and analysis;

[0060] The remote monitoring center receives monitoring results from the monitoring server, grasps the status of the wind turbines, inspects and handles the units, and takes corresponding actions.

[0061] Example 2

[0062] Gearbox failures can generally be categorized into two types: sudden failures and trending failures. Sudden failures include large pitting on tooth surfaces and broken teeth; trending failures include wear and scuffing. The effectiveness of various monitoring methods for gearbox failures is shown in the table below:

[0063] Table 1. Effectiveness of various monitoring methods for gearbox faults

[0064]

[0065] To ensure the effectiveness of gearbox operating status monitoring, this invention scientifically utilizes four monitoring methods, employing multi-parameter monitoring of gearbox faults. Furthermore, considering the independence of each unit, the monitoring indicators are adaptively optimized, exhibiting customized monitoring characteristics. Specifically:

[0066] An adaptive condition monitoring method for a large-megawatt wind turbine gearbox includes:

[0067] S1: Vibration monitoring of the gearbox is performed through the vibration monitoring module to obtain vibration monitoring data;

[0068] Vibration monitoring uses a vibration acceleration sensor in the vibration monitoring module to collect the vibration acceleration of the gearbox, monitor the raw and effective values ​​in real time, and use spectrum analysis to monitor the characteristic frequencies of various faults.

[0069] The raw values ​​are data collected in real time by the vibration acceleration sensor without any processing. When there is a sudden failure or external additional excitation, the raw values ​​will increase instantly.

[0070] The effective values ​​are primarily used for trend monitoring. Considering the data volume and feedback time, a calculation cycle of 10 minutes is used, and the vibration effective value is calculated every 10 minutes. Simultaneously, a corresponding range between unit power and vibration effective values ​​is established for different operating conditions, i.e., the normal operating range of vibration effective values ​​under a certain operating condition.

[0071] When the effective value exceeds the alarm threshold, the raw data is analyzed using spectrum analysis. Since the effective value alone cannot determine the cause of the exceedance, spectrum analysis can be used to pinpoint the fault location and formulate appropriate handling methods when faults such as gear wear or pitting occur.

[0072] S2: The gearbox oil level is monitored by the oil monitoring module to obtain oil monitoring data;

[0073] By analyzing the content of ferromagnetic particles in the gearbox lubricating oil using an oil monitoring module, the cleanliness of the oil can be confirmed, thereby assessing the overall health of the gearbox.

[0074] Since the shedding of ferromagnetic particles caused by wear, pitting, and scuffing inside the gearbox is the result of long-term accumulation, the monitoring cycle interval can be measured in hours or days. In this invention, the oil sampling and analysis cycle is selected as 1 day, that is, the gearbox oil is analyzed once a day.

[0075] S3: The gearbox is monitored via video monitoring module to obtain video monitoring data;

[0076] In this invention, video monitoring is primarily used as an auxiliary monitoring method for judgment. There are two monitoring mechanisms: when the vibration acceleration sensor detects a sudden malfunction or external additional excitation, i.e., a large vibration impact, the video automatically records data for 10 minutes before and after the vibration impact, and this data is permanently saved. Since video data occupies a very large storage space, under normal circumstances, data is recorded in a 7-day cycle, with data from the later cycle overwriting data from the previous cycle. For example, if the video monitoring system records 7 days of data from the 1st to the 7th of a month, the data from the 1st to the 7th is automatically overwritten after the data from the 8th to the 14th is recorded, and is no longer retained. This ensures that up to 14 days of original video data can be saved. If there are any abnormalities, the data can be reviewed. Additionally, videos that need to be saved can also be manually saved.

[0077] S4: The temperature of the gearbox is monitored through the temperature monitoring module to obtain temperature monitoring data;

[0078] Temperature monitoring data is obtained directly from the SCADA data of the large-megawatt wind turbine, via a temperature sensor installed inside the gearbox. Simultaneously, the temperature rise data is analyzed using the difference between the gearbox oil temperature and the nacelle ambient temperature. The sampling frequency of the temperature monitoring data is consistent with the settings in the SCADA system. Similar to vibration monitoring, temperature monitoring also establishes corresponding ranges between unit power and temperature for different operating conditions.

[0079] S5: Collects SCADA operation data of large-megawatt wind turbines through the operating condition information module.

[0080] S6: Establish a corresponding database for SCADA operation data of large-megawatt wind turbines, vibration monitoring data, and temperature monitoring data; train the database with monitoring data obtained from the normal operation of large-megawatt wind turbines to obtain the normal range of each monitoring data; based on the monitoring data collected by the data acquisition system, send the monitoring data to the monitoring server, determine whether the monitoring data exceeds the normal range, output the monitoring results, send the monitoring results to the remote monitoring center, and adjust and optimize the monitoring indicators of the monitoring data obtained by each module and the SCADA operation data of large-megawatt wind turbines based on the monitoring results;

[0081] A database corresponding to the wind speed, power, pitch angle, generator speed, and yaw status recorded in SCADA is established, along with vibration and temperature monitoring data. This means that within the same time period, these sets of data are saved and recorded accordingly to facilitate subsequent analysis and judgment of historical data. The database is trained using monitoring data obtained during normal unit operation to determine the normal range for each monitoring data point.

[0082] The temperature database primarily contains data on wind speed, power, generator speed, and temperature. A correspondence between wind speed, power, and generator speed and temperature rise is established.

[0083] The vibration database primarily contains data on wind speed, power, pitch angle, generator speed, and yaw state. It establishes the correspondence between these parameters and vibration values. Furthermore, different combinations of these parameters can be used to analyze vibration conditions. For example, by combining wind speed, pitch angle, and yaw state, at a certain wind speed, the unit may be yawing while simultaneously adjusting the pitch. Analyzing the vibration under these conditions will reveal that the vibration values ​​are higher than usual, necessitating measures to prevent false alarms.

[0084] like Figure 1 As shown, based on the monitoring results, the monitoring indicators of each module and the SCADA operation data of the large-megawatt wind turbine are adaptively corrected and optimized: when abnormal indicators appear, they are checked and confirmed. If the abnormal indicator is a false alarm, the abnormal indicator of the corresponding unit is optimized and adjusted. If the abnormal indicator is a real abnormal situation, the abnormal indicator threshold is continued to be used, and the corresponding unit is checked and processed.

[0085] Through the above methods, the goal of adaptively optimizing and correcting the parameters of the wind turbine units is achieved, making the corresponding thresholds more consistent with the actual situation of the unit. This design fully considers the actual operating conditions of wind turbine units, that is, each unit is unique, and different geographical locations and wind resource conditions will result in different operating characteristics, and thus different related threshold parameters. Through such adaptive adjustment and optimization, the probability of false alarms is reduced, while increasing the accuracy of judgment.

[0086] S7: Judgment of abnormal indicators of multi-parameter fusion;

[0087] Based on the operating characteristics of the gearbox, the parameters selected in this invention are not isolated but have an inherent mechanistic connection. For an abnormal indicator of a certain parameter, anomalies are sought in other parameters to further determine the cause of the abnormal indicator, and qualitative and quantitative analysis is performed. This judgment logic greatly improves the accuracy and effectiveness of monitoring.

[0088] Due to the different locations and wind conditions of each unit, their annual operating status will vary. Therefore, each unit is optimized and adjusted based on the actual inspection results to achieve self-adaptation.

[0089] The various monitoring indicators are cross-referenced and integrated. For example, in cases of abnormally high temperatures, the specific causes of the temperature rise can be analyzed through oil and vibration analysis.

[0090] As is known from common technical knowledge, this invention can be implemented through other embodiments that do not depart from its spirit or essential characteristics. Therefore, the disclosed embodiments described above are merely illustrative in all respects and are not the only ones. All modifications within the scope of this invention or its equivalents are included in this invention.

[0091] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A method for adaptive state monitoring of a gearbox in a large-megawatt wind turbine, characterized in that, include: The system includes a vibration monitoring module, an oil level monitoring module, a video monitoring module, a temperature monitoring module, a working condition information module, a data acquisition system, a monitoring server, and a remote monitoring center. The vibration monitoring module, oil level monitoring module, video monitoring module, temperature monitoring module, and working condition information module are all connected to the data acquisition system. The data acquisition system is connected to the monitoring server. The monitoring server has a bidirectional connection to the remote control center. The vibration monitoring module is used to monitor the vibration of the gearbox and obtain vibration monitoring data; The oil monitoring module is used to monitor the oil level in the gearbox and obtain oil monitoring data; The video monitoring module is used to perform video monitoring on the gearbox and obtain video monitoring data; The temperature monitoring module is used to monitor the temperature of the gearbox and obtain temperature monitoring data; The operating condition information module is used to collect SCADA operating data of large-megawatt wind turbine units; The data acquisition system is used to collect vibration monitoring data, oil monitoring data, video monitoring data, temperature monitoring data, and SCADA operation data of large-megawatt wind turbines, and to establish a database that establishes a correspondence between the SCADA operation data of large-megawatt wind turbines and the vibration monitoring data and temperature monitoring data; the monitoring server is used to perform analysis and judgment to obtain monitoring results. The remote monitoring center is used to receive monitoring results from the monitoring server; Vibration monitoring data of the gearbox is obtained by using a vibration monitoring module. The gearbox oil level is monitored by an oil level monitoring module to obtain oil level monitoring data; The gearbox is monitored via video monitoring module to obtain video monitoring data; The temperature of the gearbox is monitored by a temperature monitoring module to obtain temperature monitoring data; The operating condition information module collects SCADA operation data of large-megawatt wind turbine units; A corresponding database is established for the SCADA operation data of large-megawatt wind turbines, along with vibration and temperature monitoring data. The database is trained using monitoring data obtained from the normal operation of large-megawatt wind turbines to obtain the normal range of each monitoring data. Based on the monitoring data collected by the data acquisition system, the monitoring data is sent to the monitoring server. The monitoring server determines whether the monitoring data exceeds the normal range, outputs the monitoring results, and sends the monitoring results to the remote monitoring center. Based on the monitoring results, the monitoring indicators of the monitoring data obtained by each module and the SCADA operation data of the large-megawatt wind turbines are adjusted and optimized. The vibration monitoring module collects the vibration acceleration of the gearbox through a vibration acceleration sensor, monitors the raw and effective values ​​in real time, and uses spectrum analysis to monitor the frequency characteristics of each fault. The raw values ​​are data collected in real time by the vibration acceleration sensor; the effective values ​​are calculated in 10-minute cycles, and the effective vibration value is calculated every 10 minutes. The corresponding range of unit power and effective vibration value is established according to different operating conditions. When the effective value exceeds the alarm threshold, the original data is analyzed in detail using spectrum analysis.

2. The adaptive state monitoring method for a large-megawatt wind turbine gearbox according to claim 1, characterized in that, The vibration monitoring module, oil monitoring module, video monitoring module, temperature monitoring module, and operating condition information module transmit the monitored information to the data acquisition system. The data acquisition system then transmits the acquired data to the monitoring server. The monitoring server analyzes the acquired data to determine if any abnormal indicators are present, obtains the monitoring results, and sends the monitoring results to the remote control center. The remote control center receives the monitoring results from the monitoring server, checks and processes the unit, and takes appropriate actions.

3. The adaptive state monitoring method for a large-megawatt wind turbine gearbox according to claim 1, characterized in that, The vibration monitoring module includes multiple vibration acceleration sensors, which are mounted on the gearbox. The vibration data collected by the vibration acceleration sensors is sent to the data acquisition system in real time. The video monitoring module includes multiple high-definition video monitors, which are mounted on a rack next to the gearbox and are rigidly connected to the rack.

4. The adaptive state monitoring method for a large-megawatt wind turbine gearbox according to claim 3, characterized in that, The operating condition information module utilizes the SCADA operating data of the large-megawatt wind turbine, and the collected data of the large-megawatt wind turbine includes wind speed, power, pitch angle, gearbox oil temperature, nacelle ambient temperature, generator speed and yaw status.

5. The adaptive state monitoring method for a large-megawatt wind turbine gearbox according to claim 4, characterized in that, The data acquisition system collects data from vibration acceleration sensors, oil monitoring modules, high-definition video monitors, and SCADA systems of large-megawatt wind turbines, and transmits the collected data to the monitoring server.

6. The adaptive state monitoring method for a large-megawatt wind turbine gearbox according to claim 1, characterized in that, The oil monitoring module is used to analyze the content of ferromagnetic particles in the gearbox lubricating oil for oil monitoring. The video monitoring mechanism has two modes: when the vibration acceleration sensor detects a sudden fault or external additional excitation, the video automatically records the data for 10 minutes before and after the vibration impact; or, the data is recorded in a 7-day cycle, with the data recorded in the later cycle overwriting the data recorded in the previous cycle. The temperature monitoring data is obtained through a temperature sensor installed in the gearbox. The sampling frequency of the temperature monitoring data is consistent with the setting in SCADA, and the corresponding range of unit power and temperature is established according to different operating conditions.

7. The adaptive state monitoring method for a large-megawatt wind turbine gearbox according to claim 1, characterized in that, The establishment of a corresponding database for SCADA operation data, vibration monitoring data, and temperature monitoring data of large-megawatt wind turbines specifically includes: Establish a database corresponding to the wind speed, power, pitch angle, generator speed, and yaw status recorded in SCADA, and the vibration monitoring and temperature monitoring data. The temperature database mainly contains data on wind speed, power, generator speed, and temperature; and establishes the correspondence between wind speed, power, generator speed, and temperature rise. The vibration database mainly contains data on wind speed, power, pitch angle, generator speed, and yaw state, and establishes the correspondence between wind speed, power, pitch angle, generator speed, and yaw state and vibration values.

8. The adaptive state monitoring method for a large-megawatt wind turbine gearbox according to claim 1, characterized in that, The adjustment and optimization of monitoring indicators based on the monitoring results obtained from each module and the SCADA operation data of the large-megawatt wind turbine specifically includes: The monitoring data obtained from each module and the SCADA operation data of the large-megawatt wind turbine are adaptively corrected and optimized: when abnormal indicators appear, they are checked and confirmed. If the abnormal indicator is a false alarm, the abnormal indicator of the corresponding unit is optimized and adjusted. If the abnormal indicator is a real abnormal situation, the abnormal indicator threshold is continued to be used, and the corresponding unit is checked and processed.

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