Remote monitoring method for multi-drive variable pitch control of wind driven generator

Abstract

The invention discloses a remote monitoring method for multi-drive variable pitch control of a wind driven generator, and relates to the technical field of remote control of wind power generation equipment.The method comprises the steps that after system recognition and authority verification are carried out, response time delay, deviation angles, torque fluctuation rates and over-temperature trigger rates of all drivers are collected, driving behavior indexes are constructed, and a first qualified driving unit is judged; calculating a driving behavior difference coefficient based on the response delay, the error rate and the alarm frequency, and identifying a second qualified driving unit; monitoring a collaborative execution behavior, constructing a multi-drive collaborative offset index, and judging response consistency; and if the cooperation is abnormal, starting deep closed-loop intervention, remotely issuing a fine tuning instruction, collecting response starting and recovery time, a wind speed curve and the like, calculating a remote control dissipation coefficient, and evaluating a regulation effect. According to the method, state grading identification and accurate remote intervention of the multi-drive system are realized, and the operation stability and intelligent level of the wind power system are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of remote control of wind power generation equipment, and in particular to a remote monitoring method for multi-drive variable pitch control of a wind generator. Background Art

[0002] With the continuous growth of installed wind power capacity, wind turbines are becoming increasingly complex and intelligent. The pitch control system, a key subsystem for wind turbines to efficiently capture wind energy and operate safely, has a direct impact on the turbine's output efficiency and service life due to its operational stability and response consistency.

[0003] Currently, mainstream medium and large wind turbines mostly use a multi-drive variable pitch structure, whereby independent motor drive units are deployed on a single blade or multiple blades to achieve angle adjustment and balance wind load stress. However, due to differences in transmission inertia, communication delays, uneven electrical loads, and asynchronous execution responses among multiple drivers, errors in variable pitch control execution can easily accumulate, resulting in inconsistent pitch angles, which can lead to potential risks such as reduced energy efficiency, amplified vibration, and even blade failure.

[0004] Traditional control strategies primarily rely on fixed tolerance thresholds, periodic diagnostics, and alarms for management. These strategies lack the ability to monitor and dynamically adjust the coordinated response of multiple drives in real time, making them difficult to adapt to complex operating conditions such as fluctuating wind speeds, aging drives, or unstable communication links. Furthermore, most existing systems rely on local response mechanisms and are unable to effectively integrate remote policy push, closed-loop data feedback, and fine-tuned control processes, limiting operational efficiency and system robustness. Summary of the Invention

[0005] In view of the deficiencies of the prior art, the present invention provides a remote monitoring method for multi-drive pitch control of a wind turbine to solve the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: a remote monitoring method for multi-drive variable pitch control of a wind turbine, characterized in that it includes the following steps: Step 1: Identify the wind turbine pitch drive channel and its device information through the system module, verify the control authority, and collect the response delay ti and maximum allowable deviation angle of each drive. , torque fluctuation rate Mvar and over-temperature threshold trigger rate Twarn, combined with the weighted coefficient to calculate the initial driving behavior index Gdrive, and compared with the driving performance threshold Gth to determine whether the current drive is qualified. If qualified, it is marked as the first qualified drive unit. If unqualified, a strategy is given; Step 2: Extract the control instruction response data of the first qualified drive unit within the specified operation cycle; collect the response delay tdelay, instruction execution error rate Err, and alarm number Na, construct the drive behavior difference coefficient Dctrl, and compare and analyze it with the drive behavior tolerance threshold Dth to determine whether the current drive behavior characteristics are normal. If normal, mark the second qualified drive unit; if abnormal, apply a strategy; Step 3: Monitor the linkage execution behavior of the second qualified drive unit within the target collaborative control cycle; collect the instantaneous offset , the driver load fluctuation degree Ld and the response propagation difference value Ds, construct the multi-driver collaborative offset index Cmulti, and compare and analyze it with the consistency threshold Cth to determine whether the driver collaborative response is stable. If it is unstable, the deep closed-loop intervention mechanism is activated; Step 4: Start the deep closed-loop intervention mechanism and generate remote fine-tuning control instructions. After executing the instructions, collect the actual response start time tact, stable recovery time tcorr, wind speed change curve V(t) and expected wind speed curve Vtexp, calculate the remote control dissipation coefficient Cloop, and compare and analyze it with the control tolerance threshold RCth to determine whether the strategy adjustment is effective. If not, output the "control failure" record label and enter the manual review or remote diagnosis process.

[0007] Preferably, step one includes: S11. Scan the pitch drive channels of deployed wind turbines in the "Wind Turbine Operation Center - Wind Turbine Operation" module; obtain the device number, access port, and region identifier of each drive unit; connect to the configured "Settings - Region Manager" and "Settings - User Management" modules to verify user operation permissions and drive controllability. S12: For each identified drive, call the underlying communication interface to automatically collect the control parameters of the operating status: response delay ti, maximum allowable deviation angle , torque fluctuation rate Mvar and over-temperature threshold trigger rate Twarn.

[0008] Preferably, step one further comprises: S13. Enter the "Settings - Original Parameter Settings" module and load the default drive behavior template applicable to the current wind turbine model; extract the weighted coefficients w1, w2, w3 and w4 of the corresponding drive model from the database, and perform adaptive adjustment. After dimensionless processing, calculate and obtain the initial drive behavior index Gdrive

[0009] S14, by presetting the driving performance threshold Gth, and comparing and analyzing the initial driving behavior index Gdrive with the driving performance threshold Gth, obtaining a first evaluation result includes: When the initial driving behavior index Gdrive is less than the driving performance threshold Gth, it indicates that the current drive is in a qualified state and is marked as the first qualified driving unit and continuously monitored; When the initial driving behavior index Gdrive ≥ the driving performance threshold Gth, it indicates that the current drive is in an unqualified state and there are response differences and load imbalance risks between the drives. The first early warning instruction is triggered and the first strategy is generated: execute the pre-correction instruction, fine-tune the response delay, angle deviation, volatility or temperature parameters, and recalculate after correction until the initial driving behavior index Gdrive < the driving performance threshold Gth.

[0010] Preferably, step 2 includes: S21, extracting control instruction response data of the first qualified driving unit within a specified operation cycle; S211. Record the control instruction issuing timestamp tcom and the corresponding feedback timestamp tfeed through the command log module and the operation data module to obtain the response delay tdelay; S212, obtaining a command execution error rate Err by comparing the execution result fed back by the pitch drive unit with the command record; S213. Read all alarm record entries triggered by the drive unit within the target cycle through the system "alarm center", including alarm events of over-temperature, stall and abnormal current, and obtain the alarm number Na.

[0011] Preferably, step 2 further includes: S22, constructing the driving behavior difference coefficient Dctrl by dimensionlessly processing the acquired response delay tdelay, instruction execution error rate Err, and alarm number Na; S23, by presetting the driving behavior tolerance threshold Dth, and comparing and analyzing the driving behavior difference coefficient Dctrl with the driving behavior tolerance threshold Dth, obtaining a second evaluation result includes: When the driving behavior difference coefficient Dctrl is less than the driving behavior tolerance threshold Dth, it indicates that the current driver behavior characteristics are normal and is marked as the second qualified driving unit. It is then allowed to enter the next step of unified control and deviation identification process for continuous monitoring. When the driving behavior difference coefficient Dctrl is less than the driving behavior tolerance threshold Dth, it indicates that the current driver behavior characteristics are abnormal, and there is a risk of control execution fluctuation and potential loss of step, triggering the second early warning instruction and generating the second strategy: executing temporary intervention operations: parameter refresh, delay suppression and sub-channel switching; and then recalculating until the driving behavior difference coefficient Dctrl is less than the driving behavior tolerance threshold Dth.

[0012] Preferably, step three includes: S31. Call the "Fan Operation Center - Command Queue" and "Settings - Regional Speed ​​Control Encryption" modules to monitor the linkage execution behavior of the second qualified drive unit within the target collaborative control cycle; S311, call the built-in angle encoder and rotary potentiometer device of the driver to obtain the set pitch angle J and actual execution perspective Z's time series data; by comparing with the command control record, the corresponding value is extracted using the time synchronization matching algorithm to obtain the instantaneous offset ; S312. Using a torque sensor device integrated in the driver control system, collect instantaneous load change curves of the multiple drivers when wind conditions fluctuate; obtain the fluctuation amplitude and variance per unit time, and combine this with the rated working load of the driver to obtain the driver load fluctuation degree Ld; S313. Analyze the response event queue data of the underlying controller through the control response start and end time logs recorded by the drive control system; compare the response start time difference and action completion time difference of multiple drivers to obtain the response diffusion range between the drivers, and express it as the response propagation difference value Ds in the form of the difference standard deviation.

[0013] Preferably, step three further includes: S32, by obtaining the instantaneous offset , the driver load fluctuation degree Ld and the response propagation difference value Ds are dimensionlessly processed to construct the multi-driver cooperative offset index Cmulti; S33: By presetting a consistency threshold Cth, and comparing and analyzing the multi-drive cooperative offset index Cmulti with the consistency threshold Cth, a third evaluation result is obtained, including: When the multi-drive collaborative offset index Cmulti < the consistency threshold Cth, it indicates that the drive collaborative response is stable and continuously monitored; When the multi-drive collaborative offset index Cmulti ≥ consistency threshold Cth, it indicates that the drive collaborative response is unstable, triggering the third warning instruction and generating the third strategy: for the second qualified drive unit, automatically perform synchronous refresh of the pitch angle setting, call the underlying communication interface to re-issue the standard pitch control template to each drive, and refresh the control parameter cache to make the initial execution boundary consistent; adjust the motor output upper limit or delayed response strategy of the relatively lagging drive, and buffer the load difference through dynamic current limit or target angle offset compensation; re-collect the latest instantaneous offset , the driver load fluctuation degree Ld and the response propagation difference value Ds are recalculated. If the multi-driver collaborative offset index Cmulti is still ≥ the consistency threshold Cth, the deep closed-loop intervention mechanism is started.

[0014] Preferably, step four includes: S41, start a deep closed-loop intervention mechanism, call the "command log" and "user operation log" modules by the system, record the parameter adjustment history and strategy implementation record corresponding to the current warning driver; for the driver with a cooperative offset exceeding the threshold, generate a remote fine-tuning control instruction; S411, delay response compensation fine-tuning is performed, the instruction processing priority of the target driver in the regional communication network is dynamically adjusted, the execution cycle beat is shortened, and the linkage imbalance caused by delayed response is alleviated; S412, pitch angle smoothing adjustment is performed, the angle control curve is optimized, continuous fluctuations are suppressed, and the target angle change rate is adjusted through a slope limiter; S413, current fluctuation reduction is performed, the current jitter section in the current drive control loop is identified, the system is dynamically switched to the voltage stabilization mode, and the overshoot and short-time load peak are reduced.

[0015] Preferably, step four further comprises: S42, after executing the remote fine-tuning control instruction, the actual effective time point of the fine-tuning instruction is monitored through the programmable logic controller (PLC) interrupt recording mechanism of the state feedback interface built-in the driver body; the system compares the control instruction issuing time with the time when the "state change flag" of the driver feedback first changes, and obtains the response actual start time tact; S43, with the help of the real-time running state monitoring module embedded in the main control system, the time point when the drive response reaches the steady state interval is judged and recorded in combination with the dynamic trend of the pitch angle change rate and the servo current fluctuation amplitude of the drive output parameters, as the stable recovery time tcorr; S44, the wind speed data is measured in real time by the three-cup wind speed sensor installed at the blade root of the cabin top, and a time sequence is generated in combination with the acquisition time stamp to obtain the wind speed change curve V(t); S45, according to historical operation data, meteorological forecast data and wind speed trend of adjacent wind turbine groups, an expected wind speed curve Vtexp is generated.

[0016] Preferably, step four further comprises: S46, by obtaining the response actual start time tact, the stable recovery time tcorr, the wind speed change curve V(t) and the expected wind speed curve Vtexp, after non-dimensional processing, the remote control dissipation coefficient Cloop is calculated and obtained

[0017] S47, by presetting the control tolerance threshold RCth and comparing and analyzing the remote control dissipation coefficient Cloop with the control tolerance threshold RCth, a fourth evaluation result is obtained, including: When the remote control dissipation coefficient Cloop is less than the control tolerance threshold RCth, it indicates that the strategy adjustment is effective, and continuous monitoring is performed; When the remote control dissipation coefficient Cloop ≥ the control tolerance threshold RCth, it indicates that the strategy adjustment is invalid, triggering the fourth warning instruction and generating the fourth strategy: outputting the "control failure" record label and entering the manual review or remote diagnosis process.

[0018] The present invention provides a remote monitoring method for wind turbine multi-drive pitch control, which has the following beneficial effects: (1) This remote monitoring method for wind turbine multi-drive pitch control, by constructing the initial drive behavior index Gdrive and introducing a multi-dimensional parameter fusion model including response delay, angle deviation, torque fluctuation rate and over-temperature trigger rate, can accurately identify whether the drive meets the operating requirements, achieve early warning and pre-correction of fault boundary drive units, and significantly improve the operational reliability of the pitch control system.

[0019] (2) This remote monitoring method for wind turbine multi-drive pitch control uses three elements: response delay, command execution error rate, and alarm number to construct the drive behavior difference coefficient Dctrl. Combined with the set tolerance threshold, it realizes the quantitative evaluation of control accuracy and execution stability, timely detects potential out-of-step drives, and effectively suppresses the fluctuation transmission in the control chain.

[0020] (3) This remote monitoring method for wind turbine multi-drive pitch control introduces a multi-drive collaborative offset index Cmulti, which integrates instantaneous offset, load fluctuation and response propagation difference to achieve real-time consistency evaluation of the linkage control status of multiple drives. It has the ability of dynamic intervention and execution boundary adjustment, which can reduce the risk of reduced wind energy capture efficiency due to collaborative imbalance.

[0021] (4) This remote monitoring method for wind turbine multi-drive pitch control calculates the control dissipation coefficient Cloop through remote fine-tuning control and feedback data, and compares it with the preset control tolerance threshold to judge the execution effect after the strategy adjustment, realize the closed-loop evaluation of the effectiveness of the control strategy and the intelligent triggering of the failure process, and greatly improve the refinement and intelligence level of remote control. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 The figure is a schematic diagram of the steps of the remote monitoring method for multi-drive and pitch control of a wind turbine according to the present invention. DETAILED DESCRIPTION

[0023] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0024] Example 1 See also Figure 1 The present invention provides a remote monitoring method for multi-drive pitch control of a wind turbine, comprising the following steps: Step 1: Identify the wind turbine pitch drive channel and its device information through the system module, verify the control authority, and collect the response delay ti and maximum allowable deviation angle of each drive. , torque fluctuation rate Mvar and over-temperature threshold trigger rate Twarn, combined with the weighted coefficient to calculate the initial driving behavior index Gdrive, and compared with the driving performance threshold Gth to determine whether the current drive is qualified. If qualified, it is marked as the first qualified drive unit. If unqualified, a strategy is given; Step 2: Extract the control instruction response data of the first qualified drive unit within the specified operation cycle; collect the response delay tdelay, instruction execution error rate Err, and alarm number Na, construct the drive behavior difference coefficient Dctrl, and compare and analyze it with the drive behavior tolerance threshold Dth to determine whether the current drive behavior characteristics are normal. If normal, mark the second qualified drive unit; if abnormal, apply a strategy; Step 3: Monitor the linkage execution behavior of the second qualified drive unit within the target collaborative control cycle; collect the instantaneous offset , the driver load fluctuation degree Ld and the response propagation difference value Ds, construct the multi-driver collaborative offset index Cmulti, and compare and analyze it with the consistency threshold Cth to determine whether the driver collaborative response is stable. If it is unstable, the deep closed-loop intervention mechanism is activated; Step 4: Start the deep closed-loop intervention mechanism and generate remote fine-tuning control instructions. After executing the instructions, collect the actual response start time tact, stable recovery time tcorr, wind speed change curve V(t) and expected wind speed curve Vtexp, calculate the remote control dissipation coefficient Cloop, and compare and analyze it with the control tolerance threshold RCth to determine whether the strategy adjustment is effective. If not, output the "control failure" record label and enter the manual review or remote diagnosis process.

[0025] In this embodiment, by constructing a multi-level evaluation index system, including the drive behavior index Gdrive, the behavior difference coefficient Dctrl, the coordinated offset index Cmulti and the remote control dissipation coefficient Cloop, the full-process quantitative analysis and closed-loop optimization of the wind turbine multi-drive pitch control system from individual drive performance to multi-machine coordinated consistency are achieved, which significantly improves the accuracy of system fault identification, the stability of linkage control and the effectiveness of remote control.

[0026] Example 2 This embodiment is explained in Example 1, please refer to Figure 1 ,Specifically, step one includes: S11. Scan the pitch drive channels of deployed wind turbines in the "Wind Turbine Operation Center - Wind Turbine Operation" module; obtain the device number, access port, and region identifier of each drive unit; connect to the configured "Settings - Region Manager" and "Settings - User Management" modules to verify user operation permissions and drive controllability. S12: For each identified driver, call the underlying communication interface to automatically collect the control parameters of the operating status: response delay ti, which is used to characterize the response delay of the driver after receiving the control command; maximum allowable deviation angle , which reflects the maximum tolerance of the driver's angle control; the torque fluctuation rate Mvar, which indicates the severity of the torque change during the pitch change process; the over-temperature threshold trigger rate Twarn, which indicates the trigger probability of the device temperature exceeding the safety threshold.

[0027] In this embodiment, by introducing an automatic identification and authority verification mechanism for the wind turbine pitch drive channel in step one, and combining real-time collection and analysis of key operating parameters such as response delay, maximum allowable deviation angle, torque fluctuation rate and over-temperature trigger rate, a rapid assessment and controllability confirmation of the basic performance status of each drive is achieved, effectively improving the equipment access efficiency and operation safety assurance capabilities in the system initialization phase.

[0028] Example 3 This embodiment is explained in Example 2, please refer to Figure 1 Specifically, step one also includes: S13. Enter the "Settings - Original Parameter Settings" module and load the default drive behavior template applicable to the current wind turbine model; extract the weighted coefficients w1, w2, w3, and w4 of the corresponding drive model from the database, perform adaptive adjustment, and calculate the initial drive behavior index Gdrive after dimensionless processing. The formula is as follows:

[0029] The weighted coefficients w1, w2, w3 and w4 are obtained by: Based on the historical operation data and multi-operating condition parameter archive of the multi-drive pitch controller of the wind turbine operation center, the response delay ti and the maximum allowable deviation angle are obtained by statistical analysis. , torque fluctuation rate and over-temperature threshold trigger rate The system uses machine learning algorithms and system identification methods to optimize parameters and dynamically adjust the weight distribution of each parameter based on the degree of impact of key indicators. The system also combines the adaptive adjustment mechanisms of the "Settings - Original Parameter Settings" and "Settings - User Management" modules, references industry control models and equipment manufacturer performance feedback, and determines a reasonable range of weighted coefficients. Through multiple iterations of verification and expert review, the weighted coefficients are ensured to scientifically reflect the contribution of drive performance to the overall drive behavior index (Gdrive), improving the accuracy and sensitivity of drive status assessments and guiding the classification management and subsequent maintenance decisions of drive units. ,Response delay directly affects the timeliness and synchronization of pitch action, ,and is a key control indicator, which needs to be given a higher weight; ,angle deviation affects the fan power and mechanical load, and the weight is moderate to balance the control accuracy and dynamic response; ,Torque fluctuation reflects the change of mechanical load, which is important but relatively indirect and has a slightly lower weight; ,Equipment temperature safety is related to equipment life and failure risk, and a higher weight ensures safe operation; S14, by presetting the driving performance threshold Gth, and comparing and analyzing the initial driving behavior index Gdrive with the driving performance threshold Gth, obtaining a first evaluation result includes: When the initial driving behavior index Gdrive is less than the driving performance threshold Gth, it indicates that the current drive is in a qualified state and is marked as the first qualified driving unit and continuously monitored; When the initial driving behavior index Gdrive ≥ the driving performance threshold Gth, it indicates that the current drive is in an unqualified state and there are response differences and load imbalance risks between the drives. The first early warning instruction is triggered and the first strategy is generated: execute the pre-correction instruction, fine-tune the response delay, angle deviation, volatility or temperature parameters, and recalculate after correction until the initial driving behavior index Gdrive < the driving performance threshold Gth.

[0030] The drive performance threshold Gth is determined by statistically analyzing performance tests and historical operating data from a large number of wind turbine pitch drives under various operating conditions and environmental conditions. The distribution ranges of key control parameters, such as response delay, angle deviation, torque fluctuation, and temperature trigger rate, are extracted. This is then combined with the dynamic response characteristics and fault tolerance of the drive control system to determine a reasonable performance threshold. This threshold is developed based on industry-related drive performance standards, performance indicators and maintenance feedback provided by equipment manufacturers, and expert experience to accurately reflect the health of the drive, promptly identify potential performance degradation or abnormal risks, and ensure the safe and stable operation of the pitch drive system.

[0031] In this embodiment, by introducing the calculation mechanism of the driving behavior index Gdrive in step one, and combining it with the weighting coefficient and driving performance threshold Gth extracted from the database, quantitative evaluation and hierarchical management of the operating status of each driver are achieved. This not only improves the accuracy of driver health status identification, but also automatically triggers the parameter fine-tuning strategy when an anomaly is found, effectively reducing the response differences and load unevenness risks between drivers, and providing a stable basic support for subsequent collaborative control.

[0032] Example 4 This embodiment is explained in Example 3, please refer to Figure 1 ,Specifically, step 2 includes: S21, extracting control instruction response data of the first qualified driving unit within a specified operation cycle; S211. Record the control instruction issuance timestamp tcom and the corresponding feedback timestamp tfeed through the command log module and the operation data module to obtain the response delay tdelay. Use the event timestamp comparison mechanism to automatically extract the start and completion times of the execution event through an industrial communication protocol interface such as OPC-UA or Modbus, and calculate the average delay. S212. Compare the execution result fed back by the pitch drive unit (e.g., target pitch angle vs. actual pitch angle) with the command record to obtain the command execution error rate Err. Invoke the driver's built-in state feedback interface or PLC data frame, combine it with the "operation data" module in the system, and calculate the deviation rate based on the error judgment rule (e.g., an allowable deviation of ±0.2°). S213. Through the system "alarm center", read all alarm record entries triggered by the drive unit within the target cycle, including overtemperature, stall and current abnormality alarm events, and obtain the number of alarms Na; relying on the fan SCADA system, through event log analysis and statistics, combined with the alarm code and drive number, the alarm frequency of the corresponding drive is extracted.

[0033] In this embodiment, the response delay, instruction execution error rate, and alarm frequency of the first qualified drive unit within a specified operating cycle are systematically collected and analyzed through step 2. Automated and accurate data acquisition and comparison are achieved with the help of industrial communication protocols and SCADA systems. This can comprehensively reflect the actual operating behavior and abnormal conditions of the drive, effectively improve the accuracy and real-time performance of identifying drive behavior differences, and provide reliable data support for the rapid positioning and precise intervention of subsequent abnormal drives.

[0034] Example 5 This embodiment is explained in Example 4. Please refer to Figure 1 Specifically, step 2 also includes: S22. After dimensionless processing, the obtained response delay tdelay, instruction execution error rate Err, and alarm number Na are used to construct the drive behavior difference coefficient Dctrl. The formula is as follows:

[0035] Where a1, a2 and a3 represent weight coefficients; The setting method of a1, a2 and a3 is as follows: Through statistical analysis of the response delay, instruction execution error rate and alarm frequency of a large number of wind turbine drive units under different operating conditions, combined with the impact of abnormal drive behavior on system performance and safety in actual operation, a method combining multivariate regression analysis and expert experience is used to determine the reasonable distribution range of the weight coefficient; referring to the dynamic performance standards, fault warning models and manufacturer's technical parameters of wind turbine control systems, combined with historical fault cases and real-time monitoring data, the weight coefficient is dynamically adjusted to enhance the accuracy and sensitivity of risk identification. The purpose of setting the weight coefficient is to scientifically reflect the comprehensive contribution of various indicators to the differences in drive behavior, guide the formulation of fault diagnosis and control optimization strategies, and ensure the stable and safe operation of the system; ,Response delay directly affects the timeliness of driver control and is the key factor for driver behavior ,difference, with the highest weight; ,The execution error rate affects the control accuracy and system stability, and its weight is moderate; ,The number of alarms reflects the frequency of abnormal events in the drive, which is important but relatively indirect and has a low weight; S23, by presetting the driving behavior tolerance threshold Dth, and comparing and analyzing the driving behavior difference coefficient Dctrl with the driving behavior tolerance threshold Dth, obtaining a second evaluation result includes: When the driving behavior difference coefficient Dctrl is less than the driving behavior tolerance threshold Dth, it indicates that the current driver behavior characteristics are normal and is marked as the second qualified driving unit. It is then allowed to enter the next step of unified control and deviation identification process for continuous monitoring. When the driving behavior difference coefficient Dctrl is less than the driving behavior tolerance threshold Dth, it indicates that the current driver behavior characteristics are abnormal, and there is a risk of control execution fluctuation and potential loss of step, triggering the second early warning instruction and generating the second strategy: executing temporary intervention operations: parameter refresh, delay suppression and sub-channel switching; and then recalculating until the driving behavior difference coefficient Dctrl is less than the driving behavior tolerance threshold Dth.

[0036] The drive behavior tolerance threshold Dth is obtained by collecting a large amount of response data from the first qualified drive units under various control instructions and operating cycles, statistically analyzing the normal fluctuation range of response delay, instruction error rate, and alarm frequency, and combining the actual operating characteristics and fault tolerance mechanism of the drive control system to determine a reasonable tolerance limit for behavioral differences. Drawing on relevant industrial control tolerance standards, system debugging data, and expert evaluations, this threshold is formulated to scientifically measure the behavioral consistency of the drive, promptly detect control execution fluctuations or the risk of loss of step, and ensure the normality and coordination of the drive unit's behavioral characteristics.

[0037] In this embodiment, by constructing a drive behavior difference coefficient, Dctrl, and dynamically comparing it with a preset tolerance threshold, Dth, the driver's comprehensive performance in terms of response delay, execution error, and alarm frequency can be accurately quantified, enabling early identification and early warning of abnormal drive behavior. Combined with temporary intervention strategies such as parameter refresh, delay suppression, and sub-channel switching, this effectively reduces control fluctuations and the risk of loss of step, ensuring the stability and safety of the wind turbine pitch drive system and improving the reliability of overall coordinated control.

[0038] Example 6 This embodiment is explained in Example 5, please refer to Figure 1 ,Specifically, step three includes: S31. Call the "Fan Operation Center - Command Queue" and "Settings - Regional Speed ​​Control Encryption" modules to monitor the linkage execution behavior of the second qualified drive unit within the target collaborative control cycle; S311, call the built-in angle encoder and rotary potentiometer device of the driver to obtain the set pitch angle J and actual execution perspective Z's time series data; by comparing with the command control record, the corresponding value is extracted using the time synchronization matching algorithm to obtain the instantaneous offset ; S312. Using a torque sensor device integrated in the driver control system, collect instantaneous load change curves of the multiple drivers when wind conditions fluctuate; obtain the fluctuation amplitude and variance per unit time, and combine this with the rated working load of the driver to obtain the driver load fluctuation degree Ld; S313. Analyze the response event queue data of the underlying controller through the control response start and end time logs recorded by the drive control system; compare the response start time difference and action completion time difference of multiple drivers to obtain the response diffusion range between the drivers, and express it as the response propagation difference value Ds in the form of the difference standard deviation.

[0039] In this embodiment, the instantaneous offset, load fluctuation, and response propagation difference of the second qualified drive unit are monitored in multiple dimensions to accurately quantify and dynamically evaluate the coordinated execution behavior of multiple drivers. By utilizing a time synchronization matching algorithm and multi-sensor data fusion, the coordinated deviations between drivers under varying wind conditions are effectively captured, improving the coordinated stability and response consistency of the wind turbine pitch control system, and enhancing the safety and reliability of the overall operation.

[0040] Example 7 This embodiment is explained in Example 6, please refer to Figure 1 Specifically, step three also includes: S32, by obtaining the instantaneous offset , the driver load fluctuation degree Ld and the response propagation difference value Ds, after dimensionless processing, the multi-driver cooperative offset index Cmulti is constructed, and the formula is as follows:

[0041] Where s1, s2 and s3 represent weight coefficients; The setting method of s1, s2 and s3 is to extract the instantaneous offset by systematically analyzing a large amount of monitoring data and control records of various types of wind turbines under various operating conditions. , the coupling relationship between the driver load fluctuation degree Ld and the response propagation difference value Ds and the system stability; combined with the structural characteristics of the wind turbine control system, the response behavior of the drive device and the characteristic distribution of typical coordinated instability events, the principal component analysis and regression modeling method are used to determine the relative importance of each parameter in the determination of coordinated offset. At the same time, referring to the actual deployment feedback and expert experience of the mainstream wind turbine control platform, the various coefficients are corrected and dynamically updated to ensure the accuracy of identification of coordinated imbalance and the adaptability of the control strategy under different models and wind conditions. The setting of this weighted coefficient is intended to improve the representativeness and risk prediction ability of the coordinated offset index, and enhance the stable operation guarantee capability of the multi-drive closed-loop control system; ,pitch angle offset is the most direct linkage execution deviation indicator, which has a significant impact on the aerodynamic efficiency and control consistency of the wind turbine and has the highest weight; , reflects the coordinated response stability of the actual load of the driver under wind disturbance, characterizes the matching effect of multiple driving states, and has a moderate weight; , describes the temporal consistency of different drive response behaviors, plays an auxiliary role in fast linkage judgment, and has a slightly lower weight; S33: By presetting a consistency threshold Cth, and comparing and analyzing the multi-drive cooperative offset index Cmulti with the consistency threshold Cth, a third evaluation result is obtained, including: When the multi-drive collaborative offset index Cmulti < the consistency threshold Cth, it indicates that the drive collaborative response is stable and continuously monitored; When the multi-drive collaborative offset index Cmulti ≥ consistency threshold Cth, it indicates that the drive collaborative response is unstable, triggering the third warning instruction and generating the third strategy: for the second qualified drive unit, automatically perform synchronous refresh of the pitch angle setting, call the underlying communication interface to re-issue the standard pitch control template to each drive, and refresh the control parameter cache to make the initial execution boundary consistent; adjust the motor output upper limit or delayed response strategy of the relatively lagging drive, and buffer the load difference through dynamic current limit or target angle offset compensation; re-collect the latest instantaneous offset , the driver load fluctuation degree Ld and the response propagation difference value Ds are recalculated. If the multi-driver collaborative offset index Cmulti is still ≥ the consistency threshold Cth, the deep closed-loop intervention mechanism is started.

[0042] The consistency threshold Cth is obtained by statistically analyzing the distribution characteristics of instantaneous offsets, load fluctuations, and response propagation differences between drivers based on historical operation records and on-site monitoring data of multi-driver collaborative control. A reasonable response consistency threshold is determined in combination with the dynamic coupling performance and load balancing capabilities of the wind turbine's overall control system. This threshold is formulated with reference to relevant technical specifications for multi-driver collaborative control in the wind power industry, feedback from system integrators, and opinions from field experts to effectively identify stability issues in driver collaborative responses, thereby ensuring the coordinated synchronization of the multi-driver system and the safe operation of the wind turbine.

[0043] In this embodiment, a multi-drive coordination offset index is constructed to quantitatively evaluate the stability of the driver linkage response. Combined with a consistency threshold determination mechanism, this approach enables timely identification of abnormal driver coordination states. Automatically and synchronously updating the pitch angle setting and dynamically adjusting the drive response strategy effectively mitigates load variations and response lags, significantly improving the coordination and control accuracy of the multi-drive system and ensuring the stable operation and safety of the wind turbine pitch control system under complex operating conditions.

[0044] Example 8 This embodiment is explained in Example 7, please refer to Figure 1 ,Specifically, step four includes: S41. Initiate a deep closed-loop intervention mechanism. The system calls the "command log" and "user operation log" modules to record the parameter adjustment history and strategy implementation records corresponding to the current warning driver. For drivers whose coordinated offset items exceed the threshold, remote fine-tuning control instructions are generated. S411. Perform delay response compensation fine-tuning to dynamically adjust the target driver's instruction processing priority in the regional communication network, shorten the execution cycle, and alleviate the linkage imbalance caused by the response delay; S412, performing smooth pitch angle adjustment, optimizing the angle control curve, suppressing continuous fluctuations, and adjusting the target angle change rate through a slope limiter; S413. Reduce current fluctuations, identify the current jitter section in the current drive control loop, and dynamically switch to the voltage regulation mode to reduce overshoot and short-term load peaks.

[0045] In this embodiment, by starting the deep closed-loop intervention mechanism, the system automatically records the parameter adjustment and strategy implementation history, and combines remote fine-tuning control instructions to achieve precise adjustment of the driver response delay, pitch angle fluctuation and current jitter, effectively alleviating the linkage imbalance and load peak problems, and significantly improving the dynamic response capability and operational stability of the wind turbine pitch system, ensuring the safe and reliable operation of the equipment.

[0046] Example 9 This embodiment is explained in Example 8, please refer to Figure 1 Specifically, step four also includes: S42. After executing the remote fine-tuning control command, the actual effective time of the fine-tuning command is monitored through the programmable logic controller (PLC) interrupt recording mechanism of the state feedback interface built into the driver body; the system compares the time when the control command is issued with the time when the "state change flag" feedback from the driver first changes, and obtains the actual start time tact of the response; S43, using the real-time operation status monitoring module embedded in the main control system, combined with the dynamic trends of the driver output parameters pitch angle change rate and servo current fluctuation amplitude, determine and record the time point when the drive response reaches the steady-state range as the stable recovery time tcorr; S44, using a three-cup wind speed sensor installed at the blade root on top of the nacelle to measure wind speed data in real time, and generating a time series based on the acquisition timestamp to obtain a wind speed change curve V(t); S45. Generate an expected wind speed curve Vtexp based on historical operating data, weather forecast data, and wind speed trends of adjacent wind turbine groups.

[0047] In this embodiment, by real-time monitoring of the response start-up time and stable recovery time of the fine-tuning control instruction, combining the actual wind speed change curve collected by the cabin wind speed sensor with the expected wind speed curve generated based on historical and meteorological data, accurate tracking and evaluation of the dynamic response process of the wind turbine pitch drive is achieved, significantly improving the timeliness and accuracy of the remote fine-tuning strategy, and effectively ensuring the coordination of wind turbine operation and wind energy utilization efficiency.

[0048] Example 10 This embodiment is explained in Example 9, please refer to Figure 1 Specifically, step four also includes: S46. The remote control dissipation coefficient Cloop is calculated by dimensionlessly processing the obtained actual start-up time tact, stable recovery time tcorr, wind speed change curve V(t), and expected wind speed curve Vtexp. The formula is as follows:

[0049] Where, Represents the disturbance compensation weight value; Disturbance compensation weight value Setting method: Through long-term monitoring and modeling analysis of the response behavior of the wind turbine control system under different wind speed change scenarios, the quantitative coupling relationship between wind speed disturbance and driver response stability is extracted, focusing on the actual wind speed curve and expected wind speed trajectory The degree of deviation affects the closed-loop adjustment efficiency of the system. During the experiment, the system evaluated the correlation between the drive response time delay and the disturbance intensity under different wind field conditions such as sudden wind, wind shear, and gusts, and combined with factors such as wind turbine model, control strategy differences, and drive load capacity to comprehensively establish a wind speed disturbance impact model. Based on this model, the disturbance compensation weight coefficient is set through error sensitivity analysis, typical case backtracking, expert experience scoring, and statistical optimization methods. , to dynamically quantify the weight of wind speed deviation in the remote feedback closed-loop efficiency evaluation; Under moderate wind disturbances, wind speed deviation affects control efficiency by approximately 20%–30%. A weight of 0.25 can better reflect this impact while taking into account the system's robustness to sudden wind conditions and the stability requirements of the resource scheduling strategy. The numerical basis includes operational error analysis, historical deviation propagation assessment results, and industry wind energy dynamic response tolerance recommendations. S47. By presetting the control tolerance threshold RCth and comparing and analyzing the remote control dissipation coefficient Cloop with the control tolerance threshold RCth, obtaining a fourth evaluation result includes: When the remote control dissipation coefficient Cloop is less than the control tolerance threshold RCth, it means that the strategy adjustment is effective and continuous monitoring is required; When the remote control dissipation coefficient Cloop ≥ the control tolerance threshold RCth, it indicates that the strategy adjustment is invalid, triggering the fourth warning instruction and generating the fourth strategy: outputting the "control failure" record label and entering the manual review or remote diagnosis process.

[0050] The control tolerance threshold RCth is obtained by collecting the execution effect and response data of the wind turbine remote fine-tuning control instructions over a long period of time, statistically analyzing the error range of the actual start-up time, stable recovery time and wind speed curve, and combining the dynamic compensation capability and disturbance suppression effect of the control system to determine a reasonable control effect tolerance limit. With reference to the technical standards for remote control of wind turbines, system tuning feedback and expert experience, this threshold is formulated to accurately evaluate the effectiveness of the remote control strategy, promptly identify the risk of strategy adjustment failure, and ensure the accuracy of remote control and the stability of wind turbine operation.

[0051] In this embodiment, by calculating the remote control dissipation coefficient and comparing it with the preset tolerance threshold, the effectiveness of the fine-tuning control strategy can be objectively evaluated, the failure of the strategy adjustment can be identified in a timely manner, an early warning can be automatically triggered, and a manual review or remote diagnosis process can be initiated, thereby significantly improving the intelligent management level and fault response efficiency of the wind turbine pitch drive system, and ensuring the safe and stable operation of the wind turbine.

[0052] The threshold is set to facilitate comparison. The size of the threshold depends on the amount of sample data and the number of bases set by technicians in this field for each set of sample data; as long as it does not affect the proportional relationship between the parameter and the quantized value.

[0053] The above formulas are obtained by collecting a large amount of data and performing software simulation, and a formula close to the actual value is selected. The coefficients in the formula are set by those skilled in the art according to actual conditions. The above is only a preferred specific implementation method of the present invention, but the protection scope of the present invention is not limited to this. Any technician familiar with this technical field, within the technical scope disclosed by the present invention, can make equivalent replacements or changes based on the technical solution and inventive concept of the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A remote monitoring method for wind turbine multi-drive pitch control, characterized in that: The following steps are involved: Step 1: Identify the wind turbine pitch drive channel and its device information through the system module, verify the control authority, and collect the response delay ti and maximum allowable deviation angle of each drive. , torque fluctuation rate Mvar and over-temperature threshold trigger rate Twarn, combined with the weighted coefficient to calculate the initial driving behavior index Gdrive, and compared with the driving performance threshold Gth to determine whether the current drive is qualified. If qualified, it is marked as the first qualified drive unit. If unqualified, a strategy is given; Step 2: Extract the control instruction response data of the first qualified drive unit within the specified operation cycle; collect the response delay tdelay, instruction execution error rate Err, and alarm number Na, construct the drive behavior difference coefficient Dctrl, and compare and analyze it with the drive behavior tolerance threshold Dth to determine whether the current drive behavior characteristics are normal. If normal, mark the second qualified drive unit; if abnormal, apply a strategy; Step 3: Monitor the linkage execution behavior of the second qualified drive unit within the target collaborative control cycle; collect the instantaneous offset , the driver load fluctuation degree Ld and the response propagation difference value Ds, construct the multi-driver collaborative offset index Cmulti, and compare and analyze it with the consistency threshold Cth to determine whether the driver collaborative response is stable. If it is unstable, the deep closed-loop intervention mechanism is activated; Step 4: Start the deep closed-loop intervention mechanism and generate remote fine-tuning control instructions. After executing the instructions, collect the actual response startup time tact, stable recovery time tcorr, wind speed change curve V(t), and expected wind speed curve Vtexp. Calculate the remote control dissipation coefficient Cloop and compare it with the control tolerance threshold RCth to determine whether the strategy adjustment is effective. If not, output the "control failure" record label and enter the manual review or remote diagnosis process.

2. The remote monitoring method for wind turbine multi-drive pitch control according to claim 1, characterized in that: Step one includes: S11. Scan the pitch drive channels of deployed wind turbines in the "Wind Turbine Operation Center - Wind Turbine Operation" module. Obtain the device number, access port, and region ID of each drive unit. Connect to the configured "Settings - Region Manager" and "Settings - User Management" modules to verify user operation permissions and drive controllability. S12: For each identified drive, call the underlying communication interface to automatically collect the control parameters of the operating status: response delay ti, maximum allowable deviation angle , torque fluctuation rate Mvar and over-temperature threshold trigger rate Twarn.

3. The remote monitoring method for wind turbine multi-drive pitch control according to claim 2, characterized in that: Step 1 also includes: S13. Enter the "Settings - Original Parameter Settings" module and load the default drive behavior template applicable to the current wind turbine model; extract the weighted coefficients w1, w2, w3 and w4 of the corresponding drive model from the database, and perform adaptive adjustment. After dimensionless processing, calculate and obtain the initial drive behavior index Gdrive S14, by presetting the driving performance threshold Gth, and comparing and analyzing the initial driving behavior index Gdrive with the driving performance threshold Gth, obtaining a first evaluation result includes: When the initial driving behavior index Gdrive is less than the driving performance threshold Gth, it indicates that the current drive is in a qualified state and is marked as the first qualified driving unit and continuously monitored; When the initial driving behavior index Gdrive ≥ the driving performance threshold Gth, it indicates that the current drive is in an unqualified state and there are response differences and load imbalance risks between the drives. The first early warning instruction is triggered and the first strategy is generated: execute the pre-correction instruction, fine-tune the response delay, angle deviation, volatility or temperature parameters, and recalculate after correction until the initial driving behavior index Gdrive < the driving performance threshold Gth.

4. The remote monitoring method for wind turbine multi-drive pitch control according to claim 3, characterized in that: Step 2 includes: S21, extracting control instruction response data of the first qualified driving unit within a specified operation cycle; S211. Record the control instruction issuing timestamp tcom and the corresponding feedback timestamp tfeed through the command log module and the operation data module to obtain the response delay tdelay; S212, obtaining a command execution error rate Err by comparing the execution result fed back by the pitch drive unit with the command record; S213. Through the system "alarm center", read all alarm record entries triggered by the drive unit within the target cycle, including overtemperature, stall, and current abnormality alarm events, and obtain the alarm count Na.

5. The remote monitoring method for wind turbine multi-drive pitch control according to claim 4, characterized in that: Step 2 also includes: S22, constructing the driving behavior difference coefficient Dctrl by dimensionlessly processing the acquired response delay tdelay, instruction execution error rate Err, and alarm number Na; S23, by presetting the driving behavior tolerance threshold Dth, and comparing and analyzing the driving behavior difference coefficient Dctrl with the driving behavior tolerance threshold Dth, obtaining a second evaluation result includes: When the driving behavior difference coefficient Dctrl is less than the driving behavior tolerance threshold Dth, it indicates that the current driver behavior characteristics are normal and is marked as the second qualified driving unit. It is then allowed to enter the next step of unified control and deviation identification process for continuous monitoring. When the driving behavior difference coefficient Dctrl is less than the driving behavior tolerance threshold Dth, it indicates that the current driver behavior characteristics are abnormal, and there is a risk of control execution fluctuation and potential loss of step, triggering the second early warning instruction and generating the second strategy: executing temporary intervention operations: parameter refresh, delay suppression and sub-channel switching; and then recalculating until the driving behavior difference coefficient Dctrl is less than the driving behavior tolerance threshold Dth.

6. The remote monitoring method for wind turbine multi-drive pitch control according to claim 5, characterized in that: Step three includes: S31. Call the "Fan Operation Center - Command Queue" and "Settings - Regional Speed ​​Control Encryption" modules to monitor the linkage execution behavior of the second qualified drive unit within the target collaborative control cycle; S311, call the built-in angle encoder and rotary potentiometer device of the driver to obtain the set pitch angle J and actual execution perspective Z's time series data; by comparing with the command control record, the corresponding value is extracted using the time synchronization matching algorithm to obtain the instantaneous offset ; S312. Using a torque sensor device integrated in the driver control system, collect instantaneous load change curves of the multiple drivers when wind conditions fluctuate; obtain the fluctuation amplitude and variance per unit time, and combine this with the rated working load of the driver to obtain the driver load fluctuation degree Ld; S313. Analyze the response event queue data of the underlying controller through the control response start and end time logs recorded by the drive control system; compare the response start time difference and action completion time difference of multiple drivers to obtain the response diffusion range between the drivers, and express it as the response propagation difference value Ds in the form of the difference standard deviation.

7. The remote monitoring method for wind turbine multi-drive pitch control according to claim 6, characterized in that: Step three also includes: S32, by obtaining the instantaneous offset , the driver load fluctuation degree Ld and the response propagation difference value Ds are dimensionlessly processed to construct the multi-driver cooperative offset index Cmulti; S33: By presetting a consistency threshold Cth, and comparing and analyzing the multi-drive cooperative offset index Cmulti with the consistency threshold Cth, a third evaluation result is obtained, including: When the multi-drive collaborative offset index Cmulti < the consistency threshold Cth, it indicates that the drive collaborative response is stable and continuously monitored; When the multi-drive collaborative offset index Cmulti ≥ consistency threshold Cth, it indicates that the drive collaborative response is unstable, triggering the third warning instruction and generating the third strategy: for the second qualified drive unit, automatically perform synchronous refresh of the pitch angle setting, call the underlying communication interface to re-issue the standard pitch control template to each drive, and refresh the control parameter cache to make the initial execution boundary consistent; adjust the motor output upper limit or delayed response strategy of the relatively lagging drive, and buffer the load difference through dynamic current limit or target angle offset compensation; re-collect the latest instantaneous offset , the driver load fluctuation degree Ld and the response propagation difference value Ds are recalculated. If the multi-driver collaborative offset index Cmulti is still ≥ the consistency threshold Cth, the deep closed-loop intervention mechanism is started.

8. The remote monitoring method for wind turbine multi-drive pitch control according to claim 7, characterized in that: Step 4 includes: S41. Initiate a deep closed-loop intervention mechanism. The system calls the "Command Log" and "User Operation Log" modules to record the parameter adjustment history and policy implementation records corresponding to the current warning driver. For drivers whose coordinated offset items exceed the threshold, remote fine-tuning control instructions are generated. S411. Perform delay response compensation fine-tuning to dynamically adjust the target driver's instruction processing priority in the regional communication network, shorten the execution cycle, and alleviate the linkage imbalance caused by the response delay; S412, performing smooth pitch angle adjustment, optimizing the angle control curve, suppressing continuous fluctuations, and adjusting the target angle change rate through a slope limiter; S413. Reduce current fluctuations, identify the current jitter section in the current drive control loop, and dynamically switch to the voltage regulation mode to reduce overshoot and short-term load peaks.

9. The remote monitoring method for wind turbine multi-drive pitch control according to claim 8, characterized in that: Step 4 also includes: S42. After executing the remote fine-tuning control command, the actual time point of the fine-tuning command taking effect is monitored through the programmable logic controller (PLC) interrupt recording mechanism of the state feedback interface built into the driver body. The system compares the time when the control command is issued with the time when the "state change flag" feedback from the driver first changes, and obtains the actual start time of the response tact. S43, using the real-time operation status monitoring module embedded in the main control system, combined with the dynamic trends of the driver output parameters pitch angle change rate and servo current fluctuation amplitude, determine and record the time point when the drive response reaches the steady-state range as the stable recovery time tcorr; S44, using a three-cup wind speed sensor installed at the blade root on top of the nacelle to measure wind speed data in real time, and generating a time series based on the acquisition timestamp to obtain a wind speed change curve V(t); S45. Generate an expected wind speed curve Vtexp based on historical operating data, weather forecast data, and wind speed trends of adjacent wind turbine groups.

10. The remote monitoring method for wind turbine multi-drive pitch control according to claim 9, characterized in that: Step 4 also includes: S46, calculating and obtaining the remote control dissipation coefficient Cloop by dimensionlessly processing the obtained actual response start time tact, stable recovery time tcorr, wind speed change curve V(t), and expected wind speed curve Vtexp; S47. By presetting the control tolerance threshold RCth and comparing and analyzing the remote control dissipation coefficient Cloop with the control tolerance threshold RCth, obtaining a fourth evaluation result includes: When the remote control dissipation coefficient Cloop is less than the control tolerance threshold RCth, it means that the strategy adjustment is effective and continuous monitoring is required; When the remote control dissipation coefficient Cloop ≥ the control tolerance threshold RCth, it indicates that the strategy adjustment is invalid, triggering the fourth warning instruction and generating the fourth strategy: outputting the "control failure" record label and entering the manual review or remote diagnosis process.

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