A fan safety control protection method based on blade vibration signals

Abstract

This invention provides a wind turbine safety control and protection method based on blade vibration signals. It uses blade acceleration sensors to acquire acceleration signals during blade operation, extracts frequency domain features and time domain features from the acceleration signals, and compares the feature values ​​with fault thresholds. When the threshold is exceeded, a warning or fault alarm is issued. By connecting the blade acceleration signals to the wind turbine control system, they directly participate in the control and protection of the unit, significantly improving the unit's risk resistance and safety.

Description

Technical Field

[0001] This invention relates to the field of wind turbine monitoring, and in particular to a wind turbine safety control and protection method based on blade vibration signals. Background Technology

[0002] Blades are crucial components of wind turbine generator sets. As turbine capacity increases, so does the length and weight of the blades. Due to manufacturing issues and inherent structural problems, blades often experience abnormal vibrations and impeller imbalances. In severe cases, this can lead to serious accidents such as tower sweeping and tower collapse. Therefore, protecting the turbine's safety based on blade monitoring is paramount. The most common method for blade monitoring is to assess blade health by monitoring vibrations in the flapping and swaying directions. However, among various blade condition monitoring methods, simply monitoring blade health and providing early warnings does not provide real-time safety protection for the entire turbine. While some wind turbine control and protection systems use nacelle acceleration signals to analyze blade vibration signals, identifying and protecting against turbine anomalies, the effective information available from nacelle acceleration data regarding the impeller surface is limited and cannot comprehensively reflect the vibration status of the blades and impeller surface.

[0003] The following methods are also commonly used for wind turbine safety protection:

[0004] I. Blade Vibration Monitoring. Current blade vibration monitoring solutions use independent early warning systems to alert the unit to abnormalities. However, when a problem actually occurs in the unit, the unit cannot perform its protection functions and cannot cope with major wind turbine accidents.

[0005] II. Nacelle Acceleration Signal Identification Method. Using nacelle acceleration for blade anomaly detection can only obtain partial information, such as blade 3P vibration and overtone abnormal vibration. It is not comprehensive enough for obtaining vibration information of the blade and impeller surface, and cannot achieve comprehensive protection.

[0006] III. Video Monitoring Methods. Video monitoring methods can only identify surface fault features on blades, resulting in insufficient fault identification coverage.

[0007] IV. Audio Recognition Method. Audio recognition monitoring methods are difficult to use due to severe ambient noise. Summary of the Invention

[0008] To address the shortcomings of existing technologies, this invention provides a wind turbine safety control and protection method based on blade vibration signals. It uses blade acceleration sensors to acquire acceleration signals during blade operation, extracts frequency domain and time domain features from the acceleration signals, and compares the feature values ​​with fault thresholds. If the threshold is exceeded, a warning or fault alarm is triggered. By integrating the blade acceleration signals into the wind turbine control system, they directly participate in the unit's control and protection, significantly improving the unit's resilience and safety.

[0009] The technical solution adopted by this invention to solve its technical problem is: to provide a wind turbine safety control and protection method based on blade vibration signals, comprising the following steps:

[0010] S1. Arrange acceleration sensors on the blades to acquire blade acceleration signals during blade operation;

[0011] S2. Extract frequency domain and time domain features from the blade acceleration signal to obtain the first four frequencies of each blade, as well as the kurtosis and RMS value of each blade in the time domain.

[0012] S3. Obtain unit operation safety parameters based on the blade simulation model;

[0013] S4. Write the first four frequencies of each blade, the kurtosis value and RMS value of each blade in the time domain, and the unit operation safety parameters into the wind turbine controller.

[0014] S5, the wind turbine controller calculates the first four frequencies of each blade in real time, as well as the kurtosis and RMS values ​​of each blade in the time domain, and compares them with the unit's operating safety parameters, and issues warnings or fault alarms in real time.

[0015] In step S2, frequency domain feature extraction specifically involves performing FFT processing on the blade acceleration time-domain signal to obtain the blade vibration frequency-domain signal. Feature quantities representing blade vibration in the frequency-domain signal are then extracted to obtain the first four frequencies of the unit, i.e., the first-order frequencies. f 1. Second-order frequency f 2. Third-order frequency f 3rd and fourth order frequencies f 4.

[0016] In step S2, the time-domain feature extraction specifically involves directly calculating the time-domain signal of the blade acceleration and extracting intuitive representations of the blade vibration intensity, including RMS value and kurtosis value.

[0017] The unit operation safety parameters mentioned in step S3 include the theoretical safety threshold of acceleration corresponding to the first-order frequency. a A1 The theoretical safety threshold for acceleration corresponding to the second-order frequency a A2The theoretical safety threshold for acceleration corresponding to the third-order frequency a A3 The theoretical safety threshold for acceleration corresponding to the fourth order frequency a A4 RMS0 (RMS safety value) and kurtosis safety value K 0.

[0018] Step S5 specifically includes the following processes:

[0019] S5.1 For each leaf, in [ f 1-10%× f 1, f 1 + 10% × f 1]、

[0020] [ f 2-10%× f 2, f 2 + 10% × f 2]、[ f 3-10%× f 3, f 3 + 10% × f 3] and [ f 4-10%× f 4, f 4 + 10% × f Within the range of 4], the maximum amplitude and its corresponding frequency are automatically found in four ranges, and are denoted as [ ]. f i-1m , a Ai-jm ]、[ f i-2m , a Ai-jm ]、[ f i-3m , a Ai-jm ]and[ f i-4m , a Ai-jm ];in i Indicates the blade number. j Indicates the frequency order;

[0021] S5.2 For each blade, trigger and record the event as follows:

[0022] If (| f i-1m - f 1|) / f If 1 > 0.01, then event A1 is triggered; if (| f i-2m - f 2|) / f If 2 > 0.01, then event A2 is triggered; if (| f i-3m - f 3|) / f If 3 > 0.01, then event A3 is triggered; if (| f i-4m - f 4|) / f If 4 > 0.01, then event A4 is triggered;

[0023] if a Ai-1m >0.6× a A1 If, then event B1 is triggered; if a Ai-2m >0.6× a A2 Then event B2 is triggered; if a Ai-3m >0.6× a A3 Then event B3 is triggered; if a Ai-4m >0.6× a A4 Then event B4 is triggered;

[0024] if a Ai-1m >0.8× a A1 If, then event C1 is triggered; if a Ai-2m >0.8× a A2 Then event C2 is triggered; if a Ai-3m >0.85× a A3 Then event C3 is triggered; if a Ai-4m >0.8× a A4 Then event C4 is triggered;

[0025] If the average frequency difference between the three blades exceeds 5% of the initial parameter value... If so, event FP1 is triggered;

[0026] If the average difference in amplitude among the three blades exceeds 10% of the safety threshold. If so, event AP1 will be triggered;

[0027] S5.3. Early warning and control protection shall be performed according to the following logic:

[0028] a. If any one of the events A1, A2, A3 and A4 is triggered 10 times in a day, a blade modal frequency abnormality warning will be issued, prompting the unit to conduct further analysis and investigation of the blade data;

[0029] b. If events A1, A2, A3 and A4 are triggered simultaneously, and the ambient temperature is below 0, a blade icing warning will be issued, and the unit will execute an event shutdown action.

[0030] c. If any one of the events B1, B2, B3 and B4 is triggered 3 times within 1 hour, a warning of excessive blade vibration will be issued, the unit will operate at 60% of its rated power, and further analysis and investigation of the blade vibration data of the unit will be required.

[0031] d. If any one of the events C1, C2, C3 and C4 is triggered 3 times within 1 hour, a severe blade vibration fault will be indicated, the unit will execute shutdown protection, a blade excessive vibration fault will be indicated, and the unit will conduct further analysis and troubleshooting of blade vibration data.

[0032] e. If either event FP1 or event AP1 is triggered, a unit impeller imbalance warning will be executed, prompting the unit to check the zero-point consistency of the three blades.

[0033] f. When the value RMS i >0.6 RMS 0 or K i >0.6 K At 0:00, the unit issued a warning for excessive time-domain vibration, limiting its power output to 60% of its rated power; among which... RMS i For the first i RMS value of the blade, K i For the first i Kurtosis value of a leaf blade;

[0034] g, when RMS i >0.8 RMS 0 or K i >0.8 K At 0:00, the unit indicated a severe time-domain vibration fault and initiated a shutdown protection action.

[0035] The beneficial effects of this invention based on its technical solution are as follows:

[0036] This invention provides a wind turbine safety control and protection method based on blade vibration signals. By integrating blade acceleration signals into the wind turbine control system, a blade vibration-based control and protection system is implemented. The system obtains time-domain and frequency-domain characteristic values ​​of blade vibration through the blade acceleration signals, achieving unit safety protection. Peak-finding within a fixed frequency range is used to obtain the first four modal frequencies of blade operation and their corresponding amplitudes. Autocorrelation and cross-correlation analysis of the first four modal frequencies are used to evaluate the blade's operating status. When thresholds are exceeded, the unit executes warning, power limiting, and fault shutdown actions. Frequency analysis of the blade acceleration signals, combined with ambient temperature signals, identifies blade icing and enables event-based shutdown protection. Time-domain feature value extraction from the blade acceleration signals identifies blade vibration intensity, and shutdown protection control is implemented for severe blade vibration, protecting unit safety. This invention can provide real-time early warning and protection against abnormal blade conditions, such as icing, structural damage, impeller imbalance, and severe abnormal blade vibration, improving unit safety performance. Attached Figure Description

[0037] Figure 1 This is a simplified model diagram of blade vibration. Detailed Implementation

[0038] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0039] The principle of this invention:

[0040] The simplified model of blade vibration can be reduced to a simply supported beam model, as shown in the simplified model below. Figure 1 As shown.

[0041] The vibration equation for this model is:

[0042] (1),

[0043] in:

[0044] X — the displacement of the blade movement;

[0045] M—mass of the blade;

[0046] K—Stiffness of the vibration system, which is related to the stiffness of the blade and the stiffness of the pitch system;

[0047] By deriving from equation (1), the natural frequency of the vibration of this system can be obtained as:

[0048] (2),

[0049] Therefore, it can be seen from equation (2) that the main factors affecting the natural frequency of the system vibration are the system stiffness and the mass of the blade. During operation, the blade often generates abnormal excitation frequencies due to severe wind conditions and blade airfoil issues. If the vibration is too large, it can also cause serious problems for the blade.

[0050] In addition, the acceleration energy during blade vibration can be evaluated using acceleration time-domain kurtosis, RMS value, etc.

[0051] Therefore, by identifying changes in blade frequency and the intensity of vibration energy, the following fault identification methods can be used for protection:

[0052] When the blades freeze, the mass of the blades increases, and the natural frequency of the blade vibration changes. The changes can be identified and controlled for protection.

[0053] When blades are damaged or structures fall off, the natural frequency of the blade's vibration changes. This change can be identified and controlled for protection.

[0054] When the impeller is unbalanced, it will exhibit abnormal vibration characteristics of 3P, which can be identified and used for early warning and protection.

[0055] When the blade vibration time-domain characteristics are severe, in order to protect the unit's safety, a shutdown control protection will be implemented when the vibration exceeds the safety threshold.

[0056] Based on the foregoing analysis, this invention provides a wind turbine safety control and protection method based on blade vibration signals, comprising the following steps:

[0057] S1. Arrange acceleration sensors on the blades to acquire blade acceleration signals during blade operation.

[0058] S2. Extract frequency and time domain features from the blade acceleration signal to obtain the first four frequencies of each blade, as well as the kurtosis and RMS value of each blade in the time domain.

[0059] Specifically, the time-domain signal of blade acceleration is processed by FFT to obtain the frequency-domain signal of blade vibration. The feature quantities representing the blade vibration in the frequency-domain signal are extracted to obtain the first four frequencies of the unit, i.e., the first-order frequencies. f 1. Second-order frequency f 2. Third-order frequency f 3rd and fourth order frequencies f 4. Simultaneously, the blade acceleration time-domain signal is directly calculated to extract intuitive quantities representing the blade vibration intensity, including RMS value and kurtosis value.

[0060] S3. Obtain unit operation safety parameters based on the blade simulation model, including the theoretical safety threshold of acceleration corresponding to the first-order frequency. aA1 The theoretical safety threshold for acceleration corresponding to the second-order frequency a A2 The theoretical safety threshold for acceleration corresponding to the third-order frequency a A3 The theoretical safety threshold for acceleration corresponding to the fourth order frequency a A4 RMS0 (RMS safety value) and kurtosis safety value K 0.

[0061] S4. Write the first four frequencies of each blade, the kurtosis value and RMS value of each blade in the time domain, and the unit operation safety parameters into the wind turbine controller.

[0062] S5. The wind turbine controller calculates the first four frequencies, kurtosis, and RMS values ​​in the time domain of each blade from the real-time data of each blade, and compares them with the unit's operating safety parameters, issuing real-time warnings or fault alarms. Specifically, this includes the following processes:

[0063] S5.1 For each leaf, in [ f 1-10%× f 1, f 1 + 10% × f 1]、

[0064] [ f 2-10%× f 2, f 2 + 10% × f 2]、[ f 3-10%× f 3, f 3 + 10% × f 3] and [ f 4-10%× f 4, f 4 + 10% × f Within the range of 4], the maximum amplitude and its corresponding frequency are automatically found in four ranges, and are denoted as [ ]. f i-1m , a Ai-jm ]、[ f i-2m , a Ai-jm ]、[ f i-3m , a Ai-jm ]and[ f i-4m , a Ai-jm ];in i Indicates the blade number. j Indicates the frequency order;

[0065] S5.2 For each blade, trigger and record the event as follows:

[0066] If (| f i-1m - f 1|) / f If 1 > 0.01, then event A1 is triggered; if (| f i-2m - f 2|) / f If 2 > 0.01, then event A2 is triggered; if (| f i-3m - f 3|) / f If 3 > 0.01, then event A3 is triggered; if (| f i-4m - f 4|) / f If 4 > 0.01, then event A4 is triggered;

[0067] if a Ai-1m >0.6× a A1 If, then event B1 is triggered; if a Ai-2m >0.6× a A2 Then event B2 is triggered; if a Ai-3m >0.6× a A3 Then event B3 is triggered; if a Ai-4m >0.6× a A4 Then event B4 is triggered;

[0068] if a Ai-1m >0.8× a A1 If, then event C1 is triggered; if a Ai-2m >0.8× a A2 Then event C2 is triggered; if a Ai-3m >0.85× a A3 Then event C3 is triggered; if a Ai-4m >0.8× a A4 Then event C4 is triggered;

[0069] If the average frequency difference between the three blades exceeds 5% of the initial parameter value... If so, event FP1 is triggered;

[0070] If the average difference in amplitude among the three blades exceeds 10% of the safety threshold. If so, event AP1 will be triggered;

[0071] S5.3. Early warning and control protection shall be performed according to the following logic:

[0072] a. If any one of the events A1, A2, A3 and A4 is triggered 10 times in a day, a blade modal frequency abnormality warning will be issued, prompting the unit to conduct further analysis and investigation of the blade data;

[0073] b. If events A1, A2, A3 and A4 are triggered simultaneously, and the ambient temperature is below 0, a blade icing warning will be issued, and the unit will execute an event shutdown action.

[0074] c. If any one of the events B1, B2, B3 and B4 is triggered 3 times within 1 hour, a warning of excessive blade vibration will be issued, the unit will operate at 60% of its rated power, and further analysis and investigation of the blade vibration data of the unit will be required.

[0075] d. If any one of the events C1, C2, C3 and C4 is triggered 3 times within 1 hour, a severe blade vibration fault will be indicated, the unit will execute shutdown protection, a blade excessive vibration fault will be indicated, and the unit will conduct further analysis and troubleshooting of blade vibration data.

[0076] e. If either event FP1 or event AP1 is triggered, a unit impeller imbalance warning will be executed, prompting the unit to check the zero-point consistency of the three blades.

[0077] f. When the value RMS i >0.6 RMS 0 or K i >0.6 K At 0:00, the unit issued a warning for excessive time-domain vibration, limiting its power output to 60% of its rated power; among which... RMS i For the first i RMS value of the blade, K i For the first i Kurtosis value of a leaf blade;

[0078] g, when RMS i >0.8 RMS 0 or Ki >0.8 K At 0:00, the unit indicated a severe time-domain vibration fault and initiated a shutdown protection action.

[0079] This invention provides a wind turbine safety control and protection method based on blade vibration signals. It uses blade acceleration signals to access the wind turbine control system, extracts the time-domain and frequency-domain characteristic signals of blade vibration, and combines this with operating data to determine faults such as blade icing, damage, and other defects. It also identifies and classifies severe vibration faults in the unit for shutdown protection or early warning. This method, based on blade acceleration sensor data, enables shutdown protection for major blade vibration problems, avoiding significant losses from tower sweeping and collapse caused by wind turbine blade issues. While implementing unit protection, it can also monitor and issue early warnings for problems such as impeller imbalance. Correcting impeller imbalance can improve generator performance.

Claims

1. A wind turbine safety control and protection method based on blade vibration signals, characterized in that... Includes the following steps: S1. Arrange acceleration sensors on the blades to acquire blade acceleration signals during blade operation; S2. Frequency and time domain features are extracted from the blade acceleration signal to obtain the first four frequencies of each blade, as well as the kurtosis and RMS values ​​in the time domain. Specifically, time domain feature extraction involves directly calculating the blade acceleration time domain signal to extract the intuitive representations of blade vibration intensity, including the RMS and kurtosis values. Frequency domain feature extraction involves performing FFT processing on the blade acceleration time domain signal to obtain the frequency domain signal of blade vibration, and extracting the features representing blade vibration from the frequency domain signal to obtain the first four frequencies of the unit, i.e., the first-order frequencies. f 1. Second-order frequency f 2. Third-order frequency f 3rd and fourth order frequencies f 4; S3. Obtain unit operation safety parameters based on the blade simulation model, including the theoretical safety threshold of acceleration corresponding to the first-order frequency. a A1 The theoretical safety threshold for acceleration corresponding to the second-order frequency a A2 The theoretical safety threshold for acceleration corresponding to the third-order frequency a A3 The theoretical safety threshold for acceleration corresponding to the fourth order frequency a A4 RMS0 (RMS safety value) and kurtosis safety value K 0; S4. Write the first four frequencies of each blade, the kurtosis value and RMS value of each blade in the time domain, and the unit operation safety parameters into the wind turbine controller. S5, the wind turbine controller calculates the first four frequencies, kurtosis, and RMS values ​​in the time domain of each blade from real-time data, and compares them with the unit's operating safety parameters, issuing real-time warnings or fault alarms. Specifically... Includes the following processes: S5.1 For each leaf, in [ f 1-10%× f 1, f 1 + 10% × f 1]、 [ f 2-10%× f 2, f 2 + 10% × f 2]、[ f 3-10%× f 3, f 3 + 10% × f 3] and [ f 4-10%× f 4, f 4 + 10% × f Within the range of 4], the maximum amplitude and its corresponding frequency are automatically found in four ranges, and are denoted as [ ]. f i-1m , a Ai-jm ]、[ f i-2m , a Ai-jm ]、[ f i-3m , a Ai-jm ]and[ f i-4m , a Ai-jm ];in i Indicates the blade number. j Indicates the frequency order; S5.2 For each blade, trigger and record the event as follows: If (| f i-1m - f 1|) / f If 1 > 0.01, then event A1 is triggered; if (| f i-2m - f 2|) / f If 2 > 0.01, then event A2 is triggered; if (| f i-3m - f 3|) / f If 3 > 0.01, then event A3 is triggered; if (| f i-4m - f 4|) / f If 4 > 0.01, then event A4 is triggered; if a Ai-1m >0.6× a A1 If, then event B1 is triggered; if a Ai-2m >0.6× a A2 Then event B2 is triggered; If a Ai-3m > 0.6 x a A3 Event B3 is triggered. if a Ai-4m >0.6× a A4 Then event B4 is triggered; if a Ai-1m >0.8× a A1 If, then event C1 is triggered; if a Ai-2m >0.8× a A2 Then event C2 is triggered; if a Ai-3m >0.85× a A3 Then event C3 is triggered; If a Ai-4m > 0.8 x a A4 then event C4 is triggered; If the average of the frequency differences between three leaves exceeds the value of the initial parameter by 5%, then the event FP1 is triggered; If the average of the amplitude differences between three leaves exceeds 10% of the safety threshold, then the event API is triggered; S5.

3. Early warning and control protection shall be performed according to the following logic: a. If any one of the events A1, A2, A3 and A4 is triggered 10 times in a day, a blade modal frequency abnormality warning will be issued, prompting the unit to conduct further analysis and investigation of the blade data; b. If events A1, A2, A3 and A4 are triggered simultaneously, and the ambient temperature is below 0, a blade icing warning will be issued, and the unit will execute an event shutdown action. c. If any one of the events B1, B2, B3 and B4 is triggered 3 times within 1 hour, a warning of excessive blade vibration will be issued, the unit will operate at 60% of its rated power, and further analysis and investigation of the blade vibration data of the unit will be required. d. If any one of the events C1, C2, C3 and C4 is triggered 3 times within 1 hour, it indicates a severe blade vibration fault, and the unit will execute shutdown protection. If it indicates an excessive blade vibration fault, it will protect the unit's safety and requires further analysis and troubleshooting of the blade vibration data. e. If either event FP1 or event AP1 is triggered, a unit impeller imbalance warning will be executed, prompting the unit to check the zero-point consistency of the three blades. f. When the value RMS i >0.6 RMS 0 or K i >0.6 K At 0:00, the unit issued a warning of excessive time-domain vibration and limited its power to 60% of its rated power. in RMS i For the first i RMS value of the blade, K i For the first i Kurtosis value of a leaf blade; g, when RMS i >0.8 RMS 0 or K i >0.8 K At 0:00, the unit indicated a severe time-domain vibration fault and initiated a shutdown protection action.

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