scholarly journals Automatic Fault Diagnosis Method for Wind Turbine Generator Systems Driven by Vibration Signals

2018 ◽  
Author(s):  
Yu Pang
Keyword(s):  
Fault Diagnosis ◽  
Wind Turbine ◽  
Turbine Generator ◽  
Vibration Signals ◽  
Wind Turbine Generator ◽  
Diagnosis Method

Fault Diagnosis Method for Wind Turbine Gearbox Based on Image Characteristics Extraction and Actual Value Negative Selection Algorithm

2020 ◽  
Vol 34 (14) ◽  
pp. 2054034
Author(s):  
Xiaoli Xu ◽  
Xiuli Liu
Keyword(s):  
Fault Diagnosis ◽  
Wind Turbine ◽  
Negative Selection ◽  
Selection Algorithm ◽  
Turbine Generator ◽  
Time Frequency ◽  
Negative Selection Algorithm ◽  
Wind Turbine Generator ◽  
Image Characteristics ◽  
Diagnosis Method

With the development of information theory and image analysis theory, the studies on fault diagnosis methods based on image processing have become a hot spot in the recent years in the field of fault diagnosis. The gearbox of wind turbine generator is a fault-prone subassembly. Its time frequency of vibration signals contains abundant status information, so this paper proposes a fault diagnosis method based on time-frequency image characteristic extraction and artificial immune algorithm. Firstly, obtain the time-frequency image using wavelet transform based on threshold denoising. Secondly, acquire time-frequency image characteristics by means of Hu invariant moment and correlation fusion gray-level co-occurrence matrix of characteristic value, thus, to extract the fault information of the gearing of wind turbine generator. Lastly, diagnose the fault type using the improved actual-value negative selection algorithm. The application of this method in the gear fault diagnosis on the test bed of wind turbine step-up gearbox proves that it is effective in the improvement of diagnosis accuracy.

Wind Turbine Generator Fault Detection by Wavelet-Based Multifractal Analysis

2013 ◽  
Vol 644 ◽  
pp. 346-349
Author(s):  
Chang Zheng Chen ◽  
Yu Zhang ◽  
Quan Gu ◽  
Yan Ling Gu
Keyword(s):  
Wind Turbine ◽  
Multifractal Analysis ◽  
Vibration Signal ◽  
Rotational Frequency ◽  
Turbine Generator ◽  
Vibration Signals ◽  
Wind Turbine Generator ◽  
Fault Features ◽  
Multifractal Theory ◽  
Incipient Fault

It is difficult to obtain the obvious fault features of wind turbine, because the vibration signal of them are non-linear and non-stationary. To solve the problem, a multifractal analysis based on wavelet is presented in this research. The real signals of 1.5 MW wind turbine are studied by multifractal theory. The incipient fault features are extracted from the original signal. Using the Wavelet Transform Modulo Maxima Method, the multifractal was obtained. The results show that fault features of high rotational frequency of wind turbine are different from low rotational frequency, and the complexity of the vibration signals increases with the rotational frequency. These demonstrate the multifractal analysis is effective to extract the fault features of wind turbine generator.

Research on Fault Diagnosis Method of Wind Turbine Based on Wavelet Analysis and LS-SVM

2013 ◽  
Vol 724-725 ◽  
pp. 593-597 ◽  
Author(s):  
Chang Liang Liu ◽  
Wei Xue Qi
Keyword(s):  
Fault Diagnosis ◽  
Wavelet Analysis ◽  
Wind Turbine ◽  
High Speed ◽  
Wavelet Decomposition ◽  
Least Square ◽  
Support Vector ◽  
Vibration Signals ◽  
Training Samples ◽  
Diagnosis Method

Aiming at the fault characteristics of high-speed gearbox fault diagnosis of wind turbine, a fault diagnosis method of combining wavelet analysis with least square-support vector machine (LS-SVM) is proposed. According to the method, the energy of frequency bands generated by wavelet decomposition and reconstruction of the high-speed gearbox's vibration signals in different fault states is normalized as eigenvectors, forming training and testing samples of LS-SVM fault classifier. Train the LS-SVM fault diagnosis model with the training samples and test the accuracy with the testing samples. The result of research shows that the fault diagnosis method based on the wavelet analysis and LS-SVM has good diagnostics effect.

The Simulation Research of Double Fed Wind Generator Fault Diagnosis Based on MCSA

2013 ◽  
Vol 274 ◽  
pp. 103-106
Author(s):  
Xian Jiang Shi ◽  
Fu Peng Ge ◽  
Han Sun ◽  
Qing Chun Meng ◽  
Jun Shan Si
Keyword(s):  
Fault Diagnosis ◽  
Wind Turbine ◽  
Turbine Generator ◽  
Generator System ◽  
Simulation Research ◽  
Inspection Method ◽  
Rotating Speed ◽  
Wind Turbine Generator ◽  
Stator Current ◽  
Motor Current Signature Analysis

In order to research the possibility of Motor Current Signature Analysis (MCSA) applied to fault diagnosis of double fed wind turbine generator system and overcome the defect of sensor stalled installed inconveniently with regular vibration inspection method constructs a simulation model of double fed wind turbine generator with SIMULINK, which uses PWM module for stator excitation and the signal of rotating speed and torque of external dynamic changes to simulate the fault of wind turbine motor transmission system, and then verifying the accuracy of fault features of stator current when generator system has fault by emulating and analyzing the response process of signal in the stator current of generator with different situations.

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