Automatic Fault Diagnosis and Prediction of Wind Turbines

Jianping Xiang, Nannan Jiang, Simon Jonathan Watson

Research output: Contribution to journalArticleScientificpeer-review

2 Citations (Scopus)
26 Downloads (Pure)


A Morlet wavelet-based compensated algorithm was proposed to calculate the accurate amplitudes of faulty signals. The specific way is to compute the time range and frequency values of the faulty signals at first, and then to compensate the amplitudes calculated for above faulty signals according to the center frequency values of Morlet wavelet coefficients to further obtain the accurate amplitudes. A Simulink model was used to demonstrate the feasibility and generalization of the algorithm. At the same time, the algorithm was used to analyze the electric power signals of a test rig and large turbines. Results show that this algorithm can automatically find the amplitude trend of faulty components in a time sequence, and indicate the residual service life of wind turbines after faults are generated. Based on the information of the residual service life, the maintenance and repairing plan for wind turbines, especially offshore ones, can be developed to lower the cost of wind power in operation and maintenance.

Original languageChinese
Pages (from-to)821-828
Number of pages8
JournalDongli Gongcheng Xuebao/Journal of Chinese Society of Power Engineering
Issue number10
Publication statusPublished - 15 Oct 2017


  • Compensated calculation
  • Electric power signal
  • Fault diagnosis
  • Morlet wavelet transform
  • Wind turbine

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