Research On Sensorless Diagnosis Method Of Wind Turbine Rolling Bearing Fault

Wind power, as a clean and renewable energy technology, has beenwidespreadly paid attention to around the world, but the wind power system isusually installed in remote areas. At the same time, installation and maintenance ofthe detection sensors are so difficult that it is hard to do the task of the assemblingunit’s detection and diagnosis. Therefore, we need to develop a simple and effectivefault monitoring and diagnosis methods so that we can reduce losses and protect thelong-term stable and reliable of the wind turbine operation.The rolling bearing, playing an important role in the wind power transmissionchain system, is the key component of the rotating machinery equipment. And thehigh ratio of machine failure exists in rolling bearing. In this paper, we bring anmethod used to detect the wind power group’s bearing failure sensorless, by meansof establishing an experiment that can simulate doubly fed wind power generationsystem, on basis of the mathematical model that reflects magnetic flux densityimpacts on the electrical signal, using the method of stator current analysis. First ofall, we establish a union simulation model on a doubly fed wind power generator anda torque vibration dynamic model, and we simulate the bearing failure’s in the windpower transmission system, dynamic response of which occurs in the generator statorcurrent signal. Then, using the demodulation method of Hilbert transform amplitudeand frequency, we study the extraction method of this mechanical failure’s feature.Finally, establishing the failure simulating experimental equipment of the windpower generator, making the plan of collecting signals, collecting the electrical signaland shaft’s made by the generator bearing that works in normal and fault condition,analyzing the fault principle for the bearing of the transmission chain and the faultsignal’s feature, we compare the data obtained in experiments with simulationresults.The experiment results show that the torque created by failure can make the generator stator current create extra frequency. The phenomenon expresses thecurrent signal’s phase modulation. When rolling bearing fails, the stator currentsignal’s feature is familiar with the predicted failure frequency and the characteristicfrequency of the main shaft frequency signal. Finally, these results show thecorrectness and accuracy of the detecting sensorless method.