Wei Teng

Detection and Quantization of Bearing Fault in Direct Drive Wind Turbine via Comparative Analysis

Bearing fault is usually buried by intensive noise because of the low speed and heavy load in direct drive wind turbine (DDWT). Furthermore, varying wind speed and alternating loads make it difficult to quantize bearing fault feature that indicates the degree of deterioration. This paper presents the application of multiscale enveloping spectrogram (MuSEnS) and cepstrum to detect and quantize bearing fault in DDWT. MuSEnS can manifest fault modulation information adaptively based on the capacity of complex wavelet transform, which enables the weak bearing fault in DDWT to be detected. Cepstrum can calculate the average interval of periodic components in frequency domain and is suitable for quantizing bearing fault feature under varying operation conditions due to the logarithm weight on the power spectrum. Through comparing a faulty DDWT with a normal one, the bearing fault feature is evidenced and the quantization index is calculated, which show a good application prospect for condition monitoring and fault diagnosis in real DDWT.

Cyclostationary Analysis of a Faulty Bearing in the Wind Turbine

Bearing faults occur frequently in wind turbines, thus resulting in an unplanned downtime and economic loss. Vibration signal collected from a failing bearing exhibits modulation phenomenon and “cyclostationarity.” In this paper, the cyclostationary analysis is utilized to the vibration signal from the drive-end of the wind turbine generator. Fault features of the inner and outer race become visible in the frequency–cyclic frequency plane. Such fault signatures can not be produced by the traditional demodulation methods. Analysis results demonstrate effectiveness of the cyclostatonary analysis. The disassembled faulty bearing visualizes the fault. [DOI: 10.1115/1.4035846]

Iterative tuning notch filter for suppressing resonance in ultra-precision motion control

In this article, a practical iterative algorithm for tuning the parameters of notch filter is presented to suppress high-frequency resonance in ultra-precision motion control. Notch filter is a useful tool to suppress middle- and high-frequency resonance to improve control precision. The traditional tuning method for it depends on the Fourier transform of the positioning error or the modal analysis of the motion stage, which cannot get the optimal control performance. The proposed algorithm can be used to tune the parameters of notch filter iteratively through minimizing a cost function of the positioning error, and it needs only measurement signals in actual motion system rather than detailed model of the motion stage. The proposed algorithm can suppress mechanical resonance and meanwhile minimize positioning error, which are demonstrated by experimental results in wafer stage of photolithography.