Abstract:

Combination morphological filter (CMF) can effectively reject the impulse interference of vibration signal, and the result of top-hat transform can adequately reveal the periodical impact features. Based on the theory of the above two operators, a novel mathematical morphology operator named the combination morphological filter-hat transform is proposed. To accurately describe the theory basis of morphological operator in vibration detection applications, the filtering properties of morphological operators is investigated by using the analysis method of nonlinear filter frequency response characteristics. Furthermore, in view of the empirical selection of the structuring element of mathematical morphology operator, particle swarm optimization (PSO) is applied to obtain the optimal structure element of CMF-hat and improve the accuracy of mathematical morphology operator in vibration signal process. The simulation signal and practical vibration data generated from wind turbine demonstrate that the proposed method has excellent performance to eliminate the background noise and extract the impact feature, and can precisely diagnose the gear wear defect on high-speed axis of wind turbine gearbox. Therefore, it has certain practical engineering application value.

Key words: fault diagnosis, particle swarm optimization, structuring element, wind turbine, combination morphological filter-hat transform