Fault diagnosis method and device for wind generating set

Abstract

The invention provides a fault diagnosis method and device for a wind generating set. The method comprises the following steps of: acquiring a current signal and vibration data of a wind generating set; determining the angular displacement of a generator of the wind generating set according to the current signal; determining a first-order spectrum of the wind generating set according to the angular displacement and the vibration data, a first coordinate axis of the first-order spectrum being used for representing the angular displacement, a second coordinate axis of the first-order spectrum being used for representing the vibration data, and the angular displacement comprising a plurality of unit angular displacements; carrying out interpolation processing on the first-order spectrum to enable the number of the vibration data corresponding to each unit angular displacement to meet a preset condition, so as to obtain a second-order spectrum; and analyzing the second-order spectrum by adopting a fault diagnosis algorithm. The non-rotating-speed order tracking mode is more accurate and stable, the system cost is reduced, and the precision and definition of fault diagnosis are improved through interpolation processing.

Description

technical field [0001] The present application relates to the field of fault diagnosis, in particular to a fault diagnosis method and device for a wind power generating set. Background technique [0002] At present, it is possible to predict the failure of the wind generator set according to the collected speed of the wind generator set, so as to avoid the loss caused by the downtime of the wind generator set. For wind turbines, the bearing vibration and generator fault diagnosis technology at constant speed is relatively mature, and basic FFT analysis, envelope analysis, wavelet analysis, spectrum analysis, etc. can meet the basic analysis requirements. However, in actual situations, the generator is often in a state of variable speed. Generally speaking, the rotation speed is mainly obtained through the rotation speed sensor, and the vibration data and the rotation speed are collected synchronously. From the past research results, the existence of the rotation speed senso...

AI Technical Summary

Problems solved by technology

Generally speaking, the rotational speed is mainly obtained through the rotational speed sensor, and the vibration data and the rotational speed are collected synchronously. From the past research results, the existence of the rotational speed sensor makes the system installation more complicated, and the acquisition of the rotational speed signal is not necessary. Convenience, and the speed signal acquisition is unstable and inaccurate, resulting in low accuracy of fault diagnosis

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