Fault diagnosing system and method for wind generation set

Abstract

The invention discloses fault diagnosing system and method for a wind generation set. The system comprises the wind generation set, a vibration sensor, a rotating speed sensor and a signal acquiring card and computer signal processing system. The method comprises the steps of (1), generating a vibration simulating signal of the wind generation set; (2) setting initializing parameters; (3) treating a zero crossing point of a baseband signal of a rotating shaft as a key phase signal of the actual wind generation set; (4) determining whether to conduct variable upper limit type anti-aliasing filtering tracking for a composite vibration signal; (5) re-sampling the time; (6) re-sampling vibration signal amplitude; (7) calculating time domain synchronizing average value; (8) repeating steps from (4) to (7); and (9) comparing different results above. The fault diagnosing system and method for the wind generation set have the advantages that the anti-aliasing filtering tracking effect is obvious, an effective data processing method is provided for the fault diagnosing of the wind generation set, and the safe connection of the wind generation set in a grid and the safe operation of an intelligent micro-grid with the wind generation set are ensured.

Description

technical field [0001] The invention relates to the field of signal filtering, in particular to a wind turbine fault diagnosis system and method based on variable upper limit anti-aliasing tracking filter order analysis. Background technique [0002] In the context of the country's vigorous development of smart grids, wind power, as an important part of smart grids, has developed rapidly. With the increasing proportion of wind power capacity in regional power grids, while wind power has brought us many benefits, it has also brought some adverse effects, including: it may seriously affect the power quality and the safe and stable operation of the power system , and may endanger conventional power generation, which is mainly manifested in large fluctuations in voltage and frequency. What's more serious is that when wind turbines are out of operation on a large scale due to excessive wind speed or a large instantaneous drop in grid voltage, it will cause unbearable large-scale...

AI Technical Summary

Problems solved by technology

[0006] In addition, the traditional fault diagnosis system cannot accurately diagnose the faults of wind turbines, and there are still many defects in the fault diagnosis systems and methods of wind turbines currently on the domestic market: 1. The system algorithm is complex; 2. The spectrum obtained by sampling contains high The aliasing of the order quantity, the filtering effect is poor; 3. The signal frequency changes greatly, and the sampling upper limit frequency cannot be changed, and there is a situation that does not satisfy the sampling theorem. The sampling theorem indicates that the sampling frequency must be greater than twice the frequency of the sampled signal

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