Wind turbine generator impeller imbalance monitoring method based on empirical mode decomposition

Abstract

The invention discloses a wind turbine generator impeller imbalance monitoring method based on empirical mode decomposition (EMD). The wind turbine generator impeller imbalance monitoring method includes the following steps: 1) during a data collection process, collecting stator phase current iA and revolving speed r of a generator when the wind turbine generator is combined to the grid to generate electricity; 2) conducting EMD on the phase current iA collected and selecting the main component which contains fault features, namely, the first IMF component, which is marked as IMF (1); 3) conducting Hilbert envelope demodulation on the main component IMF (1) for extracting the fault features, and obtaining a spectrum signal if; and 4) extracting amplitude values Q1, Q2, and Q3 at 1, 2 and 3times operating frequencies of the rotating speed of the impeller from if, and if the three amplitude values are all higher than corresponding threshold values, then judging that an imbalance fault exists. According to the wind turbine generator impeller imbalance monitoring method, the degree of monitoring accuracy is improved and certain engineering application value is possessed in blade imbalance detection of double-fed generator units.

Description

technical field [0001] The invention belongs to the technical field of on-line fault diagnosis of wind turbines, and relates to an impeller fault monitoring method of wind turbines with empirical mode decomposition. Background technique [0002] The operating environment of wind turbines is usually relatively harsh, and the quality of the blades will be unbalanced due to sandstorms and icing. Especially in recent years, the popularization and application of offshore wind turbines and low-wind-speed models has made the blades longer and longer. The phenomenon of ice and snow is also increasing. Make the transmission system unbalanced, cause the vibration of the whole machine to intensify, and even lead to accidents in severe cases. [0003] Considering the differences of different blades and the complexity of the failure mechanism, it is difficult to establish a more accurate diagnosis model. Moreover, the operating conditions of the unit change at any time, and the surroun...

AI Technical Summary

Problems solved by technology

For example, "Double-fed Wind Turbine Generator Stator Current Diagnosis Method for Unbalanced Impeller Fault", the extraction of characteristic components in this method requires secondary derivation, reconstruction of stator current and secondary FFT operation, and the processing process is complicated

Another example is "an on-line fault diagnosis method for blade unbalance of double-fed wind turbine", which processes electric power and needs to collect voltage and current, and these methods are theoretically feasible, but in engineering, wind fields in different regions Blades from different manufacturers and different fan operating conditions have poor adaptability

Images