Feature Recognition and Extraction of Rotating Stall Signal of Mine Contra-rotating Fan
Aiming at the identification and extraction of contra-rotating fan rotating stall signal features,a variational mode decomposition(VMD)method for parameter optimization is proposed.First,in order to eliminate the influence of artificial selection of VMD parameters,a shuffled frog leaping optimization algorithm with the average envelope entropy as the objective function is proposed,and the number of modes K and penalty factor α of the VMD algorithm are optimized to realize the reasonable automatic selection of parameters K and α.Then,the effectiveness of the parameter-optimized VMD method is verified by simulation signals.Finally,applying the VMD method of parameter optimization to process and analyze the fan stall signal,the spectral characteristics of the fan stall is studied and compared with results of the empirical mode decomposition(EMD).The research results show that,compared with the EMD method,the parameter-optimized VMD method has more advantages in dealing with modal aliasing,and its processing effect is significantly better than that of the EMD method.The number of IMF components obtained by decomposition is also less than that of EMD,and it is easy to distinguish eigenfrequencies.In addition,when processing the stall signal of the fan with the optimized combination of parameters,it can well reveal the change law of the stall characteristic frequency in the process of stall development,corresponding to the fluctuation of the frequency component,from a large-scale frequency fluctuation to a small-scale frequency fluctuation.
contra-rotating fanrotating stallvariational mode decompositionfeature recognition and extraction
万方数据
维普
