A fault diagnosis method for axial flow fa

For poor diagnosis effect of existing fault diagnosis methods for axial flow fan based on spectrum analysis which correlated fault type with spectrum characteristic value simply, a fault diagnosis method for axial flow fan based on vector ellipsoid spectrum and hidden Markov model (HMM) was proposed. Firstly, two orthogonal vibration signals of axial flow fan in the same section are fused into a complex signal in time domain, and full-spectrum amplitudes of the vibration signals under multi characteristic frequencies are obtained by fast Fourier transform of the complex signal. Secondly, the full-spectrum amplitudes under different fault conditions are used to train HMM. Finally, full-spectrum amplitudes of real-time vibration signals are as input of HMM, and Viterbi algorithm is used to calculate likelihood probability outputted by HMM. Fault type is judged according to the maximum logarithm value of the likelihood probability, which avoids simple association between the vibration amplitude and fault type. The experimental result shows that correct rate of fault diagnosis of the method is above 90%.