An Adaptive Model of Rotating Machinery Subject toVibration Monitoring

摘要

This paper proposes a state-space model of nonstationary multivariate vibration signals for the on-line estimation ofrnthe state of rotating machinery by means of noise-adaptive Kalman filtering algorithm and spectral analysis in therntime-frequency domain. Experimental results demonstrate that the proposed model is able to quickly detect thernactual state of rotating machinery even under highly nonstationary conditions with abrupt changes and also preciselyrnhighlight frequency components in a signal highly contaminated with noise and therefore, yield accurate spectralrninformation for an early warning of incipient fault in rotating machinery diagnosis. This is achieved throughrncombination with a change detection statistic in bispectral domain.