Failure detection and diagnosis of rotating machinery by orthogonal expansion of density function of vibration signal

The authors present a new robust failure detection and diagnosis method based on a statistical hypothesis on vibration characteristics of the rotating machines in good condition. The hypothesis is that if the machine is in good condition, its probability density function of the vibration signal follows the normal distribution in time domain. This method based on the hypothesis for characteristics of vibration of good condition can lead to high precision failure diagnosis without any prior knowledge concerning to vibration characteristics corresponding to specific failure to be detected.