Time–Frequency Envelope Analysis for Fault Detection of Rotating Machinery Signals with Impulsive Noise

Envelope analysis is a widely used tool for fault detection in rotating machines. In envelope analysis, impulsive noise contaminates the measured signal, making it difficult to extract features of defects. This paper proposes time–frequency that overcomes effects noises. performed by dividing signal into several sections through time window. The effect noises eliminated using frequency characteristics short rectangular wave. proposed method was verified simulation and experimental data. conducted mathematically modeling cyclo-stationary process characterizes machinery signals. addition, effectiveness data normal defective air-conditioners produced on actual assembly line. simple effective enough detect faults. future, approaches big deep learning will be required development prognostic health-management framework.