A NEW FEATURE EXTRACTION METHOD FOR GEAR FAULT DIAGNOSIS AND PROGNOSIS

Robust features are very critical to track the degradation process of a gear. They are key factors for implementing fault diagnosis and prognosis. This has driven the need in research for extracting good features. This paper used a new method, Narrowband Interference Cancellation, to suppress the narrow band component and enhance the impulsive component enabling the gear fault detection easier. This method can improve the signal to noise ratio of impulse train associated with the gear fault frequency. A run-to-failure test is used to demonstrate the method's effectiveness. Based on the time synchronous signal of high speed shaft, Sideband Index is extracted from the signals processed by Narrowband Interference Cancellation. This feature has good degradation trend than traditional Sideband Index extracted from the time synchronous average signal directly. Comparison of features based on different extraction process proves the effectiveness of developed method.