WAVELETS FOR DETECTING MECHANICAL FAULTS WITH HIGH SENSITIVITY

A method of detecting transients in mechanical systems by matching wavelets with associated signal is proposed, leading to a development of joint time–frequency–scale distribution. The three variables, the time, frequency and scale, have maximised the chance for finding similar signal segments from a system under inspection. The sensitivity is shown to be very high due to closer matching and better choice of wavelet shapes, which is essential for early fault detection and failure prevention. Fundamental types of wavelets are introduced based on the shapes of widely encountered system responses. A method of processing the three-dimensional image is suggested for interpreting the time–frequency–scale wavelet map, where the properties of the object patterns uncover the features of a signal source, so as to understand the defect and to indicate the condition of a diagnosed system. The joint distribution is demonstrated to be useful in detecting transients from different mechanical systems. Implementation and examples are discussed.