A Research On Diagnosis Method Of Power Steering Motor Based On Acoustic Signal In Automobile Chassis

Chassis,as the core component of a car,its performance directly affects on the safety and reliability of vehicles.When the parts of chassis wear serious,the gap increases,parts loosing,or due to the quality of maintenance problems(the assembly and the adjustment are not accurate and other reasons).Chassis will produce various kinds of abnormal noise.Therefore,the sound signal of the chassis contains the fault information.The effective method used to quantify and analyze the acoustic signals is the basic work of the automobile chassis fault diagnosis research.Thus,the techniques for chassis fault diagnosis have become an important issue in the field of vehicle engineering.Based on the previous research findings,this thesis paper studies and presents a noise-based technology for chassis fault diagnosis,using the HERM Transform and the support vector machine.In this thesis,firstly,the common chassis faults are investigated.A data acquisition scheme is determined by analyzing the generation mechanism and propagation path of chassis noises.Subsequently,some noise measurements are performed by setting a sample chassis into different working conditions,including the normal and fault states,thereby,a data-based establishment of the measured chassis noise signals.For the engine noise signals,the wavelet packet de-noise method has an obvious advantage;the HERM is suitable for analyzing the non-stationary signals,due to its high time frequency resolution and without cross terms.The noise-based HERM algorithm,which can be extended to other sound-related fields for failure detections and recognitions,maybe a promising approach in both the theoretical research and the practical application in engineering.