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Vibration Feature Extraction of the Automobile Rear Bridge and Virtual Instrument Design

Author: ZhangZhiPing
Tutor: LiuZhengPing
School: East China Jiaotong University
Course: Mechanical Manufacturing and Automation
Keywords: Rear Axle Quality Inspection Signal analysis Spectral Entropy Wavelet Virtual instrument
CLC: U463.218
Type: Master's thesis
Year: 2004
Downloads: 209
Quote: 4
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Abstract


Automobile rear axle is the key components of the car , according to statistics , 20% of accidents are caused due to the rear axle , rear axle to conduct strict quality tests before leaving the factory . This paper decided to use the method of vibration diagnosis quality inspection of the rear axle . The analysis of the vibration characteristics of the rear axle ; actual working conditions and measured results , determine the location of the measurement point ; using my virtual instrument designed to achieve the vibration signal acquisition and analysis . The focus of this article is the signal de-noising and extraction of the characteristic parameters of the running state of the rear axle . Signal denoising is the basis of the subsequent signal processing related to the correctness of the results of the signal analysis . In this paper, wavelet and wavelet packet transform denoising , the the denoising results show that better wavelet packet denoising . Can extract correctly reflect the characteristics of the operating status of the rear axle parameters related to the ability to achieve product testing and detection reliability , using three methods of extracting characteristic parameters : the time-averaged wavelet spectrum , wavelet packet energy method and frequency domain indicator approach . Time-averaged wavelet spectrum and wavelet packet energy method , Euclidean distance , respectively, each identified as the quality detection threshold of the rear axle . In the frequency domain method to the spectrum entropy arm or gravity frequency as the the judge rear axle operation quality characteristic parameters . Measured analysis , these three methods can effectively run quality threshold determined reflect the rear axle , but the calculation of the time-averaged wavelet spectrum and wavelet packet energy method is more complex , computationally intensive , and simple calculation of the frequency domain , particularly suitable for automated diagnosis and ported to a handheld portable testing instruments .

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CLC: > Transportation > Road transport > Automotive Engineering > Automotive structural components > Transmission > Mechanical transmission > Drive axle
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