Fault Detection for Automotive Coil Spring Using Signal Processing Analysis

Alam, Mohammad Khurshed and M. H., Mohammed Faozi and A. R., Yusoff and M. Z., Zainol and Z., Khalil (2022) Fault Detection for Automotive Coil Spring Using Signal Processing Analysis. In: Enabling Industry 4.0 through Advances in Manufacturing and Materials: Selected Articles from iM3F 2021, Malaysia , 20 September 2021 , Virtually hosted by Universiti Malaysia Pahang. pp. 415-426.. ISBN 978-981-19-2890-1

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Abstract

Shock absorber failure can be easily detected during shock absorber utilization in the vehicle. The failure usually happened due to crack propagation under fatigue life of compress and extend operation. To prevent any failures during utilization it is preemptive to detect any possible fault during manufacturing quality check inspection process. However, it is very difficult to do full check to all finished product due to high time consumption they require. In order to shorten the time, automated checking method are desire. In this study, automotive coil spring health are recognized using signal processing analysis to enable automated line quality check inspection. Fatigue testing machine was use to excite the spring in order to create signal needed in the processing analysis. The analysis was carried out using excitation signal detected along cycle time. Output data for both healthy and faulted springs (pre-inserted cracked) were processed and compared using signal processing analysis. This method shown an accurate consistency for fault detection of crack occurred in automotive spring where the number of peaks and valley of the signal as well as their maximum values not only able to show defective characteristics but also the severity degree of the defect where higher number and frequency density are more severe than not. This method will definitely able to shorten time needed for quality check inspection of cracks when applied in fabrication line compared to conventional method using naked eyes where micro cracks are very hard to detect.

Item Type: Conference or Workshop Item (Lecture)
Additional Information: Indexed by SCOPUS Part of the Lecture Notes in Mechanical Engineering book series (LNME)
Uncontrolled Keywords: Shock absorber, Crack, Signal processing, Detect crack, Fast fourier transforms, Coil Spring
Subjects: T Technology > TJ Mechanical engineering and machinery
Faculty/Division: Institute of Postgraduate Studies
College of Engineering
Faculty of Manufacturing and Mechatronic Engineering Technology
Depositing User: Noorul Farina Arifin
Date Deposited: 27 Apr 2023 08:26
Last Modified: 27 Apr 2023 08:26
URI: http://umpir.ump.edu.my/id/eprint/35490
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