| Summary: | 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.
|
|---|