Two automotive light assembly monitoring systems, based on microphones and accelerometers, have been developed. Initial testing and data analysis have been conducted. The results have shown that the face-to-face dual-microphone method could distinguish the faulty from the healthy light assemblies. Results were sensitive to the face angle of the two microphones. The best angle of separation between the two microphones in the dual-microphone-based diagnostic system was found to be 180 deg. The accelerometer-based monitoring system was able to pick up differences in the low frequency range (under 3,000 Hz). The results were sensitive to the locations of the accelerometers. In summary, the accelerometer-based and the dual-microphone-based monitoring systems have good potential for automotive light assembly failure detection. This suggests that there is potential to develop these and potentially other measures for use in an adaptable, reliable, and low-cost real-time monitoring and diagnostic system that would interrupt the testing operation at the first onset of a failure. This work also shows that a simple three-layered neural network, with seven inputs (the seven RMS values) and three outputs (representing the three different conditions: good, loose parts, and broken leg) could act as an effective objective and automatic classification method. During this initial testing, all the data have been simply compared in the frequency domain. Further analysis of the data in the time domain and frequency domain needs to be conducted in the future. Future work will also involve a full endurance test with data collected throughout the test and the development of background noise control methods by using appropriate filtering to aid in extraction of useful information from the raw signals.
Failure detection in automotive light assemblies during vibration endurance testing
International Journal of Advanced Manufacturing Technology ; 51 , 5-8 ; 799-810
2010
12 Seiten, 17 Bilder, 2 Tabellen, 7 Quellen
Article (Journal)
English
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