Failure diagnosis technology discussion of vehicle based on oil detection

• Published in: 2015 Prognostics and System Health Management Conference (PHM) pp. 1 - 5
• Main Authors: Qiufang Wang, Zhong Zhang, Ke Bao, Shulin Liu, Yuanyuan Zhao, Yue Liu
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01-10-2015
• Subjects: Artificial intelligence; failure diagnosis; Friction; Gears; Maintenance engineering; Oil Detection; PHM; Reliability; Timing; Vehicles
• DOI: 10.1109/PHM.2015.7380091

The widely use of the new technique and the new material make the vehicle's structure gradually complicated. For the complicated equipment, the wear state of the mechanism is hard to estimate. And it often makes the overly maintenance or insufficient maintenance. This paper discusses the failure diagnosis technology based on oil detection and studies the key technology of the oil detection, the construction method of the detection system, and the extraction method of the oil status wear parameters. Through the debris analysis and the performance testing for the collected oil sample, the technical condition of the vehicle can be judged and predicted by comparing and analyzing the test data with the boundary value of the oil detection parameters. The pollution control of the lubricant oil and the oil deterioration control can make the vehicle keep good lubrication state, and it's the efficiency measure to reduce or avoid the happening probability of the abnormal wear and tear for the vehicle.