Publications:Using Histograms to Find Compressor Deviations in Bus Fleet Data


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Title Using Histograms to Find Compressor Deviations in Bus Fleet Data
Author Yuantao Fan and Sławomir Nowaczyk and Thorsteinn Rögnvaldsson
Year 2014
PublicationType Conference Paper
HostPublication The SAIS Workshop 2014 Proceedings
Conference The Swedish AI Society (SAIS) Workshop 2014, Stockholm, Sweden, May 22-23, 2014
Diva url
Abstract Cost effective methods for predictive maintenance are increasingly demanded in the automotive industry. One solution is to utilize the on-board signals streams on each vehicle and build self-organizing systems that discover data deviations within a fleet. In this paper we evaluate histograms as features for describing and comparing individual vehicles. The results are based on a long-term field test with nineteen city buses operating around Kungsbacka in Halland. The purpose of this work is to investigate ways of discovering abnormal behaviors and irregularities between histograms of on-board signals, here specifically focusing on air pressure. We compare a number of distance measures and analyze the variability of histograms collected over different time spans. Clustering algorithms are used to discover structure in the data and track how this changes over time. As data are compared across the fleet, observed deviations should be matched against (often imperfect) reference data coming from workshop maintenance and repair databases.