Automobile control units monitor several hundreds of signals. In addition to the high dimensionality, these signals exhibit strong interactions between them. Hence, the failure of one sensor can lead to disturbances in multiple signals. Hence, this project involves automatic selection of the sensor signals that are strongly influenced by a particular failure.
By performing such cause and effect analysis in a automated framework, the effort and time spent by the engineers for manual analysis is greatly reduced.
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