Time-series classification for industrial applications: a brake pad wear prediction use case

Abstract

Abstract Brake system is an important part for control of a vehicle. Hence condition monitoring of brake pads is essential for ensuring passenger’s safety. Many existing methods for brake pads wear assessment rely on specific sensors installed in the brake system, which could be expensive. Instead we use data from existing vehicle’s sensors and electronic control unit that are readily available in modern vehicles. We reduced the prediction problem to time-series classification problem and developed and tested several classification pipelines based on machine learning. We demonstrated that it is possible to predict a brake pad wear with an accuracy sufficient for real-life usage.