Abstract

Hydraulic brakes in automobiles play a vital role for the safety on the road; therefore vital components in the brake system should be monitored through condition monitoring techniques. Condition monitoring of brake components can be carried out by using the vibration characteristics. The vibration signals for the different fault conditions of the brake were acquired from the fabricated hydraulic brake test setup using a piezoelectric accelerometer and a data acquisition system. Condition monitoring of brakes was studied using machine learning approaches. Through a feature extraction technique, descriptive statistical features were extracted from the acquired vibration signals. Feature classification was carried out using nested dichotomy, data near balanced nested dichotomy and class balanced nested dichotomy classifiers. A Random forest tree algorithm was used as a base classifier for the nested dichotomy (ND) classifiers. The effectiveness of the suggested techniques was studied and compared. Amongst them, class balanced nested dichotomy (CBND) with the statistical features gives better accuracy of 98.91% for the problem concerned.

Highlights

  • Fault diagnosis is an important process in preventive maintenance, as it avoids serious damage during operation

  • Mean, standard error, median, standard deviation, variance, kurtosis, skewness, range, minimum, maximum, sum and count were extracted from the acquired vibration signal

  • In this paper a meta learning scheme was presented to improve the classification accuracy in brake fault diagnosis. It deals with vibration based fault diagnosis of automobile hydraulic brake system

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Summary

Introduction

Fault diagnosis is an important process in preventive maintenance, as it avoids serious damage during operation. Detection of the defects can prevent the system from malfunction which leads to damage of the entire system or accident. A condition monitoring system can be effectively used as a decision support tool to identify failures. The brake system in an automobile is such an essential component which must be monitored continuously to avoid serious damage. The malfunction of the brake system can be identified through its symptoms or some warning sign.

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