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The Influence of Tyre Balancing in Nitrogen Filled Tyres using Statistical Features and Random Forest Algorithm

Journal: International Journal of Mechanical and Production Engineering Research and Development (IJMPERD ) (Vol.10, No. 3)

Publication Date:

Authors : ; ;

Page : 6679-6690

Keywords : Tyre Condition Monitoring System; Machine Learning; Statistical Features; Random Forest; TPMS; Unbalance Effect;

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Tyre condition monitoring systems (TCMS) are the safety systems used in a vehicle for measuring the condition of tyre like tyre pressure, temperature, balancing etc. Nowadays these systems play an important role in safety, because accidents were increasing very rapidly. The current technology TCMS uses direct sensors like pressure sensors or wheel speed sensors etc, which are highly expensive. This paper recommends a new indirect TCMS system using condition monitoring techniques and machine learning. For different balancing conditions vertical wheel hub vibrations are acquired from a moving nitrogen filled tyre using an accelerometer. The statistical features are extracted from the acquired signals and feature selected using j48 algorithm. Selected features are classified using random forest algorithm and reasonable high accuracy is obtained. The proposed model can be used for monitoring the tyre pressure and tyre balancing of an automobile successfully.

Last modified: 2020-12-02 13:27:28