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tyre pressure supervision of Two Wheeler Using Machine Learning

Structural Durability & Health Monitoring 2022年第3期16卷 271-290页

作者： Sujit S.Pardeshi Abhishek D.Patange R.Jegadeeshwaran Mayur R.Bhosale Department of Mechanical Engineering College of Engineering PuneMaharashtra411005India School of Mechanical Engineering Vellore Institute of TechnologyTamil Nadu600127India Savitribai Phule Pune University Maharashtra411007India

The regulation of tyre pressure is treated as a significant aspect of‘tyre maintenance’in the domain of *** manual supervision of a tyre pressure is typically an ignored task by most of the *** existing instru-mental scheme incorporates stand-alone monitoring with pressure and/or temperature sensors and requires reg-ular manual *** these schemes turn to be incompatible for on-board supervision and automated prediction of tyre *** this perspective,the Machine Learning(ML)approach acts appropriate as it exhi-bits comparison of specific performance in the past with present,intended for predicting the same in near *** current investigation experimentally assesses the suitability of ML scheme for vibration based on-board supervision of tyre pressure of two wheeled *** order to examine the vibration response of a wheel hub,the in-house design&development of DAQ(Data Acquisition System)is *** Electro-Mechanical Scheme(MEMS)built accelerometer is incorporated with open source hardware and software to collect and store the *** framework is easy to develop,monitor and can be retrofitted in two wheeled *** various pressure conditions,the change in response of wheel hub vibration with respect to time is *** statistical parameters describing these vibration signals are determined and the decision tree is applied to select distinguishing parameters between extracted *** classification of different conditions of tyre pressure is carried out using ML classifiers.

关键词： Machine learning tree based classifiers decision tree tyre pressure supervision autotronics

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