Tyre Pressure Supervision of Two Wheeler Using Machine Learning  

作　　者：Sujit S.Pardeshi Abhishek D.Patange R.Jegadeeshwaran Mayur R.Bhosale 

机构地区：[1]Department of Mechanical Engineering,College of Engineering Pune,Maharashtra,411005,India [2]School of Mechanical Engineering,Vellore Institute of Technology,Tamil Nadu,600127,India [3]Savitribai Phule Pune University,Maharashtra,411007,India

出　　处：《Structural Durability & Health Monitoring》2022年第3期271-290,共20页结构耐久性与健康监测（英文）

摘　　要：The regulation of tyre pressure is treated as a significant aspect of‘tyre maintenance’in the domain of autotronics.The manual supervision of a tyre pressure is typically an ignored task by most of the users.The existing instru-mental scheme incorporates stand-alone monitoring with pressure and/or temperature sensors and requires reg-ular manual conduct.Hence these schemes turn to be incompatible for on-board supervision and automated prediction of tyre condition.In 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 future.The current investigation experimentally assesses the suitability of ML scheme for vibration based on-board supervision of tyre pressure of two wheeled vehicle.In order to examine the vibration response of a wheel hub,the in-house design&development of DAQ(Data Acquisition System)is described.Micro Electro-Mechanical Scheme(MEMS)built accelerometer is incorporated with open source hardware and software to collect and store the data.This framework is easy to develop,monitor and can be retrofitted in two wheeled vehicle.For various pressure conditions,the change in response of wheel hub vibration with respect to time is collected.The statistical parameters describing these vibration signals are determined and the decision tree is applied to select distinguishing parameters between extracted parameters.The 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 

分 类 号：U462.3[机械工程—车辆工程]