Classification Tree-Based Wheel Unbalance Detection

In this paper, the problem of unbalance detection in vehicle's wheels is analyzed. Starting from accelerations and angular velocities acquired from a wheel balancer machine instrumented with Micro Electro-Mechanical Systems (MEMS) sensors, meaningful features are extracted for different conditi...

Full description

Saved in:
Bibliographic Details
Main Authors: Todeschini, Riccardo, Pozzato, Gabriele, Strada, Silvia C., Savaresi, Sergio M., Dambach, Gerhard
Format: Conference Proceeding
Language:English
Subjects:
Classification algorithms
Feature extraction
Sensor phenomena and characterization
Sensor systems
Training
Velocity control
Wheels
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:In this paper, the problem of unbalance detection in vehicle's wheels is analyzed. Starting from accelerations and angular velocities acquired from a wheel balancer machine instrumented with Micro Electro-Mechanical Systems (MEMS) sensors, meaningful features are extracted for different conditions of unbalance, namely, 30 and 40 g. Then, classification trees, for both the static and pure couple unbalance, are trained for the simultaneous detection of severity and angular position of the unbalanced masses. The performance of the proposed approach is validated against experimental data and its effectiveness is compared to a cascade algorithm, previously published by the authors.
ISSN:2768-0770
DOI:10.1109/CCTA48906.2021.9659061