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Withit Chatlatanagulchai.. A comparative analysis of supervised machine learning algorithms for fault prediction in automotive suspension systems. (). King Mongkut's University of Technology North Bangkok. Central Library. : , 2568.
A comparative analysis of supervised machine learning algorithms for fault prediction in automotive suspension systems
Name: Pachara Juyploy.
Organization :
King Mongkut's University of Technology North Bangkok. Faculty of Engineering
Email :
pachara.j@eng.kmutnb.ac.th
Organization :
Kasetsart University. Faculty of Engineering
keyword:
Predictive maintenance.
LCSH:
Automobiles
-- Springs and suspension.
LCSH:
Automobiles
-- Vibration.
LCSH:
Machine learning.
LCSH:
Support vector machines.
Abstract:
Intense automotive vibrations, while common, can seriously compromise driver health. This research utilizes machine learning (ML) to predict potential failures in car suspension systems, targeting an enhancement in vehicle reliability and safety. While numerous studies have simulated suspension faults, the increasing data complexity from uncertain parameters necessitates more efficient algorithms for precise fault identification. This study, therefore, conducts a comparative analysis of several supervised machine learning algorithms to determine the most accurate method for this predictive task. The algorithms were evaluated using four distinct feature set preparations: original data, standard deviation data, principal component analysis data, and a combined set of mean standard deviation and principal component analysis. The findings reveal that the Artificial Neural Network (ANN) and Support Vector Classifiers (SVC) algorithms yield the highest prediction accuracy. Notably, this peak accuracy was achieved when utilizing the combined feature set (mean standard deviation and Principal Component Analysis (PCA)). These results offer a valuable contribution toward designing more robust car suspension systems and advancing future preventive maintenance strategies.
King Mongkut's University of Technology North Bangkok. Central Library
Address:
BANGKOK
Email:
library@kmutnb.ac.th
Created:
2568
Modified:
2569-01-05
Issued:
2026-01-05
บทความ/Article
application/pdf
BibliograpyCitation :
วารสารวิชาการเทคโนโลยีอุตสาหกรรม. ปีที่ 21, ฉบับที่ 3 (ก.ย.-ธ.ค. 68), หน้า 229-240.
eng
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Pachara Juyploy.
| Title | Contributor | Type |
|---|---|---|
| Reducing harmful effects on human health of car vibrations using a combination of unsupervised and supervised machine learning algorithm
มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ Chatlatanagulchai Withit.;Pachara Juyploy. | บทความ/Article | |
| A comparative analysis of supervised machine learning algorithms for fault prediction in automotive suspension systems
มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ Pachara Juyploy.;Withit Chatlatanagulchai. | บทความ/Article |
Withit Chatlatanagulchai.
| Title | Contributor | Type |
|---|---|---|
| The design and development of robotic arms to assist in manufacturing processes using machine vision techniques
มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ Lapitch Polsan.;Withit Chatlatanagulchai.;Sathit Wanwanitchai. | บทความ/Article | |
| A comparative analysis of supervised machine learning algorithms for fault prediction in automotive suspension systems
มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ Pachara Juyploy.;Withit Chatlatanagulchai. | บทความ/Article |