Antonis Sideris and Elias Chlis Kalogeropoulos and Konstantia Moirogiorgou
Data Analysis Techniques for Predictive Maintenance on Fleet of HeavyDuty Vehicles
300 - 304
2021
15
7
International Journal of Mechanical and Mechatronics Engineering
https://publications.waset.org/pdf/10012125
https://publications.waset.org/vol/175
World Academy of Science, Engineering and Technology
The present study proposes a methodology for the efficient daily management of fleet vehicles and construction machinery. The application covers the area of remote monitoring of heavyduty vehicles operation parameters, where specific sensor data are stored and examined in order to provide information about the vehicle’s health. The vehicle diagnostics allow the user to inspect whether maintenance tasks need to be performed before a fault occurs. A properly designed machine learning model is proposed for the detection of two different types of faults through classification. Cross validation is used and the accuracy of the trained model is checked with the confusion matrix.
Open Science Index 175, 2021