Step Towards Generalization: Fault Classification in Multivariate High-Frequency Data from Different Operating Regimes of Hydraulic Rock Drill System

Nagi Reddy, Ashit Gupta, Gauri Dhande, Vijaykumar Pasupureddy

2023

Abstract

Hydraulic rock drills operate under harsh environments of excessive humidity and vibrations. In operation, the fundamental machine frequency is hampered by various loading disturbances created by the pressure waves generated during the rock drill application, which initiates faults at different times during a complete cycle of rock drilling. These faults include failure of internal parts, excessive channel openings and damaged parts, causing enough non-linearity in the pressure data generated. A fault in such machinery can multiply quite rapidly, leading to accidents like complete failure of the equipment and loss of life. Therefore, it is crucial to classify the fault and inform the operator of it. The fault classification challenge escalates further when the rock drill operates on previously unknown operating conditions. In the present work, we compare the performance of deep learning models like Long short-term memory, Convolutional Neural Network, and Residual Network to classify faults, whose signature is recorded in data generated at a frequency of 50kHz when a rock drill is in operation. We also demonstrate how the accuracy of models vary when the models are tested on unseen operating conditions. An overall analysis is provided to generalize a model for fault classification in industrial applications over contrasting operating conditions.

Download


Paper Citation


in Harvard Style

Reddy N., Gupta A., Dhande G. and Pasupureddy V. (2023). Step Towards Generalization: Fault Classification in Multivariate High-Frequency Data from Different Operating Regimes of Hydraulic Rock Drill System. In Proceedings of the 12th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-626-2, pages 856-863. DOI: 10.5220/0011676100003411


in Bibtex Style

@conference{icpram23,
author={Nagi Reddy and Ashit Gupta and Gauri Dhande and Vijaykumar Pasupureddy},
title={Step Towards Generalization: Fault Classification in Multivariate High-Frequency Data from Different Operating Regimes of Hydraulic Rock Drill System},
booktitle={Proceedings of the 12th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2023},
pages={856-863},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011676100003411},
isbn={978-989-758-626-2},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 12th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - Step Towards Generalization: Fault Classification in Multivariate High-Frequency Data from Different Operating Regimes of Hydraulic Rock Drill System
SN - 978-989-758-626-2
AU - Reddy N.
AU - Gupta A.
AU - Dhande G.
AU - Pasupureddy V.
PY - 2023
SP - 856
EP - 863
DO - 10.5220/0011676100003411