PHM Survey : Implementation of Diagnostic Methods for Monitoring Industrial Systems

Abstract

The modernization of industrial sectors involves the use of complex industrial systems and therefore requires condition based maintenance. This one aims at increasing the operational availability and reducing the life-cycle while increasing the reliability and life expectancy of industrial systems. This maintenance also called predictive maintenance is a part of an emerging philosophy called PHM ‘Prognostics and Health Management’. In this paper, the PHM will be emphasized on the existing diagnostic methods used for fault isolation and identification. This depicts an important part of the PHM as it exploits the data given by the signal-processing step and its output is treated by the prognostic part. The diagnostic is mainly classified in three categories that will be highlighted in this paper.

Combining Wavelets and AR Identification for Condition Monitoring of Electric-cam Mechanisms Using PLCopen Readings of Motor Torque

“…In the realm of heavy-duty machinery, the occurrence of component failures is a common concern. Addressing the diagnosis of their health status and predicting their remaining useful life (RUL) has become a focal point of research efforts in the field (Soualhi et al, 2017;Qi, Zhang, & Spencer, 2023). This advancement owes much to the everincreasing computational capabilities of computers, spanning from on-board processing (edge-computing) to external systems like industrial computers and cloud-based computing.…”