Topic
Condition monitoring
About: Condition monitoring is a research topic. Over the lifetime, 13911 publications have been published within this topic receiving 201649 citations.
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TL;DR: This paper is dedicated to analyze the different AE principles in RE systems, and to comprehensively summarize and clearly highlight the advanced methods and challenges.
66 citations
TL;DR: In this paper, a non-linear principal component analysis (NPCA) is proposed to reduce the dimensionality of the process by creating a new set of variables, principal components, which attempt to reflect the true underlying system dimension.
66 citations
01 Mar 1987
TL;DR: This paper proposes to cope with monitoring by proposing a hierarchical structuration of monitoring functions and to use jointly Petri nets for detection and handling purposes and a knowledge based approach in an integrated way.
Abstract: The control of FMS is now currently performed by means of distributed and hierarchical systems and Petri nets have been proved useful to specify such systems. In this paper, we propose to cope with monitoring by proposing a hierarchical structuration of monitoring functions and to use jointly Petri nets (for detection and handling purposes) and a knowledge based approach (for diagnosis and decision) in an integrated way.
66 citations
TL;DR: In this article, a novel and sensitive frequency response analysis (FRA) technique for off/on-line condition monitoring of expensive power apparatus is presented. But the main objective is to investigate the applicability of this predictive maintenance technique to diagnosing power transformer failures, to characterize the transformer in a frequency plane for safe operation, and to develop on-line monitoring technique.
Abstract: This letter presents a novel and sensitive frequency response analysis (FRA) technique for off/on-line condition monitoring of expensive power apparatus. The main objective is to investigate the applicability of this predictive maintenance technique to diagnosing power transformer failures, to characterize the transformer in a frequency plane for safe operation, and to develop on-line monitoring technique. The effectiveness of this technique is demonstrated on a 2.5 MVA transformer housed at the High Voltage Laboratory of Pacific Power International (PPI) and then tested on three field transformers. The on-line technique is verified on a single-phase high voltage transformer. This study shows that FRA results are very sensitive to faults. The configuration of the measurement set up, frequency range and terminations play a greater role in getting reproducible, fault-indicating results. The interpretation of the voluminous data and analysis relevant to the faults opens a gateway to develop smart power apparatus.
66 citations
TL;DR: In this article, an information maximisation based blind source separation algorithm (a type of ICA) was proposed for gear vibration measurements, where the individual gear and pinion vibrations cannot be separated using the blind separation algorithm, but the learning curve can be used to detect impulsive and random changes in the data.
65 citations