Topic
Condition monitoring
About: Condition monitoring is a research topic. Over the lifetime, 13911 publications have been published within this topic receiving 201649 citations.
Papers published on a yearly basis
Papers
More filters
TL;DR: The sole purpose is to highlight the overwhelming role of CMS as a better and viable option for increasing the production rate and lowering the downtime in the wind energy converter.
144 citations
Book•
01 Jan 1994
TL;DR: In this paper, the authors present a survey of condition-based maintenance information systems in the manufacturing domain, focusing on the aspects of maintenance, including basic diagnostic techniques, vibration monitoring, and particle monitoring.
Abstract: 1.Introduction - aspects of maintenance. 2. Maintenance information systems. 3. Basic diagnostic techniques. 4. Vibration monitoring. 5. Fluid condition and particle monitoring. 6. Systems approach to condition monitoring. 7. Application of system condition monitoring. 8. Processing of diagnostics data. 9. Future developments of condition-based maintenance in manufacture. Index
143 citations
TL;DR: A new multi-speed fault diagnostic approach is presented by using self-adaptive wavelet transform components generated from bearing vibration signals that is capable of discriminating signatures from four conditions of rolling bearing.
Abstract: Condition monitoring and incipient fault diagnosis of rolling bearing is of great importance to detect failures and ensure reliable operations in rotating machinery. In this paper, a new multi-speed fault diagnostic approach is presented by using self-adaptive wavelet transform components generated from bearing vibration signals. The proposed approach is capable of discriminating signatures from four conditions of rolling bearing, i.e., normal bearing and three different types of defected bearings on outer race, inner race, and roller separately. Particle swarm optimization and Broyden-Fletche—Goldfarb-Shanno-based quasi-Newton minimization algorithms are applied to seek optimal parameters of Impulse Modeling-based continuous wavelet transform model. Then, a 3-D feature space of the statistical parameters and a nearest neighbor classifier are, respectively, applied for fault signature extraction and fault classification. Effectiveness of this approach is then evaluated, and the results have achieved an overall accuracy of 100%. Moreover, the generated discriminatory fault signatures are suitable for multi-speed fault data sets. This technique will be further implemented and tested in a real industrial environment.
142 citations
TL;DR: In this article, the authors introduce some of the basic concepts of chaos theory, then details a method for quantifying a fractal dimension from a time series, the correlation dimension.
141 citations
TL;DR: Genetic programming is used to detect faults in rotating machinery to examine the performance of two-class normal/fault recognition and the results are compared with a few other methods for fault detection.
141 citations