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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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Journal ArticleDOI
TL;DR: In this paper, a novel online technique is introduced to detect the internal faults within a power transformer by constructing the voltage-current (V - I) locus diagram to provide a current state of the transformer.
Abstract: Frequency-response analysis (FRA) has been growing in popularity in recent times as a tool to detect mechanical deformation within power transformers. To conduct the test, the transformer has to be taken out of service which may cause interruption to the electricity grid. Moreover, because FRA relies on graphical analysis, it calls for an expert to analyze the results. As so far, there is no standard code for FRA interpretation worldwide. In this paper, a novel online technique is introduced to detect the internal faults within a power transformer by constructing the voltage-current (V - I) locus diagram to provide a current state of the transformer. The technique does not call for any special equipment as it uses the existing metering devices attached to any power transformer to monitor the input voltage, output voltage, and the input current at the power frequency and, hence, online monitoring can be realized. Various types of faults have been simulated to assess its impact on the proposed locus. A Matlab code based on digital image processing is developed to calculate any deviation of the V - I locus with respect to the reference one and to identify the type of fault. The proposed technique is easy to be implemented and automated so that the requirement for expert personnel can be eliminated.

163 citations

Journal ArticleDOI
TL;DR: In this paper, a methodology is developed to use data acquisition derived from condition monitoring and standard diagnosis for rehabilitation purposes of transformers, where the interpretation and understanding of the test data are obtained from international test standards to determine the current condition of transformer.
Abstract: In this paper, a methodology is developed to use data acquisition derived from condition monitoring and standard diagnosis for rehabilitation purposes of transformers. The interpretation and understanding of the test data are obtained from international test standards to determine the current condition of transformers. In an attempt to ascertain monitoring priorities, the effective test methods are selected for transformer diagnosis. In particular, the standardization of diagnostic and analytical techniques are being improved that will enable field personnel to more easily use the test results and will reduce the need for interpretation by experts. In addition, the advanced method has the potential to reduce the time greatly and increase the accuracy of diagnostics. The important aim of the standardization is to develop the multiple diagnostic models that combine results from the different tests and give an overall assessment of reliability and maintenance for transformers.

163 citations

Journal ArticleDOI
TL;DR: In this article, the effect of the rotational speed on the diagnostics of rolling element bearing defects is investigated and an optimum sensor location on the structure is sought, which can be employed by analyzing the bearing structure following the procedure proposed in this study.

162 citations

Journal ArticleDOI
TL;DR: In this paper, a new time-frequency technique, known as basis pursuit, was developed for detecting inner race and outer race faults in a rolling bearing with inner and outer races.

161 citations

Journal ArticleDOI
TL;DR: In this article, a new condition-monitoring method based on the nonlinear state estimate technique for a wind turbine generator is proposed, which is used to construct the normal behavior model of the electrical generator temperature.
Abstract: Condition monitoring can greatly reduce the maintenance cost for a wind turbine. In this paper, a new condition-monitoring method based on the nonlinear state estimate technique for a wind turbine generator is proposed. The technique is used to construct the normal behavior model of the electrical generator temperature. A new and improved memory matrix construction method is adopted to achieve better coverage of the generator's normal operational space. Generator incipient failure is indicated when the residuals between model estimates and the measured generator temperature become significant. Moving window averaging is used to detect statistically significant changes of the residual mean value and standard deviation in an effective manner; when these parameters exceed predefined thresholds, an incipient failure is flagged. Examples based on data from the Supervisory Control and Data Acquisition system at a wind farm located at Zhangjiakou in northern China have been used to validate the approach and examine its sensitivity to key factors that influence the performance of the approach. It is demonstrated that the technique can identify dangerous generator over temperature before damage has occurred that results in complete shutdown of the turbine.

161 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
2023164
2022413
2021798
2020927
2019936
2018906