Circuit breaker condition assessment through a fuzzy‐probabilistic analysis of actuating coil's current

Razi-Kazemi, Ali A.

doi:10.1049/iet-gtd.2014.1236

Cited by 30 publications

(22 citation statements)

References 19 publications

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“…In [19] and [20], the interaction between various failures resulting from malfunction in latch, control voltage and coil have been investigated. In [21] and [22], the appropriate diagnostic features of the coil current have been identified to apply for fault prediction. In [18], this signal along with the travel curve (TC) have been employed for fault detection in HVCBs.…”

Section: Monitoring Parameters and Challengesmentioning

confidence: 99%

“…In [18], this signal along with the travel curve (TC) have been employed for fault detection in HVCBs. The problems in battery, degraded contacts and coil, and friction have been diagnosed using CC in [22], and [23]. Reference [25] employs CC signal for detection of the coil aging, core jamming and lack of core travel space.…”

Section: Monitoring Parameters and Challengesmentioning

confidence: 99%

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Condition Monitoring of High Voltage Circuit Breakers: Past to Future

Razi-Kazemi

Niayesh

2021

IEEE Trans. Power Delivery

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High voltage circuit breakers (HVCBs) play a critical role on providing the desired reliability, and resiliency in power systems. In order to extend their lifetime and predict the failures, various maintenance policies could be applied on these critical components. Amongst these strategies, condition-based maintenance (CBM) provides a satisfactory agreement with future smart environment. This paper aims to provide an insight into the relevant developments in this subject and to explore the viable visions compatible with future research stream. Accordingly, three directions, i.e. diagnostic signals, intelligent modelling and using monitoring data in asset management have been addressed in this paper. It presents challenges dealing with real-time assessment of the diagnostic signals relating to measurements, and analyses. Subsequently, the issues associated with using artificial intelligent (AI) and Machine learning for providing intelligent algorithms have been discussed. Finally, the connection between the monitoring data and the asset management approach is investigated. The latter is looking for the subjects including remaining lifetime estimation, prioritization, and health index definitions. This paper has attempted to make a bridge from past to future research trends in the failure diagnosis of HVCBs.

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Section: Monitoring Parameters and Challengesmentioning

confidence: 99%

Section: Monitoring Parameters and Challengesmentioning

confidence: 99%

Condition Monitoring of High Voltage Circuit Breakers: Past to Future

Razi-Kazemi

Niayesh

2021

IEEE Trans. Power Delivery

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“…The closing and opening electromagnet irons play important and critical roles in the operating mechanism, and the movement process of the iron core could be described by the coil current [7]. Then, the signals can be extracted based on a deep belief network [8], a real-time diagnosis algorithm [9], or a fuzzy-probabilistic-based condition assessment algorithm [10] to assess the CB operation performance. The algorithms are adopted to assist in the construction of a high-quality fault diagnosis model.…”

Section: A Previous Work 1) Fault Diagnose Of Circuit Breakermentioning

confidence: 99%

Mechanical Condition Identification and Prediction of Spring Operating Mechanism of High Voltage Circuit Breaker

et al. 2020

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Spring operation mechanism is widely used in high voltage circuit breakers, and its reliability is related to the ability of the circuit breaker breaking fault current. During the life cycle of spring operating mechanism, stress relaxation, metal fatigue, and any other mechanical defects are easily occurring. And the mechanical performance of the circuit breaker will be influenced by the above defects. Therefore, identifying and predicting the mechanical conditions of the spring operation mechanism can improve the reliability of the circuit breaker. In the present paper, the 252 kV circuit breakers are used as test objects. Firstly, the spring stress relaxation test, the life-cycle test, and the failure simulated test of 252 kV circuit breakers are carried out. Secondly, a multi-body dynamics simulation model of the experimental prototype is established. Thirdly, support vector machine, random forest, and deep neural network are used in the condition identification of the circuit breaker to compare their performances. Then, the prediction model of spring in stress relaxation test is built, however, the model is not suitable for the life-cycle test of repeat close-open operation. Finally, the remaining useful life prediction model is proposed by using Wiener Process.

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“…Pearson correlation coefficient is employed to reveal the relationships of the features of measured data [16]. And it is used via (4) to explore the correlation of the parameters.…”

Section: B Optimization Of the Featuresmentioning

confidence: 99%

Condition Assessment of High Voltage Circuit Breaker Operating Mechanism Based on Coil Current Waveform

Duan¹,

Hongcai²,

Min³

et al. 2016

Proceedings of the 2016 International Conference on Energy, Power and Electrical Engineering

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Abstract-In order to evaluate the condition of the high voltage circuit breaker (HVCB) operating mechanism, a method based on the coil current (CC) waveform of the operating mechanism has been studied in this paper. A finite element method (FEM) with high accuracy has been used to establish an electromagnetic system model of the operating mechanism. The effects of the mechanical parameter variations and mechanism faults on the CC waveform have been studied by simulation and experimental studies, and the features and inflections of the CC waveform are determined as the evaluation indices of the mechanism. Then the slope method has been used to extract features and inflections of the CC waveform after filtering, and the CC features are optimized by Pearson correlation coefficient method. Finally, the condition of the HVCB operating mechanism has been evaluated by the combination of the waveform recognition and neural network analysis. It has been concluded that the evaluation results can accurately reflect the operation condition of the HVCB operating mechanism.

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Circuit breaker condition assessment through a fuzzy‐probabilistic analysis of actuating coil's current

Cited by 30 publications

References 19 publications

Condition Monitoring of High Voltage Circuit Breakers: Past to Future

Condition Monitoring of High Voltage Circuit Breakers: Past to Future

Mechanical Condition Identification and Prediction of Spring Operating Mechanism of High Voltage Circuit Breaker

Condition Assessment of High Voltage Circuit Breaker Operating Mechanism Based on Coil Current Waveform

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