Research on a Modified Judgment Method of the Closing Moment for On-line Monitoring System of High Voltage Circuit Breaker

Mei, Fei; Mashino, Jun; Zheng, Jianhua; Yang, Sainan

doi:10.1109/cdciem.2012.137

Cited by 2 publications

(4 citation statements)

References 5 publications

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“…Recently the auto-associative kernel regression (AAKR) method has been developed as a similarity-based model (SBM) for condition monitoring and fault alerting in largescale turbomachines (Garvey 2007, Di Maio 2013, Fei 2015, Sairam 2016, Yu 2017, Guo 2011, Brandsaeter 2017, Qian 2018, Baraldi 2015. This approach utilizes multivariate historical data collected at normal conditions to establish a system identification model representing the Weijian Tang et al This is an open-access article distributed under the terms of the Creative Commons Attribution 3.0 United States License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.…”

Section: Introductionmentioning

confidence: 99%

“…A health index calculated from the difference of predicted responses and actual measurements is employed to quantitively assess the status of the system. This approach has demonstrated its high accuracy, flexibility and generalization with a broad spectrum of applications in various types of equipment (Garvey 2007, Di Maio 2013, Fei 2015, Sairam 2016, Yu 2017, Guo 2011, Brandsaeter 2017, Qian 2018, Baraldi 2015. It can be effectively applied not only for non-rotating equipment such as boiler in a coal plant (Yu 2017), and gear box in a wind turbine (Guo 2011), but also for rotating machines such as bearings in engine (Brandsaeter 2017), and blades in compressor or steam turbines (Qian 2018).…”

Section: Introductionmentioning

confidence: 99%

“…It should be noted that determination of an alarming threshold also plays a critical role on fault prediction accuracy of the AAKR approach. Several techniques such as sequential probability ratio test (SPRT) (Di Maio 2013, Fei 2015, Qian 2018, likelihood ratio test (Sairam 2016), and empirical estimation (Guo 2011) are commonly used to determine the alarming threshold level. These methods are statistical methods, which take the statistical characteristics of the unit during normal operation as health indicators to monitor the unit operation status in real time.…”

Section: Introductionmentioning

confidence: 99%

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Probabilistic Similarity Based Modeling Approach for Turbomachine Fault Prediction

Tang¹,

Jiang

Zhao³

et al. 2021

PHME_CONF

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Faults in the critical components of a turbomachine usually result in unplanned outage, leading to huge loss of properties and life. Condition monitoring becomes a promising tool to provide automatic early alerting of potential damage in critical components thus ensuring the system safety and reliability while lowering its maintenance cost. This is still a challenging hot topic due to the data imperfection and multivariate correlation, as well as the variation of faults and components in different turbomachines. This paper presents an enhanced generic probabilistic similarity-based method to address these challenges in fault prediction of large turbomachines. Bayesian wavelet multi-scale decomposition is proposed to address the potential noise in the sensed multivariate time historical data. The advanced signal processing balances the over-denoising and under-denoising of raw multivariate signals. An optimized auto-associative kernel regression (OAKR) approach is developed to represent the healthy status of the turbomachine system and further predict its responses under unknown status. The band width of the kernel function in the method is optimized through Nelder-Mead simplex algorithm. The alerting threshold based on the squared mean errors of the predicted and measured time series is adjusted automatically through a rolling window strategy. A comparison study is conducted to demonstrate the effectiveness and feasibility of the proposed methodology by using the real-world data and events collected from a centrifugal compressor.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Probabilistic Similarity Based Modeling Approach for Turbomachine Fault Prediction

Tang¹,

Jiang

Zhao³

et al. 2021

PHME_CONF

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“…In opening operation, opening coil receives the opening-control signal, then lock catch trips with magnetic forces. The energy, which is stored in opening spring, is released and contact is moved by mechanical transmission unit [7,8]. …”

Section: Action Characteristic Of Spring Operating Mechanismmentioning

confidence: 99%

State Diagnosis for Closing/Opening Spring in the Spring Operating Mechanism of Circuit Breaker

Xu¹,

Guo²,

Li³

et al. 2017

dtetr

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Abstract. In order to ensure safe and reliable operation of the spring operating mechanism, a method of spring's state diagnosis in spring operating mechanism is proposed. Through the analyze the spring's operation characteristic in storing process and in closing/opening process, the effective output of motor in storing process and the closing/opening speed are extracted, and these are used as characteristic parameters to diagnose spring's state. The diagnosis process of closing/opening spring's state is specifically analyzed and described based on the judgment of characteristic parameters. The diagnosis system of closing/opening spring's state is designed, and it is verified by combining with the CT20 spring operating mechanism. Through the contrast experiment of old and new closing/opening spring, the proposed diagnosis method for opening/closing spring is validated to be simple and accurate, and the result of the diagnosis is very well.

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Research on a Modified Judgment Method of the Closing Moment for On-line Monitoring System of High Voltage Circuit Breaker

Cited by 2 publications

References 5 publications

Probabilistic Similarity Based Modeling Approach for Turbomachine Fault Prediction

Probabilistic Similarity Based Modeling Approach for Turbomachine Fault Prediction

State Diagnosis for Closing/Opening Spring in the Spring Operating Mechanism of Circuit Breaker

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