Prognostics algorithms for circuit breaker application: A benchmark analysis

Fasanotti, Luca; Cavalieri, Sergio; Tomasini, Marco; Floreani, F.; Ierace, Stefano

doi:10.1109/indin.2014.6945557

Cited by 7 publications

(2 citation statements)

References 11 publications

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“…Combining previously mentioned frequency and time-frequency methods with fields such as chaos theory, some authors based their work on fractal dimension [14], [18], [19] or ergodic quantities such as Largest Lyapunov exponent [20] or information entropy [21], [22]. Also, there is a large portion of available literature that utilizes variations of a well-known algorithm derived from the speech recognition niche, the Dynamic Time Warp (DTW) [23], [24], [25], [26], [27].…”

Section: Introductionmentioning

confidence: 99%

Condition Assessment of Power Circuit Breakers Based on Machine Learning Algorithms

Obarcanin¹,

Skulj

Lačević

2023

IEEE Trans. Power Delivery

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This paper presents two approaches to power circuit condition assessment. The first one covers a wide variety of machine learning classification algorithms where the input for the classification is a manually selected feature set. The second one utilizes deep learning classification based on the convolutional neural network. Both approaches revolve around the idea behind spectral kurtosis, one of which exploits its visual representation in the form of kurtogram. The first approach uses a spectral kurtosis curve as the base for feature extraction while the second approach uses a spectral kurtosis kurtogram as a single input into the convolutional neural network. The validation is performed on a large set of vibration signatures and compared to competing state-of-the-art algorithms. The results indicate promising features of the proposed approach.

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Section: Introductionmentioning

confidence: 99%

Condition Assessment of Power Circuit Breakers Based on Machine Learning Algorithms

Obarcanin¹,

Skulj

Lačević

2023

IEEE Trans. Power Delivery

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“…However, the maintenance of the HVCB over its lifetime and exploitation is eminent. Several maintenance approaches are present nowadays, such as the traditional "Fail and Fix" approach, which is utilized only when a breakdown occurs, the "Predict and Prevent" approach combined with time-based maintenance or "Condition-based maintenance" [1]. Time-based maintenance defines periodic intervals for a check-up and testing of the HVCB what can lead to unnecessary intervention and even yield defects during the unnecessary operation of the HVCB [2].…”

Section: Introductionmentioning

confidence: 99%

High Voltage Circuit Breaker Vibration Signature Indices Evaluation for Condition Assessment

Obarcanin¹,

Škulj²,

Lačević

2021

B&H Electrical Engineering

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The importance of the high voltage circuit breaker for the power system’s safe and reliable operation is paramount. This research aims to analyse and provide the most significant high voltage circuit breaker health state indices based on the non-invasive vibration fingerprint measurement method. Results obtained and presented in this paper are validated on the data set acquired from the vacuum circuit breaker.

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A Pattern Recognition Methodology for Fault Detection: A Circuit Breaker Case Study

Campagnoni

Ierace

Floreani

et al. 2016

Lecture Notes in Mechanical Engineering

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Prognostics algorithms for circuit breaker application: A benchmark analysis

Cited by 7 publications

References 11 publications

Condition Assessment of Power Circuit Breakers Based on Machine Learning Algorithms

Condition Assessment of Power Circuit Breakers Based on Machine Learning Algorithms

High Voltage Circuit Breaker Vibration Signature Indices Evaluation for Condition Assessment

A Pattern Recognition Methodology for Fault Detection: A Circuit Breaker Case Study

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