A New Method to Fault Diagnosis for Circuit Breakers Based on Characteristic Entropy of Wavelet Packet

Sun, Laijun; Liu, Mingliang; Qian, Haibo; Zhen, Jianju

doi:10.1109/isdea.2010.87

Cited by 10 publications

(19 citation statements)

References 7 publications

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“…The entropy is a measure of signal heterogeneity degree. Therefore, we can use WP-entropy to detect the deviation degree of the fault state [23,24]. Fig.…”

Section: Methodsmentioning

confidence: 99%

“…Then, plus the normal working state of circuit breaker, we obtained 7 groups of vibration signals. According to previous vibration signal acquisition method and environment [21][22][23][24], as shown in Fig. (6), the recorded signals from top to bottom are respectively standard signal, signals under the condition of loose screw (3 signals for Fault I,), and signals under the condition of time-delay fault (3 signals for Fault II).…”

Section: Applicationsmentioning

confidence: 99%

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A New Fault Diagnosis Method for High Voltage Circuit Breakers Based on Wavelet Packet and Radical Basis Function Neural Network

Liu¹,

Wang²,

Sun³

et al. 2014

TOCSJ

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Abstract:A new method that researching fault diagnosis of high-voltage (HV) circuit breaker (CB) is proposed. The method combines Wavelet Packet (WP) with Radical Basis Function (RBF) Neural Network (NN). Firstly, by applying the theory of WP decomposition and reconstruction, the mechanical vibration signal of CB was decomposed into different frequency bands, and the coefficients are reconstructed in the corresponding node. After that, the feature vector was extracted by equal-energy segment entropy from reconstructed signals. Finally, fault diagnosis has been realized through the classification of feature parameters combined with RBF neural network. The experiment outputs show that the method can be applied in diagnosis.

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“…The entropy is a measure of signal heterogeneity degree. Therefore, we can use WP-entropy to detect the deviation degree of the fault state [23,24]. Fig.…”

Section: Methodsmentioning

confidence: 99%

Section: Applicationsmentioning

confidence: 99%

A New Fault Diagnosis Method for High Voltage Circuit Breakers Based on Wavelet Packet and Radical Basis Function Neural Network

Liu¹,

Wang²,

Sun³

et al. 2014

TOCSJ

View full text Add to dashboard Cite

show abstract

“…In order to detect a spring fatigue fault and a screw losing fault, the WPT is used to get energy envelopes of vibration signals [12][13] [14]. The method can be divided into three steps.…”

Section: Signal Analysis With Wptmentioning

confidence: 99%

Fault diagnosis of high-voltage circuit breakers using wavelet packet technique and support vector machine

Jin

Tang

Qian

et al. 2017

CIRED - Open Access Proceedings Journal

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The subject addressed in the paper is mechanical fault diagnosis of high-voltage circuit breakers (HVCBs) based on vibration signal analysis. In this paper, the vibration signature measured from the SF 6 HVCB is processed using the fast Fourier transform (FFT) and the wavelet packet technique (WPT). With the FFT and the WPT, the vibration signature is decomposed into different frequency bands, and the energy of the signal is extracted from individual frequency bands and calculated as the individual condition eigenvector. Followed by that, parameters captured from the WPT are optimized with the particle swarm optimization (PSO) and the result is used to train a multi-fault classification model based on the kernel method of the support vector machine (SVM). At the end, fitness values are evaluated with the trained SVM to classify conditions and diagnose faults of the SF 6 HVCB.

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“…Reference [25] uses SWPE to analyze the transient fault current in the protection location of the series compensated transmission line with static synchronous series compensator. In reference [26], based on WPT and Shannon entropy theory, a new method is presented to diagnosis fault for high voltage circuit breakers, and its steps and analysis are also introduced. The experimentation indicates the method can easily and accurately diagnose breaker faults, and gives an excellent resolution for fault diagnosis of HV circuit breakers.…”

Section: Application Of Swpe In a Power Systemmentioning

confidence: 99%

Application of Shannon Wavelet Entropy and Shannon Wavelet Packet Entropy in Analysis of Power System Transient Signals

Chen

Dou

et al. 2016

Entropy

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Abstract:In a power system, the analysis of transient signals is the theoretical basis of fault diagnosis and transient protection theory. Shannon wavelet entropy (SWE) and Shannon wavelet packet entropy (SWPE) are powerful mathematics tools for transient signal analysis. Combined with the recent achievements regarding SWE and SWPE, their applications are summarized in feature extraction of transient signals and transient fault recognition. For wavelet aliasing at adjacent scale of wavelet decomposition, the impact of wavelet aliasing is analyzed for feature extraction accuracy of SWE and SWPE, and their differences are compared. Meanwhile, the analyses mentioned are verified by partial discharge (PD) feature extraction of power cable. Finally, some new ideas and further researches are proposed in the wavelet entropy mechanism, operation speed and how to overcome wavelet aliasing.

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A New Method to Fault Diagnosis for Circuit Breakers Based on Characteristic Entropy of Wavelet Packet

Cited by 10 publications

References 7 publications

A New Fault Diagnosis Method for High Voltage Circuit Breakers Based on Wavelet Packet and Radical Basis Function Neural Network

A New Fault Diagnosis Method for High Voltage Circuit Breakers Based on Wavelet Packet and Radical Basis Function Neural Network

Fault diagnosis of high-voltage circuit breakers using wavelet packet technique and support vector machine

Application of Shannon Wavelet Entropy and Shannon Wavelet Packet Entropy in Analysis of Power System Transient Signals

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