Spectroscopic On-Line Monitoring of Cu/W Contacts Erosion in HVCBs Using Optical-Fibre Based Sensor and Chromatic Methodology

Wang, Zhixiang; Jones, G.R.; Spencer, J. W.; Wang, Xiaohua; Rong, Mingzhe

doi:10.3390/s17030519

Cited by 6 publications

(6 citation statements)

References 19 publications

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“…An HVCB’s contacts will wear out under the impact of the mechanical closing force and contact stress during current interruption, resulting in contact deterioration [ 5 , 6 ]. Establishing a state-of-the-art HVCB contact status identification model can reduce its maintenance costs and avoid potentially devastating consequences before a severe accident occurs [ 7 , 8 ].…”

Section: Introductionmentioning

confidence: 99%

SF6 High-Voltage Circuit Breaker Contact Status Detection at Different Currents

Guo

Han

et al. 2022

Sensors

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Currently, the online non-destructive testing (NDT) methods to measure the contact states of high-voltage circuit breakers (HVCBs) with SF6 gas as a quenching medium are lacking. This paper aims to put forward a novel method to detect the contact state of an HVCB based on the vibrational signal. First, for a 40.5-kV SF6 HVCB prototype, a mechanical vibration detection system along with a high-current generator to provide the test current is designed. Given this, vibration test experiments are carried out, and the vibration signal data under various currents and corresponding contact states are obtained. Afterward, a feature extraction method based on the frequency is designed. The state of the HVCB contacts is then determined using optimized deep neural networks (DNNs) along with the method of adaptive moment estimation (Adam) on the obtained experimental data. Finally, the hyperparameters for the DNNs are tuned using the Bayesian optimization (BO) technique, and a global HVCB contact state recognition model at various currents is proposed. The obtained results clearly depict that the proposed recognition model can accurately identify five various contact states of HVCBs for the currents between 1000 A and 3500 A, and the recognition accuracy rate is above 96%. The designed experimental and theoretical analysis in our study will provide the references for future monitoring and diagnosis of faults in HVCBs.

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Section: Introductionmentioning

confidence: 99%

SF6 High-Voltage Circuit Breaker Contact Status Detection at Different Currents

Guo

Han

et al. 2022

Sensors

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“…Simultaneously, this study created a database of crucial electrical life features and effectively applied the strategy to electrical fire detection. In [17,18], the corresponding relationship between the dynamic contact resistance of the circuit breaker and the contact erosion state is analyzed, and the related state evaluation methods are proposed. The authors of [19] investigate an online evaluation approach of the high-voltage circuit breaker considering multiple physical parameters.…”

Section: Introductionmentioning

confidence: 99%

Electrical Life Assessment of the Low-Voltage Circuit Breaker (LVCB) Considering Arc Voltage

Liu

Wang

2022

Energies

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The low-voltage circuit breaker (LVCB) is commonly utilized in the distribution network. An accurate evaluation of its electrical life is related to the safety and reliability of electric energy output. The traditional arc erosion model only considers the effect of current on contact wear while ignoring the impact of operation conditions (supply voltage and power factor) on electrical life. As a result of the arc voltage, the original circuit topology changes, resulting in an early current zero. At 220–660 V AC supply voltages, arc voltage causes the distortion of the breaking current waveform, and the contact erosion amount (CEA) is smaller than that in the ideal case. This work investigates the effect of arc voltage on breaking current, develops an arc erosion model that includes arc voltage, and compares the CEA curves for various supply voltages and power factors. The electrical life of the LVCB is then simulated using the Monte Carlo approach to determine the distribution of electrical life under various operating situations. The results reveal that the LVCB’s electrical life diminishes as the supply voltage increases under the same power factor; it first declines and then increases as the power factor grows under the same supply voltage. For the combination of two parameters (220 V, 0.95) and (660 V, 0.65), the electrical life difference of the LVCB can reach 21.4%. The method solves the low accuracy problem of the LVCB life assessment under different operation conditions. It improves the efficiency of overhaul and maintenance on the LVCB in power distribution systems.

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“…Degradation of the HVCB is caused by several types of stress and aging, such as mechanical maladjustment, switching arcs erosion, and insulation level decline. The existing literature covers a wide range of specific countermeasures, including mechanism dynamic features [8][9][10], dynamic contact resistance [11], partial discharge signal [12,13], decomposition gas [14], vibration [15], and spectroscopic monitoring [16]. Furthermore, numerous studies applied neural networks [8], support vector machine (SVM) [17], fuzzy logic [18], and other methods [19], to introduce more automation and intelligence into the signal analysis.…”

Section: Introductionmentioning

confidence: 99%

“…After preprocessing and generating the sub-sequences, an alternating renewal process was implemented between the new co-occurrence pattern construction and the Gibbs sampling. The final average output reflects the time decrease presented in Equation (16) due to the multi-sampling process. Finally, Equation (14) provides the future distribution prognosis using the learned parameters of the last sub-sequence of each HVCB.…”

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confidence: 99%

Failure Prognosis of High Voltage Circuit Breakers with Temporal Latent Dirichlet Allocation

Wang

Yang

et al. 2017

Energies

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Abstract:The continual accumulation of power grid failure logs provides a valuable but rarely used source for data mining. Sequential analysis, aiming at exploiting the temporal evolution and exploring the future trend in power grid failures, is an increasingly promising alternative for predictive scheduling and decision-making. In this paper, a temporal Latent Dirichlet Allocation (TLDA) framework is proposed to proactively reduce the cardinality of the event categories and estimate the future failure distributions by automatically uncovering the hidden patterns. The aim was to model the failure sequence as a mixture of several failure patterns, each of which was characterized by an infinite mixture of failures with certain probabilities. This state space dependency was captured by a hierarchical Bayesian framework. The model was temporally extended by establishing the long-term dependency with new co-occurrence patterns. Evaluation of the high voltage circuit breakers (HVCBs) demonstrated that the TLDA model had higher fidelities of 51.13%, 73.86%, and 92.93% in the Top-1, Top-5, and Top-10 failure prediction tasks over the baselines, respectively. In addition to the quantitative results, we showed that the TLDA can be successfully used for extracting the time-varying failure patterns and capture the failure association with a cluster coalition method.

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Spectroscopic On-Line Monitoring of Cu/W Contacts Erosion in HVCBs Using Optical-Fibre Based Sensor and Chromatic Methodology

Cited by 6 publications

References 19 publications

SF6 High-Voltage Circuit Breaker Contact Status Detection at Different Currents

SF6 High-Voltage Circuit Breaker Contact Status Detection at Different Currents

Electrical Life Assessment of the Low-Voltage Circuit Breaker (LVCB) Considering Arc Voltage

Failure Prognosis of High Voltage Circuit Breakers with Temporal Latent Dirichlet Allocation

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