High Voltage Circuit Breaker Research Articles

High-Voltage Circuit Breaker Fault Diagnosis Using a Hybrid Feature Transformation Approach Based on Random Forest and Stacked Autoencoder

In recent years, machine learning techniques have been applied to test the fault type in high-voltage circuit breakers (HVCBs). Most related research involves in improving the classification method for higher precision. Nevertheless, as an important part of the diagnosis, the feature information description of the vibration signal of an HVCB has been neglected; in particular, its diversity and significance are rarely considered in many real-world fault-diagnosis applications. Therefore, in this paper, a hybrid feature transformation is proposed to optimize the diagnosis performance for HVCB faults. First, we introduce a nonlinear feature mapping in the wavelet package time–frequency energy rate feature space based on random forest binary coding to extend the feature width. Then, a stacked autoencoder neural network is used for compressing the feature depth. Finally, five typical classifiers are applied in the hybrid feature space based on the experimental dataset. The superiority of the proposed feature optimal approach is verified by comparing the results in the three abovementioned feature spaces.

Analysis of heat treatment defect of load-bearing metal parts of high voltage circuit breaker mechanism

Failure analysis was carried out on the circuit breaker gear damaged in operation. Various detection methods were applied including composition analysis, hardness testing, metallographic observation, fracture scanning analysis and so on. The failure reason was found out to be improper heat treatment process, and corresponding rectification opinions were also put forward.

An Integrated Sensing Architecture Used for Depth State Perception of High Voltage Circuit Breakers

In order to strengthen the management of circuit breakers and sense its operation status at any time, condition-based maintenance has been carried out in power grids. Depending on the advanced condition monitoring and diagnosis technology, the abnormality of equipment can be judged and the failure of equipment can be predicted effectively. This paper discusses the state parameters need to be monitored for deep state sensing of high voltage circuit breakers. Monitoring parameters mainly include the current of opening/closing coils and energy storage motor coil, primary current and displacement of operating mechanism, respectively. And then, aiming at the complex installation environment of switch cabinet, a small integrated depth sensing node architecture is designed.

Accelerated life testing for reliability improvement: a case study on Moulded Case Circuit Breaker (MCCB) mechanism

MCCB plays a critical role in electricity distribution, and its failure may be costly and hazardous. According to Conseil International des Grands Reseaux Electriques (CIGRE) report CIGRE SC13 (High voltage circuit breaker reliability data for use in system reliability studies, CIGRE Publication, Paris, 1991), it is explored that majority of the circuit breaker failures (90%) occurred due to the failure of the mechanism. In this study, MCCB mechanism is under development stage due to which failure data of mechanism is not available to predict reliability. Therefore, it is essential to assess and improve reliability of MCCB mechanism to know and achieve higher reliability. This paper demonstrates the process of reliability assessment and improvement of the MCCB mechanism by using Boolean algebra and Accelerated Life Test (ALT). Further, Weibull distribution is selected for reliability prediction based on comparison with other distributions. Reliability of mechanism is compared with before improvement and after improvement conditions. In reliability testing, ALT is used, and the result shows that frequency of latch link failure is maximum due to denting and distortion of link. Further, few improvement measures are proposed based on design and manufacturing aspects, and results of suggested measures shows improvement in MCCB mechanism reliability from 72.44 to 95.06%. The design for reliability approach can be implemented rigorously if the failures identified at the development stage of the product, which helps to reduce the considerable losses in the future.

Decomposition mechanism and kinetics of iso-C4 perfluoronitrile (C4F7N) plasmas

Iso-C4 perfluoronitrile (C4F7N) is one of the most promising alternatives to SF6 for use in power equipment, such as high-voltage circuit breakers, due to its excellent electrical properties and environmentally friendly characteristics. The use of SF6 is being reduced because of its high global warming potential. To describe the physical and chemical processes occurring in the arc plasma in circuit breakers, both local thermodynamic equilibrium (LTE) and nonlocal chemical equilibrium (LCE) conditions have to be considered. The plasma composition of the arc core region can be calculated under the assumption of LTE by the method of minimization of the Gibbs free energy. The plasma composition of the arc boundary region or during the arc ignition period is not in LTE or LCE, so the use of a chemical kinetic model that considers the effects of the energy barrier in chemical reactions is required. Calculations for both conditions are presented for C4F7N. To develop the chemical kinetic model, the complete decomposition pathway and transition states were first reexamined and further developed. Based on the decomposition pathway, the rate constants of reactions were obtained according to the variational transition state theory method. The results obtained for the two cases provide a reference for the systematic understanding of the decomposition characteristics of C4F7N gas and for related engineering applications.

Fault diagnosis method for energy storage mechanism of high voltage circuit breaker based on CNN characteristic matrix constructed by sound-vibration signal

Aiming at the problem that some traditional high voltage circuit breaker fault diagnosis methods were over-dependent on subjective experience, the accuracy was not very high and the generalization ability was poor, a fault diagnosis method for energy storage mechanism of high voltage circuit breaker, which based on Convolutional Neural Network (CNN) characteristic matrix constructed by sound-vibration signal ,was proposed. In this paper, firstly, the morphological filtering was used for background noise cancellation of sound signal, and the time scale alignment method based on kurtosis and envelope similarity were proposed to ensure the synchronism of the sound-vibration signal. Secondly, the Pearson correlation coefficient was used to construct two-dimensional image characteristic matrix for the expanded sound-vibration signal. Finally, the characteristic matrix was trained by utilizing CNN. Local Response Normalization (LRN) and core function decorrelation were utilized to improve the structure of CNN model, which reduced the bad impact of large data fluctuation of energy storage process on the diagnostic accuracy of circuit breaker energy storage mechanism. Compared with the traditional method, the proposed method has obvious advantages, whose total accurate rate up to 98.2 % and generalization performance is excellent.

Condition Evaluation for Opening Damper of Spring Operated High-Voltage Circuit Breaker Using Vibration Time-Frequency Image

The working condition of opening damper directly affects the opening mechanical characteristics and component lifetime of high-voltage circuit breaker (HVCB). Vibration diagnostic technique is a noninvasive and efficient way for on-line evaluation of the opening damper. Vibration time-frequency image which constructed by using the method of time-frequency analysis (TFA) contains rich feature information of opening damper's working condition. In this paper, a condition evaluation method for opening damper of the spring operated HVCB based on vibration time-frequency image and convolutional neural network (CNN) is proposed and analyzed. The one-dimensional (1D) vibration signal of the HVCB is transformed into three-dimensional (3D) time-frequency image by utilizing Hilbert-Huang transform (HHT). The 3D time-frequency image directly served as a training sample for the CNN, which avoids the tedious and invalid work of manual feature extraction or selection and can achieves an accurate condition evaluation of the HVCB's opening damper. It can be seen that the noninvasive vibration on-line monitoring and the evaluation algorithm for the opening damper of the HVCB is feasible and effective. The test results carried out on several 12-kV vacuum HVCBs substantiate the proposed approach.

Determination of Discharge Coefficients for Valves of High Voltage Circuit Breakers

Nowadays, high voltage circuit breaker (CB) simulations are mostly based on Computational Fluid Dynamics (CFD) models. Such simulations require significant computer resources. An alternative approach is to use enthalpy flow models, which do not use space discretization of the interrupter unit chambers and valves. Gas flow is calculated based on state of gas in adjacent chambers and valve settings. However, the valve shape has significant influence on the effective flow cross section between chambers. Therefore, in order to ensure correct simulation results, it is necessary to determine the correct values of discharge coefficients for all valves in the interrupter unit of a circuit breaker. In this paper, the discharge coefficients were determined by combining a series of CFD and enthalpy flow simulations for each valve in the interrupter unit. After that, discharge coefficients are used as input for further simulations based on the enthalpy flow model. This way, benefits from both models are combined: more precise gas flow calculation and faster simulations. The proposed novel approach is validated in a high-power laboratory by pressure measurements on a 420 kV 63 kA self-blast circuit breaker.

Influence of Copper Vapors in SF6 Plasma

In this study a theoretical approach allows estimating the ablation mass flux of copper from a corrected Hertz-Knudsen flux. The influence of the copper vapours coming from the anode electrode to an SF6 plasma is studied in a simplified 2D configuration. Depending on the plasma pressure an ablation or a diffusion state is considered. The amount of copper versus time is presented. An RMS current I=10 kA is applied leading at t=10 ms to an amount of copper equal to 0.55 mg. The vapours change the plasma properties mainly the electrical conductivity and radiation and so the plasma behaviour. At time t=5 ms the electrode erosion leads to a copper plasma. This simple case shows the necessity to well consider the copper erosion in plasma modelling as in High Voltage Circuit Breaker (HVCB) where higher current are considered.

Arcing Behaviors in the Large-capacity HV SF6 Gas-blast Interrupters

A comprehension of the dielectric strength recovery processes during the interruption of short-circuit currents in the high-voltage SF6 gas-blast circuit breakers is necessary for their modernisation in order to increase the rated voltage and short circuit breaking current per one break. This paper presents numerical results of the turbulence effects on the interruption ability in the SF6 extinguishing arc chamber.

State of Art and Challenges for the Calculation of Radiative and Transport Properties of Thermal Plasmas in HVCB

This paper is focused on the state-of-the-art and challenges concerning the thermophysical properties of thermal plasmas used in numerical modelling devoted to high voltage circuit breakers. For Local Thermodynamic Equilibrium (LTE) and Non-Local Thermodynamic (NLTE) and/or Chemical Equilibrium (NLCE) plasmas, the methods used to calculate the composition, thermodynamic, transport and radiative properties are presented. A review of these last data is proposed and some comparisons are given for illustrations.

Performance Prediction Method Considering Shock Wave in Nozzle for High-Voltage Circuit Breaker

Interrupting-performance indexes that reflect the physical properties of gas flow are proposed for a breaker terminal fault of a high-voltage circuit breaker. A method of evaluating the shock wave and flow velocity was developed that uses a theoretical equation of supersonic flow which takes into account the nozzle’s shape and stagnation pressure. The predicted flow velocities and positions at which the shock wave forms have strong correlations with the test results.

Analysis of alternative parameters of dynamic resistance measurement in high voltage circuit breakers

Throughout its lifetime, high-voltage circuit breaker (HVCB) contacts suffer from inevitable degradation processes, especially during the formation of electric arcs. Highly degraded contacts can reduce the current interruption capacity and increase the chances of operational faults, which might lead to considerable financial losses. Therefore, the use of efficient evaluating techniques is a key factor to achieve systems reliability. The dynamic resistance measurement (DRM) is a technique that can be used to evaluate the degradation level of HVCB' contacts. It stands out from the usual technique, static resistance measurement, by allowing the assessment of both the main contacts and the arcing contacts (ACs). Usually, the mean resistance or the area under the DRM curve is used to estimate the AC degradation. However, DRM is a non-standardised technique and there are no specified parameters to evaluate the real wear conditions. Therefore, an analysis of alternative parameters extractible from the DRM technique is presented in this study, such as amplitude and variance of the DRM curve. The results attest the possible use of more than one parameter for the continuous evaluation of HVCB ACs, characterising the DRM as a more complete and precise diagnosis tool.

Fault Analysis of High-Voltage Circuit Breakers Based on Coil Current and Contact Travel Waveforms Through Modified SVM Classifier

High-voltage circuit breakers (HVCBs) play a substantial protection role in power networks. The reliable operation of these critical components leads to an increment of resiliency and safety of power systems. It is essential to design a fault diagnostic system that detects the defects in preliminary levels and identify the origins to establish a precise maintenance task. This paper focuses on coil current and contact travel waveforms as significant signals that bear helpful information about the fault occurrence for a typical EDF, 72.5 kV, SF6 HVCB. Healthy and faulty signals simulated based on Michael Stanek's HVCB model in MATLAB, with performing some modifications in the actuating coil and operating mechanism. In the first step, to arrange an efficient fault recognition system, neural network and support vector machine (SVM) have been designed using the information of 475 simulated healthy and faulty HVCBs and verified for 200 new samples. In the second step, to improve the classification results, an additional distinction algorithm has been recommended for the cases in which two failure modes are detected by the classifier. Since any failure mode's impact on the selected features is different, the proposed diagnostic method makes a decision, between two classes of faults, based on the extracted pattern of each failure mode. The recommended method, which is a combination of commonly used classification techniques and the defined algorithm, leads to the more accurate diagnosis.

Breakdown in CO<sub>2</sub> and CO2/C2F4 Mixtures at Elevated Temperatures in the Range 1000-4000 K

CO2 is a promising gas for replacement of SF6 in high voltage circuit breakers. The electric breakdown in CO2 and mixtures with C2F4 from PTFE nozzles is, however, still not fully understood. To understand the electric breakdown in CO2 and mixtures with C2F4 from PTFE nozzles fundamental parameters like the temperature and pressure dependence of critical electric fields are needed. Data on critical fields is usually available based on simulations only and experimental validation is lacking so far. Our present contribution aims to close this gap and presents experiments where the breakdown fields in uniform and weakly non-uniform electric fields are determined at various temperatures and pressures. The gas temperatures were estimated from measurements with pyrometers. The results are compared to theoretical predictions.

Method of Evaluating Exhaust Characteristics of High-Voltage Circuit Breaker

The exhaust characteristics at high current duty of a breaker terminal fault for a gas circuit breaker are evaluated. A method of designing the exhaust chamber so that the exhaust temperature is less than the threshold temperature is then proposed. The threshold temperature is the value at which the maximum electric field of the exhaust chamber coincides with the critical electric field. In the design, the initial value of the structure is determined so as to decrease the number of trials in the development process. The calculation time of the numerical analysis is reduced by combining a one-dimensional (1-D) arc simulation with a two-dimensional (2-D) gas flow simulation of only the exhaust parts. An optimal design of an exhaust chamber using this design method is described as an example. In the interruption test of 63 kA using the optimal structure, dielectric strength was ensured and no flashovers occurred in any opening area.

Design of intelligent detection system for high voltage circuit breaker based on functional integration

Since there are various preventive test items for high voltage circuit breaker, in this paper, a function-integrated hardware is put forward to reduce the height and wiring times of the test personnel and improve the field work efficiency. Firstly, we comprehensively analyze the electrical test requirements for high voltage circuit breaker. Then we integrate multiple detection projects into one system, taking advantage of the fact that each test project can be merged. These test projects include tests of dielectric loss of circuit breaker, capacitance value, circuit resistance, direct resistance of switching coil, mechanical characteristic, closing resistance and closing time as well as insulation resistance and AC withstand voltage of auxiliary control circuit. Next, we configure the required detection items and relevant parameters before the test. Finally, we complete the whole process, which requires connection and disconnection for only once and will automatically finish all project detection, test data collection and intelligent analysis item by item.

Simulation Analysis of Main and Arcing Contact Current Commutation Process in SF6 Circuit Breaker

In order to study the current variation characteristic and its influencing factors of the main and arcing contact during switching and opening process of high voltage circuit breaker, it is necessary to calculate the current commutation process. Firstly, the current formula in the commutation process was obtained based on the circuit model of current commutation. Secondly,based on the theoretical model of switching arc, the MODELS module and language were used to simulate the resistance variation characteristics of piecewise time-varying arc model. Finally, a simplified model of the SF6 circuit breaker arc quenching chamber was established in ATP-EMTP, and each calculation parameter was selected. The current commutation process was calculated by comparing the effect of main contact resistance and arcing contact resistance on current commutation time. It was found that the effect of the contact resistance on the current commutation time was consistent with the contact variation trend. But the effect of main contact resistance on current commutation time was small, while that of arcing contact was large.

Discussion on the method of measuring the loop resistance of high voltage circuit breaker by double-ended grounding technology

Loop resistance is an important technical indicator reflecting the performance and operating status of high-voltage circuit breakers. The traditional test method requires at least one side of the grounding switches of the circuit breaker be opened, and the field operation needs to wait for the dispatch approval, so the work efficiency is extremely low. According to the actual requirements of on-site measurement of high-voltage circuit breakers, a test method and test scheme have been proposed in this paper for measuring loop resistance by using the double-ended grounding technology. At the same time, according to the structural characteristics of high-voltage circuit breaker, the test deviation between the method and the traditional test method is analyzed and compared. Finally, it is concluded that the test method for measuring the loop resistance through using the double-ended grounding technology can fully meet the actual needs of the project.

Artificial intelligence SF6 circuit breaker health assessment

This paper presents advance artificial intelligence (AI) methods for health assessment of high voltage SF6 circuit breakers. Paper presents an overview of monitoring and diagnostics of most important indicators of the state of high voltage SF6 circuit breakers. Special attention is devoted to identifying and determining indicator limit values which can be used by AI in order to create new health assessment. Fuzzy logic as a part of AI was applied to define fuzzy expert systems which will make decisions about the maintenance of circuit breakers. Three fuzzy expert systems are created to indicate the state of: contacts, the fluid for extinguishing the electric arc and the drive mechanism. Unsupervised machine learning (UML) was applied through the k-means cluster method and cluster tree for classifying and dividing the examined high-voltage circuit breakers into groups with similar state and probability of failure. Artificial neural network (ANN) as part of supervised machine learning (SML) is created in order to predict end-life and accelerated aging of tested circuit breakers. The presented AI methods can be used to improve health assessment of high-voltage SF6 circuit breakers.