Cao Yuchen

Research on structure design of 12kV rotation disc vacuum interrupter

The synchronization breaking technology which is leading in the vacuum circuit breaker has got general concern in electrical apparatus industry, and the dispersion of each single phase interrupter and operating mechanism parameters is one of the most important influencing factors. Based on this, a new structure with three-phase vacuum interrupter in the same chamber was proposed in this paper, and so as to make the research of the concrete structure design which has applied for a invention patent. In this paper, the entirety structure design of the new rotation disc vacuum interrupter has been studied based on the electric field numerical simulation of the three-dimensional entire field. Aiming at the problem that the structure of the conductor poles in the center of the vacuum interrupter is too compact, the researches on the distribution of electric field and the insulation structure rationality have been studied. Aiming at the contact structure of the new rotation breaking and the design feature of the new arc type shielding case, the researches on structure design of contact and new arc type shielding case have been studied based on electric field analysis. The researches show that the new breaker can reduce its volume while meeting the synchronization of breaking.

Analysis on vibration and acoustic joint mechanical fault diagnosis of high voltage vacuum circuit based on wavelet packet energy relative entropy

In view of the requirement of high reliability and small disturbance in the condition of high-voltage (HV) vacuum circuit breaker (VCB), this paper puts forward a method of fault diagnosis based on online monitoring of vibration and acoustic signal. The research object is the 12kV indoor high-voltage vacuum circuit breakers and the system of fault diagnosis of the research object is built. This method uses fast kernel independent component analysis to make blind source separation processing for acoustic signals collected when HV VCB switch on. The wavelet packet energy should be calculated in each frequency of the vibration and acoustic signal. Support vector machine with the wavelet packet energy relative entropy as input vector to classify the common states, such as the normal condition, insufficient lubrication of the crank arm and mechanism fall off in moving. Experimental study has shown that, according to research on the characteristics of the vibration and acoustic signal generated by the circuit breaker, the proposed method can differentiate between normal working state and failure state and meet the high reliability of HV VCB status monitoring requirements.

Design and research of high stability repulsion mechanism of 12kV vacuum circuit breaker

Using finite element simulation method to carry a comparative analysis of the repulsion mechanism and permanent magnetic mechanism, come to the conclusion that the repulsion mechanism has the advantage of rapidity;Aiming at the problem of high speed easy to cause instability, presenting a design of adding coil and repulsion chassis on the basis of the original repulsion mechanism, and optimizing the material of the repulsion chassis;On the basis of this, the experimental prototype is designed and manufactured, and a number of switch test is conducted, measuring the breaking time of each break-barking test and compared with the simulation results to verify the accuracy of the simulation results; The time dispersion of the break-brake is calculated, verifying the high stability of the novel repulsion mechanism.

Research on fault diagnosis of operating mechanism for 12kV vacuum circuit breaker based on PSO-LSSVM

The small fault samples and single characteristic parameters in vacuum circuit breakers (VCBs) would lower the accuracy and reliability of mechanical fault diagnosis. In this paper, the problem has been solved with applying a fault diagnosis method based on particle swarm optimization (PSO) and least square support vector machine (LSSVM). By analyzing the close coil current (CC) of VCB, the eigenvalues of time and current are extracted as input vectors. The paper uses PSO to optimize the model parameters of LSSVM, which are important to fault diagnosis, and to select the best subset of eigenvectors to obtain the optimal performance of LSSVM classifier. Then the improved support vector machine (SVM) is used to train and test the eigenvectors and different states of VCB are classified. Results show that the proposed method can detect whether VCB is normal or not. And the validity and accuracy is verified.

Prediction of synchronous closing time on permanent magnet actuator for vacuum circuit breaker based on PSO-BP

In order to improve the prediction accuracy of phase controlled switching operation time, restrain overvoltage and inrush current when the circuit breaker switched on, this paper establishs BP network prediction model based on voltage and ambient temperature as the main input parameters, and weights the uncertainty influence factors such as aging and wear. In order to improve the accuracy of prediction model, proposing a method of BP neural network based on particle swarm optimization (PSO), comparing network prediction performance before and after algorithm optimized. The research results show that use the BP neural network based on PSO is more accurate than the prediction results which only by BP neural network predicts, the error of BP neural network based on PSO can control the predictive error within 0.2% and meet the requirement of synchronization control.