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The trip mechanism is a weakness in circuit breakers. Traditional fault identification based on the coil current is difficult to report early mechanical defects such as coil‐plunger jam. Here, the vibration signal during the trip process was extracted. Based on the coil current signal and vibration signal, the characteristics of the trip mechanism are analyzed. The phase space reconstruction (PSR) method is used to extract features from the vibration signal. Combined with the features from the coil current waveform, the feature set representing the health condition of the trip mechanism is proposed. The fault simulation tests are carried out and the variation of current vibration characteristics under fault conditions is studied. The fault identification model based on a support vector machine (SVM) is proposed and compared with the identification results when features are extracted from a single signal. When the power supply voltage is dispersed, the prediction accuracy of fault identification is 83.3% considering only the features of the current waveform or vibration signal. And the identification accuracy rises to 96.7% while using the feature set of current and vibration signals. On basis of the current signal, the method further combines the vibration signal so that the robustness of defect identification improves. [ABSTRACT FROM AUTHOR]

To address the difficulty in characterizing early mechanical faults in the trip mechanism of circuit breakers, a data mining method based on variational mode decomposition (VMD) and phase space reconstruction (PSR) method was proposed. First, the vibration signal in the trip stage was separated from the whole according to the current features. Then, it was decomposed using the VMD algorithm to obtain the intrinsic mode functions (IMFs) and these sub signals were mapped to high-dimensional phase space based on the PSR algorithm. Then, the features of the attractor trail shape and the recurrence plot matrixes were extracted. In order to judge the fault in the trip mechanism, a fault simulation test was carried out and the characteristic under different faults was analyzed. Based on these samples, a fault identification model is established by support vector machine (SVM) and the effectiveness is verified by other test samples. The accuracy of the SVM model is 98%, which is higher than that of the BPNN and KNN clustering models. This research supplements the existing method for condition evaluation of the trip mechanism and can provide a reference for circuit breaker fault diagnosis. [ABSTRACT FROM AUTHOR]

Jams in the tripping devices are common faults in circuit breakers, which will lead to the failures in circuit breaker. The resist force of the coil plunger in the tripping device could effectively reveal the jam faults. In this paper, a recognition method for the coil plunger motion resist force based on coil current is proposed. The electromagnetic motion model of the coil is established, and the plunger resist force in VS1‐12 is recognized. According to the recognition result and the moving process of the coil plunger, the fitting formula of the resist force is proposed. The resist force from the coil is 5 N, while the force from the latch is 52 N. Based on the fitting formula, the trip coil current of the circuit breaker is simulated. The result is in good agreement with the test result, which verifies the validity of the fitting formula and the recognition method. The method can be applied to the circuit breaker with spring operating mechanism and effectively extract the resist force from the coil current. This research can provide reference for the condition detection and fault warning of coils in circuit breaker. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]