The traditional method of detecting fault current based on threshold judgment method is limited by the current size and is easily disturbed by noise, and it is difficult to adapt to the arc ground fault detection of the distribution network. Aiming at this problem, this paper proposes a single-phase arc-optic ground fault identification method based on waveform subsequence splitting fault segmentation, combined with three-phase voltage-zero sequence voltage waveform feature extraction clustering. First of all, the waveform fault segment is segmented and located, secondly, the characteristic indexes of the time domain and frequency domain of the combined three-phase voltage-zero sequence voltage waveform are established, and the multidimensional feature distribution is reduced by the principal component analysis method, and finally, the characteristic distribution after the dimensionality reduction is identified by the K-means clustering algorithm based on the waveform subsequence. Experimental results show that the arc light grounding fault identification method proposed in this paper achieves 97.12% accurate identification of the test sample.
The traditional circuit breaker fault diagnosis method suffers from insufficient feature information extraction and is easily affected by abnormal signal acquisition. To address this, this paper introduces the phase space reconstruction algorithm to reconstruct the current signal for fault diagnosis based on phase trajectory features. The proposed method uses a first-order forward differencing method and mutual information method to process abnormal data and select the parameters of the reconstruction, then extract overall and local inflection point features to construct a fault feature set. The support vector machine algorithm-based model is trained and tested using actual samples, and the results show that the proposed method can adaptively sample anomalous signals, exhibit strong robustness, and significantly improve the accuracy of fault classification.
Existing techniques of resonance testing have shown a marked inability to find the principal modes, natural frequencies and levels of damping in a structure which possesses two or more close natural frequencies (1)§. This paper describes an experimental investigation on a two-degree-of-freedom model of a technique which makes use of dynamical influence coefficients (or receptances) measured at a number of stations on the structure (2) (3) (4) (5). The measured coefficients are used to calculate natural frequencies and modes of vibration, and the mass, damping and stiffness properties of the system. Several model configurations having different natural frequency separations were tested and no special difficulty resulted when natural frequencies were close or even coincident.
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