Underground pipeline networks suffer from severe damage by earth-moving devices due to rapid urbanization. Thus, designing a round-the-clock intelligent surveillance system has become crucial and urgent. In this study, we develop an acoustic signal-based excavation device recognition system for underground pipeline protection.The front-end hardware system is equipped with an acoustic sensor array, an Analog-to-Digital Converter (ADC) module (ADS1274), and an industrial processor Advanced RISC Machine (ARM) cortex-A8 for signal collection and algorithm implementation. Then, a novel Statistical Time-Frequency acoustic Feature (STFF) is proposed, and a fast Extreme Learning Machine (ELM) is adopted as the classifier. Experiments on real recorded data show that the proposed STFF achieves better discriminative capability than the conventional acoustic cepstrum features. In addition, the surveillance platform is applicable for encountering big data owing to the fast learning speed of ELM.
A kind of C-type of traveling wave location method is proposed in this paper. After the single phase grounding fault happened, inject a high voltage narrow pulse signal into the fault phase line and the normal one respectively, collect the reflected signals at detection point, make this two signal waveforms subtract and find the corresponding time of fault point characteristic wave, calculate the fault distance by using location equation. Conduct wavelet packet decomposition and reconstruction on the waveform subtraction signal, judge the fault section by comparing energy changed values of node characteristic waves.
The 10kV distribution networks have complicated geographical environment and the lines with many branches, as well as high grounding resistance at fault point, thus result the difficult of locating fault. Traveling wave fault-location methods locate fault by the time of traveling wave from fault point to receiver or wave subtraction from fault point to two sides receivers, and the advantages of the methods are fast and have high precision. This paper introduced A, B, C, E four types traveling wave fault-location methods and their characteristics. Many simulations are taken for single-phase earth fault in a 10kV power distribution line with branches. By comparing the waves reflected from normal line and the fault one, the fault distance is determined by the first distortion point. As a result, the simulations indicate that the fault-location precision meet the actual requirement, Type C traveling wave fault-location method is feasible for the fault location in distribution networks.
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