Study on In-process Detection and Diagnosis of Faults Arc Based on Early Sounds Signature and Intermittent Chaos

摘要

Up to now, faults arc protection in electrical power system is passive by detecting electric current or arcing light. An active technique used to forecast faults arc is presented in this paper. By applying power spectrum density analysis, two signature bands of arc sound has been found before faults arc take place, one is inside of (5～10) kHz which is strong in intensity and variable in both bandwidth and center in different experimental conditions, the other one is situated on 19.25kHz which is weak in intensity but invariable in center. The proposed technique detects the arc sounds signature in the frequency of 19.25 kHz based on Duffing chaos oscillator. The arc sound is recorded using precision fiber microphone and imported into the chaos based detecting system. For the sensitivity to periodic signal, the chaos system appears either pure chaos or intermittent chaos. So arc sound can been identified by detecting the motion state of chaotic system, and the presently fault arc protection method can been improved into an active forecast and early warning one. Some experiment results and fault arc diagnosis and early warning scheme are also detailed in the paper.