采用混沌振子和新相态判别法的局部放电检测

为了降低信号检测的信噪比,利用新型混沌振子作为检测工具,采用Lyapunov指数法分析动力学特性,通过提升临界混沌阈值精度减少在覆盖初始相位差方面混沌振子的使用数量。针对各主要相态判别方法的局限性,利用系统周期特点提出新相态判别法并设计仿真电路,实现相态的自动识别并记录间歇混沌状态周期。最后对单指数衰减振荡型局部放电信号进行检测。仿真结果表明,新型混沌振子动力学特性丰富,抗噪性能优越,能够实现更低的信噪比检测,新相态判别法不受过渡过程的影响,适用于任何混沌振子且具备电路实现的可行性,配合超高频传感器可以检测超高频毫伏级的变压器局部放电信号。

Partial discharge detection using chaotic oscillator and new phase state identification method

In order to reduce the signal-to-noise ratio of signal detection, a novel chaotic attractor was used as a detection tool. Lyapunov exponent method was used to analyze the dynamic characteristics. By increasing the accuracy of the critical chaotic state threshold, the number of chaotic oscillators used in covering the initial phase difference was reduced. In view of the limitations of the main phase state identification methods, a new phase state identification method was proposed and designed in circuit simulation. It can realize the automatic identification of phase states by using the characteristics of the system period. The period of intermittent chaotic state was recorded. The feasibility of the new phase state identification method was verified by designing circuit simulation. Finally, the single-exponentially weaken oscillating partial discharge signal was detected. The simulation results show that the novel chaotic attractor has rich dynamic characteristics and superior anti-noise performance. Unaffected by the transition process, the new phase state identification method is applicable to any chaotic oscillator and has the feasibility of circuit implementation. The novel chaotic attractor can achieve lower SNR detection and cooperate with ultra-high frequency sensor to detect ultra-high frequency millivolt-level partial discharge signals of transformer.