The Key Technology Study Of Intelligent Fault Diagnosis Systems In Power Network

Whether a power network would run safely depends on valid analysis and transaction of various faulted information. It is very difficult to determine the fault course for dispatchers only based on the numeric information of protections and breakers. But the faulted recorder data will be the important basis of analyzing and diagnosis of power system more and more. The fault types, location, phase faulted, phasor of electricity before and after fault, action of protection and breakers, sequence of events can be determined by analyzing faulted recorder information. So the dispatchers can seized the real situations of the fault, and determine how to supply power again according to all the faulted record data that come from various substations. In the same time those information can be analyzed by protection personnel and dispatchers after a fault happened.The all original faulted recorder data have been used in this paper. And the new math tools, i.e. wavelet, NN, temporal logical technology and so on are introduced. The traditional algorithms of fault diagnosis have been improved and innovated in the paper. The main achievements will be concluded as follow. The reasons to compress and transmit the fault-recorded data in HV substations in time are expanded. The virtues and disadvantages about the traditional data compression methods are analyzed. The novel eliminating noise self-adaptive data compression method based inspecting signal singularity is set forth in the first time in this paper. The matching search process of wavelet coefficient singularity in every wavelet scale and the self-adaptive threshold method of the maximum scale number are analyzed. The maximum decomposing scale n is determined by the sampling rate and frequency of faulted record data, and then inspecting the white noise and calculating the singularity exponent on the n scale can determine the optimum decomposing scale. The signal reconstruction method is discussed in the last. The validity is testified by some real faulted record data from East China power network.An advance data preprocessing and diagnosis scheme in substations is put forward according to dyadic wavelet and singularity theory. Dyadic wavelet can locate the fault time point, which could solve the time error of faulted recorders. And its error is smaller than 0.6ms after they are revised. A new algorithm of selection line and phase is presented based on wavelet theory, which brings a good condition for real-time fault diagnosis.In order to improve fault recognition capability and computational speed of the fault diagnosis system, this paper presents a new wavelet neural network mode constructed from lifting wavelet and PNN neural network. The coefficients of fault currents in the low frequency band between 0 and 375 Hz that decomposed by bior3.1 lifting wavelet are put into the neural network. Through ATP simulation and the test of real fault record data from the power network in East of China, the result indicates that the mentioned model in this paper has very high recognition rate and convergence speed.A new scheme to distinguish oscillation and fault occurring in transmission lines is proposed based on wavelet transform. So a new synthesized criterion consists of four methods as following: the first, comparison of the local maximum wavelet coefficients of the singularity point; the second, how those wavelet coefficients mentioned above changes in different frequency band at the very moment; the third, how those wavelet coefficients changes as time goes by in the same frequency band; the fourth, how the phase between voltage and current changes as time goes by in the same frequency band. Each method is evaluated by the performance and applicability based on fuzzy set theory. The algorithm proves to be feasible and of high veracity in typical experiments.A new idea was presented in this paper, which is about Linear Temporal Logic (LTL) technology and analog information be used in fault diagnosis system for High Voltage (HV) transmission lines. A linear temporal logic formal deduction system is expressed with syntax and semantic. Fault analog signal is preprocessed in substation, considering need for system fault tolerant and real-time requirement of fault diagnosis. In dispatch center, time sequence of protection and breaker actions in fault diagnosis process is analyzed, then, TDS and TAS about typical fault mode are formed and time sequence restriction relation is expressed by LTL. The reliability and tolerance of reasoning in this paper is verified by instance at last.The DEMO system programmed by MATLAB GUI can validates the integration system consisted by every function module. And the temporal logic diagnosis of protections and breakers is proved by CLIPS simulation tool. That validates the effective and intelligent diagnosis system.