Research On Fault Diagnosis System Of Electronic Instrument Transformer

Electronic instrument transformer is one of the major equipment in intelligentsubstation system, its function as electronic measurement technology with optical fibersensing technology to achieve a measurement of current and voltage signals. becauseactual hanging net electronic transformer’s running time is not long, and its majority hasa certain failure rate. So it needs online monitoring and fault diagnosis for malfunction.If electronic instrument transformer fails, it will directly affect the function of therealization of secondary equipment, electronic transformer run failure analysis hasimportant practical significance.this paper introduces the working principle and the type of electronic transformer.According to the working principle of electronic transformer analyses the faulty point ofactive electronic transformer and passive electronic transformer. this article focuses onthe study of fault diagnosis algorithm, in the first analytical model-based method isanalyzed, which based on the method of signal processing and knowledge-baseddiagnostic methods. And then simple exposition focus on optimization of fault diagnosisalgorithm, on this basis, the method which based on wavelet transform, multi-scalemodule processing method to get the signal singularity and its singular moment, andfurther information fusion of multi-channel processing method.Failure is detected with the method of using the difference between grid mutationtransformer failure and electronic transformer failure. Real-time operating conditionscan be given for each channel of electronic transformer in substation intelligentelectronic transformer. It ensures the smart substation is more secure and more stableoperation. The fault diagnosis system of hardware design and software design is studied.The hardware design includes the detection wave recording system design, remotemonitoring and control system design, time system design and testing of wave recordingdevice design, signal conditioning module design, signal processing and communicationscheduling module design, power hardware design. The software part includes signalprocessing software design, software design and communication scheduling. Finally, thecontent and its innovative point of this study are summarized exposition and the outlookof future work for lack of research.