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Title: Automatic fault location system for low voltage underground distribution networks
Author: Navaneethan, Senthivadivelu
ISNI:       0000 0001 3440 0457
Awarding Body: University of Strathclyde
Current Institution: University of Strathclyde
Date of Award: 2003
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This thesis presents a novel approach to automating Time Domain Reflectrometry (TDR) waveform acquisition and automatic TDR based fault location in Low Voltage (450-1000V) Underground Distribution Networks (LVUDNs). First, the types of faults that occur in LVUDN and previously available fault location techniques are discussed and their relative advantages and limitations described. Adaptive Filter theory, Wavelet Transform Theory and Fuzzy Logic are presented. Software is developed to automate: checking of the test lead connections, adjusting the internal balance network to match the cable surge impedance, blown fuse detection and backfeed identification, auto recording and storage of data, and voltage and current triggering for transient faults. Software is also developed for both direct and remote control of the instrument via a standard telephone line, GSM modem or direct serial link. Adaptive and fuzzy based, and wavelet based automatic fault location systems are developed. Both systems pre-process the TDR waveforms by using a simple thresholding technique to identify single phase tees and to locate three phase faults. The adaptive and fuzzy based system uses an adaptive filter to produce a composite waveform from the healthy and faulty TDR waveforms and the fault distance is calculated using the composite waveform. If the result produces more than one possible fault distance either from the TDR waveforms or the error waveforms, the system uses fuzzy reasoning to find a common fault distance. In the wavelet based fault location process the TDR waveforms are split into four multi-scales before applying the adaptive filtering and calculating the fault distance using a selected scale. To improve the accuracy of fault distance calculation, local mean and gradient techniques are used in the adaptive and fuzzy based fault location system and latter technique is used in the wavelet enhanced fault location system. The performances of both systems were tested using data from a cable model and from real LVUDNs and gave an accuracy of ±4.3m of the actual fault distance.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral