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Designing an Automatic Detector Device to Diagnose Insulator State on Overhead Distribution Lines

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An automatic detector device (ADD) has been designed and built for monitoring insulators state in overhead distribution lines. The prototyped device is suitable for measurement and analysis of the insulator… Click to show full abstract

An automatic detector device (ADD) has been designed and built for monitoring insulators state in overhead distribution lines. The prototyped device is suitable for measurement and analysis of the insulator leakage current (LC) on lines of distribution systems to diagnose insulator state. It operates based on two diagnostic indicators, third to fifth harmonic ratio (R3/5%) of the insulator's LC signal and cosine of phase angle difference (P.D%) between fundamental signals of the voltage and LC. Experimental data of the indicators in various conditions and various insulators are used to train a classifier for determining reference values of the indices for insulator state detection. The instrument has two physically separate parts: receiver and transmitter. They communicate via a radio communication channel which improves the effectiveness of incident management. The transmitter samples the LC signal of the target insulator using a ferrite core along with a series of active electronic filters. The sampled LC signal is then sent to the receiver. The transmitted LC signal is analyzed by the microprocessor embedded in receiver CPU. Indicators of the transmitted LC signal are calculated and compared with reference values extracted from the classifier. The receiver determines the insulator's state based on the comparison of the estimated and reference values of diagnostic indicators for the target insulator. The performance of the prototyped ADD was evaluated experimentally in the laboratory as well as on overhead distribution lines. These performance tests confirmed reliable performance of the ADD.

Keywords: state; insulator state; distribution lines; overhead distribution; device

Journal Title: IEEE Transactions on Industrial Informatics
Year Published: 2022

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