METHOD OF FORMING INPUT VECTOR OF NERVE NETWORK FOR AUTOMATIC INFERENCE OF PARTIAL DISCHARGE CAUSES

摘要

PPROBLEM TO BE SOLVED: To provide a method of forming input vector of nerve network for automatic inference of partial discharge causes that can be executed, even if phase information of power supply and size information of partial discharge signal are not available, can identify power supply phase, and can be used without the need for retraining the same nerve network engine individually for different partial discharge measuring machines, with respect to partial discharge signals that are predictions of failures of gas insulating systems (GIS), transformers, electric motors, power cables, and other high-voltage power equipment. PSOLUTION: A method of forming input vector of nerve network for automatic inference of partial discharge causes includes the steps of forming a ΦSBn/SB:ΦSBn-1/SB:N graphs; moving from the right bottom of ΦSBn/SB:ΦSBn-1/SB:N graphs to the left top; of extracting a phase correlation sum; of extracting a phase non-correlation sum; and of inputting the phase correlation sum and the phase non-correlation sum as input vector of a nerve network engine. PCOPYRIGHT: (C)2007,JPO&INPIT