A method for power equipment condition monitoring and fault location based on improved ant colony algorithm

Different malfunctions may arise during the operation of power equipment, impacting the quality and dependability of the power supply. Conventional monitoring techniques face challenges, prompting the introduction of a novel power equipment monitoring and fault localisation method based on an enhanced ant colony algorithm. This approach entails gathering operational signals from the power equipment and amalgamating singular value decomposition with particle filtering methods to oversee the equipment's condition. Through enhancements to the pheromone configuration and update approach of the ant colony algorithm, a fault localisation assessment function is formulated to achieve precise fault localisation. Empirical findings have illustrated that this method has the capability to promptly monitor equipment status and attain fault localisation accuracy surpassing 90%. © 2024 Inderscience Enterprises Ltd.