Fault monitoring technology of building electrical system based on neural network algorithm
SUN Fangning
Abstract：Electrical system failures in buildings can mildly affect the living experience but may also potentially cause safety accidents.Therefore,it is necessary to strictly monitor electrical system failures.An electrical system model was constructed based on a hospital,and extreme learning machine(ELM)was employed for the fault monitoring of the building electrical system.Simulations were conducted to obtain relevant data and feature extraction results,which were used to train the ELM model.The results showed that the accuracy of the ELM model reached 98%.Compared with Backpropagation(BP)neural network and Genetic Algorithm-Backpropagation(GA-BP)neural network,the ELM model exhibited faster computational speed and higher precision.The study demonstrates that the ELM model performs excellently and can meet the requirements for intelligent monitoring of electrical system failures in buildings.
Keywords：neural networkbuilding electrical systemfault monitoring
Publication Date：2025-05-25
Pages：4( 58-61 )