Multi-Device Health Management Based on Elman Neural Network

Abstract

For fault forecast and information exchange problems in multi-device health management, the paper proposed a multi-device and multi-parameter fault forecast technology based on Internet of Things, and improved fault prediction algorithm based on Elman neural network feedback. Therefore, it can implement approximating nonlinear functions by arbitrary accuracy, and use the feedback reference to historical data. Thereby, it can provide early detection, isolation, management and forecasting for component failure warning, the initial issuance of the fault condition and ancillary component failure and other states multi-device health management. It also improves self-learning and adaptive capacity of the system, and effectively improves the robustness of the fault prediction system.