On-line Monitoring Method of Large-scale Weapon Equipment Based on Multilayer Competition Neural Network

摘要

The large-scale weapon equipment is often a complex system, which applies many techniques such as mechanical technique, electronics, hydraulic and so on. Whole weapon system will lose combat capability, if the large-scale weapon equipment is fault. It is necessary to realize real-time monitoring and automatic recognition of working state, to rapidly locate fault’s components for the large-scale weapon equipment. For this reason, this method that adopts the competition network to realize on-line monitoring is put forward. When the fault has been found, the fault diagnosis is completed by calling the corresponding neural network. By this method, not only the neural network’s scale is reduced, but also the design’s complexity of diagnosis system is simplified and computing time is reduced too. This method has an important significance to realizing on-line monitoring and diagnosis of the large-scale weapon equipment.