Study on large-scale rotating machinery fault intelligent diagnosis multi-agent system

In order to adapt the complex equipment intelligent diagnosis task, based on advantages of multi-agent system, study on large-scale rotating machinery fault intelligent diagnosis multi-agent system is proposed. In the study, the system has broken through traditional unalterable multi algorithm fusion model and shows the social intelligence of multiple agents through the ability which is organizational, self-study and able to resolve diagnosis problems through dynamically negotiating among multiple agents according to the actual characteristics of device signal. The main contributions are as follows: Firstly, how to decompose the diagnosis task rationally is proposed. From this part, a distinctive diagnosis task decomposition method is proposed and which intelligent diagnosis methods adapted to achieving diagnosis successfully can be known; Secondly, how to design the large-scale rotating machinery intelligent diagnosis multi-agent system is introduced, From this part, how to design the system structure and how the system complete the dynamically negotiating and self-study process efficiently can be known. Thirdly, an example of the system is proposed and proves the system can complete the function efficiently.