Equipped With Remote Diagnosis System Based On Multi-signal Model

In recent years, with the rapid development of science and technology, the modern equipment becomes more and more complicated and large-scale. This brings the performance of equipment improved, but at the same time it is also causes the equipment failure rate raise. In order to improve the reliability of the equipment, the fault of equipment should be diagnosed fastly and effectively. Now the remote diagnostic technology has become an integral part of the diagnostic techniques with its multi-resource collaboration and sharing. So the equipment’s remote diagnostic system based on multi-signal model is introduced in this dissertation.According to the needs of the equipment which was used in different environments, three different diagnosis methods of remote diagnostic system are used in this system: real-time diagnosis, multi-fault diagnosis and interactive diagnosis. The real-time remote diagnosis is used to diagnose the failure of equipment which in running and the real-time diagnostic results was given by using the TEAMS-RT algorithm. The multi-fault remote diagnosis which using the Lagrange algorithms to diagnose is used when the user can’t get an accurate diagnosis of module depending on the operating manual in the maintenance. For minimum the cost of tests, the interactive remote diagnosis is used in this dissertation, getting the optimal sequence of fault diagnosis by using AO*algorithm, so that diagnose the module follow the sequence.In order to meet the requirements of data quantity, interactive, real-time and safety of remote diagnosis system, the Client/Server(C/S) mode is used in the network architecture of system software and the SOCKET programming technology is used to establish the connection between client and server. In order to answer the large number of client’s request, the completion port (IOCP) is used in the underlying communication module. The diagnostic algorithms DLL is loaded in the explicitly way, so that the server can update the diagnostic algorithms DLL after generate an executable file. The server’s information management module is used to manage the fault-test dependent matrix which generated by modeling and the priori probability of failure and the optimal fault diagnosis sequence. Finally, the functional verification and the performance testing of this system software are finished. The reliability of system’s real-time diagnosis, multi-fault diagnosis and interactive diagnosis are verified by setting system’s status. The real-time of remote diagnosis system is verified by testing the time of remote diagnose. The server’s performance in large-scale access is tested by using the server stress testing tool. The verification and test show that the software can meet the requirements of practical application and have practical value.