The Software Development Of Intelligent Spot Inspection System & Research On Intelligent Method Of Cooling Fan Condition Monitoring

This paper is divided into two parts which are the software development of intelligent spot inspection system and the research on intelligent method of cooling fan condition monitoring.Part I is the development of intelligent spot inspection system. At present, the information and digital management of equipment is very important for the enterprises. However, due to the geographical location, the cost of network line laying and other factors, for some enterprises of which the factories are dispersed, it is difficult to achieve this goal. In view of this situation, this paper combines the wireless network with the wired network, and integrates the concept of TPM management, has developed a set of intelligent spot inspection system, which provides a good information management platform for enterprises. The system uses a dual database storage structure, and connects the database with system software through ADO mode. At the same time, the system uses the composite structure of C/S and B/S to realize the data sharing in all factories. The structure of C/S uses C++language to design the software which adopts the design principle of "modular" through the encapsulation of OCX, DLL and other ActiveX components, and completes the functions of equipment spot inspection, report query, data analysis, expert system query and other functions outside the factory. The structure of B/S is designed by using C# language to complete the functions of data view and analysis inside the factory.Part II is the research on intelligent methods of cooling fan condition monitoring. Cooling fan is widely used in various fields. At present, owing to lack of reasonable and effective monitoring methods of fan condition, the normal operation of the main system is seriously affected. The air cooling experiment is specially designed to solve this problem, and the monitoring and data acquisition for cooling fans lasted for a long time. Through the analysis of the fan experimental data of whole life, effective monitoring methods for fan are explored. In the aspect of fault diagnosis, an intelligent method is proposed for cooling fan rolling bearings based on wavelet packet analysis and support vector machine (SVM) to achieve the accurate identification of several common faults of fan. In the aspect of life prediction, a method based on a combined model of time series analysis and BP neural network is proposed, which can accurately predict the residual life of cooling fan. The two methods proposed in this paper, provide some guiding significance for the realization of intelligent monitoring of cooling fan.Through the research on two parts of this paper, it provides a new idea and a new approach for the development of the condition monitoring and fault diagnosis of mechanical equipment.