Research And Development Of Remote Monitoring And Fault Diagnosis System For Vertical Roller Mill

Vertical roller mill is the key production equipment in the cement industry.Its structure of mechanical and electrical is complex.And the production environment is very poor.With the progress of technology,the number of vertical roller mills is increasing,and they are widely distributed in a wide range of areas.In order to improve the monitoring and fault diagnosis ability of the vertical roller mill distributed in various regions,a remote monitoring and fault diagnosis system is designed to realize the real-time remote monitoring and fault diagnosis of the key components of the vertical roller mill.The monitoring data and fault diagnosis results are displayed and feedback.The system proposed in this paper is mainly aimed at the remote monitoring and fault diagnosis during vertical roller mill operation.In terms of hardware,the reliability,scalability and durability are taken into accounted.Similarly,the accuracy,real-time and intelligence are also taken into accounted during the process of algorithm design.Meanwhile,the overall solution is proposed,including data acquisition system of vertical roller mill,the program of GPRS communication,intelligent fault diagnosis algorithm of rolling bearing,database server and platform of remote monitoring and fault diagnosis.In the design process of data acquisition system for vertical roller mill,targetedly,the front-end signal conditioning circuit is designed.Due to the large number of acquisition temperature,acquisition circuits that a single I/O mounting multiple temperature sensor are designed.In addition,for the selected chip,a number of circuits such as a chip peripheral circuit,a power supply circuit and a communication module circuit are designed.Finally,the system was debugged accordingly.Based on the analysis of the characteristics of many signal decomposition and pattern recognition algorithms,the study of CEEMD and its stopping criteria,a real-time intelligent fault diagnosis algorithm for rolling bearing is proposed.The CEEMD is used in the algorithm,making it more suitable for the decomposition of unsteady signals than the algorithm of wavelet packet,so the accuracy of the algorithm is improved.The fixed sifting number criterion is used,greatly reducing the number of iterations of the algorithm and the impact of local interference on the whole.And the intelligence of the algorithm has been improved with using the BP neural network.According to the actual needs,the remote monitoring and fault diagnosis platform has been designed.Then the database server designed with VB is used for receiving the monitoring data from data acquisition system of vertical roller mill and saving it to SQL Server database.The platform of remote monitoring and fault diagnosis is designed.The platform uses VB as a front-end development tool and uses Matlab to accomplish complicated math calculation tasks.The platform includes functions such as data reception and storage,data real-time display,data history query and fault diagnosis.The remote monitoring and fault diagnosis system of vertical roller mill in this paper,after the laboratory modular debugging,initially reached the design requirements,The experimental signal is used to verify the feasibility of the proposed real-time intelligent fault diagnosis algorithm for rolling bearing.Finally,the overall performance of the system is tested.Above the remote monitoring and fault diagnosis system for vertical roller mill has some value for engineering application.