| Metallic mineral resources are rich in China, and mine car is an important link of transport equipment for production of mines, which is the main transportation tool for underground mining,transporting, lifting and loading ore, material or personnel, but mining accidents frequently occurred. Aiming at the problems of difficult wiring, low level of informatization and visualization of the existing localization system, localization and safety monitoring system for underground mine mine car was studied and designed based on WSN. This monitoring system clearly knows the position and trajectory of each mine car at any time in this paper. The system provides scientific basis for accident emergency rescue, and more reasonable, real-time and efficient to schedules mine car, which effectively improves the monitoring level of safety production and disaster relief, and also effectively improves the mine production efficiency and guarantees safety of miners. This paper mainly introduced the overall scheme of system design,the hardware and software design of sensor nodes, the selection and optimization of localization and track algorithms, the routing protocol and the improved algorithm of Zig Bee network, the development and experimental verification on PC management system.(1) This paper firstly analyzed the mine car localization status, safety monitoring deficiencies and monitoring requirements in the future. Combined with the research and analysis of the surrounding environment of underground in mine, the loss of electromagnetic wave in underground transmission as well as the influence of node deployment were researched and analyzed, and then the overall design scheme of localization system and the deployments of three nodes were proposed.(2) The networking topology scheme of Zig Bee network was choosed, and the improved routing algorithm AODV-RD was proposed to form the multi-hop MESH routing with self recovery ability, which provides the optimal route for stable data transmission.(3) The hardware circuits of the three types of node were designed based on CC2530 core chip. With the analysis of main work flow about the fixed reference nodes, sink nodes and mobile unknown nodes, the software development about three types of node by using IAREW8051 software were achieved.(4) RSSI location algorithm and PF tracking algorithm to achieves the locating and tracking of mine car was simulated. Through the optimization of parameters and the least squares fitting method, the signal transmission range model was derived, and proposed the weighted centroid algorithm which the average localization error is reduced by 74.94%. The simulation results show that the error of PF tracking algorithm was the minimum when compared with EKF and UKFalgorithm.(5) RBF neural network was applied to forecast the speed of mine car in this paper. The mean square error of RBF neural network model was 0.04695, and it was less than 0.11796 of BP neural network. The forecast precision of RBF neural network was high, which can well meets the requirements of the system.Finally, a simple network experiment was built with a PC machine, several CC2530 nodes and an intelligent car. Through the comparison and analysis of location and tracking results, the development of host computer which is based on Lab VIEW software and C# language was verified on the rationality and feasibility of the system in application. The system has the advantages of low cost, good stability, good credibility, low power consumption and strong robustness, which makes up the insufficiency of monitoring system in metal mine and has high practical value and innovation. |
PDF Full Text Request