Study On Ant Colony Optimization Algorithm Of Monitoring And Control To Belt Conveyor

More and more complex nonlinear problems appear in optimization design and fault diagnosis of equipment. It is difficult to establish accurate mathematical model.Because of the positive feedback mechanism of ant colony optimization algorithm exists, it becomes possible to use in the field of electrical and mechanical engineering.The paper analyzes the existing problems in ant colony algorithm, and dynamic cognitive distributed multidimensional adaptive ant colony optimization algorithm is proposed. The communication model of distributed system, time synchronization technology of distributed system and synchronization strategy is constructed. Time synchronization scheme and time window strategy of sub ant colony in multidimensional system are designed. In view of the influence of the main parameters of ant colony algorithm, algorithm is proposed to adjust the parameters of improved adaptive dynamic cognition, time synchronization, information fusion, information exchange and other key technology is introduced. At the early stage of the algorithm,path selection can achieve diversity. The algorithm reaches maturity; the searching efficiency can be improved. In order to solve the TSP problem as an example, the simulation analysis of the main parameters that influence the heuristic factor,pheromone vitalization factor on Ant Colony Optimal path.In the intelligent integrated optimization framework of dynamic cognitive distributed multidimensional adaptive ant colony optimization algorithm, based on the soft start of belt conveyor technology and analysis of dynamic performance of the starting process of belt conveyor, thyristor soft start method is proposed, the soft start control strategy is designed for asynchronous motor by constructing different design knowledge, the optimization model of ant colony algorithm PID parameter isestablished. The simulation results show the effectiveness of the algorithm.Under the intelligent integrated optimization framework, based on Information fusion technology, ant colony algorithm and clustering, distributed intelligent condition monitoring and fault diagnosis system is designed. During belt conveyor dynamic monitoring and fault diagnosis, analysis of ant colony clustering algorithm convert total minimum Euclidean distance of fault samples and each cluster center. Using the orthogonal test method, the normalized data processing, cluster analysis, through fusion of the same fault on the representation of information, it reduces the probability of false alarm. Belt conveyor fault handling has more credibility, reliability, and experiments were made to verify the design.