【摘要】 为解决液压圆锥破碎站给料破碎过程自动化程度低、故障率高的问题，研究了给料输送带输送量与带速匹配关系，分析了破碎主机负载状态相关变量，设计了液压圆锥破碎站智能协同调速系统。通过Simulink平台采用模糊PID控制算法设计了给料输送带调速控制器，并进行了仿真对比验证。结果表明，模糊PID控制器的动态性能与抗干扰能力均优于传统的大林算法控制器与PID控制器，具有优良的控制效果。采用模糊论方法，以主机电流、润滑油油温为输入变量，构建了主机负载状态判定规则，针对不同负载状态制定了相应的协同调速策略。应用结果表明，智能协同调速系统能够自动调节液压圆锥破碎站的给料破碎过程，显著降低液压圆锥破碎站的堵料停机故障次数与能源消耗量。更多还原

【Abstract】 In order to solve the problems of low automation and high failure rate in the feeding and crushing process of the hydraulic cone crushing station, the matching relationship between transport capacity and belt speed of the feeding conveyor belt was studied, and the variables related to the load state of the crushing host were analyzed, and the intelligent cooperative speed regulation system of the hydraulic cone crushing station was designed. The fuzzy PID control algorithm was used to design the speed controller of the feeding conveyor belt through the Simulink platform, and the simulation comparison was verified. The results show that the dynamic performance and anti-interference ability of the fuzzy PID controller is better than that of the traditional Dalin algorithm controller and the PID controller, and it has an excellent control effect. Using the fuzzy theory method, the host current and lubricating oil temperature were taken as input variables to construct the determination rules of host load state, and the corresponding cooperative speed regulation strategies were formulated for different load states. The application results show that the intelligent cooperative speed regulation system can realize the automatic adjustment of the feeding and crushing process of the hydraulic cone crushing station, and the number of blockage and shutdown failures and energy consumption of the hydraulic cone crushing station are significantly reduced.更多还原