選煤廠CPS及其生產調度研究
發(fā)布時間：2019-03-27 15:18
【摘要】：隨著智慧礦山的發(fā)展,選煤廠對智能化的要求不斷提高。當前選煤廠控制系統(tǒng)中各子系統(tǒng)的控制和信息采集相互獨立,因此無法將整個生產過程作為整體進行建模,并通過子系統(tǒng)之間的實時交互完成整個系統(tǒng)的優(yōu)化控制。因此,研究智能化選煤廠及其生產調度十分必要。本文以兗州興隆莊選煤廠為例,將CPS引入選煤廠中,對選煤廠CPS模型及生產調度方法進行了研究。針對當前選煤廠PLC系統(tǒng)中各控制子系統(tǒng)相互獨立的問題,結合MAS特征以及PLC網(wǎng)絡結構,建立基于語義agent的選煤廠CPS模型。分析了選煤廠CPS中各主要車間代理結構和相互之間的關系以及車間管理agent相互交互過程。為了解決選煤廠CPS的智能調度問題,提出基于訂單窗口期的、以經濟效益最大化為目標的靜態(tài)生產調度模型,并利用TS-PSO對調度模型進行了求解。將PSO算法與TS算法結合,克服了粒子群過早陷入最優(yōu)及TS算法過分依賴初始解的缺點。通過理論分析證明了該靜態(tài)調度模型符合選煤廠生產線的實際情況,并通過實驗仿真表明了利用禁忌粒子群算法求解靜態(tài)調度模型的有效性�？紤]到選煤廠實際的動態(tài)生產環(huán)境,分析了引起物理環(huán)境動態(tài)變化的幾種因素,提出了設備異常及緊急訂單到達兩種動態(tài)因素情況下的選煤廠CPS動態(tài)調度策略。在環(huán)境發(fā)生動態(tài)變化時,通過選煤廠CPS中訂單agent、調度agent、車間管理agent及車間內其他agent之間的協(xié)作與合作完成動態(tài)調度。實驗仿真了在靜態(tài)調度結果的基礎上有緊急訂單到達時的動態(tài)調度,結果證明了調度策略的可行性。本文的研究成果表明了CPS應用在選煤廠中可以解決當前PLC集控系統(tǒng)存在的問題,滿足選煤廠對系統(tǒng)智能化的需求,并可以通過優(yōu)化調度提高選煤廠生產效率。
[Abstract]:With the development of intelligent mine, the requirement of intelligence of coal preparation plant is increasing. At present, the control and information collection of each subsystem in the coal preparation plant control system is independent of each other, so the whole production process can not be modeled as a whole, and the optimization control of the whole system can be completed through the real-time interaction between subsystems. Therefore, it is necessary to study the intelligent coal preparation plant and its production scheduling. Taking Xinglongzhuang Coal preparation Plant in Yanzhou as an example, this paper introduces CPS into the coal preparation plant, and studies the CPS model and production scheduling method of the coal preparation plant. In view of the problem that each control subsystem is independent of each other in the PLC system of coal preparation plant at present, combined with the characteristics of MAS and the network structure of PLC, the CPS model of coal preparation plant based on semantic agent is established. The agent structure and the relationship among the main workshops in CPS of coal preparation plant are analyzed, and the interaction process of agent in workshop management is also analyzed. In order to solve the intelligent scheduling problem of CPS in coal preparation plant, a static production scheduling model based on order window period and aiming at maximization of economic benefit is put forward, and the scheduling model is solved by using TS-PSO. The PSO algorithm and the TS algorithm are combined to overcome the shortcomings of premature particle swarm optimization and over-dependence on the initial solution of the TS algorithm. Through theoretical analysis, it is proved that the static scheduling model accords with the actual situation of coal preparation plant production line, and the effectiveness of using Tabu particle swarm optimization algorithm to solve the static scheduling model is proved by experimental simulation. Considering the actual dynamic production environment of the coal preparation plant, several factors causing the dynamic change of the physical environment are analyzed, and the dynamic dispatching strategy of CPS for the coal preparation plant under the circumstances of abnormal equipment and the arrival of emergency orders are put forward. When the environment changes dynamically, the dynamic scheduling is accomplished through the order agent, scheduling in CPS of the coal preparation plant, and the cooperation and cooperation between the agent and other agent in the workshop, which are managed by the agent, workshop. The dynamic scheduling of emergency order arrival is simulated on the basis of static scheduling results. The results show that the scheduling strategy is feasible. The research results of this paper show that the application of CPS in the coal preparation plant can solve the problems existing in the current PLC centralized control system, meet the demand of intelligentization of the system in the coal preparation plant, and improve the production efficiency of the coal preparation plant by optimizing the dispatching.
【學位授予單位】：中國礦業(yè)大學
【學位級別】：碩士
【學位授予年份】：2015
【分類號】：TD94;TP301.6
本文編號：2448303
[Abstract]:With the development of intelligent mine, the requirement of intelligence of coal preparation plant is increasing. At present, the control and information collection of each subsystem in the coal preparation plant control system is independent of each other, so the whole production process can not be modeled as a whole, and the optimization control of the whole system can be completed through the real-time interaction between subsystems. Therefore, it is necessary to study the intelligent coal preparation plant and its production scheduling. Taking Xinglongzhuang Coal preparation Plant in Yanzhou as an example, this paper introduces CPS into the coal preparation plant, and studies the CPS model and production scheduling method of the coal preparation plant. In view of the problem that each control subsystem is independent of each other in the PLC system of coal preparation plant at present, combined with the characteristics of MAS and the network structure of PLC, the CPS model of coal preparation plant based on semantic agent is established. The agent structure and the relationship among the main workshops in CPS of coal preparation plant are analyzed, and the interaction process of agent in workshop management is also analyzed. In order to solve the intelligent scheduling problem of CPS in coal preparation plant, a static production scheduling model based on order window period and aiming at maximization of economic benefit is put forward, and the scheduling model is solved by using TS-PSO. The PSO algorithm and the TS algorithm are combined to overcome the shortcomings of premature particle swarm optimization and over-dependence on the initial solution of the TS algorithm. Through theoretical analysis, it is proved that the static scheduling model accords with the actual situation of coal preparation plant production line, and the effectiveness of using Tabu particle swarm optimization algorithm to solve the static scheduling model is proved by experimental simulation. Considering the actual dynamic production environment of the coal preparation plant, several factors causing the dynamic change of the physical environment are analyzed, and the dynamic dispatching strategy of CPS for the coal preparation plant under the circumstances of abnormal equipment and the arrival of emergency orders are put forward. When the environment changes dynamically, the dynamic scheduling is accomplished through the order agent, scheduling in CPS of the coal preparation plant, and the cooperation and cooperation between the agent and other agent in the workshop, which are managed by the agent, workshop. The dynamic scheduling of emergency order arrival is simulated on the basis of static scheduling results. The results show that the scheduling strategy is feasible. The research results of this paper show that the application of CPS in the coal preparation plant can solve the problems existing in the current PLC centralized control system, meet the demand of intelligentization of the system in the coal preparation plant, and improve the production efficiency of the coal preparation plant by optimizing the dispatching.
【學位授予單位】：中國礦業(yè)大學
【學位級別】：碩士
【學位授予年份】：2015
【分類號】：TD94;TP301.6
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