挖泥船泥浆管道输送系统效率优化与控制研究
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摘要
挖泥船是现代疏浚工程中重要的疏浚工具。绞吸式挖泥船将土壤挖掘和输送的工序一次性完成,具有非常广泛的适应性和较高的工作效率,广泛应用于开发和维护航道、港口码头建设、海洋工程等方面。泥浆管道输送系统是挖泥船的重要组成部分,泥浆输送管道较长,管线上布设有一台或数台泥泵,其能耗占疏浚施工总能耗的80%以上,属于广地域分布的高能耗系统,具有很大的效率优化空间。挖泥船泥浆管道输送系统效率优化和自动控制是疏浚工程研究领域一个非常重要的课题,开展这方面的研究工作不仅可以达到节能降耗、提高系统效率、降低疏浚施工成本的目的,而且能够提高系统的安全性和减轻疏浚施工操作人员的工作强度。
实际疏浚施工过程的动态特性非常复杂,泥浆管道输送设备的特性也随着疏浚施工条件和位置的不同而明显变化,使挖泥船泥浆管道输送系统的效率优化和控制变得非常困难。本文提出了一种挖泥船泥浆管道输送系统效率优化评价方法,可以对系统的工作状态进行连续的在线准确评价,有利于在系统安全的前提下对工况点进行在线优化调节,使系统效率趋于最优。对挖泥船泥浆管道输送系统的过程控制、工况点在线动态优化方法和多泵协调控制策略进行了相关的研究工作。
工况点在线动态优化方法以系统比能耗最低为优化目标函数,以模糊推理决策和数据融合技术等智能手段为核心,将现有疏浚施工经验、领域专家知识和泥浆管道输送过程的实时数据结合在一起实现系统工况点的在线动态优化,使得在实际疏浚施工过程中,工况点能随着工况的变化而改变,动态地调节到最优,从而达到优化泥浆管道输送系统效率和提高系统安全性的目的。多泵协调控制以系统机组整体效率最高为优化目标函数,利用遗传算法对多台泥泵的转速进行在线优化协调,使得在实际泥浆管道输送过程中,在满足系统工况点动态优化的前提下,实现多台泥泵的协调优化控制,使系统机组的整体工作效率趋于最高。文中对工况点动态优化和多泵协调控制结构、约束条件、模糊推理机制等各方面都进行了比较详细的研究。在疏浚施工现场对系统效率优化和控制性能进行了测试,结果表明泥浆管道输送系统工况点在线动态优化方法和多泵协调控制策略能适应实际疏浚施工环境,可以较稳定地提高泥浆管道输送系统的安全性和工作效率,减少能耗,泥浆输送过程更加平稳。
泥浆浓度和流速的稳定控制在挖泥船泥浆管道输送系统中具有至关重要的作用。对于泥浆远距离多泵输送系统,为了消除多台泥泵之间的耦合与相互牵制作用,采用主泵站进行泥浆流速控制而接力泵站进行扬程控制的综合控制方法。针对被控制系统的不同特性,对泥浆浓度、流速和接力泵扬程采用不同的控制方案。文中通过理论分析和现场试验等多种方式验证了各种控制方案的性能,并与以PID为代表的常规控制方案进行了比较。
论文各章内容分述如下:
第一章论述了挖泥船泥浆管道输送系统效率优化与控制的研究背景、目标和意义。介绍了国内外挖泥船泥浆管道输送系统效率优化的研究内容和研究现状。对挖泥船泥浆管道输送系统自动化控制的研究现状进行了分析。概述了本课题的研究内容及论文所进行的研究工作。
第二章分析和介绍了挖泥船泥浆管道输送系统的构成。建立了包括土壤切削与吸口泥浆浓度、离心泥泵、吸泥管道和排泥管道等部分的数学模型,对泥泵的工作特性、管道系统的阻力损失和柴油机的负载特性等重要方面都进行了分析。为课题的深入研究奠定基础。
第三章对挖泥船泥浆管道输送系统效率优化的影响因素进行了全面的分析。提出了一种挖泥船泥浆管道输送系统效率优化评价方法,该方法可以对系统的工作状态进行连续的在线准确评价,有利于在系统安全的前提下对工况点进行在线优化调节,使系统效率趋于最优。
第四章针对疏浚施工过程中土质和泥浆管道输送系统特性易变的特点,提出了一种挖泥船泥浆管道输送系统工况点在线动态优化方法,使得在实际疏浚施工过程中,工况点能随着工况的变化而改变,动态地调节到最优,从而达到优化泥浆管道输送系统效率和提高系统安全性的目的。对工况点在线动态优化所必须的泥浆浓度测量、泥浆浓度和流速控制等方面进行了相关的研究工作。在疏浚施工现场对所提出的泥浆浓度和流速的控制算法以及工况点在线动态优化方法的有效性进行了试验验证。
第五章针对挖泥船泥浆远距离多泵输送系统由于多台泥泵之间存在着很强的相互耦合牵制作用而导致柴油机泥泵机组的整体工作效率偏低的问题进行了研究,提出了一种多泵协调控制方法,该方法以系统机组整体效率本身作为优化目标,利用遗传算法对多台泥泵的转速进行在线协调优化,使系统机组的整体工作效率趋于最高。对多泵协调控制所必须的接力泵扬程控制进行了控制算法方面的研究。在疏浚施工现场对所提出的接力泵扬程控制算法和多泵协调控制方法的有效性进行了试验验证。
第六章概括了论文的主要研究工作和研究成果,并展望了今后的研究工作和方向。
Cutter suction dredger is the most important dredging equipment and is widely used in dredging projects nowadays. Since it has the integrated function of cutting and transporting soil, it is very adaptable and efficient. It plays an important role in waterway reclamation and maintenance, port construction and ocean engineering projects. The slurry transport pipeline system (STPS) is the most important part of dredger, it has long slurry delivering pipeline set up with one or more pump-stations. STPS is a high energy consumption system, its energy consumption accounts for more than 80% of the total dredging project's, and there is much room for energy saving. Slurry pipeline transport optimization and automation is one of the most important subjects in the dredging researching area. Optimized slurry pipeline transport can reduce energy consumption and dredging cost, raise dredging production and efficiency remarkably. It can improve the reliability of the system and alleviate the work intensity of the dredging operators as well.
The dynamics of practical dredging are very complicated, the characteristics of slurry pipeline transport equipment are continuously changing with working conditions and environment, which makes it very difficult to optimize and control for STPS. This paper presents an efficiency optimization evaluation method of STPS. On-line evaluation of the system's operation can be accurate using this method, which helps the on-line optimization of the working points while the system is safe, and thus making the system to be highly efficient. Studies have been carried out on process control, working point on-line dynamic optimization method and multi-pump coordinated control strategy of STPS.
Using Specific Energy Consumption(SEC) as the objective function, and Fuzzy Reasoning and Decision Fusion Center as the key parts, the working point on-line dynamic optimization method makes the most of dredging experiences, expert's knowledge and the real-time data of dredging process to optimize the system's working points dynamically during slurry pipeline transportation. Accordingly, the system's working points can change with respect to working conditions to get dynamic optimization and the system's safety and efficiency can be improved. In multi-pump coordinated control, the total efficiency of multi-pump system is used as the objective function, the genetic algorithm is used to coordinate on-line working status of all the pumps in slurry transportation and make the total efficiency as high as possible. This paper emphasizes the structure of working point on-line dynamic optimization and multi-pump coordinated control, boundary conditions and fuzzy reasoning mechanism. Field experiments have been carried out to test the optimization and control performances of the proposed scheme. Experimental results show that the working point on-line dynamic optimization method and multi-pump coordinated control strategy can adapt to the continuous changing working conditions, safety and efficiency of STPS are steadily raised, the energy consumption is minimized, and the slurry pipeline transport process is much more stable.
It's crucial to control the slurry concentration and speed in STPS. For the long-distance multi-pump system, to eliminate the coupling and interactions of pumps, slurry speed is controlled in the main pump-station while head is controlled in booster pump-station. In this paper, different control schemes are presented respectively for different control target. Theoretical and field experiments have been carried out to test the performance of each proposed control scheme, and experimental results are compared with those of the conventional control schemes, especially PID.
There are six chapters in this paper.
Chapter 1 presents the research background, targets and significance of efficiency optimization and control of STPS. It introduces briefly the contents and status quo of efficiency optimization research domestically and abroad. Furthermore, it analyses the automation of STPS and summarizes our studies.
Chapter 2 analyses the components of STPS. It sets up models of soil cutting andslurry concentration of the suction, of centrifugal slurry pump, slurry suction pipeline and delivery pipeline. It analyses the important aspects as the working properties of slurry pump, the resistance loss of the pipeline system and the load properties of the diesel engine, thus provides a basis for further study.
Chapter 3 is a comprehensive analysis on factors influencing efficiency optimization of STPS. It puts forward an efficiency optimization evaluation method of STPS, which makes accurate continuous on-line evaluation of the system's working state, benefits the safe on-line adjustment of the system working points and leads to the optimal system efficiency.
As the properties of cutting soil and STPS are volatile in dredging, Chapter 4 suggests the working point on-line dynamic optimization method. In practical dredging , the working points change with the working state and approach the optimum by dynamic adjustment, thus to improve the efficiency as well as safety of STPS. Prerequisites for working point on-line dynamic optimization, such as slurry concentration measurement, control of slurry concentration and velocity, have been studied accordingly. Experiments have been carried out on the dredging spot to verify the control algorithms of slurry concentration and velocity and the method of working points on-line dynamic optimization.
Chapter 5 explores the integrated low efficiency of the unit of diesel engine and slurry pump, mainly caused by the mutual coupling and interactions among the pumps of the long distance multi-pump transportation system. It presents a multi-pump coordinated control method, which aims at optimizing the integrated efficiency of the unit, uses genetic algorithm to make on-line rotation speed coordination and optimization of the pumps, thus to approach the highest working efficiency of the unit. The necessary head control algorithm of the booster pumps for multi-pump coordinated control are studied. The control algorithm and the coordinated control method have also been verified by experiments on the dredging spot.
The last chapter, Chapter 6, summarizes our studies, the relative results and the prospects of researches in future.
实际疏浚施工过程的动态特性非常复杂,泥浆管道输送设备的特性也随着疏浚施工条件和位置的不同而明显变化,使挖泥船泥浆管道输送系统的效率优化和控制变得非常困难。本文提出了一种挖泥船泥浆管道输送系统效率优化评价方法,可以对系统的工作状态进行连续的在线准确评价,有利于在系统安全的前提下对工况点进行在线优化调节,使系统效率趋于最优。对挖泥船泥浆管道输送系统的过程控制、工况点在线动态优化方法和多泵协调控制策略进行了相关的研究工作。
工况点在线动态优化方法以系统比能耗最低为优化目标函数,以模糊推理决策和数据融合技术等智能手段为核心,将现有疏浚施工经验、领域专家知识和泥浆管道输送过程的实时数据结合在一起实现系统工况点的在线动态优化,使得在实际疏浚施工过程中,工况点能随着工况的变化而改变,动态地调节到最优,从而达到优化泥浆管道输送系统效率和提高系统安全性的目的。多泵协调控制以系统机组整体效率最高为优化目标函数,利用遗传算法对多台泥泵的转速进行在线优化协调,使得在实际泥浆管道输送过程中,在满足系统工况点动态优化的前提下,实现多台泥泵的协调优化控制,使系统机组的整体工作效率趋于最高。文中对工况点动态优化和多泵协调控制结构、约束条件、模糊推理机制等各方面都进行了比较详细的研究。在疏浚施工现场对系统效率优化和控制性能进行了测试,结果表明泥浆管道输送系统工况点在线动态优化方法和多泵协调控制策略能适应实际疏浚施工环境,可以较稳定地提高泥浆管道输送系统的安全性和工作效率,减少能耗,泥浆输送过程更加平稳。
泥浆浓度和流速的稳定控制在挖泥船泥浆管道输送系统中具有至关重要的作用。对于泥浆远距离多泵输送系统,为了消除多台泥泵之间的耦合与相互牵制作用,采用主泵站进行泥浆流速控制而接力泵站进行扬程控制的综合控制方法。针对被控制系统的不同特性,对泥浆浓度、流速和接力泵扬程采用不同的控制方案。文中通过理论分析和现场试验等多种方式验证了各种控制方案的性能,并与以PID为代表的常规控制方案进行了比较。
论文各章内容分述如下:
第一章论述了挖泥船泥浆管道输送系统效率优化与控制的研究背景、目标和意义。介绍了国内外挖泥船泥浆管道输送系统效率优化的研究内容和研究现状。对挖泥船泥浆管道输送系统自动化控制的研究现状进行了分析。概述了本课题的研究内容及论文所进行的研究工作。
第二章分析和介绍了挖泥船泥浆管道输送系统的构成。建立了包括土壤切削与吸口泥浆浓度、离心泥泵、吸泥管道和排泥管道等部分的数学模型,对泥泵的工作特性、管道系统的阻力损失和柴油机的负载特性等重要方面都进行了分析。为课题的深入研究奠定基础。
第三章对挖泥船泥浆管道输送系统效率优化的影响因素进行了全面的分析。提出了一种挖泥船泥浆管道输送系统效率优化评价方法,该方法可以对系统的工作状态进行连续的在线准确评价,有利于在系统安全的前提下对工况点进行在线优化调节,使系统效率趋于最优。
第四章针对疏浚施工过程中土质和泥浆管道输送系统特性易变的特点,提出了一种挖泥船泥浆管道输送系统工况点在线动态优化方法,使得在实际疏浚施工过程中,工况点能随着工况的变化而改变,动态地调节到最优,从而达到优化泥浆管道输送系统效率和提高系统安全性的目的。对工况点在线动态优化所必须的泥浆浓度测量、泥浆浓度和流速控制等方面进行了相关的研究工作。在疏浚施工现场对所提出的泥浆浓度和流速的控制算法以及工况点在线动态优化方法的有效性进行了试验验证。
第五章针对挖泥船泥浆远距离多泵输送系统由于多台泥泵之间存在着很强的相互耦合牵制作用而导致柴油机泥泵机组的整体工作效率偏低的问题进行了研究,提出了一种多泵协调控制方法,该方法以系统机组整体效率本身作为优化目标,利用遗传算法对多台泥泵的转速进行在线协调优化,使系统机组的整体工作效率趋于最高。对多泵协调控制所必须的接力泵扬程控制进行了控制算法方面的研究。在疏浚施工现场对所提出的接力泵扬程控制算法和多泵协调控制方法的有效性进行了试验验证。
第六章概括了论文的主要研究工作和研究成果,并展望了今后的研究工作和方向。
Cutter suction dredger is the most important dredging equipment and is widely used in dredging projects nowadays. Since it has the integrated function of cutting and transporting soil, it is very adaptable and efficient. It plays an important role in waterway reclamation and maintenance, port construction and ocean engineering projects. The slurry transport pipeline system (STPS) is the most important part of dredger, it has long slurry delivering pipeline set up with one or more pump-stations. STPS is a high energy consumption system, its energy consumption accounts for more than 80% of the total dredging project's, and there is much room for energy saving. Slurry pipeline transport optimization and automation is one of the most important subjects in the dredging researching area. Optimized slurry pipeline transport can reduce energy consumption and dredging cost, raise dredging production and efficiency remarkably. It can improve the reliability of the system and alleviate the work intensity of the dredging operators as well.
The dynamics of practical dredging are very complicated, the characteristics of slurry pipeline transport equipment are continuously changing with working conditions and environment, which makes it very difficult to optimize and control for STPS. This paper presents an efficiency optimization evaluation method of STPS. On-line evaluation of the system's operation can be accurate using this method, which helps the on-line optimization of the working points while the system is safe, and thus making the system to be highly efficient. Studies have been carried out on process control, working point on-line dynamic optimization method and multi-pump coordinated control strategy of STPS.
Using Specific Energy Consumption(SEC) as the objective function, and Fuzzy Reasoning and Decision Fusion Center as the key parts, the working point on-line dynamic optimization method makes the most of dredging experiences, expert's knowledge and the real-time data of dredging process to optimize the system's working points dynamically during slurry pipeline transportation. Accordingly, the system's working points can change with respect to working conditions to get dynamic optimization and the system's safety and efficiency can be improved. In multi-pump coordinated control, the total efficiency of multi-pump system is used as the objective function, the genetic algorithm is used to coordinate on-line working status of all the pumps in slurry transportation and make the total efficiency as high as possible. This paper emphasizes the structure of working point on-line dynamic optimization and multi-pump coordinated control, boundary conditions and fuzzy reasoning mechanism. Field experiments have been carried out to test the optimization and control performances of the proposed scheme. Experimental results show that the working point on-line dynamic optimization method and multi-pump coordinated control strategy can adapt to the continuous changing working conditions, safety and efficiency of STPS are steadily raised, the energy consumption is minimized, and the slurry pipeline transport process is much more stable.
It's crucial to control the slurry concentration and speed in STPS. For the long-distance multi-pump system, to eliminate the coupling and interactions of pumps, slurry speed is controlled in the main pump-station while head is controlled in booster pump-station. In this paper, different control schemes are presented respectively for different control target. Theoretical and field experiments have been carried out to test the performance of each proposed control scheme, and experimental results are compared with those of the conventional control schemes, especially PID.
There are six chapters in this paper.
Chapter 1 presents the research background, targets and significance of efficiency optimization and control of STPS. It introduces briefly the contents and status quo of efficiency optimization research domestically and abroad. Furthermore, it analyses the automation of STPS and summarizes our studies.
Chapter 2 analyses the components of STPS. It sets up models of soil cutting andslurry concentration of the suction, of centrifugal slurry pump, slurry suction pipeline and delivery pipeline. It analyses the important aspects as the working properties of slurry pump, the resistance loss of the pipeline system and the load properties of the diesel engine, thus provides a basis for further study.
Chapter 3 is a comprehensive analysis on factors influencing efficiency optimization of STPS. It puts forward an efficiency optimization evaluation method of STPS, which makes accurate continuous on-line evaluation of the system's working state, benefits the safe on-line adjustment of the system working points and leads to the optimal system efficiency.
As the properties of cutting soil and STPS are volatile in dredging, Chapter 4 suggests the working point on-line dynamic optimization method. In practical dredging , the working points change with the working state and approach the optimum by dynamic adjustment, thus to improve the efficiency as well as safety of STPS. Prerequisites for working point on-line dynamic optimization, such as slurry concentration measurement, control of slurry concentration and velocity, have been studied accordingly. Experiments have been carried out on the dredging spot to verify the control algorithms of slurry concentration and velocity and the method of working points on-line dynamic optimization.
Chapter 5 explores the integrated low efficiency of the unit of diesel engine and slurry pump, mainly caused by the mutual coupling and interactions among the pumps of the long distance multi-pump transportation system. It presents a multi-pump coordinated control method, which aims at optimizing the integrated efficiency of the unit, uses genetic algorithm to make on-line rotation speed coordination and optimization of the pumps, thus to approach the highest working efficiency of the unit. The necessary head control algorithm of the booster pumps for multi-pump coordinated control are studied. The control algorithm and the coordinated control method have also been verified by experiments on the dredging spot.
The last chapter, Chapter 6, summarizes our studies, the relative results and the prospects of researches in future.
引文
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