| 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.
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