Optimization Of Self-propelled Trailing Suction Hopper Dredger Mining System

With the rapid economic development and a significant increase in dredging projects, China's dredging market has become the world center in recent years. The trailing suction hopper dredger is playing an increasingly key role in the large-scale coastal land formation works and construction of industrial parks. It has high cost and complex control, tends to large-scale, automated, efficient direction. Safe operation is the premise of its working, and efficiency is the goal. Therefore, research on the mechanism of trailing suction hopper dredger dredging and search of the optimal ways will mean to the improvement of the dredger's efficiency of construction and the market competitiveness of great significance.With the support of China Communications Construction Group key Laboratory of Dredging open fund projects"Trailing suction hopper dredger predictive control and evaluation of dredging performance", this paper introduces a model-based predictive control strategy to optimize the trailing suction hopper dredger dredging process. Optimization of self-propelled trailing suction hopper dredger mining system needs a holistic solution in consideration of the mining process, the deposition process and constraints. The main contributions are as follows:Firstly, this paper models and simulates the drag-head and hopper, and then validates them using measured data. The results are very good accuracy. An important factor of performance optimization in dredging is reducing flood losses. This article provides a method to estimate the sand height and loss overflow using mathematical model and measured data. It provides an effective theoretical basis for directing construction and improving the efficiency of dredgers, and it has important significance to efficiency of trailing suction hopper dredger.Secondly, this paper optimizes the dredging process using an optimized control strategy. The control method is model-based predictive control. Operator can find the best control strategy to maximize the efficiency by changing the size of the control volume in different soil conditions with different dredging equipments. The results show that dredging the Yangtze River sand, production increases 1.7% to 14.6%, an average of 8.4%.In addition, the paper also proposes a method to evaluate dredging performance based on measured data. System through performance evaluation index according to the efficiency of production and time evaluates the performance of the dredging, achieves dredging process and production efficiency automatic optimization. By providing suitable the dredging parameters with dredge conditions for operator, system achieves optimal yield dredging to improve the performance and efficiency of the dredger purpose.