Research And Application On Dredging Control Parameters Optimization Of Trailing Suction Hopper Dredger

With the continuous economic development of in recent years,the construction and dredging technology on domestic trailing suction hopper dredger(TSHD)has made great progress.Domestic TSHD is moving in the direction of automation.With the domestic port dredging engineering is increasing,more and more attention is paid to the high efficiency of the dredging operations of TSHD.However,domestic related research to improve the efficiency of dredging operations is still inadequate.Therefore,how to improve the construction according to the site conditions has become a key research direction of the domestic dredging industry.This paper optimized construction parameters by researching the dredging process of TSHD.In the support of China communication construction National Engineering Research Center of Dredging technology equipment,this paper has researched how to improve the efficiency of dredging.This paper adopts the algorithm of genetic neural network to predict the drag head density.Multiple population genetic algorithm was used to estimate solid parameters and optimize the control parameters.The design of the TSHD interface provide control parameters and dredging data for construction personnel.The main research of this paper is as follows:First,this paper analyzed the TSHD drag head model,using genetic neural network to predict inhalation density according to the flow,speed,wave compensator pressure and other parameters.This paper verified the predictive density according to the measured data obtained from the port of Xiamen.The results show that this method has high prediction accuracy and can provide reference of inhaled density for the construction personnel.Therefore,the construction personnel can adjust construction parameters to avoid the mud pump cavitation caused by the large density.Secondly,This paper analyzed and researched the trailing suction hopper dredger hopper model.The loading weight were fitted by using multiple population genetic algorithm,which gave the current dredging soil parameters.Then,the classification of soil can be judged according to soil parameters.Simulation results show that the method can accurately fit the loading weight,and provide reference of solid parameters for construction personnel.Finally,Combining the drag head model with the hopper model,the optimized flowand pump speed were given by using multiple population genetic algorithm.Last,interface design of trailing suction hopper dredger realized the comparison of current weight and optimization weight.In addition,it can provide control parameters of the highest dredging cycle for the construction personnel.