Research Of The Online Optimizing Control Strategy For A Trailing Suction Hopper Dredger's Dredging Performance

In recent years, China's dredging industry has been booming. Its business field has been extended to the relevant industries and areas from harbor deepening and widening,such as: sea reclamation, coastal and offshore engineering construction, irrigation and anti-flood project, protection and improvement of bionomics environment, construction of artificial islands, and so on. Facing with the vast dredging market, the number of dredging equipment in our country is growing exponentially. However, dredging equipment efficiency is the key factor to improve dredging ability. Thus, the realization of automation and intelligence in dredging project is an important subject of current research.This paper chooses trailing suction hopper dredger as the research object. It carries out research on dredging mechanism and models the dredging process. Measured data is used to analyze the model validation and calibration. Than using the genetic algorithm and pattern search algorithm to estimate model parameters. At the same time, it studies the application of particle filter algorithm in dredging performance optimization. Finally put forward the related concepts of green ship and green dredging, consult the best control strategy by optimizing energy consumption.Firstly, this paper analyzes the drag head excavation process mechanism fully, and then establishes the mathematical model and black box model of drag head density. Also, this article establishes prediction model by particle filter to predict the drag head density. The accuracy of the prediction model is verified by measured data.Secondly, this paper analyzes the loading process deeply. Three kinds of model are introduced to describe the sedimentary process. Measured data is used to verify the accuracy of these models and the optimal model is picked. Genetic algorithm and pattern search method are used to estimate the soil dependant parameters of the model. The quality of loading is used to verify the result. At the same time, particle filter is used to estimate overflow rate and overflow density of the sedimentary process.In addition, the paper proposes the scheme to determine the best dredging stop time starting form the concept of “Green Ship”. Three schemes are given, it focused on the third one, which takes daily output maximization as the goal to determine the best dredging stop time. The consideration of “Green Ship” will become a new research direction.