Analysis Of Influence Factors On TSHD Production Efficiency And The Establishment Of Productivity Prediction Model

Dredging engineering develops along with port transportation industryclosely. In recent years, the economy of China grown continuously and quickly,port transportation industry developed in a high speed. Domestic portthroughput capacity was refreshed constantly, and new construction of deepwater berths, the new artificial island engineering, the reclamation projects，bigwaterway projects were planned or under construction constantly. Just undersuch a background, domestic dredging market is in great demand,International dredging market, meanwhile, is thriving. While, the internationalmarket share is captured by the world’s four main dredging companies. Theforeign dredging market needs to be developed for Chinese dredgingenterprises urgently.As the main force in dredging reclamation engineering, Trailing suctionhopper dredger (TSHD), widely used throughout the world, is a kind ofhydraulic dredger with characteristics of self-propelled, self-loading,self-dredging and self-discharging. Due to its irreplaceable advantages, largeTSHD is in demand urgently for domestic dredging enterprises. In recent years,domestic construction technology of TSHD increased significantly, and newdredgers launched constantly. Big dig deep, large capacity, modernization andinformationization is the development trend of domestic TSHD. But for a longtime, because of the dredger operator’s uneven operating level, the relativelyhysteretic enterprise management level, and the dominated extensive mode ofoperation, the production efficiency of domestic TSHD is generally on the lowside compared with international advanced dredging enterprises. In order tochange this situation, analysis and optimization of dredging technology is animportant part. Putting in more effort and energy in data accumulation, datamining, data analysis, data optimization and regular summary will benefit inguiding production.This paper sorts out the general idea in analysing influence factors ofloading efficiency before and after hopper full respectively, introduces suitableanalysis methods and research methods, and proposes a new measure to sort out sample data. On the basis of above, discuss reliable and reasonableconstruction parameters optimization methods. Based on GA-BP algorithm,the prediction model is established between sensitive factors and productionefficiency, and extremal optimization for the model is carried out as well. At thesame time, the author compile the general idea in analysis and optimizationconstruction parameters into user interface forms basing on Matlab scriptlanguage. At last, by the means of idea or measures mentioned in the paper,the author analyse parameters of ‘tongtu’ in Tianjin port30ton channel phase iiproject to verify the feasibility of the method.