During the bow blowing construction of a trailing suction dredger, the concentration meter and flow rate meter can instantly reflect the transmission situation of the mud sand mixture in the pipeline, which is the most concerned fluid parameter for construction personnel. To ensure the high efficiency and low energy consumption of the bow blowing operation, this paper proposes an LSTM trailing suction dredger bow blowing concentration prediction model that integrates Stacking. This model fully considers the dynamic characteristics of the fluid and combines machine learning advantages to achieve higher concentration prediction accuracy, which has practical application value.
In the process of pumping and shore blowing of trailing suction dredger, the mud and sand movement mechanism of mud tank and sludge discharge pipeline is complex and strongly coupled. It is difficult to obtain the relationship between mud transportation concentration and pumping hatch, mud pump, high-pressure flushing, submarine diversion valve and pipeline through mechanism analysis. Aiming at this problem, this paper proposes a prediction method of instantaneous output of trailing suction dredger pumping and bank blowing based on BP neural network. Through the training of historical construction data, PSO and GA algorithms are used to optimize respectively, and the prediction model of instantaneous output of trailing suction dredger pumping and bank blowing is established. The simulation results show that this method can effectively predict the production of mud from the suction dredger.
Limited by the complexity of the mechanism of the pumping pipeline and the construction environment in the pumping pipeline during the process of pumping out the shore, it is impossible to allow precise measuring instruments to measure internally. In the past, domestic and foreign scholars only used key equipment such as mud pumps. Work characteristics are studied and related mechanism models are established. In view of this situation, the mechanism analysis of the trailing suction dredger and the calculation method of the mechanism model are carried out, combined with the existing research results and engineering experience, the water layer model and empirical formula are used to obtain this working condition. Under the mechanism model of the extraction of the cabin pipeline, the key parameters of the extraction of the cabin obtained by the mechanism model are verified by the CFD (Computational Fluid Dynamics) software. The results show that the key parameters of bank extraction and bank blowing calculated based on the mathematical model obtained from the mechanism analysis are put into the CFD software and the results obtained are generally in line with reality. It provides a way for future research on the mechanism of the pumping and bank blowing of the trailing suction dredger. Mathematical model reference.
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