Combining the bidirectional long short-term memory neural network and temporal pattern attention mechanism, a machine learning model based on multi-feature inputs is developed to predict ship motion in irregular waves. An adaptive particle swarm optimisation algorithm is proposed to adapt the parameters of neural network to different feature inputs. The study indicates that the improved particle swarm optimisation algorithm avoids the problem of poor adaptability of empirical parameters to different advance time. The combination of bidirectional long short-term memory neural network and temporary pattern attention mechanism further enhances the data mining ability. Compared with the prediction mode solely based on the ship motion input, the inclusion of wave elevation input can effectively improve the accuracy and advance time for ship's motion prediction. Importantly, the prediction accuracy will improve with an increased number of inputs of wave probes, which are arranged along the wave propagation direction.
Estimating ice resistance and ship motion in ice-covered region is important for the planning of operations and transport routes. This paper proposes a numerical simulation method for predictions of ice loads and ship motions in level ice. The dynamic interaction between ship and level ice is considered on basis of nonlinear finite element method. Numerical simulations between level ice and a ship are carried out by LS-DYNA software. The ice material model which can simulate ice crushing and bending failure modes is used. To consider the net thrust during ship-ice interaction, the user-defined load subroutine LOADSETUD that provides a means to apply nodal loads as a function of velocity is used. In addition, the water effect on the level ice model is taken into account by using a nonlinear discrete spring model. The model tests of an icebreaker navigating in level ice is used to test the presented method. The predicted results including ice resistance, net thrust and attainable speeds for given ice conditions are compared with the model test data. The comparison shows a generally good agreement, which indicates that the presented method is able to give reasonable predictions. Furthermore, the comparison between the numerical results obtained by the rigid ship and the deformable ship is made. The ship structural response during ship-level ice interaction is investigated.
The fish pump is an important power component for aquaculture, especially in offshore engineering vessel aquaculture and cage aquaculture. Reducing fish damage, improving survival rate, and increasing fish-lifting efficiency are the key points of fish pump research. In this study, we took a new type of fluid multiplier fish pump as the research object and selected many performance parameters that affect the hydrodynamic perfor-mance of the model prototype of the fish pump. The main conclusions are as follows: the fluid multiplier fish pump body produced a flow rate 2.8-3.5 times higher than the water injection port in the jet gap area, and under the influence of the high-flow-rate area, the low-pressure area generated at the fish inlet amplified the flow at the entrance of the fish. As a result, the fluid multiplier fish pump was able to suck and lift fish. With the change in the water jet gap from 2 mm to 4 mm, the head and flow of the bladeless fish pump were improved to a certain extent. We achieved an optimal value for the runner inclination angle during the change of the inclination angle of the pump body surface from - 4 degrees to 4 degrees, and it reached the highest value when the inclination angle was 2 degrees. In the process of increasing the water injection opening of the pump body from 50 mm to 65 mm, the head and flow of the bladeless fish pump greatly increased. The flow when the water injection opening was 65 mm was approximately 1.71 times that when the water injection opening was 50 mm. The head when the water injection opening was 65 mm was approximately 1.42 times that when the water injection opening was 50 mm. When the length of the guide vane was between 4 and 6 mm, the increase and decrease in the flow rate of the bladeless fish pump approached the maximum value of merit. The fluid multiplier fish pump designed in this study featured the characteristics of simple and lightweight structure and high fish-lifting flow, which can reduce labour intensity and improve the catching efficiency of aquaculture fish.
. As the power source of the ship sailing, diesel engine will inevitably produce some thermal faults in the course of sailing, which will affect the stability of the ship sailing, so the diagnosis of thermal faults becomes very important. This paper uses Simulink software platform to simulate the thermal failure of diesel engine, and selects seven thermal parameters as the source of data set. The data set is input into LSTM neural network algorithm diagnosis model, several typical fault modes of diesel engine are output, and the data processing and image drawing are carried out in Matlab. Compared with other algorithms, LSTM neural network algorithm solves the long time dependence problem and has a high interpretation of the predicted data. The results show that the fault diagnosis model based on LSTM neural network algorithm can diagnose the diesel engine fault mode well.
通过AMESim和MATLAB/Simulink联合仿真的方法建立二次调节主动升沉补偿系统的仿真模型,模型加入了时变和非线性因素的影响,能较为真实地反映实际主动升沉补偿系统特性和实现各种控制策略.研究结果表明:采用具有双前馈补偿的串级PID闭环控制,提高了系统的升沉补偿精度;变量机构与二次元件斜盘配合的间隙等非线性因素会降低系统补偿精度;绞车的非线性摩擦力矩对补偿精度的影响较小.
