Table of Content

    28 October 2021, Volume 55 Issue 10 Previous Issue    Next Issue
    Design of Light Fireproof Enclosure Bulkheads Based on Topography Optimization for Cruise Ships
    ZHANG Fan, YANG Deqing, QIU Weiqiang
    2021, 55 (10):  1175-1187.  doi: 10.16183/j.cnki.jsjtu.2020.201
    Abstract ( 866 )   HTML ( 571 )   PDF (19957KB) ( 857 )   Save

    In order to develop a new lightweight enclosure structure with an excellent fireproof and bearing performance, and to replace the traditional stiffened fire enclosure bulkheads in the superstructure area, a design method of light fireproof enclosure bulkheads for cruise ship based on the topography optimization technology was proposed. The location and numbers of corrugated beads in lightweight wall designed by this method were generated according to the requirements of load bearing capacity and manufacturing process, and this method overcomes the disadvantages that the location and numbers of beads in the design of conventional corrugated wall have to be determined in advance. Aimed at the specified design regions, the lightweight of cruise fireproof enclosure bulkheads (CFEB) structure was taken as the objective function while the stress in the weld zone, the stress in the nonweld zone, and the first-order buckling factor of CFEB were taken as constraints. Then, the topography design models of CFEB were established and solved. Feasible configurations were obtained by topography optimization, and the final configurations of CFEB were formed by secondary design. The mechanical properties of the final configurations were compared with the traditional stiffened fireproof bulkheads. It is concluded that the new CFEB has advantages of lightweight and good strength compared with the traditional stiffened fireproof bulkheads.

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    Energy Management of Parallel Ship Power System Based on Improved Fuzzy Logic Control
    WANG Ruichang, CHEN Zhihua, MING Xinguo
    2021, 55 (10):  1188-1196.  doi: 10.16183/j.cnki.jsjtu.2020.043
    Abstract ( 573 )   HTML ( 187 )   PDF (1546KB) ( 485 )   Save

    In order to alleviate the environmental pollution caused by ship transportation, an energy management strategy of parallel ship power system based on improved fuzzy logic control is proposed for the parallel hybrid power system with diesel engines as the main propulsion device. Based on the fuzzy logic control strategy, the error between required power and output power is used as a modification item and the sum of modification item, and demand power is taken as the input of the fuzzy logic control. By changing the fuzzy rules of excitation, the output power of the diesel engine and the output power of the battery pack are redistributed, so that the error between the total output power and the actual demand power is reduced. Energy management decisions can be made easily and quickly under different conditions by using this method which provides a new solution for energy management of high-power ship power systems.

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    Surge-Suppression Power Supply System for Ship High Power Pulse Loads
    PANG Yu, HUANG Wentao, WU Jun, TAI Nengling, SUN Guoliang
    2021, 55 (10):  1197-1209.  doi: 10.16183/j.cnki.jsjtu.2020.358
    Abstract ( 827 )   HTML ( 185 )   PDF (2640KB) ( 661 )   Save

    This paper analyzes the characteristics and influences of new pulse loads of ships. The surge-suppression power supply system for high power and multi-mode pulse loads, the capacitance and inductance calculation methods for the energy buffer unit are proposed, which can realize the power suppression, energy grouping, harmonic control and support backup, so that the safety of the ship power station and high precision power supply for loads can be ensured. The integrated power system simulation model of a new survey ship with high power radar loads is established in MATLAB/Simulink to verify the effectiveness of the surge-suppression power supply system at different modes. The system can not only reduce the impact of impulse load on the system, but also effectively suppress the system voltage harmonics, thus solving the key technical difficulties in the application of high power pulse loads to the independent power system.

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    Adaptive Internal Model Control for Automotive Steer-by-Wire System with Time Delay
    LIU Wentong, CHEN Li, CHEN Jun
    2021, 55 (10):  1210-1218.  doi: 10.16183/j.cnki.jsjtu.2020.182
    Abstract ( 605 )   HTML ( 17 )   PDF (3780KB) ( 414 )   Save

    Aimed at the unknown and uncertain time delay in the steer-by-wire system, an adaptive control strategy is designed based on the internal model control framework to improve the tracking accuracy of the steering angle. Without inducing non-minimum terms, a novel nominal model is established by connecting the model of the steer-by-wire system and the linearized delay model using the all pole approximation method. The Kalman filter algorithm is designed to identify the nominal model parameters and to update in real time. Thereafter, the parameters in the inverse controller of internal model controller are tuned online. The simulation and bench test results show that compared with the traditional internal model control whose inverse control discards time delay and the classical proportion integration differentiation (PID) control, the proposed adaptive internal model control considering time delay can obtain a better tracking accuracy and has a stronger adaptability to the change of time delay.

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    Design of Three-Dimensional Layout of Ship Engine Room Equipment Based on Knowledge Based Engineering
    WANG Yunlong, JIANG Yunbo, GUAN Guan, XING Jiapeng, YU Guangliang
    2021, 55 (10):  1219-1227.  doi: 10.16183/j.cnki.jsjtu.2020.136
    Abstract ( 961 )   HTML ( 34 )   PDF (5639KB) ( 632 )   Save

    The layout design of ship engine room equipment belongs to the multi-objective optimization design problem of confined limited space. As the heart of the ship, the layout of engine room equipment will affect the performance of all aspects of the entire ship. By using CATIA software and knowledge based engineering module, the 3D layout design of the engine room of a multi-purpose cargo ship was studied. Ship engine room classification rules were established to improve the efficiency of knowledge acquisition, equipment virtual area increase rules were established to control equipment spacing, and parameterized assembly were used to complete knowledge reasoning. Finally, the generated layout scheme was verified by experts through three rules of roll torque, interference inspection, and escape time. The results are in line with expectations, and the feasibility and effectiveness of knowledge based engineering in the 3D layout design of ship engine room are verified.

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    Analysis of Cross-Platform Coupling Vibration of Ultra-High-Speed Maglev Track Beam System
    CAI Wentao, WANG Chunjiang, TENG Nianguan, WEN Quan
    2021, 55 (10):  1228-1236.  doi: 10.16183/j.cnki.jsjtu.2020.101
    Abstract ( 573 )   HTML ( 14 )   PDF (1581KB) ( 317 )   Save

    Track beam is an important structural component in maglev transportation. The analysis of its structural performance is quite critical, especially for the coupled dynamic analysis under the action of high-speed moving train, which is directly related to the operation safety and stability of the train. The dynamic coupling of the 600 km/h ultra-high-speed maglev track beam was studied, the train model was based on 5 rigid bodies and 30 degrees of freedom system, and the spatial coupling analysis model of the maglev track beam was established by using the Timoshenko beam element model with shear effect considered. For the specific implementation of the coupling analysis in the cross platform framework, the multi-body dynamics software Simpack, the large-scale finite element software ANSYS and the visual simulation tool MATLAB/Simulink modeling method were used, and the PID controller was introduced to actively control the whole suspension control system. The whole coupling system was divided into the main vehicle master system, the controller subsystem, and the track beam-pier subsystem. Besides, a coupled vibration model of maglev vehicle-controller-track beam was established. Taking a simply supported bridge with a span of 24.768 m as an example, the vertical dynamic response of the following cars and track beams of ultra-high-speed maglev vehicle running was studied, and the dynamic performance of the control system was evaluated. In addition, the change law of multi-parameter dynamic response considering the influence of bridge pier parametric vibration is given, which will provide technical support for the construction of ultra-high-speed maglev projects in the future.

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    Modeling and Application of Complex Process Knowledge for Determining Parameters
    WANG Tianlong, CHEN Yong, LIU Mengfei
    2021, 55 (10):  1237-1245.  doi: 10.16183/j.cnki.jsjtu.2020.315
    Abstract ( 515 )   HTML ( 15 )   PDF (2186KB) ( 435 )   Save

    To develop an intelligent process design system, a process knowledge modeling approach is proposed to help engineers determine the values of parameters. First, various models are introduced to represent different kinds of process information. Then, a binary tree-based approach is proposed for representing formula-based process knowledge, together with an ordered tree-based approach for representing table-based process knowledge. Thereafter, an aggregate model of process knowledge is established, which can effectively integrate process template with route selection knowledge, formula-based process knowledge, and table-based process knowledge. Finally, a knowledge-based prototype system for intelligent process design is developed. The process design of a complex cable product is taken as an example to verify the modeling method. The result demonstrates that the proposed approach can enhance the decision-making capability of an intelligent process design system, which can thus improve the efficiency and quality of process design.

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    Process Parameters of Flexible Flanging
    YOU Shuman, LI Jie, ZHAO Yixi, HU Yihui
    2021, 55 (10):  1246-1254.  doi: 10.16183/j.cnki.jsjtu.2020.162
    Abstract ( 520 )   HTML ( 17 )   PDF (8809KB) ( 394 )   Save

    Flexible flanging is a novel forming process by local continuous loading, but its process law and planning method are not perfect. Based on the characteristics of aviation sheet metal parts, the feature flanging parts were designed. Simulation of flexible flanging was conducted on the Abaqus platform, and the influence of key process parameters such as rolling pass numbers, the angle distribution of each pass, roller diameter, and rolling speed on forming quality were obtained. Considering the forming efficiency, the process parameters were optimized and verified by experiments. The results show that the forming quality of flexible flanging can be significantly improved with low cost by optimizing key process parameters, and the forming efficiency can be improved to a certain extent.

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    GA-OIHF Elman Neural Network Algorithm for Fault Diagnosis of Full Life Cycle of Rolling Bearing
    ZHUO Pengcheng, YAN Jin, ZHENG Meimei, XIA Tangbin, XI Lifeng
    2021, 55 (10):  1255-1262.  doi: 10.16183/j.cnki.jsjtu.2020.157
    Abstract ( 544 )   HTML ( 15 )   PDF (2124KB) ( 445 )   Save

    For the fault diagnosis needs of the full life cycle (light degradation, moderate degradation, and severe degradation) of rolling bearing under the environment of high background noise, a genetic algorithm-output input hidden feedback (GA-OIHF ) Elman neural network model is proposed to achieve precise diagnosis of the degradation faults of rolling bearing. Ensemble empirical mode decomposition (EEMD) is selected to effectively reduce the noise and extract fault features of the vibration signal. An OIHF Elman neural network is designed by increasing the feedbacks from the output layer to the hidden layer and the input layer based on the Elman neural network, thus further improves its ability to process full life cycle data of rolling bearing. Then, a novel GA-OIHF Elman neural network model is developed by combining the genetic algorithm (GA) and the OIHF Elman neural network. The novel GA-OIHF Elman neural network model combines the global optimization of GA and the local optimization ability of the OIHF Elman neural network to achieve an accurate fault diagnosis of the entire life cycle of rolling bearing. The experimental results show that the GA-OIHF Elman algorithm model can not only accurately diagnose the fault in the full life cycle of rolling bearing, but also ensure the stability of the diagnosis model for different faults including different fault components and stages.

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    Theoretical Model and Dynamic Performance of V-Shaped Electrothermal Actuator
    CHEN Hao, WANG Xinjie, WANG Jiong, XI Zhanwen, NIE Weirong
    2021, 55 (10):  1263-1271.  doi: 10.16183/j.cnki.jsjtu.2020.216
    Abstract ( 576 )   HTML ( 17 )   PDF (5597KB) ( 336 )   Save

    To study the dynamic performance of the V-shaped electrothermal actuator, electrothermal and thermoelastic coupling models are established based on the heat transfer theory and the forced vibration equation, respectively. A one dimensional multi-physical field coupling theoretical model of the V-shaped electrothermal actuator is proposed. The electrothermal coupling model is solved by the method in which the sine transformation and the implicit difference are combined together. Then, a convergence test is performed. The number of discrete points in the sine transformation has less influence on the temperature stability. The transient and static temperature distributions of the model coincide with that of the finite element method (FEM) at different voltages. The static displacements gained by the experiment and the edge detection algorithm also match well with that gained by the thermoelastic coupling model at different voltages. Based on the proposed model, the dynamic performances of the actuator at step and sine voltages are analyzed. The research results indicate that changes of temperature and displacement in the middle of the V-shaped electrothermal actuator are larger with the amplitude of sine voltage increasing. When the loading time of sine voltage is larger than 5 periods (50 ms), the average temperature and displacement in the middle of the actuator are equal to those with equivalent direct voltage. When applied to a periodic voltage, the motion of the actuator is also gradually cyclical and has the same time period with the voltage cycle.

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    Online Degradation Assessment of Shore Bridge Hoisting Gearbox Based on Improved Symbolic Sequence Entropy and Logistic Regression Model
    WANG Wei, WANG Bing, HU Xiong, SUN Dejian
    2021, 55 (10):  1272-1280.  doi: 10.16183/j.cnki.jsjtu.2019.169
    Abstract ( 487 )   HTML ( 14 )   PDF (4923KB) ( 381 )   Save

    Aimed at the problem of degradation assessment of shore bridge hoisting gearbox, an online evaluation method of degradation state based on improved symbol sequence entropy (O_ISSE) and logistic regression is proposed. First, a threshold factor is introduced to retain the “coarse-grained” information of the signal change direction and amplitude, reduce the “sensitivity” of original algorithm to the impact component, and propose an improved symbol sequence entropy (ISSE).Then, the sliding window Weibull fitting method is used to effectively filter out the influence of fluctuations in the ISSE characteristic sequence to form O_ISSE. Finally, a logistic regression model is trained and established, and the H value of health factor of the unknown sample are calculated to realize its status recognition online.The example analysis of the life data of the hoisting gearbox of a dock in Shanghai is conducted. The results show that the ISSE and logistic regression model can describe the complexity of signal, track and identify performance degradation status accurately.

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    Opportunistic Maintenance Modeling for Serial Production Systems with Stochastic Production Waits
    NING Xiaohan, ZHOU Xiaojun
    2021, 55 (10):  1281-1290.  doi: 10.16183/j.cnki.jsjtu.2020.320
    Abstract ( 435 )   HTML ( 9 )   PDF (1382KB) ( 316 )   Save

    In order to make full use of the maintenance opportunities brought by stochastic production waits caused by external factors such as shortage of raw materials and insufficient demands, the notions of mass center and gravity windows are introduced and an opportunity maintenance decision-making model combining the time window and the gravity window is proposed for multi-unit serial production systems. Considering both internal maintenance opportunities caused by equipment mandatory maintenance and external maintenance opportunities caused by production waits, the optimal maintenance strategy is obtained by minimizing the total maintenance cost rate of the system in the planning period. The example analysis shows that the combination of the time window and the gravity window has prominent advantages in reducing the total maintenance cost, and can effectively solve the uncertainty of the arrival and duration of production waits.

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    Multi-Order Batch Optimization of Warehouse Based on Cascaded Improved Differential Evolution Algorithm
    CHEN Guangfeng, YU Lichao
    2021, 55 (10):  1291-1302.  doi: 10.16183/j.cnki.jsjtu.2019.176
    Abstract ( 646 )   HTML ( 14 )   PDF (6723KB) ( 457 )   Save

    In order to improve the flexibility and response efficiency of warehouse dispatching, a cascaded improved differential evolution algorithm is proposed to construct the allocation of goods with the picking trolley running time, shelf stability, and inventory capacity as resource conditions. The maximum completion time for each item in the batch order assigned to the optimal location of the corresponding partition is the two-level target model that is re-batch-allocated for the conditional order. The Lagrangian interpolation algorithm is integrated into the improved algorithm of the standard differential evolution algorithm to solve the two-level target model, and the two-level solution process is cascaded to complete the cascaded differential evolution algorithm to solve the multi-order batch allocation problem. Based on the adaptive adjustment of differential evolution parameters, the improved differential evolution algorithm combines the local search ability of Lagrangian interpolation to optimize the differential evolution algorithm, and uses local and global switching factors to dynamically adjust the evolution direction and improve the convergence performance of the algorithm. The improved differential evolution algorithm is applied to solve the problem of multi-order batch allocation. The experimental results show that the improved algorithm optimization results are better than the particle swarm optimization algorithm, the genetic algorithm, and the standard differential evolution algorithm, which reduces the maximum completion time of each batch of orders and effectively balance the workload.

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    Noise Reduction Method for Intestinal Image Acquired by Intestinal Robot
    XUE Rongrong, WANG Zhiwu, YAN Guozheng, ZHUANG Haoyu
    2021, 55 (10):  1303-1309.  doi: 10.16183/j.cnki.jsjtu.2020.245
    Abstract ( 599 )   HTML ( 17 )   PDF (14436KB) ( 346 )   Save

    The wireless powered intestinal robot transmits the intestinal images taken by the image acquisition system to the external upper computer for diagnosis. However, the image transmission process will be interfered by the circuit structure and external environment, leading to noise in the collected images. Therefore, an image denoising algorithm based on non-subsampled contourlet transform (NSCT) is proposed to reduce the noise of the images collected by intestinal robots. First, histogram equalization pretreatment is adopted to improve the brightness and contrast of intestinal noise images. Next, NSCT transformation is performed on intestinal noise images and a residual network model is constructed to reduce the noise of frequency domain information after transformation. Finally, the denoised image is reconstructed by NSCT inverse transformation. The results show that the proposed algorithm can effectively reduce the influence of intestinal noise in complex environments, and better maintain the visual effect of the image. Compared with other intelligent algorithm models, both subjective and objective noise reduction effects are improved, with peak signal to noise ratio (PSNR) improved by 1.35 to 3.45 dB and structural similarity index measure (SSIM) improved by 0.0083 to 0.0252.

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    Multi-Object Fuzzy Control Strategy of Unmanned Driving Robot
    QI Dongrun, CHEN Gang
    2021, 55 (10):  1310-1319.  doi: 10.16183/j.cnki.jsjtu.2020.240
    Abstract ( 536 )   HTML ( 20 )   PDF (2679KB) ( 326 )   Save

    In order to realize the smooth control of vehicle by unmanned driving robot (UDR) in paths with different curvatures, a control strategy for UDR based on multi-objective fuzzy decision is proposed. First, the integrated dynamics models of the driving robot and vehicle are established. Then, a yaw rate generation method and a multi-objective fuzzy decision coordinated manipulation strategy are established. The yaw rate generation method generates the reference yaw rate according to the speed and path required by the test while the multi-objective fuzzy decision coordinated manipulation strategy generates sets of target speeds and target yaw rates according to the current speed. Finally, decisions are made on the scheme in the set under multiple constrains. The best scheme is chosen as the target speed and target yaw rate of the next moment. The test and simulation results demonstrate the effectiveness of the proposed strategy.

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    Orthogonal Features Extraction Method and Its Application in Convolution Neural Network
    LI Chen, LI Jianxun
    2021, 55 (10):  1320-1329.  doi: 10.16183/j.cnki.jsjtu.2020.276
    Abstract ( 868 )   HTML ( 21 )   PDF (2221KB) ( 608 )   Save

    In view of feature redundancy in the convolutional neural network, the concept of orthogonal vectors is introduced into features. Then, a method for orthogonal features extraction of convolutional neural network is proposed from the perspective of enhancing the differences between features. By building the structure of parallel branches and designing the orthogonal loss function, the convolution kernels can extract the orthogonal features, enrich the feature diversity, eliminate the feature redundancy, and improve the results of classification. The experiment results on one-dimensional sample dataset show that compared with the traditional convolution neural network, the proposed method can supervise the convolution kernels with different sizes to mine more comprehensive information of orthogonal features, which improves the efficiency of convolutional neural network and lays the foundation for subsequent researches on pattern recognition and compact neural network.

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