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Table of Content

    31 October 2017, Volume 51 Issue 10 Previous Issue    Next Issue
     The Kinematic Analysis and Structure Optimization of
     MLattice Modular Robot
    YANG Zhen,FU Zhuang,GUAN Enguang,XU Jiannan,TIAN Shihe,ZHENG Hui
    2017, 51 (10):  1153-1159.  doi: 10.16183/j.cnki.jsjtu.2017.10.001
    Abstract ( 883 )   Save
     To solve the movement interference happening during the motions of modular robots, an optimized structure design is proposed and applied to the MLattice modular robots. By introducing a translational joint, the mechanical arms of modular robots are able to shrink and stretch to avoid the movement interference. Through the kinematic analysis,  the movement interference can be avoided and also the stroke of translational joint can be minimized, then the modular robots can successfully realize the selfreconfiguration process and ensure the structural strength as well as the stability of the robots. The feasibility and motor ability of optimized structure are verified through the simulations of motion spaces under different situations and the experiment of prototype robots. The results show that the introduced translational joint can well avoid the movement interference happening among the adjacent modules, that the design of each mechanical joint is operable, and that it establishes the foundation for the further researches about large scale modular robotics system.
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    Dynamic Analysis of TwoLink Flexible Manipulators Based on
     the Absolute Nodal Coordinate Formulation 
    ZHAO Jun1,YU Haidong2
    2017, 51 (10):  1160-1165.  doi: 10.16183/j.cnki.jsjtu.2017.10.002
    Abstract ( 1567 )   Save
     A dynamic model of the flexible manipulator with variable crosssection is established based on the absolute nodal coordinate formulation. Variable boundary conditions of the link are described with some functions which are used as the upper and lower limits in the integrations to calculate mass matrix and stiffness matrix of the element. With these matrices the dynamic model of the manipulator is proposed by using the Newton equations. Manipulators with different materials and variable crosssections are employed in the numerical simulations. Results show that the increase of elastic modulus can improve the stiffness of structure and reduce its deformation. Kinematic accuracy of the structure can be improved by optimizing crosssection shape without changing its mass.
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     Modelling and Bottleneck Analysis of Product Quality in Transient  Phase
     of MultiStage Manufacturing Systems Based on Markovian Chains
    ZHAO Ziren1,DU Shichang1,HUANG Delin1,REN Fei2,LIANG Xinguang2
    2017, 51 (10):  1166-1173.  doi: 10.16183/j.cnki.jsjtu.2017.10.003
    Abstract ( 939 )   Save
    Modern manufacturing systems usually adopt multistage and multiproduct production mode. When changing product type, due to the adjustment of fixture and craft, system goes through a transient phase. The phase can be long or short depending on parameters of the system, and affect the rate of qualified products seriously. There are many mature analysis methods and successful cases about steadystate, but lacking transient phase models which connect product quality and parameters of a system. In this paper, we focus on transient analysis of Markovian model of manufacturing systems. The transient phase of manufacturing system and the relevance of processing steps are analyzed, and a Markovian model of multistage manufacturing systems in transient phase is developed and some analysis is carried out for quality bottleneck parameters identification. The effectiveness of this model is validated by multistage manufacturing system of astronautic valve used in a domestic rocket manufacturing company.
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     Study on Motion Stability of Variable CrossSection Flexible Beams
     Based on the Absolute Nodal Coordinate Formulation
    LUO Jingjinga,YU Haidonga,ZHAO Chunzhanga,b,WANG Haoa,b
    2017, 51 (10):  1174-1180.  doi: 10.16183/j.cnki.jsjtu.2017.10.004
    Abstract ( 950 )   Save
     The boundary features of the variable crosssection beams are taken into consideration and the stiffness matrix is derived based on the nonlinear continuum mechanics. A dynamic model of the beam is established by using the absolute nodal coordinate formulation. The statespace equation of the beam during motion is developed. Based on the Lyapunov theory a criterion of the motion stability of the flexible beams is proposed, and the effects of material properties and variable crosssections are investigated. The results indicate that with a small elastic modulus, the variable crosssection beam shows a better stability than the constant crosssection beam. As the elastic modulus increases, the stability of the constant crosssection becomes better than that of the variable crosssection beam. When the  elastic modulus reaches a certain value, the motion of constant crosssection beam becomes stable.
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     An Improved Modal Simulation Method for Switched Reluctance Motor
     Based on Static PreComputation
    WANG Yibo1,HUANG Yixiang1,LI Bingchu1,LING Xiao1 ZHAO Shuai1,LIU Chengliang1,ZHANG Daqing2
    2017, 51 (10):  1181-1188.  doi: 10.16183/j.cnki.jsjtu.2017.10.005
    Abstract ( 1024 )   Save
     To reduce the large errors of low order modes in modal simulation for switched reluctance motor (SRM),  an improved method for modal simulation based on static precomputation is proposed. A 3dimensional finite element model for SRM is established. The simulation research is carried with the existing simulation method and the improved simulation method. Experiments are conducted for validation. Data analysis results showed that for low order modal calculation, the existing methods still have some shortcomings. And the improved method based on static precomputation can make the relative error less than 5% by considering the effects of assembly stress and motor weight stress.
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     Identification of Product Redesign Modules Based on
     Fuzzy Random Failure Mode and Effects Analysis
    ZHOU Penghui,MA Hongzhan,CHEN Dongping,CHEN Mengyue,CHU Xuening
    2017, 51 (10):  1189-1195.  doi: 10.16183/j.cnki.jsjtu.2017.10.006
    Abstract ( 923 )   Save
     Redesign is a work for improving a new product after it has been used a period. Identification of the redesign modules is the precondition. The existing identification methods mainly focus on customer demands, without considering product failure data. Therefore, a new identification method is proposed using fuzzy random FMEA. A redesign necessity index is defined to evaluate the design risk of product modules. Considering the randomness and fuzziness of the risk judgment, a fuzzy random FMEA model is constructed to measure the relationship between the failure modes and the product modules. Besides, credibility theory and fuzzy stochastic simulation technique are employed to deal with the multi valued problem of fuzzy variables and random variables. Finally, the feasibility and effectiveness of the proposed method is verified by the identification and verification of the crawler crane.
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     Mode Transition for a Hybrid Electric Vehicle Based on
     Model Reference Control
    PENG Cheng,ZHU Jianyun,CHEN Li
    2017, 51 (10):  1196-1201.  doi: 10.16183/j.cnki.jsjtu.2017.10.007x
    Abstract ( 999 )   Save
      A model reference control (MRC) is proposed for the transition from motoronly driving mode to compound driving mode of a seriesparallel hybrid electric vehicle. The dynamics of the motoronly mode is regarded as the reference model. The stability condition is derived, and the control parameters are selected so as to guarantee the torque continuity which avoids intensive jerk. The results show that the MRC not only reduces vehicle jerk but also reduces frictional loss compared with the conventional method. Sensitivity analysis examines the influences of control parameters, actuation noise and ratio of inertia moment on the control quality.
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     Algorithm for Relatively Small Planted Clique with
     Small Edge Probability
    HUANG Xuangui
    2017, 51 (10):  1202-1206.  doi: 10.16183/j.cnki.jsjtu.2017.10.008
    Abstract ( 1074 )   Save
     Planted clique problem is a central problem in averagecase complexity theory. The random graph with planted clique model is extended, and small edge probability conditions are invented to allow the edge probability to decrease. It is shown that under such conditions there exists a polynomialtime randomized algorithm to find a relatively small planted clique by using probability tools for analysis of randomized algorithms. The result improves analysis of the algorithm in the literature.
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     A Study on Injection Mould Part Quotation Model
     Based on Back Propagation Neural Network
    LIU Wei,YANG Chao
    2017, 51 (10):  1207-1213.  doi: 10.16183/j.cnki.jsjtu.2017.10.009
    Abstract ( 739 )   Save
     General part quotations for injection mould often hold shortcomings such as low efficiency and poor accuracy. Aiming at this issue, a multiexpert quotation framework is proposed based on back propagation (BP) neural network (NN) in this paper. Weights and thresholds of the network are optimized by using generic algorithm which can avoid to fall into a local optimum solution. Meanwhile, an ideal topological structure of NN is decided by studying the Gaussian distribution of errors. A rotational quotation is thereby achieved after synthetical consideration of the evaluating results by synthesizing multiple experts. It is proved that the method greatly eliminates the randomness of a single quotation. Experiments exhibit a preferable performance, in which the average error of quotations is about 6.90%. This scheme reduces the difficulty of traditional quotation and enhances its robustness.
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     Scheduling Method of Manufacturing Cells with
     Robot Restricted Processing
    ZHOU Binghai,LI Ming
    2017, 51 (10):  1214-1219.  doi: 10.16183/j.cnki.jsjtu.2017.10.010
    Abstract ( 781 )   Save
     To solve a scheduling problem of manufacturing cells with robot restricted processing (RRP), a scheduling strategy based on time constraints was proposed. Firstly, a nonfree robotic process was formally described by introducing novel concepts of internal and external residencies and fundamental period. A mathematical programming model considering characteristics of the nonfree robotic process, resources and residency constraints was established to minimize the average manufacturing cycle time. To optimize robotarm movements, a tabu circulatory time point searching algorithm was constructed.Finally, analysis of simulation experiments was implemented. Results indicate that the proposed algorithm is valid and feasible.
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     Feasible Change Path Search and Optimization Method
    Based on Driving Parameter Modeling
    CHEN Jinping1,ZHANG Shusheng1,HE Weiping1,WANG Mingwei1,HUANG Hui2
    2017, 51 (10):  1220-1227. 
    Abstract ( 694 )   Save
     To solve the problem of difficultly analyzing the feasible change paths in the product design, a feasible change path search and optimization method was proposed based on drivenparameter modeling. The phenomenon of change propagation was described from the viewpoint of set theory. Based on traditional product parameter modeling, a product drivenparameter associated network was constructed, and the preprocess approach of product model was introduced. The depth first search (DFS) algorithm was adopted to realize the search of feasible change paths. The assessment indexes and criterions were proposed to instruct the selection of optimal change path, and technique for order preference by similarity to an ideal solution (TOPSIS) method was utilized to select the optimal change path. A case was provided to verify the feasibility of the method by a developed prototype.
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     Aerial Scene Classification Based on Nonlinear Scale Space
    CHEN Suting,WANG Zhuo,WANG Qi
    2017, 51 (10):  1228-1234.  doi: 10.16183/j.cnki.jsjtu.2017.10.012
    Abstract ( 905 )   Save
     In aerial scene classification, scale invariant feature transform (SIFT) uses linear Gaussian decomposition to extract feature points. The algorithm has many problems, such as fuzzy boundary and loss of detail. Besides, the SIFT cannot describe the color information. Combined with bagofvisualwords (BoVW) model, CKAZE (colorKAZE) descriptor which fuses color feature in nonlinear scale space is proposed to solve these problems. KAZE is used to detect the characteristic information by constructing nonlinear scale space. Color quantization matrix is calculated by noninterval quantization in the HSV (hue, saturation, value) space, and the CKAZE feature descriptor is generated by the quantization matrix. Finally, highlevel semantic features and spatial layout information are extracted and fused. Experimental results show that the average classification accuracy of the proposed algorithm, compared to the classification algorithm based on SIFT, is improved by about 8%. The proposed algorithm improves the feature description ability of KAZE, and breaks the limitation of the SIFT classification algorithm. Besides, for the unmanned aerial vehicle (UAV) scene image, the accuracy can be greatly improved.
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     Design of Random Restricted Boltzmann Machine Group
    LIU Kaia,ZHANG Liminb,ZHOU Lijuna
    2017, 51 (10):  1235-1240.  doi: 10.16183/j.cnki.jsjtu.2017.10.013
    Abstract ( 1021 )   Save
      To improve the restricted Boltzmann machine (RBM)’s data generalization ability and resolve the features homogenization problem, a random RBM group (RRBMG) design is proposed. The dimensions of observation data were randomly divided into groups, and the childRBMs were built based on the combined data group. Two methods based on the structural stories were used to compose hidden units’ layer finally, shallow structure by mean output, and deep structure through the formation of highlevel hidden units’ layer. The theoretical analysis shows that, with the increase of models’ number in the group, the training objectives of RRBMG will gradually approach the training objectives of standard RBM, and can effectively reduce the impact of feature homogeneity. The experimental results show that, compared with dropout algorithm, the proposed RRBMG can effectively improve the feature learning ability of RBM, and use the shallow structure and deep structure features to increase the classification accuracy of mixed national institute of standards and technology (MNIST) database experiment by 2% and 0.4%.
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     Research on Landing Strategy and Influencing Factors of
     an Autonomous Underwater Vehicle with Supporting Mechanism
    ZHU Xinyao1,SONG Baowei2,XU Gang1,YANG Songlin1
    2017, 51 (10):  1241-1251.  doi: 10.16183/j.cnki.jsjtu.2017.10.014
    Abstract ( 875 )   Save
     Conception and working process of an autonomous underwater vehicle (AUV) that can park on the seabed were introduced briefly. Kinematic and dynamic mathematical models of the AUV spatial motion were established based on basic mechanics theory. Combined with the characteristics of this AUV, forces’ mathematic models of variable buoyancy system and vertical thrusters were established, and control algorithm of verticalthrusters was designed. Based on this, landing simulation model was established. Four landing strategies of the AUV with supporting mechanism were proposed: diving freely with negative buoyancy, diving freely with supporting mechanics with negative buoyancy, diving under the control of vertical thrusters and diving with supporting mechanics under the control of vertical thrusters. On this basis, the impact of mass and position of water injected into the AUV on landing parameters were studied. Finally, the influences of supporting mechanism and vertical thrusters were analyzed through comparing different landing strategies. Results in this paper provide theoretical basis to landing program design and improvement of the AUV.
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     Distributed Supervisory Predictive Control of
     Main Steam Temperature for UltraSupercritical Unit
    KONG Xiaobing1,2,FAN Chang2,LIU Xiangjie1
    2017, 51 (10):  1252-1259.  doi: 10.16183/j.cnki.jsjtu.2017.10.015
    Abstract ( 804 )   Save
      Considering the main steam temperature control system in ultrasupercritical oncethrough boiler, this paper presents a distributed supervisory predictive control (DSPC) method based on neurofuzzy network to realize the coordination of each control system. The supervisory layer is added on the basis of the original adjusting layer, so the setting values of the intermediate point temperature and superheated steam temperature at all levels can be obtained by solving an online optimization problem. Cooperation between systems is achieved by exchanging information between each control system and its neighbors via supervisory layer and by optimizing the local problem with the performance index considering the related systems. Simulation experiment is carried out under the condition of disturbance load to show the effectiveness of the proposed controllers.
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     Research and Application of Urban Water Demand Forecasting
     Based on Time Difference Coefficient
    LUO Huayi,WANG Jingcheng,YANG Liwen,LI Xiaocheng
    2017, 51 (10):  1260-1267.  doi: 10.16183/j.cnki.jsjtu.2017.10.016
    Abstract ( 1011 )   Save
     The support of water supply system has been a concerned focus of urban construction. The accurate prediction of short term water quantity is important for the whole water system operation and maintenance. In this paper, the intelligent scheduling management system for raw water based on least square support vector machine with improved particle swarm optimization is proposed by means of the project Shanghai Qingcaosha Intelligent Raw Water Dispatch and Management System. After analyzing the characteristics of water quantity data, the results of water quantity prediction have a big deviation from the actual water supply during the holidays. So forecasting model of daily and hourly water demand is built  based on time difference coefficient to optimize the original prediction model. Combined with the actual operation and process conditions of water plant,  this optimized model is applied to water plant to provide more accurate water supply scheduling suggestion.
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     Machine Vision Rapid Detection Method of the Track Fasteners Missing
    MIN Yongzhi1,XIAO Benyu1,DANG Jianwu1,YIN Chao1,YUE Biao1,MA Hongfeng2
    2017, 51 (10):  1268-1272.  doi: 10.16183/j.cnki.jsjtu.2017.10.017
    Abstract ( 1134 )   Save
      The detection of missing track fasteners is an important part of daily inspection of the railway. Owing to the new requirements of realtime and self adaptation of the automatic detection technology, a method of realtime detection of missing track fasteners based on machine vision is proposed in this paper. In order to deal with the interference of environmental light, the image acquisition device includes hood and lightemitting diode (LED) auxiliary light source. The switching median filtering is used and the Canny edge detection is improved based on image gradient amplitude for image adaptive enhancement of  the characteristics of fastener edges. The feature of article fasteners to play in stable boundary and the projection curve characteristics of template matching are combined to realize the realtime detection of missing fasteners. Experimental results showed that the image detection time of every frame is 245.61ms, the average of ecognition accuracy is 85.8%. The highest speed of real time detection of missing fastener of actual operation line is 3.82m/s. These results suggest that the proposed method is adaptive.
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     Research on Image Encryption System Based on
     Chaotic Discrete Sequence
    CHEN Ning,HE Xiaobin,GUI Weihua,YANG Chunhua
    2017, 51 (10):  1273-1280. 
    Abstract ( 736 )   Save
     Aiming at the shortcomings of traditional encryption algorithm, such as small key space and simple encryption structure, a doublechaotic image encryption algorithm which can greatly extend the encryption key is proposed. At the transmitting end, the image position mapping matrix is generated by the continuous chaotic system, and the image pixel information is added to the chaotic system. The encrypted image is transmitted over Ethernet and the pixel is synchronized and decrypted at the receiving end. The method utilizes the initial sensitivity of the chaotic system and the synchronization of the chaotic system to double encrypt the image. The structure of the doublechaotic image encryption system is complex and difficult to crack and has a great key space. The experiments show that the doublechaotic image encryption based on Liu chaotic system and discrete chaotic synchronization system can resist image statistical attack and exhaustive attack, and can be realized on Windows system.
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