Volume 42,Issue 9,2019 Table of Contents

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  • 1  Coupling effect of pool rotation and axial magnetic field on Marangoni-thermocapillary convection
    MA Li PENG Lan GAO Jian ZHU Chenzhi
    2019, 42(9):1-9,54. DOI: 10.11835/j.issn.1000-582X.2019.09.001
    [Abstract](671) [HTML](749) [PDF 1.93 M](816)
    Abstract:
    There is Marangoni-thermocapillary convection of silicon melt in annular shallow pool submitted to bidirectional temperature gradients. When either of them exceeds the critical value, the flow becomes a three-dimensional oscillatory convection, which becomes complicated by thermal radiation on the free surface. In order to find an effective method to suppress the three-dimensional oscillatory convection, a series of three-dimensional numerical simulations, considering only pool rotation or only axial magnetic field or their coupling, are carried out. It is found that both pool rotation and axial magnetic field can suppress Marangoni-thermocapillary convection to a certain extent, and their combination can promote the suppression further. To avoid the negative effect of the magnetic field, the optimal parameters to maintain axisymmetric steady flow is obtained under the minimum magnetic field intensity.
    2  Experimental study of boiling heat transfer in vortex tubes and dimple tubes
    XIA Hu ZHOU Yongli WANG Guoqiang WU Qiqi TANG Jingwen
    2019, 42(9):10-17. DOI: 10.11835/j.issn.1000-582X.2019.09.002
    [Abstract](643) [HTML](412) [PDF 946.10 K](1096)
    Abstract:
    With micro turbine Capstone C30 flue gas as the heat source, the characteristics of boiling heat transfer inside tubes including vortex tubes, dimple tubes and plain tubes were investigated experimentally. The results reveal that boiling heat transfer coefficient of vortex tubes is about 1.6 to 2.1 times that of the plain tubes, external surface heat transfer coefficient is about 1.3 to 1.5 times that of the plain tube, and the overall heat transfer coefficient is about 1.3 to 1.6 times that of the plain tubes; boiling heat transfer coefficient of dimpled tubes is about 2.1 to 2.5 times that of the plain tubes, external surface heat transfer coefficient is about 1.8 to 2.0 times that of the plain tube, and the overall heat transfer coefficient is about 1.9 to 2.1 times that of the plain tubes. And the reason why the heat transfer performance of vortex tubes and dimple tubes is better than that of the plain tubes is analyzed.
    3  Simulation of the evolution process of stayed cable electrochemical corrosion based on cellular automata
    GUO Zengwei CHEN Hanlin LI Xiaogang YU Jiayu
    2019, 42(9):18-26. DOI: 10.11835/j.issn.1000-582X.2019.09.003
    [Abstract](449) [HTML](781) [PDF 1.57 M](1016)
    Abstract:
    In order to simulate the corrosion evolution process of the cable in the actual environment and explore the influence of chloride ion on the corrosion process, a cellular automaton model for simulating the electrochemical corrosion process of the cable was established based on the basic principle of metal electrochemical corrosion. The entire cable corrosion system, the key elements of which were abstracted into four cell types, was discretized into a 500×500 cell grid, and its corrosion evolution process was simulated on the mesoscopic scale by the defined local rules. The effects of corrosive solution concentration and corrosion probability on the corrosion process of steel wire were analyzed. It has been found that if the characteristic parameters of cellular automata are selected reasonably, the morphology of the crater generated by cellular automata simulation is similar to actual etch pit morphology. It has also been discovered that the pitting area and corrosion rate of the steel wire increases gradually with time. The corrosive cell with chloride ions has a significant effect on the process of cable corrosion, but that without chloride ions has little effect on the corrosion rate of the wire, which indicates that reducing the concentration of chloride ions in the surrounding environment is an effective way to mitigate cable corrosion.
    4  Energy-efficient resource allocation technique of RF energy harvesting-based cognitive radio network with quality of service assurance
    TIAN Jie CHENG Yongsheng XIAO He HOU Dong XIE Nan
    2019, 42(9):27-33. DOI: 10.11835/j.issn.1000-582X.2019.09.004
    [Abstract](437) [HTML](515) [PDF 1.02 M](931)
    Abstract:
    In this paper a research is carried out into an RF energy harvesting-based cognitive radio network (RF EH-CRN), aimming at the maximization of energy efficiency of secondary user networks by jointly optimizing transmission time and transmission power. The secondary transmitter (ST) first harvests energy from the radio frequency (RF) signals of primary user (PU) and then communicates with SU. Besides, ST maintains possible remaining energy from previous transmission blocks as initial energy. To ensure the quality of service (QoS) of secondary network, we impose a minimum throughput requirement constraint on ST in the process of energy offciency (EE) maximization. As EE maximization is a nonlinear fractional programming problem, we propose a fast iteration algorithm based on Dinkelbach method to achieve optimal resource allocation. Simulation results demonstrate that with fast convergence speed this algorithm can significantly improve the EE of the system while guaranteeing QoS constraints.
    5  Research on autofocus algorithm of digital PCR system
    CHEN Shanxiong PENG Maoling QIAN Renfei SHAN Yuli ZHENG Fangyuan
    2019, 42(9):34-43. DOI: 10.11835/j.issn.1000-582X.2019.09.005
    [Abstract](459) [HTML](620) [PDF 1.58 M](929)
    Abstract:
    The digital PCR instrument is a digital instrument for amplifying and amplifying specific DNA fragments. The problem studied in this paper is the autofocus problem of its electronic imaging device. Based on the analysis of existing SOM neural network autofocus scheme, we propose an improved scheme-BP neural network for autofocus. It directly takes the SOM input and the actual focus position as the input and output of the BP neural network, which eliminates the process of prior classification and then corresponding to the focus matrix in the original SOM scheme, saving time. The experimental results show that the traditional autofocus method has good focusing effect, but the speed is slow, and the universality of the BP neural network autofocus scheme is not good enough, but within a good accuracy range, the speed is faster. Compared to traditional focusing methods, the autofocus scheme designed in this paper successfully achieves faster focusing speed for biochips.
    6  FMEA analysis of mechanical drive system of automatic three-dimensional material warehouse
    BI Wenhai JIA Zhixin YAN Wei PAN Xinwei
    2019, 42(9):44-54. DOI: 10.11835/j.issn.1000-582X.2019.09.006
    [Abstract](606) [HTML](989) [PDF 1.50 M](928)
    Abstract:
    To solve the reliability problem of automatic three-dimensional material warehouse in sheet metal automatic production line, failure modes and effects analysis(FMEA)of mechanical drive system of material warehouse was carried out using maintenance aware design environment(MADe). The functions and failures of mechanical drive system were defined through standardized classification, and the model of mechanical drive system was established. The propagation path and influence of each failure were analyzed using fuzzy cognitive map (FCM) to generate the FMEA result of mechanical drive system. The results show that the main failure mechanisms are wear, corrosion and deformation, and the main failure causes are insufficient lubrication, pollutant entry and load problems. Thus, a series of targeted improvement measures are put forward to improve the reliability of the automatic three-dimensional material warehouse.
    7  An improved sine cosine optimization algorithm with self-learning strategy and Lévy flight
    LI Yintong HAN Tong ZHAO Hui WANG Xiaofei
    2019, 42(9):55-65. DOI: 10.11835/j.issn.1000-582X.2019.09.007
    [Abstract](777) [HTML](747) [PDF 1.53 M](1259)
    Abstract:
    In order to improve the performance of sine cosine algorithm (SCA) with poor local search ability, an sine cosine optimization algorithm with self-learning strategy and Lévy flight (SCASL) was proposed. Firstly, the self-learning strategy and nonlinear weight factor of sine cosine algorithm was proposed, so that the search individual could remember its historical optimal position, which guided the individual to update its location in the optimization process, thus improving the local search ability of SCA. When the search was stagnant, the stagnation perturbation strategy based on Lévy flight was adopted to jump out of local optimum so as to improve the local optimum avoidance ability. Based on 13 classic benchmark functions, the numerical simulation was conducted and the results show that SCASL has higher computational efficiency, convergence accuracy and stronger local optimum avoidance ability compared with standard SCA and other state-of-the-art optimization algorithms such as SSA,VCS,WOA and GSA. The simulation results of unmanned combat aircraft flight path plan show that for the battlefield environment with six enemy threat sources, SCASL can stably obtain less expensive flight path than the standard SCA.Therefore, the proposed SCASL has better optimization performance.
    8  Hand bone segmentation of skeletal age X-Ray image based on Softmax regression model
    LIU Rui JIA Yuanyuan HE Xiangqian LI Zhe CAI Jinhua LI Hao
    2019, 42(9):73-83. DOI: 10.11835/j.issn.1000-582X.2019.09.009
    [Abstract](868) [HTML](799) [PDF 1.93 M](1163)
    Abstract:
    X-ray images of wrist bone are often used for clinical bone age assessment to focus on skeletal development in children and adolescents. Among the process, the segmentation of the hand bone region is a key step in the preprocessing, and the accuracy of hand bone segmentation greatly influences the final evaluation results. The traditional threshold segmentation methods have poor robustness in the automatic segmentation process, while using the deep neural network is more accurate but really complex. Aiming at these problems, this paper proposed to predict the optimal threshold by training Softmax regression model to obtain binary image based on threshold segmentation, then use the region growing to extract the whole hand, and normalize the processed images in the end. On the 100 test sets, the proposed method was compared with the traditional threshold segmentation methods-Otsu, maximum entropy threshold and histogram mean segmentation. DSC (dice similarity coefficient), under-segmentation rate and over-segmentation rate were used to quantitatively analyze the results. The experimental results show that the method has achieved the best results with an average DSC value of 0.97, and the under-segmentation rate and the over-segmentation rate are both close to 0. It also shows good performance for complex hand radiographs, which is proved to be more robust than the traditional threshold segmentation methods and can accurately complete automatic hand bone segmentation on skeletal age X-ray images.
    9  Intelligent cognition of rotary kiln burning state based on deep transfer learning
    LUAN Qinglei CHEN Keqiong
    2019, 42(9):84-91. DOI: 10.11835/j.issn.1000-582X.2019.09.010
    [Abstract](578) [HTML](509) [PDF 1.28 M](937)
    Abstract:
    Aiming at the cognition problem of rotary kiln burning state, an intelligent cognition method based on deep transfer learning for rotary kiln burning state is explored. Firstly, based on the adaptive structure-based convolutional neural networks (ASCNN), the unstructured dynamic feature space is established with the determined mapping relationship of the flame image from global to local. Secondly, based on the feature discriminability measure and the variable precision rough set theory, under the uncertain condition of the finite field, the burning state cognitive intelligent decision information system with the discriminable and the unstructured dynamic feature representation is established from the perspective of information theory, to enhance the interpretability of the feature space of the burning states. Thirdly, a stochastic configuration networks (SCN) with universal approximation capability is built to establish a classified criterion for flame image burning states with stronger generalization ability. Finally, based on the generalized error and entropy theory, the entropy measure index of the uncertain cognition results of the flame image burning state is established, to evaluate the cognitive results of the burning state in real time. The dynamic transfer learning mechanism is constructed to realize the self-optimization adjustment and reconstruction of the multi-level differentiated feature space and its classified criteria for the burning state. The experimental results show that the intelligent cognitive model of flame image burning state based on deep transfer learning constructed in this paper is more feasible and superior to the existing method for the burning state recognition of cement rotary kiln.
    10  Research on fault simulation and reliability evaluation of pedestrian network of business district
    FENG Jie HUANG Yong WAN Dan
    2019, 42(9):92-104. DOI: 10.11835/j.issn.1000-582X.2019.09.011
    [Abstract](340) [HTML](642) [PDF 2.82 M](787)
    Abstract:
    Based on the complex network theory, the network model of pedestrian network of Chongqing commercial district is constructed, and the pedestrian network fault simulation is designed according to the real disaster analysis of the road network in the business circle and the reliability index. With Jiefangbei pedestrian road network taken as an example, case analysis of reliability is conducted and comparative study on raliability of pedestrian networks of the five major commercial circles are carried out on the basis of three types of indicators:network efficiency changes under cumulative attacks, maximum connected subgraphs changes under cumulative attacks, and network efficiency changes under single attack. The calculation lead to the conclusion of reliability evaluation, which forms corresponding opinions about of the construction and management of road network.
    11  A benefit-output model for measuring the performance of green buildings using grey relational algorithm
    YE Kunhui LIU Rui SHEN Liyin
    2019, 42(9):105-113. DOI: 10.11835/j.issn.1000-582X.2019.09.012
    [Abstract](463) [HTML](718) [PDF 487.36 K](827)
    Abstract:
    Recent years have witnessed a wide application of green buildings in the world. Properly measuring the performance of green building projects has been the cornerstone of governmental policy-making on energy saving and carbon reduction, and it has been playing a crucial role in the formulation of business competitive strategies. In this study, multidimensional evaluation indicators are identified. A benefit-output model composed of physical and currency indicators is proposed using gray relational algorithm to make quantitative evaluation of multiple schemes for green benefit of construction projects. Through the comparison of three cases in China, the proposed model is found to be more stable, reliable, and effective than others including grey cluster evaluation and data envelope analysis,presenting a multi-dimensional concept of green buildings and offering a useful framework for application in other contexts.
    12  Question similarity computing method for automatic question answering system
    CAO Jianwen WAN Fucheng
    2019, 42(9):114-122. DOI: 10.11835/j.issn.1000-582X.2019.09.013
    [Abstract](614) [HTML](1183) [PDF 534.35 K](1018)
    Abstract:
    Structured automatic question answering system lacks the division of vocabulary, word order and structure, which leads to low sentence similarity. In order to solve this problem, a method of computing sentence similarity based on Web semantics is proposed. According to the structure of the structured automatic question answering system, the system statement analysis model is designed. Through the forward matching method, the user input natural statements in the model professional lexicon are segmented and the string relationship is analyzed. The unsteady similarity coefficient is used to describe the similarity of two strings, and the similarity of morphology, word order and structure is analyzed to determine the similarity of different sentences. The experimental results show that with this method, the minimum computational accuracy is 42%, and the maximum computational accuracy can reach 96%. The overall computational accuracy has been greatly improved compared with that based on neural network and ant colony, thereby improving the overall performance of the automatic question answering system.
    13  Experiments on the impact pressure of high-pressure water jet under different nozzle shapes
    HUANG Fei HU Bin ZUO Weiqin LI Shuqing
    2019, 42(9):123-132. DOI: 10.11835/j.issn.1000-582X.2019.09.014
    [Abstract](758) [HTML](877) [PDF 2.56 M](1780)
    Abstract:
    The flexible impact force of water jet is the mechanics criterion of material breakage by water jet. The nozzle shape has a great influence on the impact pressure. Five different nozzles were designed in this paper, and the impacting tests were conducted based on the self-designed jet-impact test platform. PVDF piezoelectric film sensor and the high speed camera were used to record the experimental data. It's indicated that water jet beam from the circular nozzle presents the best strand integrity. The shock wave induced by impacting from the circular nozzle has a great influence on the diffusion form of the liquid. These features cause the highest central impact pressure of circular nozzle. The impact pressures of water jets from square, triangular and cross-shaped nozzles are much lower than that of circular nozzle. The water jet from elliptical nozzle is the most divergent and its impact pressure is the smallest consequently. The peak pressures from all shape nozzles present nonlinear relationships with the pump pressure, but the duration time of these peak pressures nearly keep constant with the pump pressure.

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