Welcome to Journal of Beijing Institute of Technology

2018 Vol. 27, No. 4

Display Method:
Cutting-Edge Space Exploration Technology Maturity Level Facilitation with Support of Space Debris Removal Missions
Hamed Ahmadloo, Jingrui Zhang
2018, 27(4): 477-484. doi:10.15918/j.jbit1004-0579.180103
Abstract:
Considering current space debris situation in outer space environment, different methods for debris removal missions are proposed. In addition, advanced technologies are needed to be demonstrated for future human space exploration programs. The main issue regarding to these missions is high mission cost for both debris removal missions and space environmental tests to achieve high maturity level for new space-usable technologies. Since, these missions are unavoidable for future of human space activities, a solution which can tackle these challenges is necessary. This paper will address to an idea which has the possibility to give a solution for facilitating technology readiness level (TRL) maturity tests by debris removal mission platform consideration.
Using Vector Representation of Propositions and Actions for STRIPS Action Model Learning
Wei Gao, Dunbo Cai
2018, 27(4): 485-492. doi:10.15918/j.jbit1004-0579.18072
Abstract:
Action model learning has become a hot topic in knowledge engineering for automated planning. A key problem for learning action models is to analyze state changes before and after action executions from observed "plan traces". To support such an analysis, a new approach is proposed to partition propositions of plan traces into states. First, vector representations of propositions and actions are obtained by training a neural network called Skip-Gram borrowed from the area of natural language processing (NLP). Then, a type of semantic distance among propositions and actions is defined based on their similarity measures in the vector space. Finally, k-means and k-nearest neighbor (kNN) algorithms are exploited to map propositions to states. This approach is called state partition by word vector (SPWV), which is implemented on top of a recent action model learning framework by Rao et al. Experimental results on the benchmark domains show that SPWV leads to a lower error rate of the learnt action model, compared to the probability based approach for state partition that was developed by Rao et al.
Generation and Display System of Measurement Matrix Based on DMD
Wenzhao Gu, Fu Zheng, Guangjie Zhai
2018, 27(4): 493-502. doi:10.15918/j.jbit1004-0579.17107
Abstract:
A measurement matrix is the key to sampling and signal reconstruction during the process of compressed sensing. On the basis of digital light processing (DLP) technology, a generation and display system of measurement matrix based on digital micro-mirror device (DMD) is proposed and well designed. In this system, the generation and controlling of measurement matrix are implemented on a PC, which reduces the hardware requirement to generate a random matrix and overcomes the difficulty of the hardware implementation for the random matrix. It can set up the display number of the measurement matrix, the mode of display and display time according to the requirements from users. The display information can be designed to complete the display of measurement matrix with a better adaptability. The system can be easily embedded into a variety of compressed sensing applications, which can be used to generate and display the corresponding measurement matrice with strong portability. In addition, the DMD of this system will be used as a spatial optical modulator to manipulate near-infrared light in a fast, accurate and efficient way in several applications such as in 3D scanning devices and spectrometers.
Parameters of Exterior Ballistic Feature Points Extraction in Radar Measurement Data by EMD
Wanjun Zhang, Kailin Wang, Xiaoying Wu, Guohui Li, Hongtian Liu
2018, 27(4): 503-509. doi:10.15918/j.jbit1004-0579.17159
Abstract:
The problem of measuring exterior ballistic feature points is always difficult to solve and it is essentiale on exterior ballistic measurement. By analysis of radar reflection characteristics and non-stationary echo signals of exterior ballistic feature points, the echo data of exterior ballistic feature points is measured by using the continuous wave radar. The parameters of feature points are extracted by the empirical mode decomposition method (EMD) of Hilbert-Huang transform (HHT) spectrum analysis technique. The radar echo signal model and EMD extraction model are established to analyze the exterior ballistic mutation point detection and EMD extraction method of aliasing echo signal. Typical feature point parameters of exterior ballistic in rocket flight tests are carried out and the effectiveness of the method is verified. A new method of measuring the parameters of exterior ballistic feature point is therefore presented.
Control Research of Dual Chamber Hydro-Pneumatic Suspension
Jinwei Sun, Mingming Dong, Zhiguo Wang, Baoyu Li, Liang Gu
2018, 27(4): 510-517. doi:10.15918/j.jbit1004-0579.17119
Abstract:
Vehicle riding comfort and handling stability are directly affected by suspension performance. A novel dual chamber hydro-pneumatic (DCHP) suspension system is developed in this paper. Based on the structural analysis of the DCHP suspension, an equivalent suspension model is proposed for the control purpose. A cuckoo search (CS) based fuzzy PID controller is proposed for the control of the DCHP suspension system. The proposed controller combines the advantage of fuzzy logic and PID controller, and CS algorithm is used to regulate the membership functions and PID parameters. Compared with tradition LQR controller and passive suspension system, the CSFPID controller can reduce the sprung mass acceleration, and at the same time with no deterioration of tire deflection.
Multi-Body Dynamics Modeling and Simulation Analysis of a Vehicle Suspension Based on Graph Theory
Jun Zhang, Xin Li, Renjie Li
2018, 27(4): 518-526. doi:10.15918/j.jbit1004-0579.18044
Abstract:
Multi-body dynamics, relative coordinates and graph theory are combined to analyze the structure of a vehicle suspension. The dynamic equations of the left front suspension system are derived for modeling. First, The pure tire theory model is used as the input criteria of the suspension multibody system dynamic model in order to simulate the suspension K&C characteristics test. Then, it is important to verify the accuracy of this model by comparing and analyzing the experimental data and simulation results. The results show that the model has high precision and can predict the performance of the vehicle. It also provides a new solution for the vehicle dynamic modeling.
Optimization and Evaluation of a Vehicular Exhaust Heat Recovery System
Meng Zhao, Mingshan Wei
2018, 27(4): 527-534. doi:10.15918/j.jbit1004-0579.17114
Abstract:
Exhaust waste heat recovery system based on organic Rankine cycle (ORC) has been considered as an effective method to achieve energy conservation and emissions reduction of engine. The performance of adiesel engine with an on-board ORC exhaust heat recovery system was evaluated through simulations in this study. The combined system was optimized through controlling the exhaust gas mass flow rate entering the ORC system. The models of the engine with ORC system were developed in GT-suite and Simulink environment. The validation results showed high accuracy of the models. The performance of the system recovering heat from different exhaust gas mass flow rates was evaluated. The comparative analysis of the performance between the optimized and un-optimized system was also presented. The results indicated that the exhaust gas mass flow rate had significant effects on the system performance. Integration with the on-board ORC system could effectively improve the engine power performance.The power output of the engine-ORC combined system with optimization had further improvement, and the maximum improvement could reach up to 1 16.kW.
Effect of Radial Resistance Gap on the Pressure Drop of a Compact Annular-Radial-Orifice Flow Magnetorheological Valve
Guoliang Hu, Jiawei Zhang, Mingke Liao, Ruqi Ding
2018, 27(4): 535-546. doi:10.15918/j.jbit1004-0579.17125
Abstract:
A compact annular-radial-orifice flow magnetorheological (MR) valve was developed to investigate the effects of radial resistance gap on pressure drop. The fluid flow paths of this proposed MR valve consist of a single annular flow channel, a single radial flow channel and an orifice flow channel through structure design. The finite element modelling and simulation analysis of the MR valve was carried out using ANSYS/Emag software to investigate the changes of the magnetic flux density and yield stress along the fluid flow paths under the four different radial resistance gaps. Moreover, the experimental tests were also conducted to evaluate the pressure drop, showing that the proposed MR valve has significantly improved its pressure drop at 0.5 mm width of the radial resistance gap when the annular resistance gap is fixed at 1 mm.
Propagation and Coalescence of Blast-Induced Cracks in PMMA Material Containing an Empty Circular Hole Under Delayed Ignition Blasting Load by Using the Dynamic Caustic Method
Zhongwen Yue, Yao Song, Zihang Hu, Yanlong Lu
2018, 27(4): 547-555. doi:10.15918/j.jbit1004-0579.17109
Abstract:
In this paper, dynamic caustic method is applied to analyze the blast-induced crack propagation and distribution of the dynamic stress field around an empty circular hole in polymethyl methacrylate (PMMA) material under delayed ignition blasting loads. The following experimental results are obtained. ① In directional-fracture-controlled blasting, the dynamic stress intensity factors (DSIFs) and the propagation paths of the blast-induced cracks are obviously influenced by the delayed ignition. ② The circular hole situated between the two boreholes poses a strong guiding effect on the coelesence of the cracks, causing them to propagate towards each other when cracks are reaching the circular hole area. ③ Blast-induced cracks are not initiated preferentially because of the superimposed effect from the explosive stress waves on the cracking area. ④ By using the scanning electron microscopy (SEM) method, it is verified that the roughness of crack surfaces changes along the crack propagation paths.
Temperature Compensation Algorithm for Hydraulic System Pressure Control
Huien Gao, Liang Chu, Jianhua Guo, Dianbo Zhang
2018, 27(4): 556-563. doi:10.15918/j.jbit1004-0579.17198
Abstract:
In this paper the control mechanism of solenoid valve is analyzed, which shows the solenoid valve control is actually the control of coil current. The response characteristic of coil current is related to coil inductance and resistance. The coil resistance is influenced greatly by the ambient temperature and the self-heating of coil, which affects the control precision of coil current. First, considering the heat dissipation mode of coil, the coil temperature model is established from the perspective of heat conduction, and a temperature compensation algorithm for hydraulic system pressure control is put forward. Then the hardware-in-the-loop testbed is set up by using the dSPACE platform, carrying out wheel cylinder pressurization tests with inlet valve fully opened at -40℃ and 20℃, and testing the actual pressure of wheel cylinder with the target pressures at -40℃ and 6.000 kPa/s (pressurization rate). The results show that the pressure control temperature compensation algorithm proposed in this paper accurately corrects the influence of resistance temperature drift on the response accuracy of wheel cylinder pressure. After the correction, the pressure difference is less than 500 kPa, which can meet the control accuracy requirements of solenoid valve, enriching the linear control characteristic of solenoid valve.
Design and Strategy of Series-Parallel Hybrid System Based on BSFC
Huien Gao, Liang Chu, Jianhua Guo, Dianbo Zhang
2018, 27(4): 564-574. doi:10.15918/j.jbit1004-0579.17199
Abstract:
In this paper, a drive control strategy is developed based on the characteristics of series-parallel plug-in hybrid system. Energy management strategies in various modes are established with the basis on the minimum brake specific fuel consumption (BSFC) curve of engine. The control strategy, which is based on rules and system efficiency, is adopted to determine the entry/exit mechanisms of various modes according to battery state of charge (SOC), required power and required speed. The vehicle test results verify that the proposed control strategy can improve vehicle economy efficiently and makes a good effect on engine control.
Continuous-Wave Interference Mitigation for Acquisition Method in Unified Carrier TT&C Systems
Yunyun Wu, Xiuli Yu, Yongqing Wang
2018, 27(4): 575-583. doi:10.15918/j.jbit1004-0579.17126
Abstract:
An interference mitigation for acquisition method, based on both energy center and spectrum symmetry detection, has been proposed as a possible solution to the problem of signal acquisition susceptibility to continuous-wave interference (CWI)in unified carrier telemetry, tracking, and command (TT&C) systems.With subcarrier modulation index as a priori condition, the existence of CWI is determined by comparing the energy center with the symmetric center.In the presence of interference, the interference frequency point is assumed and culled; sequentially, the spectral symmetry is used to verify whether the signal acquisition is realized. Theoretical analysis, simulations, and experimental results demonstrate that the method can realize the acquisition of the main carrier target signal with an interference-to-signal ratio of 31 dB, which represents an improvement over the existing continuous-wave interference mitigation for acquisition methods.
Ultra-Low Power 1 Volt Small Size 2.4 GHz CMOS RF Transceiver Design for Wireless Sensor Node
Muhammad Yasir Faheem, Shun'an Zhong, Abid Ali Minhas, Muhammad Basit Azeem
2018, 27(4): 584-591. doi:10.15918/j.jbit1004-0579.17099
Abstract:
Ultra-low power transceiver design is proposed for wireless sensor node used in the wireless sensor network (WSN). Typically, each sensor node contains a transceiver so it is required that both hardware and software designs of WSN node must take care of energy consumption during all modes of operation including active/sleep modes so that the operational life of each node can be increased in order to increase the lifetime of network. The current declared size of the wireless sensor node is of millimeter order, excluding the power source and crystal oscillator. We have proposed a new 2.4 GHz transceiver that has five blocks namely XO, PLL, PA, LNA and IF. The proposed transceiver incorporates less number of low-drop outs (LDOs) regulators. The size of the transceiver is reduced by decreasing the area of beneficiary components up to 0.41 mm2of core area in such a way that some functions are optimally distributed among other components. The proposed design is smaller in size and consumes less power, <1 mW, compared to other transceivers. The operating voltage has also been reduced to 1 V. This transceiver is most efficient and will be fruitful for the wireless networks as it has been designed by considering modern requirements.
Recognition of Group Activities Using Complex Wavelet Domain Based Cayley-Klein Metric Learning
Gensheng Hu, Min Li, Dong Liang, Mingzhu Wan, Wenxia Bao
2018, 27(4): 592-603. doi:10.15918/j.jbit1004-0579.17120
Abstract:
A group activity recognition algorithm is proposed to improve the recognition accuracy in video surveillance by using complex wavelet domain based Cayley-Klein metric learning. Non-sampled dual-tree complex wavelet packet transform (NS-DTCWPT) is used to decompose the human images in videos into multi-scale and multi-resolution. An improved local binary pattern (ILBP) and an inner-distance shape context (IDSC) combined with bag-of-words model is adopted to extract the decomposed high and low frequency coefficient features. The extracted coefficient features of the training samples are used to optimize Cayley-Klein metric matrix by solving a nonlinear optimization problem. The group activities in videos are recognized by using the method of feature extraction and Cayley-Klein metric learning. Experimental results on behave video set, group activity video set, and self-built video set show that the proposed algorithm has higher recognition accuracy than the existing algorithms.
High-Dimensional Spatial Standardization Algorithm for Diffusion Tensor Image Registration
Tao Guo, Quan Wang, Yi Wang, Kun Xie
2018, 27(4): 604-616. doi:10.15918/j.jbit1004-0579.18033
Abstract:
Three high dimensional spatial standardization algorithms are used for diffusion tensor image (DTI) registration, and seven kinds of methods are used to evaluate their performances. Firstly, the template used in this paper was obtained by spatial transformation of 16 subjects by means of tensor-based standardization. Then, high dimensional standardization algorithms for diffusion tensor images, including fractional anisotropy (FA) based diffeomorphic registration algorithm, FA based elastic registration algorithm and tensor-based registration algorithm, were performed. Finally, 7 kinds of evaluation methods, including normalized standard deviation, dyadic coherence, diffusion cross-correlation, overlap of eigenvalue-eigenvector pairs, Euclidean distance of diffusion tensor, and Euclidean distance of the deviatoric tensor and deviatoric of tensors, were used to qualitatively compare and summarize the above standardization algorithms. Experimental results revealed that the high-dimensional tensor-based standardization algorithms perform well and can maintain the consistency of anatomical structures.
Terrain Rendering LOD Algorithm Based on Improved Restrictive Quadtree Segmentation and Variation Coefficient of Elevation
Zhenwu Wang, Xiaohua Lü
2018, 27(4): 617-622. doi:10.15918/j.jbit1004-0579.17193
Abstract:
Aiming to deal with the difficult issues of terrain data model simplification and crack disposal, the paper proposed an improved level of detail (LOD) terrain rendering algorithm, in which a variation coefficient of elevation is introduced to express the undulation of topography. Then the coefficient is used to construct a node evaluation function in the terrain data model simplification step. Furthermore, an edge reduction strategy is combined with the improved restrictive quadtree segmentation to handle the crack problem. The experiment results demonstrated that the proposed method can reduce the amount of rendering triangles and enhance the rendering speed on the premise of ensuring the rendering effect compared with a traditional LOD algorithm.
Novel On-Line North-Seeking Method Based on a Three-Axis MEMS Gyroscope
Yu Liu, Gaojun Xiang, Junqi Guo, Min Zhou, Hongzhi Liu
2018, 27(4): 623-629. doi:10.15918/j.jbit1004-0579.17128
Abstract:
A novel on-line north-seeking method based on a three-axis micro-electro-mechanical system (MEMS) gyroscope is designed. This system processes data by using a Kalman filter to calibrate the installation error of the three-axis MEMS gyroscope in complex environment. The attitude angle updating for quaternion, based on which the attitude instrument will be rotated in real-time and the true north will be found. Our experimental platform constitutes the dual-axis electric rotary table and the attitude instrument, which is developed independently by our scientific research team. The experimental results show that the accuracy of north-seeking is higher than 1°, while the maximum root mean square error and the maximum mean absolute error are 0.906 7 and 0.910 0, respectively. The accuracy of north-seeking is much higher than the traditional method.
Convolutional Neural Network Based on Spatial Pyramid for Image Classification
Gaihua Wang, Meng Lü, Tao Li, Guoliang Yuan, Wenzhou Liu
2018, 27(4): 630-636. doi:10.15918/j.jbit1004-0579.17140
Abstract:
A novel convolutional neural network based on spatial pyramid for image classification is proposed. The network exploits image features with spatial pyramid representation. First, it extracts global features from an original image, and then different layers of grids are utilized to extract feature maps from different convolutional layers. Inspired by the spatial pyramid, the new network contains two parts, one of which is just like a standard convolutional neural network, composing of alternating convolutions and subsampling layers. But those convolution layers would be averagely pooled by the grid way to obtain feature maps, and then concatenated into a feature vector individually. Finally, those vectors are sequentially concatenated into a total feature vector as the last feature to the fully connection layer. This generated feature vector derives benefits from the classic and previous convolution layer, while the size of the grid adjusting the weight of the feature maps improves the recognition efficiency of the network. Experimental results demonstrate that this model improves the accuracy and applicability compared with the traditional model.
Evaluation of Ambient Light Display for High Information Capacity
Hua Ma
2018, 27(4): 637-644. doi:10.15918/j.jbit1004-0579.17168
Abstract:
Ambient light display presents peripheral information unobtrusively, and it can be context aware and aesthetically enhance specific environment. However, since the abstract characteristic of light, people should attentively keep a good balance between unobtrusiveness and effectiveness, when designing an ambient light display. Especially, in the condition of high information capacity, ambient light display need a mechanism to portray information effectively. In this paper, a framework with an overlay mechanism is evaluated for high information capacity. Based on the framework, two ambient light displays are designed to support the evaluation work. The evaluation questions are related with three aspects including information understanding, transition and encoding, special output channel. From the perception level, interpretation level and experience level, the process of evaluation is implemented. The results indicate that the framework with the overlay mechanism can effectively support varied and specific communicating information. The transitions and information encoding benefit from the proper mapping of states and notification levels in the framework.
TOTAL CONTENTS(Vol. 27)
2018, 27(4): 645-650.
Abstract:
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