JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY

Trajectory Optimization for 7-Dofs Space Manipulator

Wencheng Ni, Zhihong Jiang, Hui Li, Bo Wei, Xiaoyun Li, Bainan Zhang, Qiang Huang

2017, 26(2): 143-149. doi:10.15918/j.jbit1004-0579.201726.0201

[Abstract](739) [PDF 275KB](701)

Abstract:
The space manipulator is always designed to have 7 degrees of freedom (Dofs) with the consideration of energy limitation, as well as the flexible moving possibility. Therefore, how to plan the trajectory is important to improve the performance of the manipulator. In this paper, the speed of the end effector is configured as a projecting parameter, when a constant acceleration is applied to adjust the velocity. To implement this trajectory planning strategy, an optimization algorithm through the pseudo inverse of Jacobin matrix is designed, which adjusts the weight functions of joints. According to the functional theory, this algorithm is analyzed and the optimal solution is found in numerous sets of planning. A MATLAB simulation platform is established and the results verity the effectiveness of the algorithm.

Novel Real-Time Seam Tracking Algorithm Based on Vector Angle and Least Square Method

Guanhao Liang, Qingsheng Luo, Zhuo Ge, Xiaoqing Guan

2017, 26(2): 150-157. doi:10.15918/j.jbit1004-0579.201726.0202

[Abstract](569) [PDF 3126KB](426)

Abstract:
Real-time seam tracking can improve welding quality and enhance welding efficiency during the welding process in automobile manufacturing. However,the teaching-playing welding process, an off-line seam tracking method, is still dominant in automobile industry,which is less flexible when welding objects or situation change. A novel real-time algorithm consisting of seam detection and generation is proposed to track seam. Using captured 3D points, space vectors were created between two adjacent points along each laser line and then a vector angle based algorithm was developed to detect target points on the seam. Least square method was used to fit target points to a welding trajectory for seam tracking. Furthermore, the real-time seam tracking process was simulated in MATLAB/Simulink. The trend of joint angles vs. time was logged and a comparison between the off-line and the proposed seam tracking algorithm was conducted. Results show that the proposed real-time seam tracking algorithm can work in a real-time scenario and have high accuracy in welding point positioning.

Central Discontinuous Galerkin Method for the Navier-Stokes Equations

Tan Ren, Chao Wang, Haining Dong, Danjie Zhou

2017, 26(2): 158-164. doi:10.15918/j.jbit1004-0579.201726.0203

[Abstract](736) [PDF 265KB](536)

Abstract:
Central discontinuous Galerkin (CDG) method is used to solve the Navier-Stokes equations for viscous flow in this paper. The CDG method involves two pieces of approximate solutions defined on overlapping meshes. Taking advantages of the redundant representation of the solution on the overlapping meshes, the cell interface of one computational mesh is right inside the staggered mesh, hence approximate Riemann solvers are not needed at cell interfaces. Third order total variation diminishing (TVD) Runge-Kutta (RK) methods are applied in time discretization. Numerical examples for 1D and 2D viscous flow simulations are presented to validate the accuracy and robustness of the CDG method.

Experimental Investigation on Shock Wave Characteristics of Aluminized Explosives in Air Blast

Xiaoyu Duan, Qingzhong Cui, Xueyong Guo, Qiushi Wang, Qingjie Jiao

2017, 26(2): 165-173. doi:10.15918/j.jbit1004-0579.201726.0204

[Abstract](651) [PDF 797KB](581)

Abstract:
To investigate the shock wave characteristics of RDX-based aluminized explosives, air blast tests were conducted for measuring the parameters of 10.kg aluminized explosives which contained 0-40% aluminum. The results showed that with the increasing of aluminum content, the overpressures and impulses increase at first and then decrease within 7 m or 5 m, which reached the maximum when aluminum content was 20% or 30%. Power exponential formulas are used to fit the shock wave parameters vs scaled distance, where an equal weight of TNT is used to calculate the scaled distance. The overpressures of HL0 and TNT in tested locations not only conform to the similar law, but also conform to the same attenuation law after gaining the scaled distances of equal TNT mass. The pre-exponential factors of overpressure and impulse,k_pandk_I, decrease along with the increasing of Al content and keep the same pace as the calculatedP_CJ. The attenuation coefficientsa_Panda_Iincrease at first and decrease later with the increasing of aluminum content, and they reached the maximal values with 30% Al containing, which keeps the same pace as the calculatedQ_V.

Dynamic Path Following Control of a Ground Ackerman Steering Robot to Avoid a Collision

Guangming Xiong, Xiaoyun Li

2017, 26(2): 174-182. doi:10.15918/j.jbit1004-0579.201726.0205

[Abstract](640) [PDF 2651KB](691)

Abstract:
A novel method is proposed to dynamically control the path following of a ground Ackerman steering robot to avoid a collision. The method consists of collision prediction module, collision avoidance module and global path following module. The elliptic repulsive potential field method (ER-PFM) and the enhanced vector polar histogram method (VPH +) based on the Ackerman steering model are proposed to predict the collision in a dynamic environment. The collision avoidance is realized by the proposed cost function and speed control law. The global path following process is achieved by pure pursuit. Experiments show that the robot can fulfill the dynamic path following task safely and efficiently using the proposed method.

Influence of Structural Parameters of Turbocharger Floating Bearing on Its Dynamic Characteristic Coefficients

Junsheng Zhao, Yuantong Gu, Shengxian Yi, Xuelong Lu

2017, 26(2): 183-190. doi:10.15918/j.jbit1004-0579.201726.0206

[Abstract](623) [PDF 290KB](562)

Abstract:
The structure parameters in an actual industrial production have a great influence on the coefficient of supercharger floating bearing dynamic characteristics,but there has been little systematic study so far. In this paper, the influence of structural parameters of the turbocharger floating bearing on its dynamic characteristic coefficientsis systematically investigated based on the theories of hydrodynamic lubrication and tribology. The influence of clearance ratio on eccentricity and the influence of internal to external radius ratios, and Sommerfeld number were analyzed.A new formula of responding characteristics of the oil film force caused by the displacement or velocity disturbance was deduced near an equilibrium in the steady state. Applying the newly developed formula, the dynamic characteristic was studied for floating bearings. Regularity for change of oil film stiffness and damping was analyzed with the structural parameters of floating bearing such as radius ratios and eccentricity.It has been found that the clearance ratio increases with eccentricity when the radius ratio is unchanged.The eccentricity decreases with the internal to external radius ratio of floating rings when the clearance ratio is constant.The absolute value of total principal stiffness and total main damping decrease with the clearance ratio and radius ratio of floating rings when the total cross damping is stable. The results and findings in this paper can contribute to nonlinear dynamics designs of turbocharger rotor-bearing systems.

Importance Analysis on Subsystem of CNC Lathe Based on TOPSIS

Xiaoyan Qi, Guixiang Shen, Yingzhi Zhang, Shuguang Sun

2017, 26(2): 191-196. doi:10.15918/j.jbit1004-0579.201726.0207

[Abstract](390) [PDF 227KB](381)

Abstract:
An importance analysis model for computer numerical control (CNC) lathe subsystems was proposed. The model was based on technique for order preference by similarity to an ideal solution (TOPSIS) and considered the structure correlation between subsystems and the complete machine, the fault correlation of each subsystem and so on. The model can obtain a comprehensive sequencing of subsystems based on their importance to the complete machine. It lays a theoretical foundation for reliability allocation.

Image Classification Based on the Fusion of Complementary Features

Huilin Gao, Wenjie Chen

2017, 26(2): 197-205. doi:10.15918/j.jbit1004-0579.201726.0208

[Abstract](919) [PDF 3583KB](633)

Abstract:
Image classification based on bag-of-words (BOW) has a broad application prospect in pattern recognition field but the shortcomings such as single feature and low classification accuracy are apparent. To deal with this problem, this paper proposes to combine two ingredients:(i) Three features with functions of mutual complementation are adopted to describe the images, including pyramid histogram of words (PHOW), pyramid histogram of color (PHOC) and pyramid histogram of orientated gradients (PHOG). (ii) An adaptive feature-weight adjusted image categorization algorithm based on the SVM and the decision level fusion of multiple features are employed. Experiments are carried out on the Caltech 101 database, which confirms the validity of the proposed approach. The experimental results show that the classification accuracy rate of the proposed method is improved by 7%-14% higher than that of the traditional BOW methods. With full utilization of global, local and spatial information, the algorithm is much more complete and flexible to describe the feature information of the image through the multi-feature fusion and the pyramid structure composed by image spatial multi-resolution decomposition. Significant improvements to the classification accuracy are achieved as the result.

Novel Apriori-Based Multi-Label Learning Algorithm by Exploiting Coupled Label Relationship

Zhenwu Wang, Longbing Cao

2017, 26(2): 206-214. doi:10.15918/j.jbit1004-0579.201726.0209

[Abstract](644) [PDF 296KB](476)

Abstract:
It is a key challenge to exploit the label coupling relationship in multi-label classification (MLC) problems. Most previous work focused on label pairwise relations, in which generally only global statistical information is used to analyze the coupled label relationship. In this work, firstly Bayesian and hypothesis testing methods are applied to predict the label set size of testing samples within theirknearest neighbor samples, which combines global and local statistical information, and then apriori algorithm is used to mine the label coupling relationship among multiple labels rather than pairwise labels, which can exploit the label coupling relations more accurately and comprehensively. The experimental results on text, biology and audio datasets shown that, compared with the state-of-the-art algorithm, the proposed algorithm can obtain better performance on 5 common criteria.

Human-Object Interaction Recognition Based on Modeling Context

Shuyang Li, Wei Liang, Qun Zhang

2017, 26(2): 215-222. doi:10.15918/j.jbit1004-0579.201726.0210

[Abstract](570) [PDF 5243KB](849)

Abstract:
This paper proposes a method to recognize human-object interactions by modeling context between human actions and interacted objects. Human-object interaction recognition is a challenging task due to severe occlusion between human and objects during the interacting process. Since that human actions and interacted objects provide strong context information, i.e. some actions are usually related to some specific objects, the accuracy of recognition is significantly improved for both of them. Through the proposed method, both global and local temporal features from skeleton sequences are extracted to model human actions. In the meantime, kernel features are utilized to describe interacted objects. Finally, all possible solutions from actions and objects are optimized by modeling the context between them. The results of experiments demonstrate the effectiveness of our method.

Design and Realization of Schottky Barrier Didoes in 130nm CMOS Process

Junyu Shi, Dasheng Cui, Haidong Hao, Haixia Wu, Xin Lyu

2017, 26(2): 223-227. doi:10.15918/j.jbit1004-0579.201726.0211

[Abstract](568) [PDF 1309KB](385)

Abstract:
A polysilicon separated CMOS Schottky barrier diode is designed and tested in this study. By replacing the shallow trench isolation (STI) of a ploy ring, the series resistances of Schottky diodes are reduced, leading to an improvement in cut-off frequencies. The device structure is detailed and a device model is developed. Our analysis on the device shows that the cut-off frequency increases with the decreasing of the Schottky contact area. Based on this observation, the Schottky contact area is set to 0.38×0.38μm², which is the minimum contact diffusion area allowed by the process flow. The distance between the anode and the cathode is also discussed. Diodes with different dimensions are fabricated and measured. Through extensive measurements, the optimum dimensions are obtained. Bond-pads with a reduced area are used to improve the measurement accuracy. The measurement results show that these diodes can achieve a cut-off frequency of 1.5THz. Thus, it is possible to use these diodes in THz detection.

Fully-Differential Multichannel Integrated Neural Signal Recording Front-End

Xiaoran Li, Shun'an Zhong, Haidong Yang, Libin Yao

2017, 26(2): 228-234. doi:10.15918/j.jbit1004-0579.201726.0212

[Abstract](656) [PDF 1615KB](581)

Abstract:
Neural signal can be used for clinical disease diagnosis, data analysis and real-time life signal monitoring. Its analysis requires high-performance signal processors.Based on the 180nm standard CMOS technology, a 16-channel fully-differential neural recording chip is designed. The chip consists of 16-channel low-noise pre-amplifiers, a multiplexer and a successive approximation register (SAR) ADC. The result shows that the equivalent input-referred noise of recording amplifier is 3.63 μV, bringing down noise efficiency factor to 4.24 At 8.5 bits effective number of bit (ENOB), the analog-to-digital converter (ADC) has an SNR of 52.6dB. The core area of the proposed neural recording front-end is about 2.46mm².

Optimized Implementation for Wave Digital Filter Based Circuit Emulation on FPGA

Yue Ma, Shun'an Zhong, Shiwei Ren

2017, 26(2): 235-244. doi:10.15918/j.jbit1004-0579.201726.0213

[Abstract](711) [PDF 1268KB](471)

Abstract:
A binary tree representation is designed in this paper for optimization of wave digital filter (WDF) implementation. To achieve this, an equivalent WDF model of the original circuit is converted into abinary tree representation at first. This WDF binary tree can then be transformed to several topologies with the same implication, since the WDF adaptors have a symmetrical behavior on their ports. Because the WDF implementation is related to field programmable gate array (FPGA) resource usage and the cycle time of emulation,choosing a proper binary tree topology for WDF implementation can help balance the complexity and performance quality of an emulation system. Both WDF-FPGA emulation and HSpice simulation on the same circuit are tested. There is no significant difference between these two simulations. However, in terms of time consumption, the WDF-FPGA emulation has an advantage over the other. Our experiment also demonstrates that the optimized WDF-FPGA emulation has an acceptable accuracy and feasibility.

Sparse Recovery of Linear Time-Varying Channel in OFDM System

Jiansheng Hu, Zuxun Song, Shuxia Guo

2017, 26(2): 245-251. doi:10.15918/j.jbit1004-0579.201726.0214

[Abstract](541) [PDF 260KB](383)

Abstract:
In order to improve the performance of linear time-varying (LTV) channel estimation, based on the sparsity of channel taps in time domain, a sparse recovery method of LTV channel in orthogonal frequency division multiplexing (OFDM) system is proposed. Firstly, based on the compressive sensing theory, the average of the channel taps over one symbol duration in the LTV channel model is estimated. Secondly, in order to deal with the inter-carrier interference (ICI), the group-pilot design criterion is used based on the minimization of mutual coherence of the measurement. Finally, an efficient pilot pattern optimization algorithm is proposed by a dual layer loops iteration. The simulation results show that the new method uses less pilots, has a smaller bit error ratio (BER), and greater ability to deal with Doppler frequency shift than the traditional method does.

Channel Estimation and Compensation for Underwater Acoustic Pipeline Communication

Weijiang Wang, Nan Su, Jianyan Liu

2017, 26(2): 252-258. doi:10.15918/j.jbit1004-0579.201726.0215

[Abstract](567) [PDF 278KB](651)

Abstract:
An estimation and compensation algorithm for underwater acoustic pipeline channel is investigated. A joint time-frequency adaptive signal-to-noise ratio (SNR) estimation based on the maximum likelihood method is introduced firstly, and the Cramer-Rao lower bound (CRLB) is proposed so as to evaluate the performance of the SNR estimation algorithm. For frequency-selective fading channel part, estimation and compensation are made to improve the robustness of the system on the basis of the LMS algorithm. Furthermore,real-time update iteration algorithm in the frequency domain is investigated to realize synchronous receiving and estimation. For verification, simulations and actual data tests were made, and the results show that the algorithm possesses great robustness, efficiency and accuracy inrealization of SNR estimation, signal detection and frequency impulse compensation for the channel.

Online Detection of State Estimator Performance Degradation via Efficient Numerical Observability Analysis

Zheng Rong, Shun'an Zhong, Nathan Michael

2017, 26(2): 259-266. doi:10.15918/j.jbit1004-0579.201726.0216

[Abstract](904) [PDF 2410KB](414)

Abstract:
An efficient observability analysis method is proposed to enable online detection of performance degradation of an optimization-based sliding window visual-inertial state estimation framework. The proposed methodology leverages numerical techniques in nonlinear observability analysis to enable online evaluation of the system observability and indication of the state estimation performance. Specifically, an empirical observability Gramian based approach is introduced to efficiently measure the observability condition of the windowed nonlinear system, and a scalar index is proposed to quantify the average system observability. The proposed approach is specialized to a challenging optimization-based sliding window monocular visual-inertial state estimation formulation and evaluated through simulation and experiments to assess the efficacy of the methodology. The analysis result shows that the proposed approach can correctly indicate degradation of the state estimation accuracy with real-time performance.

Combined Transmission Interference Spectrum of No Core Fiber and BP Neural Network for Concentration Sensing Research

Fang Wang, Heng Lu, Yunpeng Li, Yufang Liu

2017, 26(2): 267-275. doi:10.15918/j.jbit1004-0579.201726.0217

[Abstract](666) [PDF 1660KB](450)

Abstract:
To investigate wavelength response of the no core fiber(NCF)interference spectrum to concentration, a three-layer back propagation(BP) neural network model was established to optimize the concentration sensing data. In this method,the measured wavelength and the corresponding concentration were trained by a BP neural network, so that the accuracy of the measurement system was optimized. The wavelength was used as the training set and got into the input layer of the three layer BP network model which is used as the input value of the network, and the corresponding actual concentration value was used as the output value of the network, and the optimal network structure was trained. This paper discovers a preferable correlation between the predicted value and the actual value, where the former is approximately equal to the latter. The correlation coefficients of the measured and predicted values for a sucrose concentration were 1.000 89 and 1.003 94; similarly, correlations of 0.999 51 and 1.018 8 for a glucose concentration were observed. The results demonstrate that the BP neural network can improve the prediction accuracy of the nonlinear relationship between the interference spectral data and the concentration in NCF sensing systems.

Synthesis and Characterization of Novel Biodegradable Poly Copolymers

Jie Ouyang, Hongquan Yin, Qingshan Zhang, Yunzheng Li, Pengjun Yao

2017, 26(2): 276-284. doi:10.15918/j.jbit1004-0579.201726.0218

[Abstract](605) [PDF 335KB](464)

Abstract:
Novel biodegradable aliphatic polyesters, poly(butylene succinate-co-triethylene glycol succinate) (P(BS-co-TEGS)) and poly(butylene succinate) (PBS), were synthesized through a two-step procedure of esterification and polycondensation with succinic acid and 1, 4-butanediol/triethylene glycol as raw materials as well as tetrabutyl titanate and diphenylphosphinic acid as the co-catalysts. The chemical structure and molecular weight of the copolymers were characterized by¹H nuclear magnetic resonance (¹H NMR) and gel permeation chromatography (GPC), respectively. In addition, thermal properties, crystal structure and mechanical properties were also analyzed with various techniques. P(BS-co-TEGS) exhibited more excellent mechanical properties than PBS, especially in elongation at break. Meanwhile, the crystal structure and thermal stability of the P(BS-co-TEGS) have hardly changed. The crystallinity of P (BS-co-TEGS) was lower than that of PBS and decreased with the increase of mole ratio of triethylene glycol. With the increase of TEGS unit molar composition, the melting point (T_m), crystallization temperatures (T_c) and heat of fusion (ΔH_m) of P(BS-co-TEGS) decreased, while glass transition temperature (T_g) increased.

2017 Vol. 26, No. 2