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2020, 40(1): .

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2020, 40(1): .

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Development Trends of New Energy Vehicle Technology Under Industrial Integration

WANG Zhen-po, LI Xiao-hui, SUN Feng-chun

2020, 40(1): 1-10. doi:10.15918/j.tbit1001-0645.2019.309

Abstract(1522) PDF(567)

Abstract:
Developing new energy vehicle (NEV) plays an important role in promoting the renewable energy applications and the development of electrified transportation technologies. The vigorous growth of NEV is considered to be effective for ensuring national energy security, alleviating energy shortages and improving environmental quality. At present, developing NEV has become a global consensus and collective action. NEV industry in China has made significant achievements, showing the characteristics of multi-industry integration. In this paper, the trend in the automotive industry was analyzed and six technological hotpots in the future were presented. Focusing on the goals of high efficiency, energy-saving, safety, comfort and all-climate applications, eight key technical directions of NEV were proposed for industrial integration. Analysis results show that, boosted by big data system, the large-scale commercial applications of NEV will be accelerated, and the deeper integration and sustainable healthy development of the industry will be realized.

Reliability Analysis for Competing Failure Based on Mahalanobis Distance

GAI Bing-liang, TENG Ke-nan, WANG Hao-wei, CHEN Yu, HONG Liang

2020, 40(1): 11-16. doi:10.15918/j.tbit1001-0645.2018.362

Abstract(1088) PDF(352)

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A reliability analysis method based on mahalanobis distance (MD) was proposed for the reliability evaluation at competing risk involving both degradation-based failure and shock-based failure. Firstly, MD was used to transform the multivariate degradation data to one dimensional MD data, and the MD data was modeled by Wiener process with random effects. Then, two extreme shock processes were considered, the shock processes with Poisson process and the shock processes with a fixed time. The reliability models of the two situations were established respectively. Both the shift threshold and minimum magnitude of shock loads were considered synchronously in these dependent competing failure models. Finally, the effectiveness of proposed models was demonstrated by a fatigue crack increase example. Besides, sensitivity analysis was performed to assess the effects of model parameters on the reliability. Results show that, both the shocks with Poisson process and with a fixed time affect the analysis results of product reliability.

Study on the Dynamic Characteristics of a Double-Layered Hyper-Damping Isolator

LIU Hai-ping, LUO Jie

2020, 40(1): 17-22. doi:10.15918/j.tbit1001-0645.2018.395

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A new double-layered isolator was proposed, compose of positive and negative stiffness elements. A dynamic mechanical model was established for the double-layered hyper-damping isolator. Based on this dynamic model, the frequency response characteristics, time history series and force transmission rate were provided, respectively, by using Laplace transformation and 4th-order Runge-Kutta methods. The calculation results show that, comparing the dynamic responses of the single-layered and double-layered reference linear isolators and single-layered hyper-damping isolators, the dynamic responses of the double-layered hyper-damping isolators can be controlled effectively in middle and low frequency domain. Especially, the double-layered isolator is optimal for the control of multi-frequency excitations. In addition, the influences of design parameters, stiffness ratio α and factor of safetyε, on the dynamic performance were also studied. According to the calculating results, the hyper-damping isolator can realize the dynamic performance without resonance peak when the design parameters are chosen properly.

Research on Interaction of Weld Cracks in Pipe Based on Finite Element Method

ZHANG Yu, MA Guo-yin, REN Hui-bang, DUAN Meng-lan, WANG Yi

2020, 40(1): 23-28,47. doi:10.15918/j.tbit1001-0645.2018.236

Abstract(1027) PDF(452)

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About the effect of crack interaction on the pipe welding line,two cracks interaction model was constructed based on finite element method in this paper.Considering the factors of crack dimension and distance,a fitting formula was proposed for stress intensity factors and crack dimension and distances between them.And also an interaction law was discussed.Results show that,with the increase of crack tip distance,the amplification coefficient decreases according to the negative exponential law,tending to 1 finally.And the influence of crack dimension on interaction law is approximately quadric positive correlation.Based on the interaction law and research results,the engineering critical assessment (ECA) for cracks was carried out.Compared with the crack evaluation results with BS 7910 criterion,the proposed fitting formula,which takes interaction effect into consideration,can provide more accurate evaluation results.

Design of Three-Degree-of-Freedom Water Hydraulic Artificial Muscle Joint System

CHE Jin-kai, ZHANG Zeng-meng, LIU Pei-pei, NING Da-yong, GONG Yong-jun, GONG Xiao-feng

2020, 40(1): 29-34. doi:10.15918/j.tbit1001-0645.2018.435

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A three-degree-of-freedom water hydraulic artificial muscle mechanical joint with a serial-parallel hybrid model was designed based on the motion mechanism of human shoulder joint. According to the output torque range of the human shoulder joint, the mechanical joint output torque range were designed, and the parameters of water hydraulic artificial muscle were calculated to match the joint. According to the force displacement characteristics of water hydraulic artificial muscle under different working pressures, the relationship between rotation angle and torque was analyzed. A three-degree-of-freedom joint test system was designed and set up. This joint test system can achieve three-degree-of-freedom turning motion under a certain torque, which provides the conditions for further research on the motion control and maneuverability of the underwater manipulator.

Recovery and Reuse of Gravity Potential Energy of Forging Manipulator Based on Secondary Regulation

ZHAI Fu-gang, LI Rui-yang, WEI Li-zhong, HAN Shao-yong

2020, 40(1): 35-40. doi:10.15918/j.tbit1001-0645.2018.434

Abstract(1049) PDF(320)

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To solve the problem of gravity potential energy waste during the clamp descending of the traditional valve-controlled forging manipulator,an energy-saving forging manipulator hydraulic circuit was constructed by combining the secondary hydraulic control system with the secondary adjustment technology. On the basis of the hydraulic circuit,a pressure closed loop control strategy with constant pressure differential was proposed for the recovery and reuse of the clamp's gravitational potential energy,and a simulation study was carried out based on a company's 100 kN forging manipulator. The results show that,this type of energy-saving forging manipulator hydraulic circuit can achieve potential energy recovery and energy reuse effects on the basis of satisfying the system control characteristic index. It can reduce the energy consumption of the hydraulic system and provide new ideas for the hydraulic system design of the forging manipulator in the future.

Analytical Method for Computing Creep Secondary Internal Forces of Continuous Composite Beams Influenced by Support Constraints

HAN Chun-xiu, ZHANG Jiu-chang, ZHOU Dong-hua, SHUANG Chao

2020, 40(1): 41-47. doi:10.15918/j.tbit1001-0645.2018.494

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To calculate the creep effects of steel-concrete composite beams under support constraints, and to predict the long-term mechanical properties, the coupling relationship between sectional stress redistribution in the continuous composite beams and restrained internal force redistribution of structural supports was unlocked based on the principle of force method and creep constitutive equation of concrete. The analytical formulas for computing the creep secondary internal forces of the composite beam under the two conditions of fast and slow support constraints were deduced. Then, both of theoretical and numerical methods were adopted to analyze an example. The calculation results show that, the creep plays a beneficial role in restricting the settlement of support. The creep secondary moment in the steel-concrete composite beam is affected by the internal stress redistribution, can be controlled by the redistribution coefficient, and varies with the stiffness ratio between concrete and steel beam. The internal stress and external internal force can influence each other. This change process is related to the creep coefficient and aging coefficient. These formulas derived in this paper are proposed based on clear mechanics concepts. Therefore, this method can be more conveniently used to calculate the internal forces of the steel-concrete composite beams under the influence of bearing changes. The obtained results can effectively reflect the mechanics characteristics of steel-concrete composite beams. This method is an effective supplement to evaluate the long-term mechanical characteristics of the composite beams.

An Interference Alignment Solution for MIMO Interference Channels with Asymmetric Structure

JIANG Hao, HOU Jian-jun

2020, 40(1): 48-52. doi:10.15918/j.tbit1001-0645.2018.063

Abstract(1101) PDF(326)

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The interference alignment (IA) problem of multiple-input multiple-output (MIMO) interference channels with asymmetric structure was studied. The interference alignment problem of the whole system was resolved into the IA problems of two subsystems to build the equations which could be solved by symbolic computation software using the interaction between the subsystems. The proposed method can realize the IA of an asymmetrical MIMO channel under the condition that the number of antennas is minimum. Taking 4-user as an example to show the process of the proposed solution, simulation result reveals the advantages and disadvantages of the method which validates the proposed method and analyzes the complexity.

Adaptive Beamforming of CSB sin-FDA Based on RCB Algorithm

WANG Bo, XIE Jun-wei, ZHANG Jing, ZHAO Min

2020, 40(1): 53-61. doi:10.15918/j.tbit1001-0645.2019.109

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In the process of suppressing interference near the target position,the minimum variance distortionless response (MVDR) beamformer will appear the mainlobe distortion problem in the condition of mismatched steering vector and more array cells.To solve the problem,the CSB sin-FDA receiving array was used to replace the ULA-FDA receiving array,and the mismatched steering vector was modified based on the RCB algorithm,calculating the optimal power vector.Simulation test was carried out to validate the performance advantages of the proposed method,compared with the MVDR based on PA,MVDR based on FDA-BFF,and the MVDR based on FDA-MIMO.

Larceny Ex-Convict Classification by Combining Static Attribute and Dynamic Trajectory

HU Xiao-feng, SHI Tuo, QU Ke

2020, 40(1): 62-68. doi:10.15918/j.tbit1001-0645.2018.051

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It's one of the social issues, that the different authorities in the world pay considerable attention to the ex-convicts for recommitting crimes. Previous studies of ex-convict classification are usually focused on static attributes of historical criminal data rather than dynamic trajectory. And fewer are focused on risk predicting analysis of crime-recommitting of larceny ex-convicts. For this reason, a larceny ex-convict (first offenders and recidivisms) classification was studied by combining static attributes and dynamic trajectory in this paper. Firstly, a long-timespan data base about the larceny ex-convict classification was developed based on static attributes and dynamic trajectory. Then the performances of different types of machine learning models on larceny ex-convict classification were explored and compared to define the most relevant features to it. Finally, an early warning model of larceny crimes was established based on weighted association rules. The research achievement can be applied to early warning of larceny crimes, and will show practical significance for crime crackdown and security precaution.

Support Vector Machine for Acoustic Scene Classification Algorithm Research Based on Multi-Features Fusion

ZHAO Wei, JIN Cong, TU Zhong-wen, SRIDHAR Krishnan, LIU Shan

2020, 40(1): 69-75. doi:10.15918/j.tbit1001-0645.2018.171

Abstract(1297) PDF(452)

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For the sound environment dataset of the DCASE 2017 Challenge, Mel frequency cepstral coefficients (MFCC), short-time energy (SE), acoustic event likelihood features (AELF), and mute time (MT) features were extracted to form a multi-features fusion matrix. Comparing various kernel functions and optimization algorithms, radial basis function kernel (RK) was finally selected to establish the support vector machine (SVM) model, and cross validation (CV) method was utilized to optimize SVM parameters and to classify 15 acoustic scenes. The experimental results show that the classification accuracy of grocery store and office can reach more than 90%, and the average classification accuracy reaches 71.11%, which is much higher than the average classification accuracy of 61% of the baseline system given in the challenge.

Cave Target Recognition Method Based on Multiple Characteristics

CHEN Ke-shan, JIA Bo-ran, LIU Kai, ZHANG Ming-bo

2020, 40(1): 76-82. doi:10.15918/j.tbit1001-0645.2018.038

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In order to solve the problems of automatic identification of cave target, a target recognition algorithm was designed based on various features. Firstly, discussing the model of typical cave target, summarizing its main features, and filtering the input images according to HOG feature, the images of the cave target were classified. Then a self-adaptive threshold algorithm Wiblack was proposed based on the gray feature of the cave target to extract the suspected target in the image. Finally, a mathematical model of the cave target was designed, and a target discrimination algorithm was developed based on shape similarity. The target discrimination and the target profile describing were completed with circular and ellipse similarity methods. The experimental results show that the proposed algorithm possesses better recognition accuracy, higher adaptability and robustness.

Short-Term Stock Price Movement Prediction Model

Based on Social Media Sentiment Analysis JI Zi-zheng, SHEN Ting-ting, ZHANG Xiao

2020, 40(1): 83-89. doi:10.15918/j.tbit1001-0645.2018.149

Abstract(1078) PDF(353)

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To improve the capability of stock price movement prediction,the sentiment information in social media was utilized.Different from the coarse-grained utilization of all the sentiment information in text,the fine-grained sentiment information correlated with the specific topic of a company was taken into consideration in this study.The topic and its corresponding sentiment information were co-extracted and simultaneously used to predict the stock price movement.Moreover,to verify the efficiency of the fine-grained sentiment information,a stock dataset,consisting of more trading dates and stocks,was utilized.It is superior to previous research with only few trading dates or few stocks.

A Representation Learning Method of Fusing Entity Affinity Constraints

LIU Qiong-xin, MA Jing, ZHENG Pei-xiong

2020, 40(1): 90-97. doi:10.15918/j.tbit1001-0645.2018.039

Abstract(1128) PDF(371)

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Representation learning on knowledge graph aims to project both entities and relations into a low-dimensional continuous space and dig out the hidden relations between two entities. Traditional method does not make full use of entity's description text and most of representation learning methods based on entity description project text into vector space without considering the relevance of entities in text. In this paper, a knowledge graph representation learning method was proposed, taking the advantage of entity description based on the traditional structure-based representation learning. In this method, the different relevant entities extracted based on entities description and relevant entities were fused as supplementary constraints information to knowledge graph representation learning. Experimental results on real world datasets show that, this method can enhance the inference effectiveness and outperforms structure-based representation learning method, especially outperform deep convolutional neural model which encode semantics of entity descriptions into structure-based representation learning.

Predicting Crime Distribution Based on Transition Probability Matrix Self-Learning Algorithm

WEI Xin-lei, YAN Jin-yao, SHI Tuo, ZHANG Yuan

2020, 40(1): 98-104. doi:10.15918/j.tbit1001-0645.2018.042

Abstract(882) PDF(324)

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Aiming at the problem of low accuracy of crime distribution prediction and serious lack of historical crime data, a crime distribution prediction algorithm, TWcS, was proposed based on a transition probability matrix model, the historical crime data and integrating social environmental factors in the studied area. In this paper, the social environment factors including distance information, area information and population information were introduced as weights into the gradient descent strategy, and the transition probability matrix self-learning of TWcS algorithm was realized by gradient descent. The experimental results show that the performance of TWcS algorithm is superior to other prediction algorithms including TPML-WMA, LR, AR, Lasso regression algorithm, Bayesian algorithm, decision tree algorithm, etc.The MAE value of TWcS algorithm is only 33% of the average MAE value of the other algorithms.

Effect of P-Glycoprotein Inhibitor Verapamil on Pharmacokinetics of Loureirin A B C in Rats

LI Yu-juan, KANG Li-ting, GUO Jing-jing, WANG Shi-bo, LI Yong-zhi, WANG Jia-ping, GAO Jian-yi

2020, 40(1): 105-110. doi:10.15918/j.tbit1001-0645.2018.289

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To study how P-glycoprotein inhibitor verapamil affect pharmacokinetics of the active constituents Loureirin A, B and C in rat plasma after oral administration of Dragon's Blood,SD rats were randomly put into different group:control group and inhibitor group. A single dose of 5 g/kg of Dragon's Blood was orally administered to rats in control group, and rats in the inhibitor group were given verapamil (1 mg/kg) and Dragon' Blood (5 g/kg). Plasma samples were collected from the two groups in the same series of time. A HPLC-MS/MS method was used to determine the content of Loureirin A, B and C in rat plasma, and the plasma samples pharmacokinetic parameters were calculated. Comparing the area under curve (AUC0-t) of the rats in the inhibitor group with the control group, it increased by 109.4%,78.5%, 22.8%. And the peak concentration(C_max) of Loureirin A, B and C increased by 69.6%, 115.0%, and 42.1%. The time of Loureirin A and B reaching peak concentration (t_max) was prolonged, while thet_maxof Loureirin C was unchanged. All three biological half-life (t_0.5) decreased. It indicates that P-glycoprotein inhibitor can significantly change the plasma pharmacokinetic parameters of Loureirin A, B and C in rats. Loureirin A, B and C may be potential substrates of P-glycoprotein. This article provides basic data for the subsequent in-depth study of the relationship between P-glycoprotein and transportation of Dragon's Blood in the intestinal tract of rats.

Computer-Assisted Method for HPLC MS/MS Identification of Salmon Calcitonin Related Substances

ZHANG Jun, ZHANG Li-jun, HUANG Hai-wei, XIAO Sheng-yuan

2020, 40(1): 111-116. doi:10.15918/j.tbit1001-0645.2018.124

Abstract(1135) PDF(364)

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A computer assisted mass spectrometry method for salmon calcitonin related impurities was proposed. The theoretic fragments produced from the peptide bond fragmentation were calculated in accordance to the sequence of salmon calcitonin and were matched with the observed fragments. The observed mass spectrum of salmon calcitonin was assigned according to the match result. For impurity identification, the difference between the elementary compositions of the impurity and salmon calcitonin was calculated according to the high resolution pseudo-molecular ions. The theoretic fragments for each probable sequence were calculated and were matched with the observed mass spectrum. The matched result of the candidate sequence of the impurity was finally compared to the mass spectrum of salmon calcitonin to validate the structure. The procedures described were automated with ASP+HTML programming method. The sequences of seven impurities of a salmon calcitonin were identified with the method described, including 1 demoted impurity, 1 acetyl impurity, 4 aminophenol iteration impurities, and 1 isomer impurity.

Quickest Detection of a Change Point Related to a Step Function

CAI Liang, ZHANG Jia-jia

2020, 40(1): 117-120. doi:10.15918/j.tbit1001-0645.2018.216

Abstract(971) PDF(380)

Abstract:
A quickest detection method related to a step function was proposed. Firstly, a probability model was established, making the priori probability of a change point be switched with current states. Then a Bayesian quickest detection rule was established based on the optimal stopping theory. Finally, computer simulation was carried out, analyzing the probability of false alarm and the mean time of delay. Simulation results show the validity of the method. This method can introduce Bayesian quickest detection theory into more application area.

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