Table of Content

15 May 2019 Volume 32 Issue 5

  

The Construction of Fear Measuring Model Based on Virtual Reality

HAO Wenqiang,Mathilde Magontier

Electronic Science and Technology. 2019, 32(5):  1-4.  doi:10.16180/j.cnki.issn1007-7820.2019.05.001

Abstract ( 380 )   HTML ( 15 )   PDF (568KB) ( 82 )  

Figures and Tables | References | Related Articles | Metrics

The objective evaluation of the degree of fear plays an important role in mental health and professional ability assessment. Physiological and exercise data in the immersive training process can improve the interface design and increase the safety of virtual training. This article used the HTC Vive head-mounted VR system to realize the immersive VR experience. OpenVR open source software package was used to collect the position information of the controller and the head, which was combined the ECG signals and body acceleration collected by the Equivital belt EQ02 Lifemonitor to realize feature extraction of various signals. In this paper, the feature ranking method and support vector regression utilizing recursive feature elimination were used to select 10 features from 50 physiological and motion features. Finally, the multivariate polynomial regression based on self-tested fear values and features achieved a binary classification with an accuracy rate of 90%, which completed the classification of fear or non-fear of the subject.

Research on Ultrasonic 3D Target Recognition Based on Visual and Non-Visual Feature Fusion

SONG Shoupeng,SHEN Jingjing,LU Cuie

Electronic Science and Technology. 2019, 32(5):  5-6.  doi:10.16180/j.cnki.issn1007-7820.2019.05.002

Abstract ( 340 )   HTML ( 5 )   PDF (684KB) ( 65 )  

Figures and Tables | References | Related Articles | Metrics

Nowadays, the main method of ultrasonic 3D target recognition was using sensors to obtain one or more one-dimensional echo in space and getting the 3D information of the target body by signal processing to realize the 3D target recognition. These methods generally exist the problem of low recognition rate and poor robustness,which restrict the popularization and application of this technology. In this paper, an ultrasonic 3D target recognition method based on visual and non-visual feature fusion was proposed. This method combined the target body echo signal processing method with the synthetic aperture method, carried out data fusion of the extracted target information in the feature layer and realized the classification recognition by the BP neural network, by which the shortage of existing methods can be significantly improved. Experiments on three kinds of artificial targets showed that the method can significantly improve the 3D recognition rate of the defect which can be kept above 90%, and the robustness was also improved obviously.

Research on Reactive Power Optimization of Power Distribution Network Based on Improved Genetic Algorithm

CHEN Qiang,LIU Jin,YANG Haima,LIU Haishan,WEI Yu

Electronic Science and Technology. 2019, 32(5):  11-16.  doi:10.16180/j.cnki.issn1007-7820.2019.05.003

Abstract ( 456 )   HTML ( 13 )   PDF (652KB) ( 95 )  

Figures and Tables | References | Related Articles | Metrics

Effectively reducing the loss of distribution network active power has been an important issue in the safe and economic operation of distribution networks. In order to solve the problem of large network loss in local areas,an improved genetic algorithm was proposed for reactive power compensation optimization. While considering the topological structure of distribution network, an adaptive genetic operator was designed and an exponential fitness function was constructed to promote the convergence speed and precision of genetic algorithm. In this way, the global random search capability of genetic algorithm could be fully utilized. The results of optimizing a 16-node study showed that the active network loss of the distribution network dropped from 6.76% to 5.16%,and the voltage qualification rate increased from 70.61% to 92.86%,indicating both the global optimization accuracy and the voltage quality of the regional network were improved. In addition, it also proved that this improved genetic algorithm is feasible for reactive power optimization.

Optimization of Nonlinear Model Based on GA-BFO Combination Algorithm

LI Yapin,ZOU Dexuan,DUAN Na

Electronic Science and Technology. 2019, 32(5):  16-20.  doi:10.16180/j.cnki.issn1007-7820.2019.05.004

Abstract ( 336 )   HTML ( 4 )   PDF (824KB) ( 128 )  

Figures and Tables | References | Related Articles | Metrics

A combination of genetic algorithm and bacterial foraging optimization algorithm (GA-BFO) was presented to solve the nonlinear model optimization problems. Firstly, GA-BFO employed genetic algorithm to conduct global search and reduce the exploiting range of global optimum. Secondly, GA-BFO employed the bacterial foraging optimization algorithm to conduct local search in the reduced range. This combined search strategy could both enhance the convergence of GA-BFO and balance global search and local search. Three typical nonlinear function models including unimodal, multi-peak and complex multi-peak models were used to test the performance of the proposed algorithm. Experimental results showed that GA-BFO could achieve 30% and 50% precision improvements for GA and BFO respectively. Above results indicated the combined optimization approach had faster convergence speed and higher calculation precision, and it was more suitable for solving large-scale nonlinear problems with multiple optima.

Design and Implementation of Demodulator Componentization Based on Heterogeneous Signal Processing Platform

JI Lei,HUANG Yan,WANG Yang

Electronic Science and Technology. 2019, 32(5):  21-27.  doi:10.16180/j.cnki.issn1007-7820.2019.05.005

Abstract ( 288 )   HTML ( 7 )   PDF (965KB) ( 107 )  

Figures and Tables | References | Related Articles | Metrics

With the increasingly development of communication system, the corresponding demodulation algorithm also takes on a variety of forms. Combined with the application of the software radio technology, it is more and more important to research the efficient and fast way of modem development. Using the idea of software radio and the method of componentization, the study investigated the demodulator software refactoring technology based on component and designed the model of modem software refactoring to solve the problem of refactoring and form the modem development component library. Based on the developed component library and demodulator software reconstruction model and aiming at the 16QAM continuous signal demodulation, the proposed paper designed and implemented integrated development based on new components to form new functions.

Research on Information Distribution Coefficient of Federated Filter Based on Trade-off Factor

MA Xingyuan,LI Zhi,WANG Yongjun

Electronic Science and Technology. 2019, 32(5):  28-31.  doi:10.16180/j.cnki.issn1007-7820.2019.05.006

Abstract ( 267 )   HTML ( 3 )   PDF (631KB) ( 51 )  

Figures and Tables | References | Related Articles | Metrics

The fusion algorithm of integrated navigation system generally adopted a federated filtering algorithm with fast running speed, strong real-time performance, and low computational complexity. For the current information distribution principle in the algorithm couldn't take into account the defects of system filtering accuracy and fault tolerance at the same time, an adaptive information distribution method based on the balancing factor was adopted. Through the error covariance and measurement noise variance of each subsystem, the information distribution coefficient that could improve the filtering accuracy and fault tolerance of the system was calculated. The failure probability of each subsystem was normalized to obtain the balancing factor of the subsystem. Under the balancing factor, the proportion of the above two information distribution coefficients was adjusted adaptively, so as to achieve both the accuracy and fault tolerance of the system. Simulation results showed that the proposed method successfully reduced the fusion error of the system and guaranteed the performance and fusion accuracy of the system.

Marine Mammal Sound Recognition Based on Feature Fusion

ZHONG Mingtuo,CAI Wenyu

Electronic Science and Technology. 2019, 32(5):  32-37.  doi:10.16180/j.cnki.issn1007-7820.2019.05.007

Abstract ( 422 )   HTML ( 8 )   PDF (856KB) ( 84 )  

Figures and Tables | References | Related Articles | Metrics

In order to improve the recognition rate and robustness of marine mammal sound recognition algorithm, this paper proposed a method for sound recognition by using the fusion of MFCC,LFCC and temporal features as feature parameters. This method enhanced the characterization ability of different frequency bands by fusing different cepstral coefficients and described the sound information more comprehensively by integrating the temporal features. To be specific, each continuous marine mammal recording was first preprocessed into individual syllables. Then, cepstral coefficients and temporal features were calculated from each syllable. Finally, the fused features were identified by support vector machine. Unlike traditional algorithms which only recognized few mammals, this method was tested in a sample database containing 61 marine mammal sounds. The test results showed that the proposed algorithm improved the recognition rate by 5.5% compared with the traditional MFCC, and had a better recognition performance in the low SNR environment.

Improved CFSFDP Algorithm Based on Spark Framework

LI Qi,ZHANG Xin,ZHANG Pingkang,ZHANG Hang

Electronic Science and Technology. 2019, 32(5):  38-44.  doi:10.16180/j.cnki.issn1007-7820.2019.05.008

Abstract ( 314 )   HTML ( 2 )   PDF (815KB) ( 59 )  

Figures and Tables | References | Related Articles | Metrics

CFSFDP algorithm based on density is a clustering algorithm. In order to rid dependency on artificial selection of decision graph, this paper used the idea of slope to calculate the demarcation point of clustering center points and un-clustering center points. This improvement eliminated personal equation and realized auto-calculation of center points. Parallel processing for the algorithm was conducted through the Spark framework. The experiments showed that this algorithm was applicable to clustering analysis of mass data, since it improved efficiency by eliminating personal equation and displayed great speed up ratio and extendibility after paralleling.

Video Retrieval Algorithm Based on Multiple Feature Fusion

HOU Yanming,LI Feifei,CHEN Qiu

Electronic Science and Technology. 2019, 32(5):  44-49.  doi:10.16180/j.cnki.issn1007-7820.2019.05.009

Abstract ( 465 )   HTML ( 6 )   PDF (810KB) ( 64 )  

Figures and Tables | References | Related Articles | Metrics

Due to the exponential growth of video data on the World Wide Web, efficient and fast video retrieval algorithm has attracted a lot of attentions. Because the traditional video image features, such as color histogram and scale invariant feature transform could not obtain promising results on the retrieval speed and detection precision in video copy detection, a video retrieval algorithm using multiple feature fusion was proposed in this paper. Using the temporal and spatial characteristics of the two frames before and after, the time alignment algorithm based on sliding window was applied to reduce the retrieval range and improve retrieval speed. In order to improve the detection precision, this algorithm performed the global feature, the color correlation graph, and the local feature extraction of the SIFT, and then combined the advantages of both global and local features. Experimental results showed that the proposed method could achieve better performance.

Indoor Location Algorithm Based on WiFi-geomagnetism

ZHANG Yurun,WU Fei,MAO Wankui

Electronic Science and Technology. 2019, 32(5):  49-54.  doi:10.16180/j.cnki.issn1007-7820.2019.05.010

Abstract ( 515 )   HTML ( 6 )   PDF (724KB) ( 145 )  

Figures and Tables | References | Related Articles | Metrics

For the problem that the single fingerprint location results were large errors and drifting in indoor environment, an improved algorithm of geomagnetic and WiFi fingerprint system was proposed. First, the larger matching area was divided into smaller sub-regions with more distinctive features by K-means clustering method. In the online phase, Wi-Fi fingerprints were used to coarsely locate small areas, and then a further fine-match positioning was performed through the geomagnetic fingerprint positioning system. Experimental results showed that the integration of algorithm reduced the searching area, and greatly reduced the problem of mis-matching. In the experiment, the average positioning error was only 2.17 m, and the maximum positioning error was 3.61 m. Compared with the single fingerprint positioning system, the performance was greatly improved, which proved that the positioning method had certain feasibility and advancement.

Link Prediction on Bank Transaction Network

MA Qingqing,YAN Guanghui,WANG Yafei,WU Yu

Electronic Science and Technology. 2019, 32(5):  55-62.  doi:10.16180/j.cnki.issn1007-7820.2019.05.011

Abstract ( 334 )   HTML ( 2 )   PDF (901KB) ( 36 )  

Figures and Tables | References | Related Articles | Metrics

Based on the dynamic changes in bank transactions and the characteristics of timeliness and repeatability, the basic topology statistical properties and clustering structure of the bank's network were studied, and obtained the transaction network satisfied with the small-world and scale-free characteristics.Based on the deficiency of existing link prediction algorithms in dynamic network prediction, a new dynamic link algorithm was proposed to predict bank customer transactions. Then, based on the algorithm mentioned above, two characteristics, the three predictive algorithms combined with the random algorithm were compared. These three algorithms were applied to the three types of real data sets with dynamic transaction characteristics for experimental verification. The results showed that the prediction accuracy of the algorithm was about 75%. Finally, comparing the algorithm with the classical prediction algorithm, the proposed algorithm improved the prediction by 5% to 10%.

Research on Improved Dual Switch Table Direct Power Control Strategy

HU Huizhi,JI Peirong,ZHANG Yunning,WU Zhang’ao

Electronic Science and Technology. 2019, 32(5):  62-67.  doi:10.16180/j.cnki.issn1007-7820.2019.05.012

Abstract ( 256 )   HTML ( 4 )   PDF (1014KB) ( 104 )  

Figures and Tables | References | Related Articles | Metrics

In order to effectively solve the problem that the dynamic sector direct power control strategy of the voltage type three-phase PWM rectifier has a large difference between the input power and the specified power, a new double switch DPC regulation mechanism was studied in this paper. By introducing a three state hysteresis comparator, a new power amplitude control function was formed. The switch table and the switch vector were selected by the system according to the power amplitude control function and the output value of the three state hysteresis comparator, so that the rectifier could choose the appropriate switch vector based on the real time power difference. Finally, compared with the MATLAB/Simulink simulation of the traditional dynamic sector DPC strategy, the double switch DPC strategy could effectively improve the DC side output voltage characteristics and reduced the reactive power ripple.

Design of Transplant Test Program Set Based on ATML

LIU Ming,GAO Haiying,ZHANG Weikun

Electronic Science and Technology. 2019, 32(5):  68-74.  doi:10.16180/j.cnki.issn1007-7820.2019.05.013

Abstract ( 288 )   HTML ( 2 )   PDF (1331KB) ( 55 )  

Figures and Tables | References | Related Articles | Metrics

The traditional automatic test system focused on the instrument development, and the test program heavily relied on the specific instrument, which resulted in s a series of problems including inability to interact with test information, non-portability of test programs, and poor system interoperability. In view of the above problems, a transplant TPS design method based on ATML was proposed. The ATML standard was used to uniformly describe the information of test resources. By defining multiple XML Schemas, test information was stored in a consistent format.The proposed method separated and kept the TPS-related information independent from each other, and defined the signals by using the STD standard.This method described the test requirements and instrument capabilities in a signal way, and solved the cross-platform migration problem of TPS in the past, which effectively improved the interoperability of the system.

Study on Output Characteristics of Topologies of Photovoltaic Arrays under Local Shadows

WANG Guixin,ZHENG Qi

Electronic Science and Technology. 2019, 32(5):  75-80.  doi:10.16180/j.cnki.issn1007-7820.2019.05.014

Abstract ( 406 )   HTML ( 5 )   PDF (902KB) ( 44 )  

Figures and Tables | References | Related Articles | Metrics

Under the condition of partial shadow, solar panels of different topologies have different power output characteristics, which directly affect the output efficiency of the entire photovoltaic array. Based on the mathematical model of photovoltaic array under partial shadow conditions, the simulation models of 4*4 PV arrays of SP, TCT and BL were designed and built. In each case of partial shadows, the maximum output power of the three topologies was simulated and the simulation data was analyzed. The research showed that the maximum output power and topology of the PV array exhibited certain regularity in different shadow movement modes, which had certain reference significance for the design of photovoltaic panel topography.

Research of Sun Ray Tracing Sensors Based on Rotating Cylinder with Solar Cell

YAN Fagao,CHEN Hong

Electronic Science and Technology. 2019, 32(5):  81-85.  doi:10.16180/j.cnki.issn1007-7820.2019.05.015

Abstract ( 357 )   HTML ( 2 )   PDF (610KB) ( 90 )  

Figures and Tables | References | Related Articles | Metrics

As for the solar ray angle measurements, the switching measurement method has disadvantages including poor precision and a large number of photosensitive elements while analog measurement have the deficient of small measurement range, inconsistent photosensor characteristics. To solve these problems, a method of rotating cylinder with PV cell was proposed in the study. The cylindrical surface has a special groove that is axially and inclined. After the cylinder was rotated, the azimuth and elevation angles were calculated by measuring the rotation angle of the maximum current at the bottom of the photovoltaic cell. Parabolic interpolation was utilized to increase the accuracy of the rotation angle at the maximum point of quadratic curve. Experimental test showed that the proposed method could achieve better measurement accuracy.

The Design of Unmanned Aerial Vehicle Power Patrol base on Oblique Photography Technology

XI Laiying,ZHAO Henan,WANG Songbo,ZHANG Xiaochao,MA Mingyang

Electronic Science and Technology. 2019, 32(5):  85-88.  doi:10.16180/j.cnki.issn1007-7820.2019.05.016

Abstract ( 445 )   HTML ( 10 )   PDF (531KB) ( 124 )  

Figures and Tables | References | Related Articles | Metrics

With the development of economy and technology, the length of power transmission lines was also growing. In order to ensured the safe operation of the power system, power inspection work was very important. This paper designed a drone power inspection system based on tilt photography. The UAV was equipped with a tilt camera to collected the image information of the transmission line and peripheral devices, and then the image data information was transmitted to the ground station through the wireless transmission of the drone for data analysis, and 3D model construction, thereby completing the troubleshooting of the electric line fault. The elimination of safety hazards ensured the safety of power transmission. Using this tilt photography technology can effectively improved the accuracy of power inspection judgment.

Research on Signaling Data Acquisition Technology Based on Big Data Platform

WU Liang

Electronic Science and Technology. 2019, 32(5):  89-92.  doi:10.16180/j.cnki.issn1007-7820.2019.05.017

Abstract ( 439 )   HTML ( 9 )   PDF (522KB) ( 157 )  

Figures and Tables | References | Related Articles | Metrics

Aiming at the problems of mass data acquisition requirements and storage difficulties faced by existing signaling data acquisition technology, this paper studied signaling data acquisition technology based on big data platform. Firstly, this paper designed the architecture of signaling monitoring system based on big data platform and analyses the solution of big data of signaling monitoring system. In addition, further divides the signaling data acquisition architecture based on big data platform, which mainly included three parts: big data signaling acquisition architecture, big data signaling acquisition mode and big data signaling acquisition content. The architecture of signaling data acquisition technology for large data platform designed in this paper could be effectively applied to massive signaling data acquisition scenarios and provide tools for large-scale distributed signaling data acquisition.

Particle Swarm Optimization Surface Defect Recognition Algorithm Based on Radial Basis Neural Network

LAN Jiman

Electronic Science and Technology. 2019, 32(5):  92-95.  doi:10.16180/j.cnki.issn1007-7820.2019.05.018

Abstract ( 299 )   HTML ( 7 )   PDF (514KB) ( 99 )  

Figures and Tables | References | Related Articles | Metrics

Surface defect recognition of metal parts is a hot topic in the field of pattern recognition. Efficient and reliable surface defect identification method can effectively improve production efficiency and maintain production safety. To solve this problem, a surface defect recognition algorithm based on radial basis function (RBF) neural network and particle swarm optimization (PSO) algorithm was proposed. The weight parameters of RBF neural network were determined and improved by PSO algorithm, and the inertia weight of PSO algorithm was processed linearly. The local oscillation of the optimal solution in PSO algorithm was effectively eliminated. The RBF-PSO surface defect recognition algorithm was trained by network aiming at several common defects on the surface of metal parts, and the corresponding actual test was carried out. The recognition accuracy of RBF-PSO surface recognition algorithm proposed in this paper could reach 96%. Compared with traditional neural network algorithm, it had obvious performance improvement.