bob手机在线登陆学报自然版

cover

2022, 42(11)

Abstract(99) PDF(21)

Abstract:

2022, 42(11): 1-2.

Abstract(66) HTML(28) PDF(21)

Abstract:

Logic Analysis on the Establishment Progress of Genetic Central Dogma in Prokaryote

ZHAO Dongxu, FENG Yongjun, WANG Feng, ZHANG Jinfeng

2022, 42(11): 1105-1126. doi:10.15918/j.tbit1001-0645.2021.363

Abstract(171) HTML(91) PDF(34)

Abstract:
It’s one valuable work to deduce the establishment process of genetic information transmission rule in prokaryote cell from early life origin. According to the physical and chemical condition and evolution existed possibly in early stage after Earth birth, the chemical inevitability of forming small biological molecular and the logical inevitability of forming biomacromolecule and showing clue of life were proposed in this paper. Firstly, based the proposal views of keeping relative balance among those original chemical reactions, the reasons and significance were analyzed for the relative stabilization of biomacromolecule structure, little harm to involved system and its congeries cause of formation. And the forming mechanism of vesicula (structure of cell-like) and its significance were also elucidated. Then, based on template reaction, an inter-chose (Model of Soft-Hard Butt-joint) between the “soft template” (mRNA) and “hard synthesizing structure” (ribosome) was presented in synthesizing protein and the reason was also proposed for many sorts of RNA introduced in protein synthesis. Subsequently a mode of “weak genetic relationship” formed from long time evolution in vesicular was presented. And then, several important scientific topics on the origin of life and evolution were analyzed from the Logic angle, including early or late of DNA and RNA formation, early or late of protein and nucleic acid formation and the relation of Virus evolution and Cell evolution etc. Finally, the logic of life origin and redefinition of life phenomenon etc. were discussed.

Study on Influence of Liner’s Structure Parameters on Effects of JPC Operating Underwater

CHEN Xing, LU Yonggang, CHENG Xiangzhen

2022, 42(11): 1127-1135. doi:10.15918/j.tbit1001-0645.2021.346

Abstract(166) HTML(70) PDF(20)

Abstract:
Influences of the ace-cone liner structural parameters (wall thickness, radius of curvature and cone angle) on the underwater action effect of jetting projectile charge(JPC) were studied using the LS-DYNA finite element software. The results show that the wall thickness had a great influence on the initial velocity of JPC into water, the arc radius and cone angle controlled the axial tensile and radial shrinkage of JPC, respectively, affecting the JPC morphology and mass distribution. Increasing liner thickness, and reducing arc radius and cone angle could enhance the underwater effect of JPC. The formation, velocity attenuation and damage efficiency of JPC was comprehensively analyzed, and structural parameters of the liner with better underwater operating effect of JPC were obtained, wall thickness ranged from 0.036D_kto 0.055D_k, the radius of curvature ranged from 0.30D_kto 0.45D_k, and cone angle ranged from 120° to 130°. The experiment results show that water layer thickness has a strong attenuation effect on the JPC kinetic energy. When the water layer thickness is 60 cm, JPC can penetrate the target with an average diameter of 0.54D_k.

Dynamic Performance of Vibration Isolating System with Variable Rod Length X-Shaped Structure

ZHU Dongmei, LIU Wei, LIU Haiping, LU Guangyang

2022, 42(11): 1136-1143. doi:10.15918/j.tbit1001-0645.2021.345

Abstract(144) HTML(62) PDF(19)

Abstract:
To solve the differ problem of the vibration isolation effect of the resonant section and high frequency section in traditional three parameter vibration isolator, a model of variable rod length X-shaped structure vibration isolator with geometric nonlinear characteristics was proposed. Firstly, a dynamic response analytical model was established based on the harmonic balance method. And then, comparing with the time-domain numerical solution and the simulation data got from the multi-body dynamics software ADAMS, the analytical solution was proved accurately. On the basis, the equivalent stiffness coefficient, equivalent damping coefficient, force transfer rate, dynamic force transmitted to the foundation under multi frequency steady-state excitation and the influence of key design parameters on the transmission characteristics of the vibration isolation system were analyzed finally. The results show that the equivalent stiffness and equivalent damping of the vibration isolation system with variable rod length X-shaped structure can change monotonically. The resonant peak value of variable rod length X-shaped structure vibration isolation system decreases significantly, the frequency does not change, and the corresponding time-domain stress response also presents the same variation characteristics.

D Distance Classifier for HRRP Multi-Class Recognition

YAO Lu, HAN Lei, YANG Lei, CHAI Xiaofei

2022, 42(11): 1144-1149. doi:10.15918/j.tbit1001-0645.2021.318

Abstract(134) HTML(64) PDF(12)

Abstract:
In the field of Radar Automatic Target Recognition (RATR), in order to ensure that the target recognition algorithm based on High-Resolution Range Profile (HRRP) still has excellent recognition performance when performing small-sample and multi-class target recognition , it is necessary to propose a recognition algorithm with excellent generalization performance and low computational complexity. Use the ratio to calculate a ratio distance between two vectors, and apply the ratio distance to a distance classifier, which is called D distance classifier. Then, the D distance classifier is compared with some other RATR statistical models using the measured data of eight ground targets, and its recognition accuracy in small samples and multi-class targets is analyzed respectively. The final result verifies that the D distance classifier still has excellent generalization performance and low computational complexity when recognition is performed with small-sample and multi-class target.

Design and Experimental Research of Wall-Climbing Robot with Reverse Thrust Adsorption

FAN Ming, LIANG Peng, GAO Xueshan, ZHANG Qingfang, LI Mingkang

2022, 42(11): 1150-1158. doi:10.15918/j.tbit1001-0645.2021.352

Abstract(114) HTML(60) PDF(14)

Abstract:
A robot design approach was proposed that uses the reverse thrust of the dual-rotor propeller as the forward driving force and the wall adsorption force to achieve steady, rapid, and efficient robot movement on various contacting walls. The structure and the power system of the wall-climbing robot were designed. The dynamic performance of the robot was ideal when the inclination angle of the rotor was 60°, as determined by the traction force experiment of the robot in the horizontal state, according to the statics of the robot in different motion modes. The motion impact of a single-degree change in the rotor inclination angle of the robot was better than that of a doubling change in the rotor inclination angle, according to an experimental test in the actual operation process. The aerodynamic effectiveness of the propeller was considerably lowered due to the intricacy of the construction, according to experimental measurements of the robot’s adsorption force on horizontal and vertical walls. Finally, the stable adsorption ability of the robot on small slopes and vertical walls was verified by experiments.

Bolt Detection and Positioning System Based on YOLOv5s-T and RGB-D Camera

WANG Xiangzhou, YANG Minwei, ZHENG Shuhua, MEI Yunpeng

2022, 42(11): 1159-1166. doi:10.15918/j.tbit1001-0645.2021.339

Abstract(199) HTML(69) PDF(21)

Abstract:
Replacing manual works with robots is a feasible solution for solving the safety problem of fastening bolts on the angle steel tower. In order to meet the operating requirements of the angle steel tower bolt fastening robot, a detecting and positioning system was proposed based on neural network and RGB-D camera for the main bolts of the angle steel tower. Applying the lightweight YOLOv5s-T network to the image of the Intel® RealSense™ depth camera D435i, the system was used to realize real-time detection, three-dimensional positioning and reordering the main bolts of the angle steel tower. Experiments show that YOLOv5s-T can improve the inference speed of the original algorithm by about 31% without reducing mAP (mean average precision) basically. Using three-dimensional coordinates measured by the RGB-D camera to calculate the distance between adjacent bolts, the average distance error is less than 1 mm. When the RGB-D camera is facing the bolt group template, the correct sorting rate of the template is above 95%. It can guide the end-effector of the 6-dof manipulator toward the target bolt within a short time.

Identification of Medical Service Quality Factors Based on COA-BTM Model

GAO Huiying, GONG Mengqiu, YU Sijia

2022, 42(11): 1167-1174. doi:10.15918/j.tbit1001-0645.2021.350

Abstract(137) HTML(63) PDF(10)

Abstract:
Aiming at short text and sparse semantics of online medical reviews, an improved biterm topic model (BTM) topic mining model was proposed based on word co-occurrence analysis (COA) for online medical reviews. Due to the lack of semantic relevance consideration when BTM topic model was used to select word pairs in short texts, a word co-occurrence analysis method was introduced to calculate the semantic relevance, and thresholds were set to screen the participating word pairs for topic mining. Comparing with the traditional BTM and LDA topic models in the topic consistency TC value and JS divergence, the effect of improved COA-BTM was put up in medical review mining. The experiment results show that the improved COA-BTM model can provide a better result in topic consistency and topic quality, proving its effectiveness in the field of online medical review mining. Based on the mining results of this algorithm and SERVQUAL model, the medical service quality factors can be identified more comprehensively.

A Global-Local Dual Branch Network for Congested Crowd Counting

DI Huijun, SONG Lingxiao, YU Xiao, WANG Weiran

2022, 42(11): 1175-1183. doi:10.15918/j.tbit1001-0645.2021.311

Abstract(142) HTML(57) PDF(19)

Abstract:
Convolutional neural network based crowd counting methods have promoted a significant improvement in the accuracy of crowd counting. However, for congested crowd, huge scale variations of crowd heads and complex scenes still hinder the accuracy of crowd counting. In order to overcome this problem a global-local dual branch network was proposed. The local branch was arranged with the proposed scale-aware feature extraction modules to model the scale changes of the heads in congested crowds. The global branch was arranged with a localization-aware attention module to enhance the network's ability to discriminate between the crowd and the background objects. Then the extracted local features and global features were sent to the feature fusion branch to produce a crowd density map. The proposed method was evaluated on three commonly-used crowd counting datasets and one remote sensing object counting dataset. The quantitative and qualitative results show the effectiveness of the proposed method.

Multi-Stage State of Health Estimation Based on Charging Phase for Lithium-Ion Battery

WEI Zhongbao, RUAN Haokai, HE Hongwen

2022, 42(11): 1184-1190. doi:10.15918/j.tbit1001-0645.2021.336

Abstract(147) HTML(65) PDF(21)

Abstract:
State of health estimation of lithium-ion battery is the basis of lithium-ion battery life assessment and health management. A practical multi-stage state of health estimation method was proposed to deal with different charging stages, including the scene of serious lack of charging data. According to the voltage, the constant current-constant voltage charging process was divided into three stages and their target state of health estimation methods were proposed respectively. Especially for the constant current-constant voltage transition stage, being a lack of constant current data and constant voltage data heavily, the relationship between raw voltage/current data and battery state of health was directly established taking the strong data mining capability of convolutional neural network. The proposed method was evaluated by long-term aging experiments on lithium-ion battery. The results show that this method possesses the advantages of high estimation accuracy, strong ability to deal with serious data loss, and strong robustness to battery inconsistency.

A Recommendation System with Fusion Relation Extraction

GAO Chunxiao, LU Shishuai, LIU Qiongxin, SONG Xiang

2022, 42(11): 1191-1199. doi:10.15918/j.tbit1001-0645.2021.351

Abstract(132) HTML(57) PDF(10)

Abstract:
Aiming at the problem of insufficient knowledge utilization in the existing content-based recommendation methods, a recommendation system based on fusion relation extraction was proposed in this paper. Using word2vec model to encode object knowledge, using supplementary template features to excavate the object knowledge in a deeper level, an enhanced knowledge graph was constructed. Moreover the enhanced entity features were obtained, being combined with text features and basic entity features to construct object features. Experimental results show that the recommendation effect based on fusion relation extraction is better than that of the similar models, and the improvement of each part is effective.

Fast FPGA Implementation of Solving Moore-Penrose Inverse Matrices in ESPRIT Algorithm

WANG Weijiang, ZHANG Tuofeng, JIANG Rongkun, LI Zeying, WANG Xiaohua, TAN Zhixin, XUE Chengbo

2022, 42(11): 1200-1206. doi:10.15918/j.tbit1001-0645.2021.320

Abstract(232) HTML(162) PDF(30)

Abstract:
The estimating signal parameter via rotational invariance techniques (ESPRIT) algorithm involves solving the inverse matrix of the signal subspace matrix. To overcome the shortcomings of commonly used algorithms, such as high computational complexity and poor real-time performance, a generalized inverse formula-based method was proposed to solve the signal subspace matrix. Firstly, a generalized inverse matrix solution system was implemented on FPGA platform, composed with complex matrix multiplication sub-module, matrix LU decomposition sub-module, and lower triangular matrix inversion sub-module. The calculation time with this system to solve the generalized inverse matrix is about 2.18ms, reducing by 7.2 times compared with the same matrix on MATLAB, average time 15.7ms. And then, a subsequent simulation of the results was completed on MATLAB, and the error of the final angle obtained by ESPRIT algorithm was analyzed. The average estimation error of the final angle is about 0.04 °. The results demonstrate that the proposed method can effectively reduce the operation time, while improving the estimation accuracy.

Sea Target Detection Algorithm for Airborne Radar Based on Map Information

WANG Changjie, GUO Shuai, LIU Quanhua

2022, 42(11): 1207-1212. doi:10.15918/j.tbit1001-0645.2021.342

Abstract(121) HTML(56) PDF(22)

Abstract:
The airborne radar may affected by sea clutter or ground clutter when detecting targets on the sea surface. Due to the strong ground clutter, a lot of land targets will be detected, severely degrading the radar’s detection performance of sea surface target. In this paper, a sea target detection algorithm for airborne radar based on map information is proposed. The proposed algorithm first calculate the longitude and latitude information of the area, which the radar antenna beam illuminates, by using the carrier aircraft attitude data provided by inertial navigation system. Then search the sea-land information in the map data according to the longitude and latitude to realize the sea-land segmentation and realize the sea land detection. The proposed method is experimentally validated using real X-band radar detection experiment data, indicating that this method can recognize the target’s sea-land position exactly and help select or eliminate targets as demanded, significantly improve the radar’s detection performance.

Experiment and Optimization Method for Coal Dust Restrain Reagent

ZHAO Zhenbao, YAN Jie, XIE Jun, SHU Xinqian, HAO Yongjiang

2022, 42(11): 1213-1218. doi:10.15918/j.tbit1001-0645.2022.075

Abstract(94) HTML(51) PDF(9)

Abstract:
In this paper, an optimization design was carried out based on Box-Behnken method for the formula of dust restrain reagent. Picking APG-10, SDBS and APAM as response variables, taking sedimentation time and transmission rate as response values, a regression model was established to get an optimization compound proportion of surfactant and additive for dust restrain reagent modulation. Experiment results show that, when the correlation coefficientR₂is 0.9082 in the regression model of reagent and sedimentation time, theFvalue of the equation is 7.69 and the probability is 0.0068<0.01. And when the correlation coefficientR₂is 0.9190 in the regression model of reagent and transmission rate, theFvalue of the equation is 8.83 and the probability is 0.0045<0.01. The conclusion is that, the best compounding concentration is 0.17% APG-10, 0.49% SDBS and 0.05% APAM, the predicted settlement time is 34.9025 s, and the predicted transmittance is 93.7259%, reaching the optimum state of wetting and agglomeration.

Submission System

Author Related

Writing Norms

Links

2022 Vol. 42, No. 11

Archive