bob手机在线登陆学报自然版

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2022, 42(3)

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2022, 42(3): 1-2.

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Numerical Simulation Method of Impact/Deflagration Behavior by Reactive Materials Projectile

XIAO Jianguang, XIE Zhiyuan, WANG Yanxin, WANG Zhao, NIE Zhengyuan

2022, 42(3): 223-232. doi:10.15918/j.tbit1001-0645.2021.079

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Aiming at the quantity research on the impact/deflagration behavior of reactive materials, the user subroutines of equation of state (EOS), ignition model and overall reaction ratio were edited and compiled based on the secondary development function of AUTODYN codes, and then the numerical simulation on impact/deflagration behavior by reactive materials projectile during high speed penetration was conducted. Based on the numerical simulation of high-speed collision of Al/PTFE reactive materials projectile with 2024 aluminum spacer plate, the morphologic evolution of Al/PTFE reactive materials fragments was obtained, and the variation of reaction ratio, pressure and temperature of reactive materials particle versus time during the impact event were extracted, so that the quantity research on the impact/deflagration behavior of reactive materials was achieved. The simulation results show that the trend of overall reaction ratio calculated with time is well consistent with the deflagration flame in experiments, and the temperature is compatible with previous research, implying that the proposed simulation method can reproduce the impact and energy release process by Al/PTFE reactive materials projectile at a high level.

Transformer Fault Judgment Method Based on Acoustic Signal Feature Fusion

YANG Guanghui, YANG Guangcan, LI Hongrui

2022, 42(3): 233-241. doi:10.15918/j.tbit1001-0645.2021.081

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Aiming at the problems of various transformer faults and insufficient fault samples, a transformer fault judgment method based on acoustic signal feature fusion was proposed. A large number of normal sound signals were extracted from the normal transformer to find out the characteristics of the transformer. In different spatial domains such as time domain and frequency domain, feature extraction was carried out on the collected normal transformer acoustic signals, and the feature set that was most consistent with the transformer acoustic signals was found by the maximum-correlating-minimum-redundancy algorithm, and then the weighted entropy principal component method was used to obtain the fusion index for the feature set. The fusion index was compared with the normal signal and fault simulation signal of 220 kV and 110 kV transformer of a substation under the condition of noise interference. The results show that the fusion index obtained by this method can distinguish clearly between normal and simulation fault, and has good recognition effect, which verifies the feasibility of this method.

Study on the Splitting Tensile Failure Characteristics of Concrete Based on the Particle Flow Method

WANG Yiyang, REN Huilan, SONG Shuizhou, NING Jianguo

2022, 42(3): 242-250. doi:10.15918/j.tbit1001-0645.2021.048

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Based on the two-dimensional particle flow program, a two-dimensional concrete mesoscopic model was established including cement mortar, irregular polygonal aggregate and the interface (ITZ) between cement mortar and aggregate. The crack evolution and failure mechanism of fracture concrete was investigated using the calibrated flat joint model parameters. The simulation results indicate that the meso-mechanism of the macroscopic failure is induced by the crack propagation and evolution in the cement mortar, aggregate and ITZ. In addition, the distribution of random aggregates has an impact on the peak stress and failure mode of concrete at a certain level. The crack in the Brazilian disc specimen is generated at the loading end, and expands to the center of the specimen as the load increases. Finally, a split tensile failure mode appears in the concrete specimen. Moreover, as the loading speed increases, a large number of fragments in the concrete specimen are generated due to the interaction between the main cracks along the loading direction and other secondary cracks. The statistical results of cracks indicate that tensile cracks dominate the split failure of concrete specimens at the mesoscopic level. At the same time, a few shear cracks are mainly generated near the aggregate at the loading end of the specimen.

Analysis of Thermal Effect on Proportional Solenoid Valve Used in Vehicles Based on Hybrid Modeling

REN Yanfei, XI Junqiang, CHEN Huiyan, MA Kaiwen

2022, 42(3): 251-260. doi:10.15918/j.tbit1001-0645.2021.057

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In order to tackle the problem that existing methods cannot accurately analyze and evaluate the influence of thermal effects on dynamic performance of proportional solenoid valves used in vehicles, a hybrid modeling analysis method based on multi-physics finite element method and system dynamics was proposed. Firstly, taking ambient temperature into account, based on heating and heat dissipation characteristics of electromagnets, a finite element model including electromagnetism, temperature, and structure was established to obtain accurate temperature field distribution and the change law of key parameters; then, electromagnet data and system dynamic equations were combined to establish a system dynamic model with temperature field considered. Finally, two types of dynamic characteristics were analyzed through experiments when there was no temperature rise and when there was a temperature rise. The research results show that: parameter changes caused by temperature field have a great influence on dynamic characteristics. When supply voltage is 8 V, the start-up time of solenoid valve is delayed by 2 ms, and the pressure building time is delayed by 3 ms. It is verified by experiments that this method can analyze the influence of thermal effects on the dynamic performance of solenoid valves.

A Collision Warning Strategy Considering Environmental Complexity for Dangerous Goods Transportation Vehicles

GAO Li, DAI Yu, ZHAO Yanan, WANG Xiancai

2022, 42(3): 261-270. doi:10.15918/j.tbit1001-0645.2021.146

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In order to solve the problem of higher false alarm rate in the traditional vehicle collision warning system, a concept of environmental complexity was introduced into the collision warning strategy to suit the requirements of dangerous goods transport vehicles. Analyzing the influence factors of static complexity and dynamic complexity, a calculation method of risk identification index and a specific framework of early warning strategy were proposed. On this basis, combined with the domestic open truck accident reports and the environmental information of the real transportation section, a quantitative model of environmental complexity was established taking the advantage of the neural network in nonlinear relationship fitting ability. Based on real vehicle data collected from the dangerous goods transportation vehicles with common warning system in real road section, the strategy verification test was carried out. The results show that, compared with the common collision warning system on the market, the false alarm rate of the proposed warning strategy can be reduced from 41% to 8%. The classification mechanism can better adapt to the driver's judgment of danger and braking habits, and improve the safety of dangerous goods transport vehicles.

SOC Estimation of Six-Wheeled-Legged Robot Battery Based on FFRLS-AEKF

WANG Shoukun, LU Shuai, CHEN Zhihua, LIU Daohe, YUE Wei

2022, 42(3): 271-278. doi:10.15918/j.tbit1001-0645.2020.240

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In view of the problems of the six wheeled-legged robot, such as low estimation accuracy of state of charge (SOC) and low accuracy of battery model, an estimation algorithm based on forgetting factor-based recursive least squares (FFRLS) and adaptive extended Kalman filter (AEKF) was proposed. Firstly, the parameters of the power battery equivalent model were identified based on FFRLS algorithm. Secondly, AEKF was used to estimate SOC online and provide accurate open circuit voltage for parameter identification. Finally, taking lithium battery pack of the robot as an example, a validating experiment was carried out under dynamic stress test (DST) conditions. The results show that the algorithm can accurately estimate the SOC of power battery, and the relative error of SOC estimation is less than 2.5%.

Research on Real Time Detection and Modification Method of Enameled Wire Winding Defects

JIA Jiangming, LI Chuang, LI Zhen, TONG Junhua, ZHOU Shuiqin, WANG Yibo

2022, 42(3): 279-288. doi:10.15918/j.tbit1001-0645.2021.221

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In order to improve the quality of coil winding and detect the winding defects such as gap errors and overlap errors in high-precision winding operations, a method was proposed for real-time detection and modification of different winding states in the winding process. Considering the winding characteristics of the coil, a real-time detection algorithm was proposed for winding defects of the enameled wire, and a corresponding visual detection system and control system were designed for the winding equipment. Based on the 1×3 template, an extraction algorithm was developed for the contour point extraction of the preprocessed effect images. Based on the winding state detection of the contour point fitting, a modification method was provided to realize the real-time detection of the coil winding state, and to modify the wrong winding state according to the results of visual real-time detection. The verification results of visual detection stability test, system accuracy rate test and orthogonal test show that the proposed method can obviously increase the tightness of the coil winding, and effectively improve the production efficiency and quality of the coil winding products.

Fault Diagnosis of Liquid Rocket Engine Based on Hierarchical Bayesian Network Variational Inference

LIU Jiufu, DING Xiaobin, WANG Hengyu, WANG Biao, LIU Haiyang, YANG Zhong, WANG Zhisheng

2022, 42(3): 289-296. doi:10.15918/j.tbit1001-0645.2020.143

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In order to improve classification accuracy of traditional multinomial-Dirichlet model in sparse data scenario, a hierarchical Bayesian network parameter estimation method was proposed based on variational inference. Introducing a hyper-prior into the traditional multinomial-Dirichlet model, the hierarchical multinomial-Dirichlet model was constructed to estimate the conditional distribution in Bayesian networks. Analyzing the prior dependency structure of hierarchical multinomial-Dirichlet model, a fast and accurate self-organizing variational reasoning algorithm was developed. Compared with the traditional classification model, the hierarchical multinomial-Dirichlet model proposed in this paper shows a significant performance improvement in dealing with the fault classification problem of liquid rocket engines with small data sets.

Improved AlexNet Based Recognition Algorithm for Deformable Convolution Skin Lesions

LI Haiyan, MA Yan, LI Haijiang, GUO Lei, LI Hongsong

2022, 42(3): 297-303. doi:10.15918/j.tbit1001-0645.2020.242

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In order to solve the problem of poor adaptability of standard convolution to unknown changes and high similarity between classes of skin lesions, large differences within a class, and serious class imbalance in data, a skin lesion recognition algorithm of deformable convolutional network was proposed based on improved AlexNet. First, an improved AlexNet deformable convolutional network model was established, adding sampling offset, making the position of the convolution kernel sampling point change adaptively according to the image content. And it was arranged to automatically adjust different scales or acceptable information field, and to extract finer features than standard convolution. And then, a weighted loss function of the cross-entropy loss function and the focus loss function was used to reduce the weight of samples classified easily in training, making the model focus on difficult and error-prone samples to solve the problem of sample proportion imbalance and to optimize the recognition rate of the model. Finally, a simulation experiment was carried out with the HAM10000 data set. The subjective and objective experimental results show that the proposed method is superior to the existing methods in identifying seven skin lesions, and has higher accuracy, specificity and robustness.

Fractional-Order Virtual Model Control for Single Leg of Hydraulic Quadruped Robot

ZHAO Jiangbo, GONG Sijin, MA Shicheng, WANG Junzheng

2022, 42(3): 304-311. doi:10.15918/j.tbit1001-0645.2020.007

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As the most widely-used method for motion control of quadruped robot, virtual mode control （VMC）can achieve compliant interaction between foot and ground at the cost of trajectory tracking precision. A fractional-order VMC (FOVMC) was proposed to improve the robustness and precision of VMC for single-leg tracking of hydraulic quadruped robot. And the implementation detail about the frequency domain modeling process of force control system for hydraulic-cylinder-driven joints and optimization-based FOVMC parameter tuning method were provided. Some trotting experiments were carried out on a quadruped robot platform to validate that the superiority of FOVMC over classical VMC in performance improvement of single-leg motion control.

High Sensitivity Orthogonal Receiving System for Preclinical Magnetic Particle Imaging

SHI Yueting, REN Shiwei, WANG Xiaohua, XUE Chengbo

2022, 42(3): 312-317. doi:10.15918/j.tbit1001-0645.2021.307

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In this paper, a high-sensitivity orthogonal receiving system was designed based on finite-unit analysis to improve MPI signal detection sensitivity and magnetic field homogeneity for preclinical MPI of small animal imaging. The orthogonal receiving coil set was designed to add a new x-direction receiving coil, to improve the reception sensitivity and optimize imaging field of view area in z-direction. Simulation experiments, construction and calibration were carried out in the preclinical MPI platform with the high sensitivity orthogonal receiving systems to perform phantom imaging and small animal imaging experiments. Results show that the new orthogonal system can improve the image quality and contrast-noise rate effectively.

Multi-Target Detection Based on Camera and Radar Feature Fusion Networks

CHANG Liang, BAI Jie, HUANG Libo

2022, 42(3): 318-323. doi:10.15918/j.tbit1001-0645.2021.164

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A network model for radar and camera feature fusion was proposed to deal with the impact of low light, rain and fog and other harsh scenes on the detection capability of intelligent driving vision systems. A radar attention mechanism feature module was constructed based on millimeter wave radar information and attention model to provide a priori information and increase the weight of the algorithm in the target candidate region for the feature fusion network. The test results show that, introducing the radar attention mechanism module, the target detection performance of the feature fusion network is significantly better than the detection performance of that relying on computer vision alone, and the target detection is more robust in complex scenes.

Effects of Chain Extenders on Mechanics and Network of Polyethylene Oxide-Tetrahydrofuran Copolyether Polytriazole Elastomer

HU Jinghui, ZOU Yecheng, HE Jiyu, YANG Rongjie

2022, 42(3): 324-330. doi:10.15918/j.tbit1001-0645.2020.223

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In order to significantly increase the molecular weight of the prepolymer by using a chain extender, in this paper, taking azide-terminated polyethylene oxide-tetrahydrofuran copolyether (AzTPET) and azido-terminated diethylene glycol (KL-1) as chain extenders seperatly respectively, a reaction with ATPET was arranged to prepare a polyethylene oxide-tetrahydrofuran copolyether polytriazole (PTPET) elastomer. Under the condition of maintaining the viscosity of the reaction system, some tests were carried out to analyze the influence of two chain extenders on mechanical and cross-linking network properties of the PTPET elastomer. The results show that the elongation of the PTPET elastomer synthesized by AzTPET can increase from 112% (no AzTPET) to 300% (add 40% AzTPET) at 20 ℃, while at 60 ℃, the elongation can increase from 70.1% (no AzTPET) to 153% (add 40% AzTPET). Correspondingly, the elongation of PTPET can increase from 112% (no KL-1) to 200% (add 50% KL-1) at 20 ℃, while at 60 ℃, the elongation can increase from 70.1% without KL-1 to 120% (add 50% KL-1), which can increase the elongation at break while maintaining stable tensile strength. It is obvious that the elongation at break of PTPET with both chain extenders can be greatly improved, while the tensile strength decreases with the first one. The tensile strength of the above PTPET samples can be increased with the increase of the amount of chain extender at −40 ℃. Both types of chain extenders can significantly increase the elongation at break of PTPET, but KL-1 in PTPET is better than AzTPET from the perspective of mechanical strength effect.

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2022 Vol. 42, No. 3

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