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2022 International Conference on Computer Engineering and Artificial Intelligence, ICCEAI 2022

作者： Zhao, Zhihong Liu, Kejian Zhao, Jingjiao Shijiazhuang TieDao University School of Information Science and Technology Shijiazhuang050043 China Shijiazhuang TieDao University State Key Laboratory of Structural Mechanics Behavior and System Safety of Traffic Engineering Shijiazhuang050043 China

ISBN: (数字)9781665468039

ISBN: (纸本)9781665468039

Rolling bearing, as a vulnerable part of rotating machinery, acts an essential role in mechanical equipment. Once fails, it will cause huge economic losses, even lead to major safety accidents which threaten human life. Considering that, it's of great significance for the bearing fault diagnosis. Aiming at the issue that the accuracy of the shallow diagnosis model is limited in big data set and generalization ability is weak, an end-To-end fault diagnosis method based on one-dimensional densely connected convolutional neural network and long short-Term memory neural network (1-D DenseNet-LSTM) is proposed. First, the bearing vibration signal after preprocessing is input into the fault diagnosis model. Then, Convolution layer can effectively extract the local features of bearing vibration signal, in which, dense connection mechanism will fuse the low-level features and high-level features. After that, LSTM layer pays more attention to temporal information and extracts deep features. Finally, the fault feature information is fully extracted and input to the classification layer and output the fault type. Experiments showed that the fault diagnosis model based on 1-D DenseNet-LSTM can fully extract bearing fault feature information, and classify different fault types effectively. The accuracy of bearing fault diagnosis is more than 99%, which has higher accuracy of diagnosis compared with the depth network model. © 2022 IEEE.

关键词： Failure analysis

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Numerical study on the polydispersive effect of filler size distribution on the properties of thermal interface materials 4

Numerical study on the polydispersive effect of filler size ...

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2024 4th International Conference on Advanced Materials and Mechatronics, ICAMM 2024

作者： Zong, Ruoyu Liu, Bin Jia, Xiao Wang, Shijun Li, Shikun Huai, Xiulan School of Engineering Science University of Chinese Academy of Sciences Beijing100049 China Institute of Engineering Thermophysics Chinese Academy of Sciences Beijing100190 China Nanjing Institute of Future Energy System Jiangsu Nanjing211135 China State Key Laboratory of Advanced Power Transmission Technology State Grid Smart Grid Research Institute Co. Ltd. Beijing102209 China

Advanced thermal interface materials (TIMs) are indispensable for work reliability and lifespan assurance of high-power density electronic systems by facilitating timely and effective heat dissipation. A random algorithm consisting of diluting, dropping, and stirring processes is first proposed to simulate microstructures of TIMs with continuous particle size distribution, with an accessible maximum volume fraction of 55 vol%. Then the size polydispersity impact on the thermal performance and the fluidity of TIMs is numerically investigated. Simulation results reveal that as the particle size polydispersity increases, the thermal conductivity of TIMs improves, along with the improved fluidity. Therefore, it is necessary to consider the polydispersive impact of filler size distribution in actual production and optimize the material preparation process based on the actual distribution of particles. This work provides a deeper understanding of the influence of particle polydispersity on the co-optimization of the desired attributes of TIMs. © Published under licence by IOP Publishing Ltd.

关键词： Thermal insulating materials

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Exploring Self- and Cross-Triplet Correlations for Human-Object Interaction Detection

arXiv

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arXiv 2024年

作者： Jiang, Weibo Ren, Weihong Tian, Jiandong Qu, Liangqiong Wang, Zhiyong Liu, Honghai State Key Laboratory of Robotics and System School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Science China Department of Statistics and Actuarial Science The University of Hong Kong Hong Kong

Human-Object Interaction (HOI) detection plays a vital role in scene understanding, which aims to predict the HOI triplet in the form of . Existing methods mainly extract multi-modal features (e.g., appearance, object semantics, human pose) and then fuse them together to directly predict HOI triplets. However, most of these methods focus on seeking for self-triplet aggregation, but ignore the potential cross-triplet dependencies, resulting in ambiguity of action prediction. In this work, we propose to explore Self- and Cross-Triplet Correlations (SCTC) for HOI detection. Specifically, we regard each triplet proposal as a graph where Human, Object represent nodes and Action indicates edge, to aggregate self-triplet correlation. Also, we try to explore cross-triplet dependencies by jointly considering instance-level, semantic-level, and layout-level relations. Besides, we leverage the CLIP model to assist our SCTC obtain interaction-aware feature by knowledge distillation, which provides useful action clues for HOI detection. Extensive experiments on HICO-DET and V-COCO datasets verify the effectiveness of our proposed SCTC. Copyright © 2024, The Authors. All rights reserved.

关键词： Distillation

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Laser Implicit Interaction technology Based on Object Affordance for Wmra

SSRN

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SSRN 2022年

作者： Liu, Yaxin Liu, Yan Yao, Yufeng Zhong, Ming State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin150001 China

It is particularly important for the disabled to operate the wheelchair mounted robotic arm (WMRA) with as few limb movements as possible. This human-robot implicit interaction problem for the elderly and handicapped has attracted extensive attention. Several studies have documented that laser pointer interaction is an attractive method enabling humans to unambiguously point out objects and pick them up. However, how to further convey user intention and instruct the robot to complete complex tasks based on this method has yet to be studied. Therefore, based on the idea of object affordance, this paper proposes an implicit intention interaction technology using a laser pointer. The user could point to the object in the scene through the residual limb movement ability and the WMRA will reason the action intention and assemble the task content according to the intention. Firstly, a laser semantic identification algorithm based on the YOLOv4 & the SVM is proposed to identify laser points in the scene, which can effectively avoid the error operation caused by hand twitch. Then, an automatic execution technology based on the concept of object affordance is proposed to perform household tasks, which would identify the implicit action intention of the selected objects based on the conditional random field and assemble the mapping action of intention based on the finite state machine. Finally, the feasibility of the proposed implicit interaction technology is verified on the WMRA platform. The evaluation results show that the user only needs a simple operation and the WMRA can recognize the user's desired intentions and perform household tasks automatically. Compared with previous methods, the proposed method can output the desired intention faster and significantly reduce the user's limb involvement time (about 85%) in operating the WMRA under the same task. © 2022, The Authors. All rights reserved.

关键词： Random processes

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MRIN: Fine-grained Feature Interaction based on Multiple Feature Relationships for CTR Prediction

MRIN: Fine-grained Feature Interaction based on Multiple Fea...

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International Conference on Computer Supported Cooperative Work in Design

作者： Jianbang Ju Yingyuan Xiao Peilin Yang Wenguang Zheng Enginnering Research Center of Learning-Based Intelligent System Ministry of Education Tianjin University of Technology Tianjin China Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology Tianjin University of Technology Tianjin China

CTR prediction is an important task in personalized recommendation and online advertising. In recent years, many models have been applied in CTR prediction systems to imporve the predcition accuracy. Although the current work has achieved results, the diversity of relationships between the different features was ignored: 1) most existing models usually use the vector-product to realize the interaction of each feature pairs, which ignore the potential contexts between the different feature interactions and lack the different interactive behaviors between the same pair of features; 2) most existing models usually only consider the importance of features of the same order, which ignore the weight relationships between the different feature *** this paper, we propose a novel deep learning model called Multi-Relational Interaction Network (MRIN), which learns fine-grained feature interactions and captures latent relationships between features. On the one hand, we design two interactive modules that take different interactive methods to learn the feature interactions in the potential contexts. On the other hand, we flexibly apply attention network to further automatically learn the weight relationships between different feature representations. Extensive experiments conducted on two public datasets prove the effectiveness of our proposed model, which has better performance than the state-of-the-art models.

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Robotic Inside-out Recording Method Based on Vesicle Rupture Detection

Robotic Inside-out Recording Method Based on Vesicle Rupture...

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International Conference on Manipulation, Automation and Robotics at Small Scales (MARSS)

作者： Yuzhu Liu Ruimin Li Jinyu Qiu Zuqi Wang Minghui Li Xin Zhao Qili Zhao National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases Engineering Research Center of Trusted Behavior Intelligence Ministry of Education Tianjin Key Laboratory of Intelligent Robotic (tikLIR) Institute of Robotics and Automatic Information System(IRAIS). Nankai University. Tianjin China Institute of Intelligence Technology and Robotic Systems Shenzhen Research Institute of Nankai University Shenzhen China

ISBN: (数字)9798350376807

ISBN: (纸本)9798350376814

The inside-out patch clamp technique is widely used in brain science and neuroscience research because of its ability to detect the extremely weak currents flowing through a single ion channel. In the inside-out patch clamp operations, a micrometer-scale dimensions pipette is used to aspirate part of the cell membrane, creating a giga omega-scale seal (usually termed as gigaseal) between the cell membrane and the inner wall of the micropipette to suppress the environmental electromagnetic noise. The aspirated cell membrane is then gently pulled away from the cell to form a vesicle, which is subsequently exposed to low-calcium liquid or air to induce its rupture, forming an inside-out seal for signal detection on a single ion channel. Current manual operations of inside-out patch clamp are complex and require a high level of operator expertise. Moreover, existing robotic inside-out patch clamp technologies are usually applicable to suspension cells, limiting the widespread application of this technique. This paper proposed a robotic inside-out recording patch clamp technique based on vesicle rupture detection to address these limitations. Firstly, impedance models were established to detect the state of the vesicle before and after the rupture. Further, the detection of vesicle rupture was performed based on transmembrane current responses under step inputs. Based on the above work, a robotic inside-out recording patch clamp method based on vesicle rupture detection was established in this paper. Experimental results demonstrated the effectiveness of the proposed method in achieving successful inside-out recording patch clamp mode on adherent HEK-293 cells with a success rate of 60 %, laying the foundation for subsequent studies on single ion channel functionality.

关键词： Vesicles Neuroscience Liquids Limiting Seals Ions Recording

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Reliable observer-based control against sensor failures for fractional order systems

Reliable observer-based control against sensor failures for ...

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第42届中国控制会议

作者： Bingxin Li Yujie Zhang Yaowei Liu Xin Zhao Institute of Robotics and Automatic Information System and the Tianjin Key Laboratory of Intelligent Robotics Nankai University Institute of Intelligence Technology and Robotic Systems Shenzhen Research Institute of Nankai University

In the paper,stability analysis of a class of incommensurate fractional-order systems(IFOS) is *** sufficient conditions are based on the linear matrix inequality(LMI) and straightforwardly used to solve the feasible solutions with the LMI ***,two examples including a circuit example are given to illustrate the effectiveness of the proposed method,and the comparison with the previous results shows that the proposed method is less conservative.

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Ultra-Compact Magnetoelectric Sensors for Femto-Tesla Vlf Signal Reception

SSRN

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SSRN 2024年

作者： Dong, Cunzheng Sun, Changxing Chen, Lei He, Yifan Liu, Yisi Luo, Bin Sun, Nian-Xiang Department of Electrical and Computer Engineering Northeastern University BostonMA02115 United States State Key Laboratory of Reliability and Intelligence of Electrical Equipment Hebei University of Technology Tianjin300130 China Key Lab of Computer Vision and Intelligent Information System Chongqing University of Arts and Sciences Chongqing402160 China

Very low-frequency (VLF) electromagnetic waves can penetrate dense conductive media, such as earth and saltwater, with minimal attenuation, allowing for long-distance signal transmission via ionospheric reflection. These characteristics make VLF waves ideal for applications in submarine navigation, subterranean mapping, underground communication, and ionospheric remote sensing. Conventional VLF signal reception has relied on magnetic loop antennas due to their low noise performance;however, their large size and reduced sensitivity due to low quality factors (Q) limit their use in portable and compact applications, particularly in underwater and underground environments. To address these challenges, we propose an ultra-compact room-temperature extremely sensitive femto-tesla magnetic sensor based on a strain-mediated high-Q Metglas/Quartz magnetoelectric (ME) resonator operating at its electromechanical resonance (EMR) at 24.55 kHz for VLF signal reception. The Metglas/Quartz ME sensor demonstrates a sensitivity and magnetic noise performance enhancement by an order of magnitude compared to conventional Metglas/PZT ME sensors, achieving an ultra-low equivalent magnetic noise level of 5 fT/Hz1/2, owing to high magnetic permeability and magnetostriction of Metglas and the high-quality factor of Quartz at EMR. Moreover, the Metglas/Quartz ME VLF receiver exhibits overwhelming near-field and far-field VLF signal reception capability, realizing a successful reception of VLF signal 400 km away from the NAA VLF Transmitter Cutler. The demonstrated ultra-compact high-Q Metglas/Quartz ME sensor capable of femto-tesla VLF signal reception shows significant improvements in magnetic sensing capability, size, power consumption, and cost compared to traditional magnetic loop antennas, making it a promising solution for portable VLF signal reception in challenging environments. © 2024, The Authors. All rights reserved.

关键词： Loop antennas

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FINITE ELEMENT-BASED COMPRESSION SIMULATION AND PERMEATION PERFORMANCE MEASUREMENT AND CONTROL OF HIGH TEMPERATURE SEALING MATERIALS

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UPB Scientific Bulletin, Series D: Mechanical Engineering 2023年第2期85卷 103-118页

作者： Chen, Lifang Guo, Yixiang Key Lab of Engine Health Monitoring Control and Networking of Ministry of Education Beijing University of Chemical Technology Beijing100029 China State Key Laboratory of High-end Compressor and System Technology Beijing University of Chemical Technology Beijing100029 China

To obtain the characteristic operational parameters of spacecraft heat seals, a customized tester is used to carry out the structure and performance research of the P-shaped heat seals. A heat-sealing test system is built to simulate real working conditions. The structure and the plan of the tester are optimized based on the finite element thermal analysis method. For different compression rates and pore-opening structures, the leakage rates of the P-shaped seal are tested at room temperature, high temperature, and different air pressures. The test results show that the leakage of the P-shaped sealing ring decreases with the increase of compression rate and the number of openings on the outer high-pressure side. These results are following those of the finite element theoretical analysis. The main control factors that affect the size of seal leakage have been preliminarily determined, and the data obtained from the test has laid the foundation for future research on sealing theory. © 2023, Politechnica University of Bucharest. All rights reserved.

关键词： Seals

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Combined active and passive adaptive variable admittance compliant control for space robotic manipulators

Combined active and passive adaptive variable admittance com...

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IEEE International Conference on Robotics and Biomimetics

作者： Hang Gao Xiaodong Zhang Chao Ma Cheng Zhou School of Mechanical Engineering University of Science and Technology Beijing Beijing China Beijing Key Laboratory of Intelligent Space Robotic Systems Technology and Application Beijing Institute of Spacecraft System Engineering CAST China

This paper develops a combined active and passive adaptive variable admittance compliant control algorithm for space robotic manipulators. In fact, the assembly task for space robots requires compliance and precision while ensuring avoidance of any occurrences of rigid collision throughout the process. Therefore, we design a new combined active and passive variable admittance control structure combined with the following three parts to meet these acquirements. Firstly, we develop an active variable admittance algorithm to facilitate the space robot rapid movement, enabling it to achieve higher speeds while maintaining compliance. Then, to mitigate the occurrence of unforeseen rigid collisions during the robot motion, we devise a passive variable admittance control algorithm, which aims to minimize the impact of collision events and ensure the robot safe operation. Furthermore, by employing the Lyapunov theory, a new active adaptive variable admittance control algorithm is presented for robot constant force output. Consequently, through contrast experiments, we demonstrate the effectiveness and enhanced performance of the proposed algorithm.

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