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14th International Conference on Quality, Reliability, Risk, Maintenance, and Safety engineering, QR2MSE 2024

作者： Hu, Junming Vehicle Measurement Control and Safety Key Laboratory of Sichuan Province Xihua University Chengdu China Provincial Engineering Research Center for New Energy Vehicle Intelligent Control and Simulation Test Technology of Sichuan Xihua University Chengdu China School of Automobile and Transportation Xihua University Chengdu China

ISBN: (纸本)9781837242672

Enhancing vehicle reliability is of paramount importance during the research and development phase, with reliability growth testing playing a crucial role in this process. Traditional reliability growth testing often treats vehicle failures under varying environmental conditions with uniform significance, overlooking the specific impacts these conditions may have on failure occurrence. This paper aims to illuminate the influence of environmental factors on vehicle failures. To explore the relationship between vehicle failures and the contexts in which they occur, Principal Component Analysis (PCA) was employed. The findings indicate that a diversified testing approach, which assigns different levels of importance to various testing scenarios, is recommended. This approach is likely to yield a more nuanced understanding of vehicle performance and foster a more effective strategy for enhancing reliability. © The Institution of engineering & technology 2024.

关键词： FAILURE DATA ANALYSIS PRINCIPAL COMPONENT ANALYSIS RELIABILITY GROWTH TESTING TRACKED VEHICLE

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A shape memory alloy spring actuated gripper with self-sensing feedback for control 16

A shape memory alloy spring actuated gripper with self-sensi...

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16th International Conference on Sensing technology, ICST 2023

作者： Ganapathy, Then Mozhi Kaliaperumal, Dhanalakshmi Banu Sundareswari, M. National Institute of Technology Instrumentation and Control Engg. Tamil Nadu Tiruchirappalli India Saveetha School of Engineering Electronics and Communication Engg. Tamil Nadu Chennai India

ISBN: (纸本)9798350395341

This article suggests a self-sensing gripper that is driven by a single Shape memory alloy (SMA) spring to enable precise self-sensing. The gripper that is in normally open mode consists of two arms, one of which is fixed and an SMA spring actuator controls the other. This article demonstrates that the variation in the resistance of the shape memory alloy spring reveals phase transitions and can be used to detect the position of the gripper arm, enabling position control. The development of self-sensing technology broadens the concept of gripper sensing, which helps to advance compactness and miniaturization. This work suggests the design, manufacture, and characterization of a gripper that gives the benefit of sensorless position control. © 2023 IEEE.

关键词： Grippers

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BFP Net: Balanced Feature Pyramid Network for Small Apple Detection in Complex Orchard Environment

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Plant Phenomics 2022年第1期4卷 75-93页

作者： Meili Sun Liancheng Xu Xiude Chen Ze Ji Yuanjie Zheng Weikuan Jia School of Information Science and Engineering Shandong Normal UniversityJinanChina Key Laboratory of Facility Agriculture Measurement and Control Technology and Equipment of Machinery Industry Zhenjiang 212013China National Engineering Research Center for Apple Shandong Agriculture UniversityTaian 271018China School of Engineering Cardiff UniversityCardiff CF243AAUK

Despite of significant achievements made in the detection of target fruits,small fruit detection remains a great challenge,especially for immature small green fruits with a few *** closeness of color between the fruit skin and the background greatly increases the difficulty of locating small target fruits in the natural orchard *** this paper,we propose a balanced feature pyramid network(BFP Net)for small apple detection.

关键词： Net pyramid locating

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Self-Supervised Multi-Transformation Learning for Time Series Anomaly Detection

SSRN

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SSRN 2023年

作者： Han, Han Han, Chuang Fan, Haoyi School of Measurement and Control Technology and Communication Engineering Harbin University of Science and Technology Harbin150080 China School of Computer and Artificial Intelligence Zhengzhou University Zhengzhou450001 China

Time series anomaly detection aims to find specific patterns in time series that do not conform to general rules, which is one of the important research directions in machine learning. However, most existing time series anomaly detection methods solely consider the original observed state space. In this paper, we investigate the different views of the original signals by reconstructing them from the different transformations to learn better comprehensive representations of normal patterns. Specifically, we propose a time series anomaly detection model based on self-supervised multi-transformation learning while jointly learning the noise and filter transformation of the normal time series and capturing the anomaly simultaneously in both transformation patterns. Firstly, the model randomly adds noise to the original signal to construct the noisy signal, and the Kalman filter is applied to the original signal to construct the filtered signal. The noisy and filtered signals are subsequently used to reconstruct the original signal, and the randomly added noise is classified. Finally, the model captures the two transformation patterns of normal time series signals and transforms the anomaly detection problem into the reconstruction metric problem of time series signals under noise and filter transformations. The effectiveness of the proposed method is verified on the UCR time series dataset. © 2023, The Authors. All rights reserved.

关键词： Time series

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Polar Coded OFDM with Code-Frequency Index Modulation

Polar Coded OFDM with Code-Frequency Index Modulation

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International Conference on communication technology (ICCT)

作者： Jia-Qi Zhang Si-Yu Zhang School of Information and Communication Engineering Beijing Information Science and Technology University Beijing China Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing Information Science and Technology University Beijing China

ISBN: (数字)9798350363760

ISBN: (纸本)9798350363777

In this paper, we introduce a polar coded orthogonal frequency division multiplexing with code-frequency index modulation (PC-CFIM) scheme, designed to enhance spectral efficiency (SE) while improving error performance. At the transmitter, PC-CFIM divides the information bits into two subsets. One subset is utilized for selecting the spreading code index, and the other is utilized for polar coded OFDM with index modulation (PC-OFDM-IM). In the proposed PC-CFIM framework, the polar-coded sequence is spread using the indices from code domain index modulation. At the receiver, the system employs code index selection coupled with polar decoding to ensure accurate retrieval of information bits. The integration of polar code with hybrid index modulation significantly improves interference resilience, thereby reducing bit error rates (BER). Moreover, the transmission of additional bits via the spreading code index further enhances the system’s SE. Simulation results show that compared to the conventional PC-OFDM-IM, the proposed PC-CFIM significantly improves the BER performance with enhanced SE.

关键词： Codes Spectral efficiency Transmitters OFDM Simulation Bit error rate Modulation Receivers Indexes Polar codes

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Dynamic Programming Based Strategies of Future Crop Plant 24

Dynamic Programming Based Strategies of Future Crop Plant

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Proceedings of the 2024 5th International Conference on Big Data Economy and Information Management

作者： Beining Zhang Xueying Wang Yongkang Deng Kai Chen Qinglang Liu Measurement and Control Technology and Instruments School of Nuclear Technology and Automation Engineering Chengdu University of Technology Chengdu Sichuan China School of Nuclear Technology and Automation Engineering Chengdu University of Technology Chengdu Sichuan China

ISBN: (纸本)9798400711862

In this paper, we develop a decision model based on dynamic programming to create an optimal crop plan for 2024-2030 in rural northern China. Considering different marketing scenarios, uncertainties, and crop substitutions and complementarities, this paper solves the problem with three sub-problems. First, the optimal cropping plan for 2024-2030 is calculated based on the cropping scenario for 2023. It is assumes that expected sales, cropping costs, yields and marketing prices are stable. Secondly, a multi-objective planning model was developed. It aimed at profitability and stability and took into account uncertainties. Finally, the planting plan was further optimised and it considered crop substitutability and complementarity, and the relationship between expected sales and selling prices and planting costs. Through dynamic planning and Monte Carlo simulation, this paper takes into account uncertainty and crop relationships and it solves the optimal crop planting plan for the years 2024-2030 with a maximum profit of about $7.737 million. Therefore, this paper proposes a decision model based on dynamic programming and it takes into account various factors of the planting plan for the next seven years. An effective method is provided for solving the crop planting strategy problem in sustainable agricultural development.

关键词： Dynamic Programming

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A Lightweight Anchor-Free Detector Using Cross-Dimensional Interactive Feature Balance for SAR Ship Detection 23

A Lightweight Anchor-Free Detector Using Cross-Dimensional I...

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Proceedings of the 2023 5th International Conference on Video, Signal and Image Processing

作者： Jiaming Shen Lin Bai Haijuan Wang Bo Ji Wenming Cheng Guocai Zhang School of Electronics and Control Engineering Changan University China Zhejiang Aerospace Runbo Measurement and Control Technology Co. Ltd China

ISBN: (纸本)9798400709272

In recent years, the deep convolutional neural network (CNN) model has rapidly developed, and it is widely used in SAR remote sensing target detection. Many methods utilize preset anchor boxes for target classification and boundary box coordinate regression. However, these methods encounter challenges when deployed to edge devices. Firstly, in SAR images, ships are sparsely and unevenly distributed, rendering most anchor boxes redundant. Secondly, the target detection model relying on anchor boxes demands extensive computation during anchor box generation, typically running on hardware-rich environments. Nevertheless, edge devices lack the necessary hardware environment to meet the deployment requirements of the CNN model. To address these issues, this paper proposes a lightweight anchor-free detector called Cross-Dimensional Interactive Feature Balance (CDIFB-Net). We adopt a key point strategy to predict the bounding box, eliminating the reliance on anchors. CDIFB-Net employs a partial convolution (PConv) based model as a lightweight feature extraction network to tackle the model's lightweight problem. Additionally, considering the characteristics of large target scale differences and unbalanced target distribution in SAR ship images, and to reduce the precision decline problem caused by lightweight, this paper introduces a cross-dimensional interactive feature balance pyramid (CDI-FBP), which balances semantic information of different levels through feature pyramid aggregation and averaging. The cross-dimensional interaction module (CDIM) establishes the relationship between the ship target and the background. Experiments conducted on the SAR Ship dataset (SSDD) and High-resolution SAR Image dataset (HRSID), along with inference experiments in different hardware environments, validate the effectiveness of the network for SAR ship detection. The experimental results demonstrate that the proposed CDIFB-Net maintains fast reasoning, low delay, and excellent detectio

关键词： CDI-FBP Convolutional neural network lightweight ship detection

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Scalable parallel ultrafast optical random bit generation based on a single chaotic microcomb

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Light(Science & Applications) 2024年第4期13卷 637-644页

作者： Pu Li Qizhi Li Wenye Tang Weiqiang Wang Wenfu Zhang Brent ELittle Sai Tek Chu KAlan Shore Yuwen Qin Yuncai Wang Institute of Advanced Photonics Technology School of Information EngineeringGuangdong University of TechnologyGuangzhou 51006China. Key Laboratory of Photonic Technology for Integrated Sensing and Communication Ministry of Education of ChinaGuangdong University of TechnologyGuangzhou 51006China. Guangdong Provincial Key Laboratory of Information Photonics Technology Guangdong University of TechnologyGuangzhou 51006China. Key Laboratory of Advanced Transducers andIntelligent Control System Ministry of EducationTaiyuan University of TechnologyTaiyuan 030024China. State Key Laboratory of Transient Optics and Photonics Xi’an Institute of Optics and Precision MechanicsChinese Academy of SciencesXi’an 710119China. Department of Physics and Materials Science City University of Hong KongHong KongChina. School of Electronic Engineering Bangor UniversityBangorWales LL571UTUK

Random bit generators are critical for information security,cryptography,stochastic modeling,and *** and scalability are key challenges faced by current physical random bit ***,we propose a massively parallel scheme for ultrafast random bit generation towards rates of order 100 terabit per second based on a single micro-ring resonator.A modulation-instability-driven chaotic comb in a micro-ring resonator enables the simultaneous generation of hundreds of independent and unbiased random bit streams.A proof-of-concept experiment demonstrates that using our method,random bit streams beyond 2 terabit per second can be successfully generated with only 7 comb *** bit rate can be easily enhanced by further increasing the number of comb lines *** approach provides a chip-scale solution to random bit generation for secure communication and high-performance computation,and offers superhigh speed and large scalability.

关键词： resonator random chaotic

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Quantum state tomography from observable time traces in closed quantum systems

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control Theory and technology 2024年第2期22卷 222-234页

作者： Shuixin Xiao Yuanlong Wang Qi Yu Jun Zhang Daoyi Dong Ian R.Petersen University of Michigan–Shanghai Jiao Tong University Joint Institute Shanghai Jiao Tong UniversityShanghai200240China School of Engineering The Australian National UniversityCanberraACT2601Australia Key Laboratory of Systems and Control Academy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing100190China Centre for Quantum Computation and Communication Technology(Australian Research Council) Centre for Quantum DynamicsGriffith UniversityBrisbaneQLD4111Australia School of Engineering and Technology University of New South WalesCanberraACT2600Australia

The task to estimate all the parameters of an unknown quantum state, also called quantum state tomography, is essential for characterizing and controlling quantum systems. In this paper, we utilize observable time traces to identify the initial quantum state of a closed quantum system, based on the state space approach in the control theory. In the informationally complete scenario, we show that with a linear regression estimation (LRE), the mean squared error (MSE) scales as , where N is the resource number. In the informationally incomplete scenario, we introduce regularization LRE to perform the state tomography task. We employ PBH test to demonstrate that closed quantum systems with only one observable are informationally incomplete and propose using observables, where d is the dimension of the quantum state, for informational completeness. Numerical examples demonstrate the effectiveness of our method.

关键词： Quantum state tomography Time trace Quantum system identification

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Path Optimization of Complex and Large-Scale Automated Antenna Assembly Lines

Path Optimization of Complex and Large-Scale Automated Anten...

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UNIfied Conference of International Workshop on Defence Applications of Multi-Agent Systems, DAMAS 2023, International Conference on Maintenance engineering, IncoME-V 2023, International conference on the Efficiency and Performance engineering Network, TEPEN 2023

作者： Ma, Zeyu Wang, Hongjun Zhang, Mingliang Jiang, Fan Li, Bin School of Mechanical Electrical Engineering Beijing Information Science and Technology University Beijing100192 China Beijing International Science Cooperation Base of High-End Equipment Intelligent Perception Beijing100192 China Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing100192 China Beijing Institute of Radio Measurement Beijing100854 China School of Information Management Beijing Information Science and Technology University Beijing100192 China

ISBN: (纸本)9783031494208

Considering issues such as low assembly efficiency and the inability of the assembly process index and product characteristics to be fully reflected in the traditional construction mechanical arm assembly process, the concept of a digital twin was introduced. The study involved the modeling and simulation technology of the construction mechanical arm assembly process based on the digital twin, and included some path optimization. Furthermore, according to the virtual model, a genetic algorithm was employed to optimize the path in Matlab. Additionally, the Hamiltonian cycle algorithm was utilized to enhance the efficiency of the robot and decrease the working time. Taking the assembly line of a screw arm as an example, it was demonstrated that the assembly simulation based on digital twinning can monitor the assembly process in real time. It can also optimize its configuration to improve assembly efficiency and implement an effective closed-loop feedback mechanism to enhance production efficiency, improve production quality, and reduce production cost. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Cyber Physical System

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