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Parameter estimation of the shell transfer arm of a loading mechanism

Parameter estimation of the shell transfer arm of a loading ...

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2022 international Symposium on Advanced Launch Technologies, ISALT 2022

作者： Zhou, S.J. Chen, G.S. Gao, X.K. School of Mechanical Engineering Nanjing University of Science and Technology Jiangsu Nanjing210094 China Northwest Institute of Mechanical and Electrical Engineering Shaanxi Xianyang712099 China

The shell transfer arm is a key component of gun automatic loading mechanism, the coordination speed and positioning accuracy have an important impact on gun ammunition delivery effect. Establishing an accurate dynamic model is the foundation for better control and prediction, therefore, it is necessary to identify the dynamic parameters of the shell transfer arm. In this paper, the dynamic model is established based on the topology method. The parameter identification model of the shell transfer arm is constructed by applying the dynamic model and unscented Kalman filter theory. Dynamic parameters of the shell transfer arm such as the mass, inertia and centroid position are estimated under unscented Kalman filter scheme. By comparing the parameter estimation results with the nominal design values, the feasibility and effectiveness of applying the proposed method to identify the dynamic parameters of the shell transfer arm are verified. © Published under licence by IOP Publishing Ltd.

关键词： Parameter estimation

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Equivalent Number of Bits in Delta-Sigma Analog-to-Digital Converter in automatic control and Monitoring Systems

Equivalent Number of Bits in Delta-Sigma Analog-to-Digital C...

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2023 international conference on electrical engineering and Photonics, EExPolytech 2023

作者： Samoilov, Leontiy K. Denisenko, Darya Chumakov, Vladislav E. Prokopenko, Nikolay N. Information and Computer Engineering Southern Federal University Taganrog Russia Don State Technical University Rostov-on-Don Russia Southern Federal University Taganrog Russia

ISBN: (纸本)9798350310481

The dynamic error of delta-sigma ADC working in analog information input devices of control and monitoring systems (CMS) is investigated. The traditional structure of the analog information input unit in CMS contains a sensor of physical quantity, ADC, analog anti-alias filter, amplitude multiplexer and analog storage device. These functional units determine the static and dynamic errors of the analog-to-digital conversion process. At the same time the equivalent number of bits of delta-sigma ADC, which are widely used today in the devices of radio engineering, automation and communication, is determined by the total error of the above mentioned functional nodes, consistently converting the output signal of the sensor. It is shown that in order to reduce dynamic errors it is reasonable to leave only the sensor and delta-sigma ADC in the signal conversion chain, which in this case is introduced into the channel of each sensor. In this case, to assess the influence of the dynamic characteristics of the sensor it is proposed to approximate its signal spectrum as a function of the signal spectrum at the output of the anti-alias low-pass filter with Butterworth approximation. Analytical dependences for determining the errors of analog-to-digital conversion with delta-sigma ADC are obtained, allowing to solve direct and inverse problems of CMS input circuit design: to evaluate the chosen variant or to design CMS functional units with the required characteristics. © 2023 IEEE.

关键词： Analog to digital conversion

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An Efficient Detection of Intracranial Hematoma Using Window-Based Stacking and YOLOv5 Framework 2

An Efficient Detection of Intracranial Hematoma Using Window...

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2nd international conference on Advancements in electrical, Electronics, Communication, computing and Automation, ICAECA 2023

作者： Vidhya, V. Gudigar, Anjan Raghavendra, U. Basak, Sudipta Mallappa, Sankalp Hegde, Ajay Menon, Girish Computer Science and Engineering Manipal Institute of Technology Manipal Academy of Higher Education Manipal576104 India Manipal Institute of Technology Manipal Academy of Higher Education Instrumentation and Control Engineering Manipal576104 India Department of Neurosurgery Manipal Hospitals Karnataka India Department of Neurosurgery Manipal Academy of Higher Education Kasturba Medical College Manipal576104 India

ISBN: (纸本)9798350306811

Traumatic brain injury (TBI) is a burgeoning medical disorder across the world particularly among young adults and children. TBI can cause intracranial hematoma (ICH), a lethal condition which requires prompt and accurate interpretation of computed tomography (CT) images for timely diagnosis and treatment. Since manual detection of CT images is a tedious and operator-dependent task, a deep learning framework is proposed for locating and categorizing ICH for improved diagnostic performance. Firstly, the input images are processed by using various techniques such as local directional pattern, local binary pattern, and windowing. Then the single stage YOLOv5 object detection model with faster spatial pyramid pooling is applied to detect hematoma regions of various types in the brain. The proposed model using windowing approach realized an overall mAP of 0.969, precision of 0.945 and recall of 0.943. The experimental results from the research study demonstrated that the suggested framework can help radiologists in strategic decision-making and improve quality care to the patients. © 2023 IEEE.

关键词： Object detection

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Knee Brace Prototype with Electrostimulation System as an Auxiliary for Postoperative Treatment for Anterior Cruciate Ligament Injuries

Knee Brace Prototype with Electrostimulation System as an Au...

引用

international conference on electrical engineering, computing science and automatic control (CCE)

作者： Perla Tamara Martínez-Lara Jesús Antonio Garduño-Aguirre Marcos Mendoza-Mejia Lorenzo Leija-Salas Arturo Vera-Hernández Rafael Bayareh-Mancilla Department of Electrical Engineering/Bioelectronics CINVESTAV- IPN Mexico City Mexico Biomedical Engineering Universidad del Valle de México Mexico Mexico Dept. Advanced Technologies UPIITA-IPN Mexico City Mexico

The recovery of knee mobility plays a crucial role in the postoperative phase after an anterior cruciate ligament injury, necessitating the use of articulated knee braces to strike a delicate balance between immobilization and progressive angular movements. While immobilization is vital to prevent muscle contractions, controlled movement is essential for therapy. To address these challenges, an innovative knee brace prototype with an integrated electrostimulation system was designed and developed. The prototype was meticulously crafted using CAD software, and materials were carefully selected based on the Von Mises study to ensure adequate resistance. The integrated electrostimulation system generates electrical pulses with specific characteristics, promoting muscle relaxation, increased blood flow, and endorphin secretion in the stimulated muscle, particularly the quadriceps. ABS and 3003 aluminum alloy materials were used for the modeling of the knee brace, because they demonstrate a behavior of elasticity close to the desired, indicating that the prototype would only have a minimal deformation in the initial section of the lower part of the knee brace if a load of 150 kgf is applied, as athletes can weigh around 90-120 kg. Further improvements to the power stage and implementation of a Darlington pair to maintain the mirror current are planned, aiming at optimizing the electrostimulation system's performance, the output current should be between 1 to 1.5 amperes which is enough to produce the muscle contraction and relax. This knee brace prototype presents significant potential as an auxiliary tool for postoperative ACL rehabilitation, contributing to patients' successful recovery and improved quality of life.

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Based on Embedded Technology to Real-Time control for Analogous Active Suspension System 2nd

Based on Embedded Technology to Real-Time Control for Analog...

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2nd international conference on Intelligent Systems Design and engineering Applications, ISDEA 2023

作者： Hung, San-Shan Tsai, Yi-Jui Lin, Kuo-Wei Department of Automatic Control Engineering Feng-Chia University Taichung Taiwan

ISBN: (纸本)9789819963027

Conventional vehicle suspension system is mainly composed of coil springs and hydraulic dampers, and the elasticity coefficient K ad damping coefficient C are fixed values, so the traditional suspension system cannot adjust the suspension system according to different road conditions. Due to the varying road quality, many potholes, patches and manhole covers, and rainy climate, the comfort and maneuverability of driving are reduced. Therefore, this study proposes the application of embedded technology combined with road image to determine and control the class of Analogous Active Suspension System. In this study, the Analogous Active Suspension System is composed of air springs, proportional valve hydraulic dampers instead of traditional suspension system, and various sensors. For different types of uneven road surfaces such as potholes, speed bump, manhole covers, etc., the controller Area Network (CAN bus) communication is used to transmit the road surface information to the vehicle embedded system, and then the control decision is calculated to adjust the corresponding air spring coefficients according to the corresponding conditions. At the same time, the optimal damping coefficients are calculated by using neural-like algorithms, so that the system can adjust the suspension parameters immediately according to the current road conditions to achieve better driving comfort and handling. Finally, the dynamic characteristics of the suspension system and the vehicle are investigated in a real vehicle dynamic test to optimize the control decision parameters to achieve the best driving comfort and to give the best driving safety. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Embedded systems

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Research on capacity configuration method of optical storage charging integrated charging station considering economic and environmental benefits 5

Research on capacity configuration method of optical storage...

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2024 5th international conference on electrical Technology and automatic control, ICETAC 2024

作者： Yu, Changle Yang, Lin Zhang, Su Liu, Jun Wan, Jia Song, Mingda State Grid Liaoning Power Co. Ltd. Skills Training Center Jinzhou121001 China School of Electrical Engineering Shenyang University of Technology Shengyang110870 China

In order to deeply explore the economic and environmental benefits of the photovoltaic-storage-charging integrated power station and optimize the capacity allocation of the power station, a capacity allocation strategy integrating economic considerations and environmental benefits is proposed. Firstly, based on the summary analysis of the typical architecture and operation characteristics of photovoltaic microgrid, the dual objectives of maximizing system economy and efficient utilization of photovoltaic energy are set, and multiple constraints such as power balance, installed capacity, charging and discharging efficiency and energy storage status are incorporated. A multi-objective optimization framework of microgrid adapted to time-of-use electricity price is constructed. In view of the complex model, multi-objective conflict and nonlinear characteristics, this paper introduces the improved weed algorithm as a solution tool. Finally, the examples of typical daily operation scenarios are simulated and verified by the Matlab platform. The results show that the method effectively realizes the capacity configuration of the integrated power station of optical storage and charging, provides a reference for the construction of a green energy system, and ensures the rationality and effectiveness of the construction of charging stations. © Published under licence by IOP Publishing Ltd.

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Online Transfer Learning-based Method for Predicting Remaining Useful Life of Aero-engines 7

Online Transfer Learning-based Method for Predicting Remaini...

引用

7th international conference on Intelligent computing and Signal Processing, ICSP 2022

作者： Han, Xiaoxuan Xiang, Gang Cui, Langfu Wang, Junle Zhang, Qingzhen Lin, Ruishi Jin, Yang Liu, Haodong Beijing University of Aeronautics and Astronautics School of Automation Science and Electrical Engineering Beijing China Beijing Aerospace Automatic Control Institute Beijing China

ISBN: (纸本)9781665478571

Aero-engine is the heart of aircraft, and its reliability and safety are extremely important. It is necessary to predict its remaining useful life to achieve the purpose of early maintenance decision. In this paper, the existing aero-engine prediction methods are analyzed. Aiming at the problem of inaccurate training of prediction models due to the operation of aero-engines under multiple operating conditions and insufficient amount of data for specific operating conditions, an online transfer learning-based method for remaining useful life prediction is proposed to realize the transfer of prediction models between different operating conditions. After introducing the idea of online transfer learning, based on the HomOTL-I algorithm, this paper makes improvements to the regression problem to make it applicable to remaining useful life prediction, and validates the algorithm using aero-engine test data. The results show that the online transfer model can obtain higher accuracy and convergence speed compared with the offline and online models, proving the effectiveness of the method on the small sample prediction problem. © 2022 IEEE.

关键词： Forecasting

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Breast Three-Dimensional Reconstruction and Feature Points Tracking 8th

Breast Three-Dimensional Reconstruction and Feature Points T...

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8th international conference on computing, control and Industrial engineering, CCIE 2024

作者： Huang, Yawen Xu, Zengbo Tian, Bingqiang Shanghai University of Engineering Science Long Teng Road Shanghai201600 China

ISBN: (纸本)9789819769360

In recent years, three-dimensional human body reconstruction technology has been widely applied and developed, and three-dimensional reconstruction can comprehensively and accurately observe the movement patterns from a three-dimensional perspective. At this stage, 3D human body reconstruction technology is mostly applied to static whole-body measurements, and there are fewer studies on breast local modelling. Moreover, the special structure of the breast area is that the breast does not follow the trajectory of the torso completely during the movement, and will be displaced relative to the torso. This study proposes a measurement method for tracking feature points based on three-dimensional breast dynamic reconstruction. In this paper, the Kinect body sensor is used to capture dynamic images of the breast, and the raw point cloud is preprocessed to generate a coloured point cloud set of the breast. The initial alignment is performed using the SMPL model, and then the ICP alignment algorithm is used for accurate alignment, while the vertex displacement D component is optimised to fit the 3D imaging and generate the final 3D breast dynamic model. Feature points are marked on the breast model, and the displacement parameters of the breast relative to the torso in the motion state are obtained by tracking the trajectory of the feature points. This method constructs a more accurate breast model and better describes the breast motion mechanism. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： 3D reconstruction

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A System for Simultaneous Optogenetics Stimulation, Calcium Imaging, electrical Signal Detection, and electrical Stimulation of In Vitro Neuronal Networks

A System for Simultaneous Optogenetics Stimulation, Calcium ...

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2024 Asia Communications and Photonics conference, ACP 2024 and international conference on Information Photonics and Optical Communications, IPOC 2024

作者： Deng, Yin Lin, Yarong Cao, Shiyang Li, Tao Li, Jie Lu, Zeying Lan, Yueheng Sun, Xiaojuan Sha, Longze Gui, Lili Xu, Qi Xu, Kun School of Electronic Engineering Beijing University of Posts and Telecommunications State Key Laboratory of Information Photonics and Optical Communications Beijing China Department of Biochemistry and Molecular Biology Chinese Academy of Medical Sciences Peking Union Medical College State Key Laboratory of Common Mechanism Research for Major Diseases Beijing China School of Science Beijing University of Posts and Telecommunications State Key Laboratory of Information Photonics and Optical Communications Beijing China

ISBN: (纸本)9798350379266

In vitro neuronal networks are promising models for neural computing. Despite numerous efforts to determine the activities of these neuronal networks, achieving high spatiotemporal resolution in recording and controlling neuronal activities remains challenging. Here, we propose the OptoCaMEA system, which simultaneously records neuronal network activities with a temporal resolution of 50 microseconds and a spatial resolution smaller than 10 micrometres. Additionally, it achieves single-neuron control with a spatial resolution smaller than 10 micrometres. OptoCaMEA offers a more precise method for recording and controlling the dynamics of in vitro neuronal networks, facilitating the development of computational frameworks based on biological neural networks and contributing to the in-depth study of related neurological disease models. © 2024 IEEE.

关键词： Neurons

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Automating Dermatological Diagnosis - A Comparative Analysis 5

Automating Dermatological Diagnosis - A Comparative Analysis

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5th IEEE international conference on Advances in computing, Communication control and Networking, ICAC3N 2023

作者： Johnson, Aleen Arora, Vishnupriya Aggarwal, Lakshita Goswami, Puneet Srm University Dept. Of Computer Science & Engineering Haryana Sonepat India Srm University Dept. Of Computer Science Haryana Sonepat India

ISBN: (纸本)9798350330861

Evolving and adapting healthcare along with growing technology is an urgent need of an hour using machine learning is an addition to classify health data for the large aspect of identifying dermatological illness. Convolution Neural Network (CNN) can accurately classify a variety of skin illnesses by extracting complex information from images. CNN do away with the requirement for manual feature engineering because they are able to learn from large amounts of data. They are resistant to noise and changes in lighting, ensuring accurate analysis every time. CNN help in early detection, increasing the efficacy of treatment, and lowering the possibility of a false positive. Their combination has the potential to greatly improve patient care and change dermatological procedures. Objective: The goal of this study is to determine the best effective algorithm, whether it comes from deep learning or machine learning, based on a thorough comparative analysis that considers elements like accuracy, interpret ability, and scalability. Methodology: This study uses a comparative analysis methodology to decide which machine learning and deep learning algorithms are the most effective. It entails a review of the literature, the gathering of data, the design and execution of experiments, statistical analysis, and result interpretation. Findings: This study's findings shows that deep learning approaches are more effective than machine learning ones. In contrast to machine learning, which depends on manual, subjective techniques, deep learning allows for automatic and objective feature extraction. Deep learning achieves greater prediction accuracy and generalization ability despite requiring more training time and computational resources, demonstrating its superior learning powers. © 2023 IEEE.

关键词： Learning algorithms

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