Thermal residual stress is identified as one of the major reasons of stress concentration in material’s microstructures which initiates failure in the microstructure. Considering the details of microstructural featur...
Thermal residual stress is identified as one of the major reasons of stress concentration in material’s microstructures which initiates failure in the microstructure. Considering the details of microstructural features (inclusions shape, size, and distri-bution) can provide better understanding of the thermal residual stress developed in the materials due to the temperature change. In this paper, we have extended the self-consistent clustering analysis (SCA) method for efficient and accurate modeling of thermal residual stress for thermoelastic heterogeneous materials. The governing equations of the thermoelasticity has been implemented through a eigenstrain problem and solved using a Fast Fourier Transform (FFT) based solution scheme and later extended for SCA formulation. The thermoelastic formulation of SCA method has been verified for a single inclusion (homogeneous and inhomoge-neous) problem with the analytical solution of Eshelby and the FFT-based solution for multiple clusters. An example problem with multiple inhomogeneous inclusions has been solved for different temperatures and the residual stress developed has been analyzed. Results show that the thermoelastic formulation of SCA can have order of hundred times speed up compare to the traditional FFT-based solution scheme. The proposed methodology can be implemented in thermomechanical problems and provide efficient multiscale capabilities for prediction of thermal residual stress.
We present a new framework for cognitive maintenance (CM) based on cyber-physical systems and advanced artificial intelligence techniques. These CM systems integrate intelligent deep learning approaches and intelligen...
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We present a new framework for cognitive maintenance (CM) based on cyber-physical systems and advanced artificial intelligence techniques. These CM systems integrate intelligent deep learning approaches and intelligent decision-making tech-niques, which can be used by maintenance professionals who are working with cutting-edge equipment. The systems will provide technical solutions to real-time online maintenance tasks, avoid outages due to equipment failures, and ensure the continuous and healthy operation of equipment and manufacturing assets. The implementation framework of CM consists of four modules, i.e., cyber-physical system, Internet of Things, data mining, and Internet of Services. In the data mining module, fault diagnosis and prediction are realized by deep learning methods. In the case study, the backlash error of cutting-edge machine tools is taken as an example. We use a deep belief network to predict the backlash of the machine tool, so as to predict the possible failure of the machine tool, and realize the strategy of CM. Through the case study, we discuss the significance of implementing CM for cutting-edge equipment, and the framework of CM implementation has been verified. Some CM system applications in manufacturing enterprises are summarized.
The design of wearable sensors and development of novel wireless radio protocols drive advances in the assisted living technology which is a promising approach in terms of future domestic healthcare. In this paper we ...
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ISBN:
(数字)9781728171807
ISBN:
(纸本)9781728171814
The design of wearable sensors and development of novel wireless radio protocols drive advances in the assisted living technology which is a promising approach in terms of future domestic healthcare. In this paper we propose the system architecture for vital signs monitoring in home conditions. The prototype device is based on the microcontroller supporting Bluetooth Low Energy which may be used for medical data transfer in assisted living applications. We developed a respiration rate sensor and thermometer pickup to provide basic measurements of physiological signals. We tested a range of proposed wireless system in urban conditions. The temperature and respiration rate was then recorded to verify the system operation. We measured the power consumption to evaluate the low energy performance of the device which is vital aspect of the telemedical wearable system.
Identifying structure phase transformation path is essential but challenging in plastic deformation under high-pressure high-strain rate experiments. In this paper, we adopt a framework based on non-equilibrium molecu...
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作者:
D NedelcuT Latinovic'Eftimie Murgu' University of Resita
Romania Faculty of Engineering and Management Department of Mechanical Engineering and Management Traian Vuia square no.1-4 320085 Resita University of Banja Luka
Bosnia and Herzegovina Faculty of Mechanical Engineering Department of Mechatronics and Robotics Stepe Stepanovica 71 78000 Banja Luka
The paper describes the PyChart module (aimed at analysis and visual view of 2D/3D Charts), which was created with the help of free and Open Source resources, using Python as a programming language and *** as a graphi...
The paper describes the PyChart module (aimed at analysis and visual view of 2D/3D Charts), which was created with the help of free and Open Source resources, using Python as a programming language and *** as a graphical user interface toolkit. The chart data is imported from a Excel/CSV file with a template structure and is drawn in the PyChart module as XY or XYZ curves similar with Excel scatter with smooth lines and markers style. The main functions of the charts are activated using the toolbar. The module is provided with zooming instruments (fit, pan, zoom in, zoom out), cubic spline curves interpolation, chart intersection with constant X, Y or Z values, visual follow of the 2D chart points to view coordinates, export of data in Windows Clipboard, Excel or Microsoft Word format and saving the chart as a image file.
Existing approaches for robotic control of magnetic swarms are not capable of generating magnetic aggregates precisely in an arbitrarily specified target region in a fluidic flow environment. Such a swarm control capa...
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ISBN:
(数字)9781728173955
ISBN:
(纸本)9781728173962
Existing approaches for robotic control of magnetic swarms are not capable of generating magnetic aggregates precisely in an arbitrarily specified target region in a fluidic flow environment. Such a swarm control capability is demanded by medical applications such as clinical embolization (i.e., localized clogging of blood vessels). This paper presents a new magnetic swarm control strategy to generate aggregates only in a specified target region under fluidic flow. Within the target region, the magnetic field generates sufficiently large magnetic forces among magnetic particles to maintain the aggregates' integrity at the junctions of blood vessels. In contrast, unintended aggregates outside the target region are disassembled by fluidic shear. The aggregation control approach achieved a mean absolute error of 0.15 mm in positioning a target region and a mean absolute error of 0.30 mm in controlling the target region's radius. With thrombin coating, 1 μm magnetic particles were controlled to perform embolization both in vitro (using microfluidic channel networks) and ex vivo (using porcine tissue). Experiments proved the effectiveness of the swarm control technique for on-demand, targeted embolization.
In the context of control and estimation under information constraints, restoration entropy measures the minimal required data rate above which a system can be regularly observed. The observer here is assumed to recei...
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In the context of control and estimation under information constraints, restoration entropy measures the minimal required data rate above which a system can be regularly observed. The observer here is assumed to receive its state information through a communication channel of a finite bit-rate capacity. In this paper, we provide a new characterization of restoration entropy which does not require to compute any temporal limit, i.e., an asymptotic quantity. Our new formula is based on the idea of finding an adapted Riemannian metric on the state space that allows to ‘see’ the decisive quantity that determines the restoration entropy - a certain type of Lyapunov exponent - in only one step of time.
The electronics industry is one of the growing industrial sectors because of the need for electronics industry products continuously increases. This situation of development is driving the fast pace of electronics ind...
The electronics industry is one of the growing industrial sectors because of the need for electronics industry products continuously increases. This situation of development is driving the fast pace of electronics industry companies in Malaysia to be better prepared to face competition in the era of free trade. The study was carried in an electronic company in Malaysia that produce hard disk components. In this company, the number of defective products is very high which is the average defect (they call it u-loss) in the brushing room for arm body actuator products reaches 0.454% and one type of actuator arm body has reached 0.982% of defect units which means the company loses 65,000.88 RM per year. This study only focused on actuator arm body production in brushing room and aim to determine the dominant product which have the biggest percentage of defect, determine types of defects in the production of selected product, determine the root cause of the biggest defects in the production of selected product in brushing area, and recommend improvements in order to minimize the occurrence of defects in the production of selected product. This research uses Six Sigma in solving problems in the company. This study did not evaluate the results of the Six Sigma implementation directly. Therefore, as an alternative, quality improvement is done through Monte Carlo simulation with several scenarios. If zero defect in actuator arm body production is reached, company can save 65,000.88 RM per year.
We investigate the structural, vibrational, and mechanical properties of jammed packings of deformable particles with shape degrees of freedom in three dimensions (3D). Each 3D deformable particle is modeled as a surf...
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