Design and Experimental Validation of Two Cam-Based Force Regulation Mechanisms

2020 ◽  
Vol 12 (3) ◽  
Author(s):  
Ming Li ◽  
Wei Cheng ◽  
Ruili Xie
Keyword(s):  
Experimental Validation ◽  
Design Principle ◽  
High Accuracy ◽  
Experimental Results ◽  
Negative Stiffness ◽  
Future Research ◽  
Test Accuracy ◽  
Mechanical Parts ◽  
Regulation Mechanisms ◽  
Noise Phenomenon

Abstract This paper presents the design and experimental validation of two force regulation mechanisms (FRMs) containing a translational cam and a rotational cam, respectively. With the friction-considered profile identification method (FCPIM) to define the cam and through the squeezing between the cam and the spring-supported slider, the FRMs can passively output the desired force over the designed displacement. Under the premise of that the friction coefficient can be accurately obtained, the friction-considered design principle will be significant for the realization of FRMs in actual applications since it is no longer necessary to achieve high accuracy by pursuing the frictionless condition. Hence, the conventional materials and mechanical parts can be directly used to assemble the FRMs without sacrificing the force regulating accuracy. We are highly interested in the actual experimental behavior of the proposed FRMs under the friction-considered condition. Then, prototypes of the two FRMs capable of outputting multiple types of forces including in zero-stiffness, positive and negative stiffness are specially designed, fabricated, and tested quasi-statically. The experimental results verify the correctness of FCPIM since they agree with the design objective well. Meanwhile, the effectiveness of the FCPIM is proved as the errors of the experimental results considering friction is much lower than those ignoring friction. The experiments also show that the noise phenomenon in the testing curves that may affect the judgment of test accuracy can be highly degraded by using more stable and controllable loading tools, which is helpful for future research.

Approaches of Ontological Concept Mapping Based on Multi-Strategy

2014 ◽  
Vol 519-520 ◽  
pp. 820-823
Author(s):  
Rong Li ◽  
Lei Liu
Keyword(s):  
Concept Mapping ◽  
High Accuracy ◽  
Experimental Results ◽  
Future Research ◽  
Research Directions ◽  
Future Research Directions ◽  
Ontological Concept

Aiming at solving ontology heterogeneity, in this paper, we propose approaches of ontological concept mapping based on multi-strategy. At first, we use strategies based on concept name, property and taxonomy to calculate similarity. Then mapping results of multi-strategy are obtained. Finally, we present experimental results with high accuracy and point out future research directions.

scholarly journals An Experimental Study of the Decomposition and Carbonation of Magnesium Carbonate for Medium Temperature Thermochemical Energy Storage

Energies ◽  
2021 ◽  
Vol 14 (5) ◽  
pp. 1316
Author(s):  
Daniel Mahon ◽  
Gianfranco Claudio ◽  
Philip Eames
Keyword(s):  
Thermal Analysis ◽  
Thermal Decomposition ◽  
Energy Storage ◽  
Magnesium Carbonate ◽  
Experimental Results ◽  
Future Research ◽  
Medium Temperature ◽  
Different Temperatures ◽  
Decomposition Enthalpy ◽  
Co2 Atmosphere

To improve the energy efficiency of an industrial process thermochemical energy storage (TCES) can be used to store excess or typically wasted thermal energy for utilisation later. Magnesium carbonate (MgCO3) has a turning temperature of 396 °C, a theoretical potential to store 1387 J/g and is low cost (~GBP 400/1000 kg). Research studies that assess MgCO3 for use as a medium temperature TCES material are lacking, and, given its theoretical potential, research to address this is required. Decomposition (charging) tests and carbonation (discharging) tests at a range of different temperatures and pressures, with selected different gases used during the decomposition tests, were conducted to gain a better understanding of the real potential of MgCO3 for medium temperature TCES. The thermal decomposition (charging) of MgCO3 has been investigated using thermal analysis techniques including simultaneous thermogravimetric analysis and differential scanning calorimetry (TGA/DSC), TGA with attached residual gas analyser (RGA) and diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) (up to 650 °C). TGA, DSC and RGA data have been used to quantify the thermal decomposition enthalpy from each MgCO3.xH2O thermal decomposition step and separate the enthalpy from CO2 decomposition and H2O decomposition. Thermal analysis experiments were conducted at different temperatures and pressures (up to 40 bar) in a CO2 atmosphere to investigate the carbonation (discharging) and reversibility of the decarbonation–carbonation reactions for MgCO3. Experimental results have shown that MgCO3.xH2O has a three-step thermal decomposition, with a total decomposition enthalpy of ~1050 J/g under a nitrogen atmosphere. After normalisation the decomposition enthalpy due to CO2 loss equates to 1030–1054 J/g. A CO2 atmosphere is shown to change the thermal decomposition (charging) of MgCO3.xH2O, requiring a higher final temperature of ~630 °C to complete the decarbonation. The charging input power of MgCO3.xH2O was shown to vary from 4 to 8136 W/kg with different isothermal temperatures. The carbonation (discharging) of MgO was found to be problematic at pressures up to 40 bar in a pure CO2 atmosphere. The experimental results presented show MgCO3 has some characteristics that make it a candidate for thermochemical energy storage (high energy storage potential) and other characteristics that are problematic for its use (slow discharge) under the experimental test conditions. This study provides a comprehensive foundation for future research assessing the feasibility of using MgCO3 as a medium temperature TCES material. Future research to determine conditions that improve the carbonation (discharging) process of MgO is required.

scholarly journals Deep Learning Based Pavement Inspection Using Self-Reconfigurable Robot

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2595
Author(s):  
Balakrishnan Ramalingam ◽  
Abdullah Aamir Hayat ◽  
Mohan Rajesh Elara ◽  
Braulio Félix Gómez ◽  
Lim Yi ◽  
...  
Keyword(s):  
Deep Learning ◽  
Semantic Segmentation ◽  
High Accuracy ◽  
Experimental Results ◽  
Mobile Mapping ◽  
Mapping System ◽  
Mobile Mapping System ◽  
Reconfigurable Robot ◽  
Nvidia Gpu ◽  
Inspection Task

The pavement inspection task, which mainly includes crack and garbage detection, is essential and carried out frequently. The human-based or dedicated system approach for inspection can be easily carried out by integrating with the pavement sweeping machines. This work proposes a deep learning-based pavement inspection framework for self-reconfigurable robot named Panthera. Semantic segmentation framework SegNet was adopted to segment the pavement region from other objects. Deep Convolutional Neural Network (DCNN) based object detection is used to detect and localize pavement defects and garbage. Furthermore, Mobile Mapping System (MMS) was adopted for the geotagging of the defects. The proposed system was implemented and tested with the Panthera robot having NVIDIA GPU cards. The experimental results showed that the proposed technique identifies the pavement defects and litters or garbage detection with high accuracy. The experimental results on the crack and garbage detection are presented. It is found that the proposed technique is suitable for deployment in real-time for garbage detection and, eventually, sweeping or cleaning tasks.

Review of Fire Performance Experiment of Concrete-Filled Steel Tubular Columns

2014 ◽  
Vol 638-640 ◽  
pp. 1397-1401
Author(s):  
Kai Xiang ◽  
Guo Hui Wang ◽  
Yan Chong Pan
Keyword(s):  
Load Ratio ◽  
Experimental Results ◽  
Research Progress ◽  
Future Research ◽  
Fire Performance ◽  
Cross Sectional ◽  
Tubular Columns ◽  
Cross Sectional Dimension ◽  
Cfst Columns ◽  
In Fire

This paper presents a review of research progress in fire performance of concrete-filled steel tubular (CFST) columns. Experimental results of CFST columns in fire are reviewed with influence parameters, such as heights, cross-sectional dimension, section types, concrete types, concrete strengths, load ratio, load eccentricity, fire exposed sides and so on. Some conclusions of CFST columns under fire conditions are summarized. Deficiencies in the fire performance experiments of CFST columns are identified, which provide the focus for future research in the field.

scholarly journals High-Accuracy Tracking Using Ultrawideband Signals for Enhanced Safety of Cyclists

2017 ◽  
Vol 2017 ◽  
pp. 1-13 ◽  
Author(s):  
Davide Dardari ◽  
Nicoló Decarli ◽  
Anna Guerra ◽  
Ashraf Al-Rimawi ◽  
Víctor Marín Puchades ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Real Time ◽  
High Accuracy ◽  
Experimental Results ◽  
Localization Error ◽  
Localization System ◽  
Dynamic Conditions ◽  
The Road ◽  
Road Users

In this paper, an ultrawideband localization system to improve the cyclists’ safety is presented. The architectural solutions proposed consist of tags placed on bikes, whose positions have to be estimated, and anchors, acting as reference nodes, located at intersections and/or on vehicles. The peculiarities of the localization system in terms of accuracy and cost enable its adoption with enhanced risk assessment units situated on the infrastructure/vehicle, depending on the architecture chosen, as well as real-time warning to the road users. Experimental results reveal that the localization error, in both static and dynamic conditions, is below 50 cm in most of the cases.

Artificial intelligence in the digital twins: State of the art, challenges, and future research topics

Digital Twin ◽  
2021 ◽  
Vol 1 ◽  
pp. 12
Author(s):  
Zhihan Lv ◽  
Shuxuan Xie
Keyword(s):  
Artificial Intelligence ◽  
Smart City ◽  
Traffic Accidents ◽  
Intelligent Manufacturing ◽  
Unmanned Vehicles ◽  
Urban Traffic ◽  
Future Research ◽  
Test Accuracy ◽  
Digital Twins ◽  
The Future

Advanced computer technologies such as big data, Artificial Intelligence (AI), cloud computing, digital twins, and edge computing have been applied in various fields as digitalization has progressed. To study the status of the application of digital twins in the combination with AI, this paper classifies the applications and prospects of AI in digital twins by studying the research results of the current published literature. We discuss the application status of digital twins in the four areas of aerospace, intelligent manufacturing in production workshops, unmanned vehicles, and smart city transportation, and we review the current challenges and  topics that need to be looked forward to in the future. It was found that the integration of digital twins and AI has significant effects in aerospace flight detection simulation, failure warning, aircraft assembly, and even unmanned flight. In the virtual simulation test of automobile autonomous driving, it can save 80% of the time and cost, and the same road conditions reduce the parameter scale of the actual vehicle dynamics model and greatly improve the test accuracy. In the intelligent manufacturing of production workshops, the establishment of a virtual workplace environment can provide timely fault warning, extend the service life of the equipment, and ensure the overall workshop operational safety. In smart city traffic, the real road environment is simulated, and traffic accidents are restored, so that the traffic situation is clear and efficient, and urban traffic management can be carried out quickly and accurately. Finally, we looked forward to the future of digital twins and AI, hoping to provide a reference for future research in related fields.

Identification and Compensation of Geometric and Elastic Errors in Large Manipulators: Application to a High Accuracy Medical Robot

1998 ◽  
Author(s):  
Marco A. Meggiolaro ◽  
Constantinos Mavroidis ◽  
Steven Dubowsky
Keyword(s):  
High Accuracy ◽  
Measured Data ◽  
Experimental Results ◽  
Geometric Errors ◽  
Medical Robot ◽  
Error Sources ◽  
End Effector ◽  
Positioning Errors ◽  
Structural Deformations ◽  
Manufacturing Tolerances

Abstract A method is presented to identify the source of end-effector positioning errors in large manipulators using experimentally measured data. Both errors due to manufacturing tolerances and other geometric errors and elastic structural deformations are identified. These error sources are used to predict, and compensate for, the end-point errors as a function of configuration and measured forces. The method is applied to a new large high accuracy medical robot. Experimental results show that the method is able to effectively correct for the errors in the system.

Design Optimization of RML Glove for Improved Grasp Performance

2018 ◽  
Author(s):  
Teja Vanteddu ◽  
Bijo Sebastian ◽  
Pinhas Ben-Tzvi
Keyword(s):  
Design Optimization ◽  
Daily Living ◽  
Experimental Validation ◽  
Large Diameter ◽  
Future Research ◽  
Linkage Mechanism ◽  
Design Variables ◽  
Wide Range ◽  
Optimal Values ◽  
Optimal Set

This paper describes the design optimization of the RML Glove in order to improve its grasp performance. The existing design is limited to grasping objects of large diameter (> 110mm) due to its inability in attaining high bending angles. For an exoskeleton glove to be effective in its use as an assistive and rehabilitation device for Activities of Daily Living (ADL), it should be able to interact with objects over a wide range of sizes. Motivated by these limitations, the kinematics of the existing linkage mechanism was analyzed in detail and the design variables were identified. Two different cost functions were formulated and compared in their ability to yield optimal values for the design variables. The optimal set of design variables was chosen based on the grasp angles achieved and the resulting mechanism was simulated in CAD for feasibility testing. An exoskeleton mechanism corresponding to the index finger was manufactured with the chosen design variables and detailed experimental validation was performed to illustrate the improvement in grasp performance over the existing design. The paper ends with a summary of the experimental results and directions for future research.

scholarly journals Cost-effectiveness and value of information analysis of NephroCheck and NGAL tests compared to standard care for the diagnosis of acute kidney injury

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Elisabet Jacobsen ◽  
Simon Sawhney ◽  
Miriam Brazzelli ◽  
Lorna Aucott ◽  
Graham Scotland ◽  
...  
Keyword(s):  
Acute Kidney Injury ◽  
Cost Effectiveness ◽  
Diagnostic Accuracy ◽  
Value Of Information ◽  
Standard Care ◽  
Kidney Injury ◽  
Current Evidence ◽  
Future Research ◽  
Test Accuracy ◽  
Decision Uncertainty

Abstract Background Early and accurate acute kidney injury (AKI) detection may improve patient outcomes and reduce health service costs. This study evaluates the diagnostic accuracy and cost-effectiveness of NephroCheck and NGAL (urine and plasma) biomarker tests used alongside standard care, compared with standard care to detect AKI in hospitalised UK adults. Methods A 90-day decision tree and lifetime Markov cohort model predicted costs, quality adjusted life years (QALYs) and incremental cost-effectiveness ratios (ICERs) from a UK NHS perspective. Test accuracy was informed by a meta-analysis of diagnostic accuracy studies. Clinical trial and observational data informed the link between AKI and health outcomes, health state probabilities, costs and utilities. Value of information (VOI) analysis informed future research priorities. Results Under base case assumptions, the biomarker tests were not cost-effective with ICERs of £105,965 (NephroCheck), £539,041 (NGAL urine BioPorto), £633,846 (NGAL plasma BioPorto) and £725,061 (NGAL urine ARCHITECT) per QALY gained compared to standard care. Results were uncertain, due to limited trial data, with probabilities of cost-effectiveness at £20,000 per QALY ranging from 0 to 99% and 0 to 56% for NephroCheck and NGAL tests respectively. The expected value of perfect information (EVPI) was £66 M, which demonstrated that additional research to resolve decision uncertainty is worthwhile. Conclusions Current evidence is inadequate to support the cost-effectiveness of general use of biomarker tests. Future research evaluating the clinical and cost-effectiveness of test guided implementation of protective care bundles is necessary. Improving the evidence base around the impact of tests on AKI staging, and of AKI staging on clinical outcomes would have the greatest impact on reducing decision uncertainty.

scholarly journals A Single Target Grasp Detection Network Based on Convolutional Neural Network

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Longzhi Zhang ◽  
Dongmei Wu
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Transfer Learning ◽  
High Accuracy ◽  
Experimental Results ◽  
Detection Accuracy ◽  
Single Object ◽  
Single Target ◽  
High Detection ◽  
Good Detection

Grasp detection based on convolutional neural network has gained some achievements. However, overfitting of multilayer convolutional neural network still exists and leads to poor detection precision. To acquire high detection accuracy, a single target grasp detection network that generalizes the fitting of angle and position, based on the convolution neural network, is put forward here. The proposed network regards the image as input and grasping parameters including angle and position as output, with the detection manner of end-to-end. Particularly, preprocessing dataset is to achieve the full coverage to input of model and transfer learning is to avoid overfitting of network. Importantly, a series of experimental results indicate that, for single object grasping, our network has good detection results and high accuracy, which proves that the proposed network has strong generalization in direction and category.

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