Digital twin-driven system for roller conveyor line: design and control

The key technilogies of ship-welding mobile robot applied to ship-building in plane block production line were researched and realized. The mechanical structure design of the robot was completed. The motion-controlling system of of two-wheel differential driving mobile robot was developed. A novel precision positioning control method of welding torch using ultrasonic motors was putforward. The mechanism and control-driven system of precision positioning system for welding torch were completed. The platform of obstacle avoidance navigation system was designed and the strategies of seam tracking, trajectory and posture adjustment were preliminary studied. The methods and results put forward in the paper could act as the base of deep research on the theories and technologies of ship-welding mobile robot.

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Boosting the Capabilities of Gas Stand Data Acquisition and Control Systems by Using a Digital Twin Based on a Holistic Turbocharger Model

10.1115/icef2021-66745 ◽

2021 ◽

Author(s):

José R. Serrano ◽

Luis Miguel García-Cuevas ◽

Vishnu Samala ◽

Juan Antonio López-Carrillo ◽

Holger Mai

Keyword(s):

Data Acquisition ◽

Control Systems ◽

Heat Fluxes ◽

Testing Time ◽

Time Saving ◽

Digital Twin ◽

Dimensional Modeling ◽

On Line ◽

And Control

Abstract During the last decade, increasingly advanced turbocharger models have been developed for sizing, engine matching and one-dimensional modeling. This work goes further and, instead of using these models for turbocharged engines design or analysis, it implements them in the data acquisition and control system of a turbocharger gas stand. This way, interesting new capabilities arise. The paper shows that there are important synergies between advanced turbocharger gas stand data acquisition and control systems and the modern turbocharger holistic models that have not been deeply exploited until now. They can be summarized as: on-line heat fluxes analysis, in-situ outlier testing points detection, testing time saving and using digital-twin techniques to monitor turbocharger health during testing.

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Data Coverage Assessment on Machine-Learning based Digital Twin for Diagnosis in a Nearly Autonomous Management and Control System

10.13182/t123-33555 ◽

2020 ◽

Author(s):

L. Lin ◽

N. Dinh ◽

L. Wang

Keyword(s):

Machine Learning ◽

Control System ◽

Digital Twin ◽

Data Coverage ◽

Autonomous Management ◽

And Control

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A Concept for Floating Offshore Wind Mooring System Integrity Management Based on Monitoring, Digital Twin and Control Technologies

10.1115/omae2021-61936 ◽

2021 ◽

Author(s):

Alberto Puras Trueba ◽

Jonathan Fernández ◽

Carlos A. Garrido-Mendoza ◽

Alessandro La Grotta ◽

Jon Basurko ◽

...

Keyword(s):

Control Strategies ◽

Offshore Wind ◽

Motion Sensor ◽

Mooring System ◽

Mooring Lines ◽

Efficient Operation ◽

Digital Twin ◽

System Integrity ◽

Integrity Management ◽

And Control

Abstract Efficient operation of mooring systems is of paramount importance to reduce floating offshore wind (FOW) energy costs. MooringSense is an R&D project which explores digitization to enable the implementation of more efficient integrity management strategies (IMS) for FOW mooring systems. In this work, the MooringSense concept is presented. It includes the development of several enablers such as a mooring system digital twin, a smart motion sensor, a structural health monitoring (SHM) system and control strategies at the individual turbine and farm levels. The core of the digital twin (DT) is a high-fidelity fully coupled numerical model which integrates simulation tools to allow predictive operation and maintenance (O&M). Relevant parameters of the coupled model are updated as physical properties evolve due to damages or degradation. The DT assimilates information coming from the physical asset and environmental sensors. Besides, a smart motion sensor provides feedback of the attitude, position, and velocity of the floater to allow the computation of virtual loads in the mooring lines, the detection of damages by the SHM system and the implementation of closed-loop control strategies. Finally, the IMS takes advantage of the mooring system updated condition information to optimize O&M, reduce costs and increase energy production.

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IoT-Based Digital Twin for Energy Cyber-Physical Systems: Design and Implementation

Energies ◽

10.3390/en13184762 ◽

2020 ◽

Vol 13 (18) ◽

pp. 4762 ◽

Cited By ~ 1

Author(s):

Ahmed Saad ◽

Samy Faddel ◽

Osama Mohammed

Keyword(s):

Power Systems ◽

Systems Design ◽

Cyber Physical Systems ◽

Superior Performance ◽

Physical Systems ◽

Digital Twin ◽

Power And Control ◽

Amazon Web Services ◽

High Bandwidth ◽

And Control

With the emergence of distributed energy resources (DERs), with their associated communication and control complexities, there is a need for an efficient platform that can digest all the incoming data and ensure the reliable operation of the power system. The digital twin (DT) is a new concept that can unleash tremendous opportunities and can be used at the different control and security levels of power systems. This paper provides a methodology for the modelling of the implementation of energy cyber-physical systems (ECPSs) that can be used for multiple applications. Two DT types are introduced to cover the high-bandwidth and the low-bandwidth applications that need centric oversight decision making. The concept of the digital twin is validated and tested using Amazon Web Services (AWS) as a cloud host that can incorporate physical and data models as well as being able to receive live measurements from the different actual power and control entities. The experimental results demonstrate the feasibility of the real-time implementation of the DT for the ECPS based on internet of things (IoT) and cloud computing technologies. The normalized mean-square error for the low-bandwidth DT case was 3.7%. In the case of a high-bandwidth DT, the proposed method showed superior performance in reconstructing the voltage estimates, with 98.2% accuracy from only the controllers’ states.

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SphereWalker: A Hexapod Walking Machine

Journal of Autonomous Vehicles and Systems ◽

10.1115/1.4048483 ◽

2020 ◽

Vol 1 (1) ◽

Author(s):

Pierre Larochelle ◽

Xiaoyang Mao

Keyword(s):

Control System ◽

The Other ◽

Walking Machine ◽

Digital Twin ◽

Physical Prototype ◽

And Control

Abstract This article describes the design and the development of a novel six-legged robotic walking machine named SphereWalker. The six legs are arranged into pairs, and each pair of legs is supported and actuated by a single spherical four-bar mechanism. Two of the four-bar mechanisms are operated in a synchronous fashion, while the middle one is operated at 180 deg out of phase with respect to the other two. A physical prototype has been built, a digital twin has been generated, an actuation and control system has been designed, and the technology has been patented.

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Development and Assessment of a Nearly Autonomous Management and Control System During a Single Loss of Flow Accident

Volume 1: Beyond Design Basis; Codes and Standards; Computational Fluid Dynamics (CFD); Decontamination and Decommissioning; Nuclear Fuel and Engineering; Nuclear Plant Engineering ◽

10.1115/icone2020-16908 ◽

2020 ◽

Author(s):

Linyu Lin ◽

Paridhi Athe ◽

Pascal Rouxelin ◽

Nam Dinh ◽

Jeffrey Lane

Keyword(s):

Knowledge Base ◽

Confusion Matrix ◽

Data Generation ◽

Digital Twin ◽

Control Functions ◽

Digital Twins ◽

Twin Models ◽

Autonomous Management ◽

And Performance ◽

And Control

Abstract In this work, a Nearly Autonomous Management and Control (NAMAC) system is designed to diagnose the reactor state and provide recommendations to the operator for maintaining the safety and performance of the reactor. A three layer-hierarchical workflow is suggested to guide the design and development of the NAMAC system. The three layers in this workflow corresponds to knowledge base, digital twin developmental layer (for different NAMAC functions), and NAMAC operational layer. Digital twin in NAMAC is described as knowledge acquisition system to support different autonomous control functions. Therefore, based on the knowledge base, a set of digital twin models is trained to determine the plant state, predict behavior of physical components or systems, and rank available control options. The trained digital twin models are assembled according to NAMAC operational workflow to support decision-making process in selecting the optimal control actions during an accident scenario. To demonstrate the capability of the NAMAC system, a case study is designed, where a baseline NAMAC is implemented for operating a simulator of the Experimental Breeder Reactor II (EBR-II) during a single loss of flow accident. Training database for development of digital twin models is obtained by sampling the control parameters in the GOTHIC data generation engine. After the training and testing, the digital twins are assembled into a NAMAC system according to the operational workflow. This NAMAC system is coupled with the GOTHIC plant simulator, and a confusion matrix is generated to illustrate the accuracy and robustness of implemented NAMAC system. It is found that within the training databases, NAMAC can make reasonable recommendations with zero confusion rate. However, when the scenario is beyond the training cases, the confusion rate increases, especially when the scenarios are more severe. Therefore, a discrepancy checker is added to detect unexpected reactor states and alert operators for safety-minded actions.

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