Reuse of models in the lifecycle of production plants using HiL simulation models for diagnosis

Kain, Sebastian; Schiller, Frank; Dominka, Sven

doi:10.1109/isie.2008.4677244

Cited by 12 publications

(6 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It can be used for determining the nominal state of the plant. If the simulation is operated in parallel to the plant, the measurable states of the real plant and of the simulation can be compared and deviations can be detected (Kain et al, 2008;Kain et al 2010;). Thus, the signals in the simulation can be used for realizing diagnostics.…”

Section: Methodsmentioning

confidence: 99%

“…Additionally, if the control system was optimized in the engineering phase according to assumed process parameters divergent from the current situation, changes of the parameters in the control system can improve the plant behavior. Therefore, the models of HiL Simulation can be applied predicting the behavior of the controlled plant, called Forward Simulation (Kain et al, 2008;Kain et al 2010;). Optimizing the control system offline based on verified HiL Simulation models representing the behavior of the plant in detail offers several advantages: In a first step, the optimal parameters can be determined based on simulation experiments with diverse constraints without influencing the real plant.…”

Section: Forward Simulationmentioning

confidence: 99%

See 1 more Smart Citation

Methodology for Reusing Real-time HiL Simulation Models in the Commissioning and Operation Phase of Industrial Production Plants

Kain¹,

Schiller²,

Dominka³

2011

Intelligent Mechatronics

Self Cite

View full text Add to dashboard Cite

Section: Methodsmentioning

confidence: 99%

Section: Forward Simulationmentioning

confidence: 99%

Methodology for Reusing Real-time HiL Simulation Models in the Commissioning and Operation Phase of Industrial Production Plants

Kain¹,

Schiller²,

Dominka³

2011

Intelligent Mechatronics

Self Cite

View full text Add to dashboard Cite

“…It is already scheduled, but not yet implemented. The need to use simulation or engineering data parallel to the production process has also been recognized by [20].…”

Section: Figure 14 Opc Ua Client and Address Spacementioning

confidence: 99%

OPC UA supporting the automated engineering of production monitoring and control systems

Schleipen

2008

2008 IEEE International Conference on Emerging Technologies and Factory Automation

View full text Add to dashboard Cite

Control systems monitor and control production plants and manufacturing systems. Before they can be taken into operation, they have to be configured. To automate this process, which is called engineering, a standardized exchange format is required that forms the basis of the work of all those who are involved in the project and that is understood by anyone involved. In addition, the contents to be exchanged have to be transmitted on the basis of a standardized communication mechanism with maximum efficiency. This article will present a standardized communication method capable of fulfilling these requirements. On the basis of an OPC UA framework acting as a communication, synchronization and processing mechanism, the opportunities of the Unified Architecture and its application in the automated engineering of Control systems will be evaluated

show abstract

“…The appearance of industrial applications based on tracking simulators has been hindered by the high development cost and time-consuming maintenance of first principle models (FPMs) [1]. In order to overcome this, simulation models developed during the process engineering could be used for implementing tracking simulators [4]. However, because these simulation models are created when the plant is not yet functioning, their results cannot be tuned using measurements from the targeted physical system and only data series of similar process plants are used as a reference.…”

Section: Introductionmentioning

confidence: 99%

Towards a systematic path for dynamic simulation to plant operation: OPC UA-enabled model adaptation method for tracking simulation

Martínez

Karhela

Ruusu

et al. 2017

IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society

View full text Add to dashboard Cite

A tracking simulator is an online simulation system that utilizes dynamic parameter estimation for calibrating model parameters to achieve state synchronization with the process. It can be utilized as a plant-wide virtual sensors or as a predictive tool to provide production forecasts based on the current state of the plant. The appearance of industrial applications based on tracking simulators has been hindered by high development cost and time-consuming sustainability of simulation models. In order to overcome this, dynamic simulation models developed during the process design and engineering stages could be used for implementing industrial tracking simulators. However, before these models can be utilized online, they require going through a model adaptation procedure where their structure and parameters are updated. This paper presents a model adaptation method for the implementation of tracking simulators which utilizes OPC Unified Architecture to adapt simulation models developed during the engineering phases of the process plant and apply them at the operation and maintenance stages. In this work, the method is described, implemented and tested using a representative process.

show abstract

Reuse of models in the lifecycle of production plants using HiL simulation models for diagnosis

Cited by 12 publications

References 12 publications

Methodology for Reusing Real-time HiL Simulation Models in the Commissioning and Operation Phase of Industrial Production Plants

Methodology for Reusing Real-time HiL Simulation Models in the Commissioning and Operation Phase of Industrial Production Plants

OPC UA supporting the automated engineering of production monitoring and control systems

Towards a systematic path for dynamic simulation to plant operation: OPC UA-enabled model adaptation method for tracking simulation

Contact Info

Product

Resources

About