Efficient address space generation for an OPC UA server

Girbea, Alina; Nechifor, Septimiu; Sisak, F.; Perniu, Liviu

doi:10.1002/spe.1076

Cited by 13 publications

(3 citation statements)

References 4 publications

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“…In a Big Data perspective, by comparing simulation results and patient evolution over different time ranges, such an approach is useful for predicting patient-specific disease evolution and outcome. This can also be combined with optimization based frameworks [15][16][17].…”

Section: Discussionmentioning

confidence: 98%

A method for modeling surrounding tissue support and its global effects on arterial hemodynamics

Itu

Suciu

2014

IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI)

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We propose a methodology for separating the total stiffness of arteries, determined in vivo, into stiffness of the arterial wall and stiffness of the surrounding tissue. An effective perivascular pressure is considered which introduces a radial constraint. Next, based on vivo data, acquired at diastolic pressure, the cross-sectional area at zero pressure is estimated. Finally, the stiffness of the arterial wall and of the surrounding tissue are determined based on a model with two parallel springs. By employing a reduced-order multiscale model, the methodology is used for studying the global effects of surrounding tissue support on arterial hemodynamics. The main effects are: higher wave speed, earlier arriving backward travelling pressure and flow rate waves, lower total compliance, higher pressure pulse, and reduced arterial cross-sectional areas. In a Big Data perspective, by combining this methodology with arterial wall growth models and by comparing simulation results and patient evolution over different time ranges, such an approach is useful for predicting patient-specific disease evolution and outcome.

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Section: Discussionmentioning

confidence: 98%

A method for modeling surrounding tissue support and its global effects on arterial hemodynamics

Itu

Suciu

2014

IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI)

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“…Developing the information model for a complex manufacturing system requires a huge amount of programming work. Girbea et al [42] proposed several algorithms that aid an efficient and automatic generation of address space in OPC UA servers. Owing to the generic and flexible information modelling method, OPC UA has also been implemented in various types of process monitoring and control systems in different industries such as Smart Grid [43], Oil and Gas production [44] and Public transportation systems [45].…”

Section: Opc Ua Related Researchmentioning

confidence: 99%

A Cyber-Physical Machine Tools Platform using OPC UA and MTConnect

Liu

Vengayil

Lu³

et al. 2019

Journal of Manufacturing Systems

186

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Cyber-Physical Machine Tools (CPMT) represent a new generation of machine tools that are smarter, well connected, widely accessible, more adaptive and more autonomous. Development of CPMT requires standardized information modelling method and communication protocols for machine tools. This paper proposes a CPMT Platform based on OPC UA and MTConnect that enables standardized, interoperable and efficient data communication among machine tools and various types of software applications. First, a development method for OPC UA-based CPMT is proposed based on a generic OPC UA information model for CNC machine tools. Second, to address the issue of interoperability between OPC UA and MTConnect, an MTConnect to OPC UA interface is developed to transform MTConnect information model and data to their OPC UA counterparts. An OPC UA-based CPMT prototype is developed and further integrated with a previously developed MTConnect-based CPMT to establish a CPMT Platform. Third, different applications are developed to demonstrate the advantages of the proposed CPMT Platform, including an OPC UA Client, an advanced AR-assisted wearable Human-Machine Interface and a conceptual framework for CPMT powered cloud manufacturing environment. Experimental results have proven that the proposed CPMT Platform can significantly improve the overall production efficiency and effectiveness in the shop floor.

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“…Users may map the OPC point name, value, quality and timestamp by ODBC source table column, custom queries or through preconfigured stored procedures. CAD applications that require connectivity to databases can use this MatrikonOPC Server to access real-time and historical process data that is archived [7].…”

Section: The Interface Servicementioning

confidence: 99%

Solution for Real Time Design Data Transport for the CAD Parametric Features

Pomazan¹,

Sintea²,

Bordea³

et al. 2012

Proceedings of the 23rd International DAAAM Symposium 2012

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Designs that work in many models can be included in parametric parts defined in Autodesk Inventor® as iParts. Parameter values are to be selected from a list, or can be specified, when the iPart are placed in an assembly. There are many situations when, the custom parameters table can be remote accessed and filled-in with data, needed in the real situation. This paper offers a solution for data transportation and import into the appropriate format, so that the designer that builds the digital prototype of a part or assembly has constantly the newest data provided from the remote industrial context (real time in-situ measurements, dimensional modifications, geometric relationships).

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Efficient address space generation for an OPC UA server

Cited by 13 publications

References 4 publications

A method for modeling surrounding tissue support and its global effects on arterial hemodynamics

A method for modeling surrounding tissue support and its global effects on arterial hemodynamics

A Cyber-Physical Machine Tools Platform using OPC UA and MTConnect

Solution for Real Time Design Data Transport for the CAD Parametric Features

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