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Wednesday, 16 Jan 2019

PI-Compare: Matching On-Line Historian Databases and Simulators

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Hyperion introduces a PI System comparison tool to obtain additional value from Operator Training Simulators

Athens, Greece. 19 November 2007. Hyperion Systems Engineering Ltd., the leading independent Operator Training Simulator supplier and provider of lump-sum turn-key solutions and services to the process industries worldwide, announced the availability of a PI system historian database comparison tool for use with process simulators.

PI-Compare is an easy to use tool used to identify the simulator initial condition that closely matches a PI system recorded plant state just before a disturbance. Instructors and engineers can then quickly identify and use the simulation which matches that plant state and use the simulator to investigate and/or train operators in the characteristics of the disturbance and in mitigating its effects.

The tool features:
  • An engineering unit conversion manager; this ensures that the data comparison is done in the same unit set.
  • A user interface based on MS Excel, which is familiar to the industrial user, and having the flexibility to support future enhancements of the comparison engine for other data historian systems.
  • A report showing any variables in the selected initial condition having a significant deviation from the plant data.
Dean Jones, Vice President for Modeling and Simulation Solutions at Hyperion, stated: “In Hyperion we continue to develop novel tools to support the needs of our customers. Dynamic modeling and Operator Training Simulators generate significant value for the process industries. Our tools such as PI-compare enable customers to obtain additional value from their investments.

About Operator Training Systems
Operator Training Simulators are detailed, high fidelity, real-time simulation systems that are custom-built to match the dynamic behavior of single or multiple plant units and their associated control systems. An Operator Training System may be used throughout the plant lifecycle to train operating crews, resulting in fewer operating errors and quicker and safer startups and shutdowns, improve plant reliability due to improved response to abnormal situations, optimize throughput and product quality, and provide the basis for evaluation of control strategies.