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Исследовательский проект INTAS

Исследовательский проект INTAS

Initial INTAS project, network or fellowship
Title: Intelligent Adaptive Condition Monitoring of Gas Turbines Based on Markov Modelling
Reference Nr: INTAS-2000-757
Contractual End Date: 31/07/04

Инновационный проект INTAS

Title: Hardware-in-the-Loop Simulation and Testing Technology for Integrated Control-and-Condition-Monitoring Systems of Gas Turbines Using Diagnostic Markov Modelling
Reference Nr: 05-1000007-421
Duration: 2006-2008

Avia Expo, UGATU, Ufa 2007

MAKS-2007, Moscow

China, Nanjing, 2007

Summary:
The proposed innovation comprises a novel technology of Hardware-in-the-Loop (HIL) simulation of gas turbines for cost-effective testing and fine-tuning of

integrated automatic-control-and-condition-monitoring systems, using diagnostic

Markov modelling.

The modelling and testing technology enables the control and monitoring algorithms to be exhaustively tested in close-to-the-real-life conditions, including

realistic simulation of most probable single and multiple faults, along with chains of faults. Multiple faults and chains of faults are modelled using the Markov transition probabilities matrix, where elements are defined based on statistical analysis combined with specialists expert estimates.

In order to link the researchers and prospective users, the exploitation activities will include (1) pilot technology implementation, demonstrating cost-efficient achievement of high flight safety and (2) contacting prospective users via

participation at aero shows and industrial fairs and visits to industrial companies. This will be accompanied by protection of intellectual property rights, market investigation and preparation of promo materials.

The expected outcome consists of improved flight safety which depends largely on the reliable power plant, controlled and monitored by the on-board avionics. The reliability of the monitoring system is achieved through the proposed simulation and testing technology, which provides more deep investigation of the system under a variety of operating conditions and combined faults. The social impact for the innovation is that the time losses due to flight delays/cancellations are reduced. Economically, more reliable condition monitoring improves predictive maintenance, which will substantially reduce ownership costs for the airlines.

The innovative modelling and testing technology should also be of strong interest for organisations connected with other gas turbine applications, such as on-ground installations.

Контактное лицо: Арьков Валентин Юльевич