Model-Based Sensor Placement for Component Condition Monitoring and Fault Diagnosis in Fossil Energy Email Page
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Performer: 
Texas Tech University System
A two-tier sensor network will monitor conditions of<br/>plant components and diagnose faults in the plant<br/>system to improve overall health of the gasification<br/>plant. (Source: Texas Tech)
A two-tier sensor network will monitor conditions of
plant components and diagnose faults in the plant
system to improve overall health of the gasification
plant. (Source: Texas Tech)
Website:  Texas Tech University System
Award Number:  FE0005749
Project Duration:  10/01/2010 – 12/31/2014
Total Award Value:  $981,909.00
DOE Share:  $757,992.00
Performer Share:  $223,917.00
Technology Area:  Coal Utilization Science
Key Technology:  Sensors and Controls
Location:  Lubbock, Texas

Project Description

The overall objective of this work is the development of model-based sensor placement algorithms for maximizing the robustness and effectiveness of the sensor network to monitor the plant health both at the unit level and at the systems level. This will be achieved by developing a two-tier sensor network algorithm capable of performing component condition monitoring and system-level fault diagnosis. The algorithms will be implemented on a coal-based plant-wide simulation of an Integrated Gasification Combined Cycle (IGCC) with a rigorous gasifier model. The work is also extendable to similar fossil energy plants.

Project Benefits

This project will focus on development of algorithms that will improve the operation and performance of advanced power generating systems. Improvements in robustness and effectiveness of power industry algorithms will lead to higher efficiency power plant opearation, improved grid dispatch, and reduced emissions.

Contact Information

Federal Project Manager 
Steven Seachman: Steven.Seachman@netl.doe.gov
Technology Manager 
Susan Maley: Susan.Maley@netl.doe.gov
Principal Investigator 
Raghunathan Rengasamy: Raghu.Rengasamy@ttu.edu

 

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