INTELLIGENT MONITORING SYSTEM WITH HIGH TEMPERATURE DISTRIBUTED FIBEROPTIC SENSOR FOR POWER PLANT COMBUSTION PROCESSES
The objective of the proposed work is to develop an intelligent distributed fiber optical sensor system for real-time monitoring of high temperature in a boiler furnace in power plants. Of particular interest is the estimation of spatial and temporal distributions of high temperatures within a boiler furnace, which will be essential in assessing and controlling the mechanisms that form and remove pollutants at the source, such as NOx. The basic approach in developing the proposed sensor system is three fold: (1) development of high temperature distributed fiber optical sensor capable of measuring temperatures greater than 2000 C degree with spatial resolution of less than 1 cm; (2) development of distributed parameter system (DPS) models to map the three-dimensional (3D) temperature distribution for the furnace; and (3) development of an intelligent monitoring system for real-time monitoring of the 3D boiler temperature distribution. Under Task 1, the efforts focused on developing an innovative high temperature distributed fiber optic sensor by fabricating in-fiber gratings in single crystal sapphire fibers. So far, our major accomplishments include: Successfully grown alumina cladding layers on single crystal sapphire fibers, successfully fabricated in-fiber gratings in single crystal sapphire fibers, and successfully developed a high temperature distributed fiber optic sensor. Under Task 2, the emphasis has been on putting into place a computational capability for simulation of combustors. A PC workstation was acquired with dual Xeon processors and sufficient memory to support 3-D calculations. An existing license for Fluent software was expanded to include two PC processes, where the existing license was for a Unix workstation. Under Task 3, intelligent state estimation theory is being developed which will map the set of 1D (located judiciously within a 3D environment) measurement data into a 3D temperature profile. This theory presents a semigroup-based approach to the design and training of a system type neural network which performs function extrapolation. The assumption of the semigroup property suffices to guarantee the existence of a generic mathematical architecture and operation which is explicit enough to support the direct design and training of a neural network.
- Research Organization:
- Pennsylvania State University (US)
- Sponsoring Organization:
- (US)
- DOE Contract Number:
- FG26-02NT41532
- OSTI ID:
- 839166
- Resource Relation:
- Other Information: PBD: 26 Dec 2003
- Country of Publication:
- United States
- Language:
- English
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Intelligent Monitoring System with High Temperature Distributed Fiberoptic Sensor for Power Plant Combustion Processes
INTELLIGENT MONITORING SYSTEM WITH HIGH TEMPERATURE DISTRIBUTED FIBEROPTIC SENSOR FOR POWER PLANT COMBUSTION PROCESSES