INTELLIGENT MONITORING SYSTEM WITH HIGH TEMPERATURE DISTRIBUTED FIBEROPTIC SENSOR FOR POWER PLANT COMBUSTION PROCESSES

PDF Version Also Available for Download.

Description

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 ... continued below

Physical Description

28 pages

Creation Information

Lee, Kwang Y.; Yin, Stuart S. & Boheman, Andre December 26, 2003.

Context

This report is part of the collection entitled: Office of Scientific & Technical Information Technical Reports and was provided by UNT Libraries Government Documents Department to Digital Library, a digital repository hosted by the UNT Libraries. More information about this report can be viewed below.

Who

People and organizations associated with either the creation of this report or its content.

Sponsor

Publisher

  • Pennsylvania State University
    Publisher Info: Pennsylvania State University (United States)
    Place of Publication: [University Park, Pennsylvania]

Provided By

UNT Libraries Government Documents Department

Serving as both a federal and a state depository library, the UNT Libraries Government Documents Department maintains millions of items in a variety of formats. The department is a member of the FDLP Content Partnerships Program and an Affiliated Archive of the National Archives.

Contact Us

What

Descriptive information to help identify this report. Follow the links below to find similar items on the Digital Library.

Description

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.

Physical Description

28 pages

Notes

OSTI as DE00839166

Source

  • Other Information: PBD: 26 Dec 2003

Language

Item Type

Identifier

Unique identifying numbers for this report in the Digital Library or other systems.

  • Report No.: NONE
  • Grant Number: FG26-02NT41532
  • DOI: 10.2172/839166 | External Link
  • Office of Scientific & Technical Information Report Number: 839166
  • Archival Resource Key: ark:/67531/metadc783125

Collections

This report is part of the following collection of related materials.

Office of Scientific & Technical Information Technical Reports

Reports, articles and other documents harvested from the Office of Scientific and Technical Information.

Office of Scientific and Technical Information (OSTI) is the Department of Energy (DOE) office that collects, preserves, and disseminates DOE-sponsored research and development (R&D) results that are the outcomes of R&D projects or other funded activities at DOE labs and facilities nationwide and grantees at universities and other institutions.

What responsibilities do I have when using this report?

When

Dates and time periods associated with this report.

Creation Date

  • December 26, 2003

Added to The UNT Digital Library

  • Dec. 3, 2015, 9:30 a.m.

Description Last Updated

  • Feb. 20, 2017, 1:27 p.m.

Usage Statistics

When was this report last used?

Yesterday: 0
Past 30 days: 0
Total Uses: 5

Interact With This Report

Here are some suggestions for what to do next.

Start Reading

PDF Version Also Available for Download.

International Image Interoperability Framework

IIF Logo

We support the IIIF Presentation API

Lee, Kwang Y.; Yin, Stuart S. & Boheman, Andre. INTELLIGENT MONITORING SYSTEM WITH HIGH TEMPERATURE DISTRIBUTED FIBEROPTIC SENSOR FOR POWER PLANT COMBUSTION PROCESSES, report, December 26, 2003; [University Park, Pennsylvania]. (digital.library.unt.edu/ark:/67531/metadc783125/: accessed September 22, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.