Coal-Fired Central Energy Plant Operations Expert System and Editor (CEPES Version 4.3 and CEPES Editor Version 2.4) User's Guide.

Abstract

Rising operation and maintenance (O&M) costs of central heating plants have forced the Army to seek alternative methods of running these facilities. Computer technology offers a great potential to automate and assist in many O&M tasks by helping diagnose equipment malfunctions and failures. An automated diagnostic tool for coal-fired heating plant equipment could reduce the demand for human labor, freeing personnel for higher priority work; reduce downtime for repair; promote thermal efficiency; and improve on-line reliability. In this project researchers developed a Coal-Fired Central Energy Plant Operations Expert System (CEPES), which analyzes and recommends solutions to coal-fired boiler operational problems. This phase of the project included the selection of hardware and software platforms, development and coding of the expert system, and knowledge acquisition for one module for field testing. The design of CEPES is unique due to the development of a system editor (CEPES Editor) that allows a field engineer to construct a plant configuration and insert expertise without the use of source level code. (MM)

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1995
Accession Number
ADA296883

Entities

People

  • Madhavi Kantameni
  • Mike Brewer
  • Ralph Moshage
  • Todd Blindt
  • Tony Magliero

Organizations

  • Construction Engineering Research Laboratory

Tags

Communities of Interest

  • Biomedical
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Acquisition
  • Computer Programming
  • Computer Programs
  • Computers
  • Downtime
  • Efficiency
  • Engineering
  • Engineers
  • Expert Systems
  • Heating
  • Heating Plants
  • Instructions
  • Operating Systems
  • Platforms
  • Reliability
  • Test And Evaluation
  • Thermal Efficiency

Fields of Study

  • Engineering

Readers

  • Computer Science.
  • Energy Conservation and Renewable Energy Engineering.
  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.