Instrumentation System for High Speed Data Sampling of Electrical Machinery.

Abstract

Computer models of AC generators have been developed, but they are cumbersome, complicated, and lengthy. Reducing the complexity while retaining sufficient accuracy would reduce the cost of the model, thereby reducing the test and development costs. High speed data sampling of an AC generation system is required to investigate the possibility of modifying the model, and, to determine the accuracy limits of the revised model. Verification of the revised model will require measurements from several points in the electrical system as nearly simultaneously as possible and at short intervals. The objective of this paper is to develop criteria for an instrumentation system capable of acquiring the data necessary for the modification of the computer model. Development of the criteria involves analyzing the environment, the available major items of equipment (installed and moveable), the variables of the model, and the acquisition and processing of quality analog signals of these model variables. The main items of installed equipment from which measurements were to be taken are an MG set and an exciter which are located in the power laboratory. The MG set consists of a synchronous motor, a DC generator, and an AC generator. The exciter consists of an induction motor and a DC generator.

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Document Details

Document Type
Technical Report
Publication Date
Dec 15, 1975
Accession Number
ADA052637

Entities

People

  • Glen Edward Brisbine

Organizations

  • Oregon State University

Tags

Communities of Interest

  • Advanced Electronics
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Accuracy
  • Acquisition
  • Amplifiers
  • Capacitance
  • Computers
  • Couplings
  • Data Acquisition
  • Diagrams
  • Equivalent Circuits
  • Frequency
  • Generators
  • Impedance
  • Instrumentation
  • Measurement
  • Power Supplies
  • Rejection
  • Resistance

Readers

  • Computational Modeling and Simulation
  • Computer Science/Computer Engineering/Data Science/Digital Signal Processing.
  • Electrical Engineering