Predictive Models of an Electro-mechanical Driving System for Failure Testing of Strain Gauges

Author

Brent Ellis, University of Tennessee - Knoxville

Date of Award

8-2007

Degree Type

Thesis

Degree Name

Master of Science

Major

Electrical Engineering

Major Professor

L. Montgomery Smith

Committee Members

Bruce Bomar, Roy Schulz

Abstract

Strain gauges are bonded at high stress locations on the surface of critical structural components such as turbine blades to measure fatigue characteristics and detect early warning signs of high cycle fatigue. However, strain gauges do not always report expected measurements. The usual response by maintenance technicians to these failing signals is to investigate the component for weakness, check the placement of the gauges on the component, or examine the instrumentation for failure or damage. However, little research has been conducted to show when the failing signals are the fault of the strain gauge. Such failure modes of strain gauges include improper gauge installation, over-straining, operating outside the temperature limits, physical damage and environmental wear, and improper gauge selection. Failure Modes and Effects Analysis, FMEA, is a methodology for monitoring failure modes and their potential effects, causes, and solutions. This research consisted of the introductory steps in developing and analyzing a laboratory setup for FMEA strain gauge testing and analysis. The primary goal of this research was to develop predictive models for strain gauge responses under controlled laboratory conditions. A testing station was developed that generated a mechanical motion on a beam, subjecting strain gauges to a sinusoidally-varying strain. Predictive models of the testing station were developed and experimentally analyzed. Models were also developed for two particular failure modes, debonding and wire lead termination, and experimental analysis was conducted. In general, the models adequately describe the operation of a strain gauge operating under normal conditions and in the studied failure mode. Predicted and experimental data are presented that show the characteristic signals in terms of time domain, histogram, and frequency domain analysis.

Recommended Citation

Ellis, Brent, "Predictive Models of an Electro-mechanical Driving System for Failure Testing of Strain Gauges. " Master's Thesis, University of Tennessee, 2007.
https://trace.tennessee.edu/utk_gradthes/125