Masters Theses

Date of Award

5-1992

Degree Type

Thesis

Degree Name

Master of Science

Major

Aerospace Engineering

Major Professor

Ching F. Lo

Abstract

The rapid detection of flow instabilities like rotating stall and surge is of paramount importance in operating axial-flow compressors safely and efficiently. Monitoring these phenomena before they have reached full strength is difficult, and requires watching the axial-flow compressor in great detail. A number of measurement methods exist which can aid in this detection: they include, hot-wire anemometers, thermocouples, pressure transducers, strain gages, optical sensors, and acoustical sensors. Research is currently under way on using high response static pressure transducers to detect rotating stall before its inception, and shows some promise for the early recognition of surge and stall. The use of artificial intelligence to speed up the detection of these flow instabilities has been shown to have great potential for implementing the monitoring and control process. The utilization of artificial neural networks and correlation matching for the detection process has been demonstrated. Pattern recognition and expert systems are also available techniques for the identification of rotating stall and surge in axial-flow compressors.

Download
Files over 3MB may be slow to open. For best results, right-click and select "save as..."

Share

COinS