Document Type

Poster Session

Department

Engineering

Faculty Mentor

James Masi, PhD

Abstract

Currently there are no efficient or inexpensive methods of determining the wear condition of a tool in metal cutting machines. In the past, people have used load cells and strain gauges embedded into a machine tool to detect tool wear. Using broadband microphones in addition to the machine mounted accelerometers and strain gauges, a more complete picture of the tool condition can be obtained. The first step in this research is to measure and interpret vibration and model the structures. Appropriate sensors need to be selected and designed to measure self-excited vibrations. The vibrations of the investigated machines need to be understood by analyzing the sensor signals and isolating these signals from those generated at the tool tip. The remaining vibrations produced by a lathe tool over its life will undergo spectral analyses to determine patterns of wear and develop a more efficient method of determining the wear condition of a tool.

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May 8th, 12:00 AM

Measurement of Tool Wear Through Acoustic Analysis

Currently there are no efficient or inexpensive methods of determining the wear condition of a tool in metal cutting machines. In the past, people have used load cells and strain gauges embedded into a machine tool to detect tool wear. Using broadband microphones in addition to the machine mounted accelerometers and strain gauges, a more complete picture of the tool condition can be obtained. The first step in this research is to measure and interpret vibration and model the structures. Appropriate sensors need to be selected and designed to measure self-excited vibrations. The vibrations of the investigated machines need to be understood by analyzing the sensor signals and isolating these signals from those generated at the tool tip. The remaining vibrations produced by a lathe tool over its life will undergo spectral analyses to determine patterns of wear and develop a more efficient method of determining the wear condition of a tool.

 

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