Machinery Sensing: Analysis and Optimization

Principal Investigator: Professor Pratt

AWaRE REU Researcher: Loren Hahn, Bethel College

Project Description: Equipment health monitoring and system characterization are important to ensure reliable and safe operation. The Machinery Sensing project involved the investigation of practical methods for achieving these objectives using radio-frequency (RF) non-contact sensors to detect vibrations, debris, and abnormal behaviors in machinery. Sensor data was collected in an industrial plant known as I/N Tek on a machine where conventional health monitoring methods could not easily be employed.

Finding: The project provided evidence of the value of RF-based sensing methods for health monitoring in certain industrial settings. Data analysis revealed a differential performance in gearbox responses, suggesting that one of the gearboxes was in a declining state of health relative to the other gearbox.