Accession Number : ADP010165
Title : Multisensor Monitoring of Gear Tooth Fatigue for Predictive Diagnostics
Corporate Author : PENNSYLVANIA STATE UNIV UNIVERSITY PARK APPLIED RESEARCH LAB
Personal Author(s) : Gordon, Grant A. ; Garga, Amulya K. ; Moose, Clark
PDF Url : ADP010165
Report Date : APR 1996
Pagination or Media Count : 12
Abstract : Successful machine diagnostics is critically dependent on the collection and processing of prognostic features that relate back to failure precursors. Since the significance of gear tooth failure is recognized as a critical component to the overall condition of drive train mechanical systems, single gear tooth failure has been examined. By employing a special jig to orient and constrain the gear samples, Hertzian loading was applied along a single contact line on the gear tooth to simulate the conditions seen during operation. Optical, ultrasonic and mechanical sensors measured a variety of observables including load, deflection, and acoustic emission. After monitoring the fatigue test with these three noncommensurate sensors, features of the data could consistently be related to crack growth phenomena. Data collection, analysis, and interpretation are discussed for spur gear samples that show both the absence and presence of cracks and support the validity of the extracted features as failure precursors. Cyclostationary analysis, an advanced signal processing techniques, was used to promote earlier indication and sharper resolution of these measures. The results demonstrate the potential for using nontraditional sensors and techniques, which are more amenable to commercial use, for an in situ monitoring system.
Descriptors : *SYMPOSIA, *MULTISENSORS, *GEAR TEETH, SIGNAL PROCESSING, PREVENTIVE MAINTENANCE, DEFLECTION, ACOUSTIC EMISSIONS, FATIGUE TESTS(MECHANICS).
Subject Categories : Machinery and Tools
Test Facilities, Equipment and Methods
Distribution Statement : APPROVED FOR PUBLIC RELEASE