DETERMINATION OF THE WEAR FAULT IN SPUR GEAR SYSTEM USING STATISTICAL PROCESS CONTROL METHOD

Vibration analysis is one of the early warning methods widely used in obtaining information about faults occurring on the machine elements and structures. In this method, gear fault detection can be performed by analyzing of the vibration test results using signal processing, artificial intelligence and statistical analysis methods. The objective of this study is detection the existence of wear by examining changes in the vibrations of spur gears due to wear faults in statistical process control carts. In this study, artificial wear was created on the surfaces of spur gears in order to be examined in gears test rig. Then, these gears were attached and vibrations data were recorded by operating the system at various loading and number of cycles conditions. Detection of fault was demonstrated by analyzing undeformed and worn gears data in statistical process control carts by means of real-time experimental studies.