@article { author = {Eissa, M. and Gomaa, F. and Khader, K.}, title = {BEARING'S EARLY FAULT DETECTION USING VIBRATION ANALYSIS}, journal = {The International Conference on Applied Mechanics and Mechanical Engineering}, volume = {18}, number = {18th International Conference on Applied Mechanics and Mechanical Engineering.}, pages = {1-22}, year = {2018}, publisher = {Military Technical College}, issn = {2636-4352}, eissn = {2636-4360}, doi = {10.21608/amme.2018.34974}, abstract = {ABSTRACTOver recent decades, predictive maintenance's usage attracted the attention ofmaintenance specialists in some important industries. Moreover, machinery conditionmonitoring is an effective indicator for planning the maintenance schedules. Machinemonitoring or early detection of incipient fault is an important judgment tool of themachine's health at critical parts such as; gears and bearings. Furthermore, vibrationmonitoringprocess can be achieved by experienced operators using their visualinspection. However, many specialists in maintenance field recommend using thecomputerized inspection to meet increased demand for the automated monitoringapplications and helpful engineering software.This paper deals with condition monitoring of machines in addition to designingmachine monitoring assisting tool as software for time saving. This software ispresented as fast tool affording instantaneous calculations of bearing faultfrequencies for different bearing types. In addition, the presented software caninstantaneously calculate the basic dynamic load rating considering bearing ratinglife.}, keywords = {condition monitoring,Wavelet Analysis,Bearing Lifetime,Computer Software}, url = {https://amme.journals.ekb.eg/article_34974.html}, eprint = {https://amme.journals.ekb.eg/article_34974_a9b138ec9a642dac2e4a02979fb49a9d.pdf} }