الفهرس 
Types of bearings based on the type of contactOnly 14 pages are availabe for public view
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Abstract
Machine monitoring or early detection of primary fault, aims to survey the machine health or condition at critical locations as bearings. As well as it possibly predicts a future failure. At a certain stage of defects progress or severity, a scheduled maintenance can be made in order to replace the damaged element. Hence, the production can continue without unnecessary delays. This thesis deals with the requirements of an instantaneous effective calculated dynamic load that cause decreases in the lifetime of ball bearing software. This software to assist in the process of monitoring machinery for time saving which is the main goal of the monitoring process.
The purpose of this thesis is focus on the latest developments in the area of early fault detection in rotating machine. Also, evolution diagnosis in rotating machine based on vibration analysis. Bearing is considered to improve detection consentience in fault identification using de-noising wavelet transform (WT) technique.
This thesis reports first step actual test conducted as online test simulated of rotating system. This test to investigate type of fault and diagnostic vibration technique in rotating machine. Second step for localization damage and its severity in bearing to obtain vibration of dynamic characteristic. Using classical modal analysis (CMA) for bearing with different size of damage and de-noising wavelet transform (WT) technique.
The test performance in this study were used to validate and verify finite element method (FEM) to study the actual behaviour. The output only modal test was performance to rotating machine structure designed for measuring vibration response at variable speed to detect any damage in vibration spectrum. The different available diagnosis vibration techniques were applied CMA furthermore operation modal analysis (OMA) for frequency analysis, envelop and de-noising wavelet transform (WT) technique.
This test acted as control test for measured severe damage to assessment continuous wavelet transform (CWT) and discrete wavelet transform (DWT) techniques. Using these techniques improve detection confidence in fault identifications using WT de-noising.
In this thesis, it was found that the wavelet transform (WT) is more effective than frequency domain in detection local defect which are in outer race in ball bearing and additional information demonstrate the sensitivity of detection fault severity. The study has provided detailed valuable experimental and numerical data for bearing fault detection in rotating machine.