Rotary Machines Fault Diagnosis based on Principal Component Analysis

Rotating machines are commonly used in industrial applications. Mechanical faults such as rotor unbalance, shaft misalignment, pulley structural looseness, and bearing leading to unplanned shutdown based on the severity of these faults. The condition monitoring technique vibration analysis has potential detect diagnose a great number early stage However, some mechanical have correlated features ambiguous diagnosis identify distinguish In this paper, proposed method Principal Component Analysis (PCA) is presented produce uncorrelated Components (PCs) healthy different faulty cases. A test rig was prepared simulate group belt damage, combined unbalance with damage. conventional measurements were collected for each case their extracted equivalent PCs. It found that produced PCs superior majority simulated which rest paper.