Rolling element bearings are a critical component of rotating machinery. Timely prediction of bearing faults become of great importance to minimizing unscheduled machine downtime. Most of the bearings experience gradual condition degradation due to repeated mechanical loads.
Vibration signals are often used for bearing diagnosis and prognosis with a predefined threshold. However, false (positive/negative) alarms are often observed, thus leading to unnecessary downtime and expensive corrective maintenance. This is mainly because the thresholds are defined without accounting for bearing physics and a great deal of uncertainty in manufacturing and operation condition. To resolve this difficulty, this study aims at investigating the degradation physics of rolling element bearings using a vibration signal, while accounting for bearing physics and a substantial amount of uncertainty in manufacturing and operation condition. First, bearing feature engineering is thoroughly studied through time
domain and frequency domain analyses. This study proposes the features that are most sensitive to the change in bearing physics. Second, bearing degradation physics is investigated so that the bearing degradation process can be modeled into four degradation stages. To the end, the
proposed idea is demonstrated with vibration data measured from rolling element bearings, which experience accelerated life tested to simulate naturally induced degradation. This study will benefit to enhance physical understanding for bearing faults in various engineering applications.
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