Health Index Construction for Crack Fault Diagnosis of Rotating Shaft by Full-Scale Experiments
Publication: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 10, Issue 1
Abstract
Crack fracture in large rotating shaft results in catastrophic failure in many industrial plants. To prevent this, a health index model is developed to diagnose the crack severity by the vibration sensor. A full-scale test rig was constructed with a similar configuration to the field conditions to reduce the associated uncertainties. Vibration signals were collected under various operating conditions for artificial cracks with different severities and locations. After identifying useful features and operation parameters, which include 1st shaft harmonic frequency (1X), 9th frequency domain feature (FF9), and the rotating speed, random forest regression was employed to establish the health index model using them. Uncertainties were accounted for in determining the thresholds of normal and crack conditions. In order to apply the model in the field, features from the field equipment were scaled to those of the test rig in a statistical manner. Health ranges for the normal, caution, and danger with respect to the crack severity are recommended for practical applications.
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Data Availability Statement
All data, models, and code generated or used during the study appear in the published article.
Acknowledgments
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (2020R1A4A4079904).
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Published In
ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 10 • Issue 1 • March 2024
Copyright
© 2023 American Society of Civil Engineers.
History
Received: May 8, 2023
Accepted: Aug 19, 2023
Published online: Oct 25, 2023
Published in print: Mar 1, 2024
Discussion open until: Mar 25, 2024
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