CONSIDERATIONS ON ORDER ANALYSIS AND FAULT DETECTION ON A SPEED REDUCER WITH HELICAL GEARS

Iulian LUPEA

Abstract


Fault diagnosis on a test rig with a speed reducer and helical gears is observed by using order analysis. The vibration is monitored on the reducer housing with a triaxial accelerometer. Various speed profiles are imposed with the variable frequency drive and tracked with a tachometer. Three load levels are imposed with a magnetic powder brake. Based on colormaps, orders and power spectrum peaks were assigned to the associated machine elements of the speed reducer, the AC motor, and shafts. GMFs for the first and the second gear pairs, their harmonics, the frequency peaks of the input and output reducer's shafts, the kurtosis value and sideband energy ratio were considered to detect a fault in the helical pinion of the first stage of the reducer and the misalignment at the interface between the speed reducer and the powder brake.


Full Text:

PDF

References


Randall, R.B., Vibration-Based Condition Monitoring: Industrial, Automotive and Aerospace Applications, John Wiley & Sons: Hoboken, NJ, USA, 2021.

Scheffer C., Girdhar P., Practical Machinery Vibration Analysis and Predictive Maintenance, First Edition, Newnes, 2004.

Maurice L. Adams, Jr., Rotating Machinery Vibration, CRC Press, 2000.

Mogal, S.P., Lalwani, D.I., Experimental

investigation of unbalance and misalignment in rotor bearing system using order analysis, Journal of Measurements in Engineering, Vol. 3, Issue 4, 2015.

Li, Y.; Chen, Z.;Wang, L. A New Order Tracking Method for Fault Diagnosis of Gearbox under Non-Stationary Working Conditions Based on In Situ Gravity Acceleration Decomposition. Appl. Sci. 14., 2024.

Barrios, M. L. R., Montero, F. E. H., Mancilla, J. C. G., & Marín, E. P. Tacho-less automatic rotational speed estimation (TARSE) for a mechanical system with gear pair under non-stationary conditions. Measurement, 145, 480-494, 2019.

Getting Started with Order Analysis, Toolkit User Manual, www.ni.com., 2007

Lupea, I., Considerations on order analysis

of a rotating machinery test rig, Acta Technica Napocensis, Series: Applied Mathematics, Mechanics, and Engineering, Vol. 64, Issue III, 2021.

ISO 10825; Gears—Wear and Damage to

Gear Teeth., International Organization for Standardization: Geneve, Switzerland, 2022.

Fyfe,K.,R., Munck,E., Analysis of

computed order tracking, Mechanical Systems and Signal Processing, 11(2), 1997.

Order Analysis - Solution User Manual -

Order Tracking Analysis V23-1, www.dewesoft.com 2023.

Bagri, I., Tahiry, K., Hraiba, A., Touil, A.,

Mousrij, A. Vibration Signal Analysis for Intelligent Rotating Machinery Diagnosis and Prognosis: A Comprehensive Systematic Literature Review. Vibration,7, 2024.

Lupea, L., Lupea, M., Detecting Helical

Gearbox Defects from Raw Vibration Signal Using Convolutional Neural Networks, Sensors, 23, 8769, 2023.

Wang, KS, Feng,K., Zuo,M., An order spectrum based method to ensure consistent

monitoring through Vold-Kalman filter order tracking, 19th World Conf. Non- Destructive Testing, 2016.

Gade,S., Herlufsen, H., Konstantin-Hansen, H., Vold, H., B&K, Tech. review: Characteristics of the Vold-Kalman Order Tracking Filter, www.bksv.com, 1999.

Wu,J-D, Wang, Y., Chiang,P., Bai,M.,

A study of fault diagnosis in a scooter using adaptive order tracking technique and neural network, Expert Systems with Applications, 36, 2009.

Rodrigues, C.E., e.a., Machine Learning

Techniques for Fault Diagnosis of rotating machines using spectrum images of vibration orbits, www.sba.org.br, 2020.

Zhao, D., Li, J., Cheng,W, Feature Extraction of Faulty Rolling Element Bearing under Variable Rotational Speed and Gear Interferences Conditions, Hindawi Publishing Corporation Shock and Vibration, Vol. 2015.

Lupea, I., Lupea, M., Continuous Wavelet

Transform and CNN for Fault Detection in a Helical Gearbox. Appl. Sci., 15, 950, 2025.

Lupea, I., Lupea, M., Coroian, A., Helical

Gearbox Defect Detection with Machine Learning Using Regular Mesh Components and Sidebands. Sensors, 24, 3337, 2024.

Lupea, I., Lupea, M., Fault detection on a rotating test rig based on vibration analysis and machine learning. PROCEEDINGS OF THE ROMANIAN ACADEMY, 2022.

Mistry,R., Finley,W.R., Kreitzer,S.,

Induction motor vibrations in view of the API 541- 4th edition. Material IEEE Paper No. PCIC, 2007.

Finley, W.R., Hodowanec,M., Holter, W., An Analytical Approach to Solving Motor Vibration Problems, IEEE Transactions On Industry Applications, Vol. 36, No. 5, 2000.

Wexler, J., Raz, S., Discrete Gabor expansions, Signal Processing, vol. 21, no.3, pp. 207-221, Nov. 1990.

Shie,Q., Dapang, C., Discrete Gabor Transform, IEEE Transactions On Signal Processing, Vol. 41, No. 7, July 1993.

Dempsey, P.J. Investigation of Sideband Index Response to Prototype Gear Tooth Damage, Glenn Research Center, Cleveland, Ohio, 2013, https://ntrs.nasa.gov/ citations/ 20140011094

M. Zhang, H. Cui, Q. Li et al. An improved sideband energy ratio for fault diagnosis of planetary gearboxes, Journal of Sound and Vibration, 491, 2021


Refbacks

  • There are currently no refbacks.


JOURNAL INDEXED IN :