Propulsion shafting whirling vibration: case studies and perspective

Batrak, Yuriy; Batrak, Roman; Berin, D; Mikhno, Andriy

doi:10.5957/pss-2015-002

Day 1 Tue, September 15, 2015 2015

DOI: 10.5957/pss-2015-002

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Propulsion shafting whirling vibration: case studies and perspective

Yuriy Batrak

Roman Batrak

D Berin

et al.

Abstract: Since 1869 the main goal of whirling vibration calculations of rotating machinery was to determine critical speeds. Currently, all Classification Societies require a propulsion shafting whirling vibration calculation (also named bending or lateral vibration calculation) in the scope of the critical speeds i.e. free whirling vibration calculation. However, fatigue failure of the bracket and aft stern tube bearings, destruction of high-speed shafts with universal joints, noise and hull vibrations, generated by s… Show more

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Journal Bearing Performance Prediction Using Machine Learning and Octave-Band Signal Analysis of Sound and Vibration Measurements

Moschopoulos

Rossopoulos

Papadopoulos

2021

Polish Maritime Research

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Journal and thrust bearings utilise hydrodynamic lubrication to reduce friction and wear between the shaft and the bearing. The process to determine the lubricant film thickness or the actual applied load is vital to ensure proper and trouble-free operation. However, taking accurate measurements of the oil film thickness or load in bearings of operating engines is very difficult and requires specialised equipment and extensive experience. In the present work, the performance parameters of journal bearings of the same principal dimensions are measured experimentally, aiming at training a Machine Learning (ML) algorithm capable of predicting the loading condition of any similar bearing. To this end, an experimental procedure using the Bently Nevada Rotor Kit 4 is set up, combined with sound and vibration measurements in the vicinity of the journal bearing structure. First, sound and acceleration measurements for different values of bearing load and rotational speed are collected and post-processed utilising 1/3 octave band analysis techniques, for parametrisation of the input datasets of the ML algorithms. Next, several ML algorithms are trained and tested. Comparison of the results produced by each algorithm determines the fittest one for each application. The results of this work demonstrate that, in a laboratory environment, the operational parameters of journal bearings can be efficiently identified utilising non-intrusive sound and vibration measurements. The presented approach may substantially improve bearing condition identification and monitoring, which is an imperative step to prevent journal bearing failures and conduct condition-based maintenance.

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Journal Bearing Performance Prediction Using Machine Learning and Octave-Band Signal Analysis of Sound and Vibration Measurements

Moschopoulos

Rossopoulos

Papadopoulos

2021

Polish Maritime Research

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show abstract

Establishing the True Dynamic Bending Moment of Propeller Shaft Using a Single Bridge of Strain Gauge

Vuong

Lee

et al. 2022

Applied Sciences

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The measurement of shaft bending (whirling) moment can be performed via a telemetry system including strain gauges which can obtain the bending stress. By using a single bridge of strain gauge, it was possible to obtain only the nominal bending moment. However, in case of the propeller shaft vibration measurement, the true dynamic bending moment is needed to evaluate the effect of propeller forces on the stability of the bearings. To deal with this, typically two bridges of strain gauge at 90 degrees are needed. This research presents a novel reliability assessment method in establishing the true dynamic bending moment using only one bridge of strain gauge. This is achieved by using the actual bending stress measured by strain gauge combined with its own phase lag stress at an angle of 90 degrees. To validate this technique, the experiments were performed under the rapid turning transient states during a sea trial of a 50,000 DWT oil/chemical tanker. As a result, great fluctuations in propeller force were detected, resulting in a non-uniform oil film in the bearings. The displacement sensor was also installed and confirmed the established true dynamic bending moment.

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Propulsion shafting whirling vibration: case studies and perspective

Cited by 2 publications

References 0 publications

Journal Bearing Performance Prediction Using Machine Learning and Octave-Band Signal Analysis of Sound and Vibration Measurements

Journal Bearing Performance Prediction Using Machine Learning and Octave-Band Signal Analysis of Sound and Vibration Measurements

Establishing the True Dynamic Bending Moment of Propeller Shaft Using a Single Bridge of Strain Gauge

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