Tribological comparison of an optimum single and double slope design of the stern tube bearing, case study for a marine vessel

Rossopoulos, Georgios N.; Papadopoulos, Christos I.; Leontopoulos, C

doi:10.1016/j.triboint.2020.106343

Cited by 10 publications

(13 citation statements)

References 3 publications

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“…This work will focus on solving classification problems mainly regarding the prediction of shaft misalignment within the bearing. A strict methodology to ensure specific margins of acceptable operation was developed, based on the existing regulatory framework, 26,27 literature findings such as 10 and best practices such as 9 in the study of marine journal bearings. A case study was designed for specific application in a marine stern tube bearing that sustains large vertical loads and operates at excessive shaft misalignment angles.…”

Section: Methodsmentioning

confidence: 99%

“…Focusing only on acceptable operating conditions offers significant advantages, since it is possible to conduct extensive simulations and acquire a rich and well-balanced dataset. More specifically the variation of shaft misalignment as defined in 9 has been studied aiming at identifying and predicting different states given the minimum fluid film thickness (h min ) and maximum pressure (P max ) as well as the applied radial load (w), the RPM, the geometrical characteristics (L, B, c r ) of the bearing and the lubricant viscosity. Alternatively other performance characteristics of the journal bearing performance that is correlated with the h min such as the shaft eccentricity and attitude angle 10 could also be utilized.…”

Section: Introductionmentioning

confidence: 99%

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A journal bearing performance prediction method utilizing a machine learning technique

Rossopoulos

Papadopoulos

2021

Proceedings of the Institution of Mechanical Engineers, Part J:

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A predictive analytics methodology is presented, utilizing machine learning algorithms to identify the performance state of marine journal bearings in terms of maximum pressure, minimum film thickness, Sommerfeld number, load and shaft speed. A dataset of different bearing operation states has been generated by solving numerically the Reynolds equation in the hydrodynamic lubrication regime, for steady-state loading conditions and assuming isothermal and isoviscous lubricant flow. The shaft has been modelled with four different values of misalignment angle, lying within the acceptable operating range, as defined in the existing regulatory framework. The journal bearing was modelled parametrically using generic geometric parameters of a marine stern tube bearing. The lift-off speed was estimated for each loading scenario to ensure operation in the hydrodynamic lubrication regime and the effect of shaft misalignment on lift-off speed has been evaluated. The generated dataset was utilised for training, testing and validation of several machine learning algorithms, as well as feature selection analysis, in order to solve several classification problems and identify the various bearing operational states.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A journal bearing performance prediction method utilizing a machine learning technique

Rossopoulos

Papadopoulos

2021

Proceedings of the Institution of Mechanical Engineers, Part J:

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“…Hasil analisis dari beberapa penelitian menyarankan bahwa derajat kemiringan diperhitungkan ketika memperkirakan titik tumpuan efektif bantalan terlebih ketika kapal beroperasi tentunya ada beban yang diterima bantalan selama proses tersebut [12,13]. Hipotesis sementara menunjukkan bahwa penetapan pedoman pemasangan poros propeller dengan mempertimbangkan efek kemiringan poros propeller dapat mempengaruhi pencegahan kerusakan pada bantalan poros propeller.Sementara itu penelitian lainnya, sebuah simulasi numerik yang difokuskan pada penyelidikan fenomena termal di bawah pengoperasian bantalan berpelumas air menunjukkan bahwa terdapat suatu aliran aksial terbatas yang mendorong aliran balik air dari zona sisi bantalan melalui alur yang telah terbantuk [14]. Sehingga dapat diketahui suhu aliran balik lebih tinggi dari suhu suplai awal pendingain oleh air karena dibawah kondisi aliran aksial yang terbatas, hal itu dipengaruhi terutama oleh suhu aliran air dari celah yang terdapat pada didalam bantalan poros propeller, yang lebih tinggi karena film pelumas [15].…”

Section: Gambar 1 Kondisi Beban Kerja Stren Tube Poros Propellerunclassified

Analisis Perbaikan Stern Tube Poros Propeller Single Screw pada Kapal General Cargo 4192 GT

2021

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Dalam proses perencanaan kapal, pada tahap pemasangan poros propulsi di kapal, tentu saja diperlukan penyelarasan yang benar. Kesalahan dapat menyebabkan distribusi beban yang tidak merata pada bantalan, akibatnya menyebabkan abrasi yang tidak normal, kondisi kelebihan beban, kelebihan beban dan kerusakan pada bagian bantalan tertentu, hal tersebut berlaku juga kepada struktur yang mendapat beban statis sebagai tumpuannya. perlunya uji numerik untuk proses analisa terjadinya beban berlebih dalam persiapan reparasi bantalan poros propeller sehingga menunjukan karakter hidrodinamik dan beban yang terjadi ketika bantalan dan poros propeller mulai kontak. Tujuan penelitian ini,menganalisis desain bantalan poros propeller untuk direparasi dan untuk mendapatkan performa terbaik dari sistem kontak antara bantalan dengan poros propeller sehingga merepresentasikan perbandingan kinerja dari propeller sebelum dan sesudah perbaikan. Metode perhitungan dengan metode finite elemen berbasis persamaan matematik merepresentasikan tegangan yang terjadi sesuai karakter material bronze ( AlBr dan CuSn) yang diaplikasikan pada performa bantalan proros propeller kapal tipe general cargo seberat 4192 GT. Hasil analisa menunjukan saat putaran propeller pada rpm mesin yang optimum, tegangan maksimum juga terjadi sesuai dengan hasil percobaan temperatur yang terjadi juga semakin tinggi. Pada beban rpm 525 maka shear stress untuk stern tube material AlBr bernilai 978 Mpa dan pada material SnCu bernilai 948 Mpa. Nilai deflect atau cleareance pada setiap posisi setelah dilakukan perbaikan mengalami peningkatan rata-rata sebesar 24,4 % dari pengukuran awal sebelum dilakukan reparasi. Proses reparasi menunjukan performa yang cukup baik, rata-rata temperatur kerja yang dihasilkan ketika dilakukan pengujian sea trial menurun dari sebelumnya sebesar 7,5%.

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“…In operation, shaft alignment may be considerably influenced by hull deflections, due to different loading and environmental conditions. The robustness of the shaft alignment at different loading conditions of the ship should be carefully assessed [5], to avoid conditions where the bearings are either overloaded (which leads to operation with very small minimum film thickness, increased wear and inability to support sudden impact loads) or very lightly loaded, characterised by very limited vertical stiffness and thus prone to extreme lateral vibration levels and oil whirling (several case studies regarding whirling vibration problems have been presented in [6]). The current effective regulations for elastic shaft alignment in ships [7,8] demonstrate upper and lower bearing load limits for safe and reliable operation of the ship propulsion shaft.…”

Section: Introductionmentioning

confidence: 99%

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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Tribological comparison of an optimum single and double slope design of the stern tube bearing, case study for a marine vessel

Cited by 10 publications

References 3 publications

A journal bearing performance prediction method utilizing a machine learning technique

A journal bearing performance prediction method utilizing a machine learning technique

Analisis Perbaikan Stern Tube Poros Propeller Single Screw pada Kapal General Cargo 4192 GT

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

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