Permodelan Sistem Predictive Maintenance Engine Health Monitoring pada Mesin Bantu Kapal dengan Variabel Getaran

Endrianto, Egas Wahyu (2025) Permodelan Sistem Predictive Maintenance Engine Health Monitoring pada Mesin Bantu Kapal dengan Variabel Getaran. Masters thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Penelitian ini menyajikan pendekatan pemodelan sistem dinamis untuk predictive maintenance (pemeliharaan prediktif) pada mesin bantu kapal menggunakan variabel getaran. Model ini mengintegrasikan komponen mekanis utama—piston, crankshaft, camshaft, valve train, dan timing gear—berdasarkan spesifikasi mesin diesel Yanmar TF85. Setiap subsistem dimodelkan menggunakan kerangka kerja multi-degree-of-freedom (MDOF) berbasis state-space untuk merepresentasikan dinamika getaran dan struktural. Simulasi dilakukan dalam MATLAB/Simulink pada berbagai kondisi operasi mesin, termasuk kondisi normal pada RPM tinggi, sedang, dan rendah, serta skenario gangguan seperti penurunan redaman pada piston dan crankshaft. Sistem logika fuzzy digunakan untuk menginterpretasikan data getaran dan menentukan tingkat dampak dari setiap kondisi. Hasil menunjukkan bahwa pada kondisi normal, mesin mempertahankan tingkat getaran yang stabil, sementara gangguan menyebabkan peningkatan signifikan pada nilai RMS kecepatan dan tingkat dampak. Gangguan pada piston menghasilkan perubahan amplitudo yang dominan, sedangkan gangguan pada crankshaft memengaruhi propagasi frekuensi di seluruh sistem. Temuan ini mengonfirmasi bahwa model yang diusulkan mampu mendeteksi penyimpangan mekanis sejak dini dan mendukung penerapan strategi pemeliharaan prediktif pada mesin diesel kapal.
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This research presents a dynamic system modelling approach for predictive maintenance of ship auxiliary engines using vibration variables. The model integrates key mechanical components—piston, crankshaft, camshaft, valve train, and timing gear—based on the specifications of a Yanmar TF85 diesel engine. Each subsystem is modeled using a multidegree-of-freedom (MDOF) state-space framework to represent vibrational and structural dynamics. Simulations are carried out in MATLAB/Simulink under various engine operating conditions, including normal operation at high, medium, and low RPMs, as well as fault scenarios such as damping degradation in the piston and crankshaft. A fuzzy logic system is employed to interpret the vibration data and determine the impact level for each condition. The results indicate that under normal conditions, the engine maintains stable vibration levels, while faults lead to significant increases in velocity RMS values and impact severity. Disturbances in the piston result in dominant amplitude changes, while crankshaft faults affect the frequency propagation throughout the system. These findings confirm that the proposed model can effectively detect early mechanical deviations and support the implementation of predictive maintenance strategies for marine diesel engines.

Item Type:	Thesis (Masters)
Uncontrolled Keywords:	Model Dinamik, Getaran Mesin, Predictive Maintenance
Subjects:	V Naval Science > VC Naval Maintenance V Naval Science > VM Naval architecture. Shipbuilding. Marine engineering > VM731 Marine Engines
Divisions:	Faculty of Marine Technology (MARTECH) > Marine Engineering > 36101-(S2) Master Theses
Depositing User:	Egas Wahyu Endrianto
Date Deposited:	07 Aug 2025 02:17
Last Modified:	07 Aug 2025 02:17
URI:	http://repository.its.ac.id/id/eprint/127750

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