One of the most important elements of the reliability structure of a motor vessel is its power subsystem, with the most crucial component being the engine. An engine failure excludes the ship from operation or significantly limits its operation. Therefore, accurate fault diagnosis should be a crucial issue for modern maintenance strategies. In mechanical engineering, the vibration and acoustic signals recorded during the operation of the device are the most meaningful data used to identify the reliability state. In this paper, a novel system-oriented method of reliability state identification is proposed. The method consists of the analysis of the vibration and noise signals collected on each of the engine cylinders using supervised machine learning. The main novelty of this method is data augmentation application and SVM classifier implementation. Due to these aspects, the method becomes robust in the case of poor-quality data or a limited and incomplete learning dataset. The quality of the proposed identification method was evaluated by addressing a new industrial issue (Sulzer 6AL20/24 marine engine reliability state identification). During the tests, the efficiency of the method was analyzed in the case of a complete learning data set (all types of inability states were presented in the learning data set) and an incomplete learning data set (in the testing data set, there were new types of inability states). As a result, in both cases, a very high (100%) identification accuracy of the reliability state and the type of inability state was obtained. This is a significant increase in accuracy (4.6% for the complete and 22% for the incomplete learning data set) in comparison to the efficiency of the same method without the use of machine learning and data science.

The application of fuels from renewable energy sources for combustion engine powering involves a great demand for this kind of energy while its production infrastructure remains underdeveloped. The use of this kind of fuel is supposed to reduce the emission of greenhouse gases and the depletion of natural resources and to increase the share of renewable energy sources in total energy consumption and thus support sustainable development in Europe. This study presents the results of research on selected performance parameters of transport by internal combustion engines including: power, torque, the emission of sound generated by the engine, the content of exhaust components (oxygen O₂, carbon monoxide CO, carbon dioxide CO₂, nitrogen dioxide NO₂), and the content of particulate matter (PM) in exhaust emission. Three self-ignition engines were tested. The fuel injection controllers of the tested internal combustion engines were additionally adjusted by increasing the fuel dose and the load of air. The material used in the tests were mixtures of diesel oil and fatty acid methyl esters of different concentration. A statistical analysis was performed based of the results. The purpose of the work was to develop a resulting model for assessing the operation of engines fueled with biofuel and diesel mixtures while changing the vehicle’s computer software. A computer simulation algorithm was also developed for the needs of the tests which was used to prognose the state of the test results for variable input parameters.

The most common indicators used for assessing combustion engines powered by renewable fuels with simultaneous fuel injection are: power, torque, fuel consumption, noise emission, amount of particulates present in the exhaust fumes and composition of exhaust fumes (oxygen, carbon dioxide, hydrocarbons, nitric oxides and air excess coefficient). The aim of this study is to analyze the impact of the addition of fatty acid methyl esters to diesel oil on the value of transport means performance parameters, particularly the level of noise generated by the transport means drive units. Generating noise by internal combustion piston engines is the effect of their operation. Our study compared emissions of sound generated by diesel oil powered with diesel oil and the mixture of 30% of fatty acid methyl esters (biocomponents) and 70% of diesel oil. The object of the study is the piston combustion engine with self-ignition of 80 kW rated power. The experiment was conducted for four scopes of the fuel controller’s settings: standard ones, increased for 2%, 4%, and 6% dosage of fuel and supercharging for 50 mb. We found that the increased dosages of fuel at powering with diesel oil without the additive of biocomponent influences the increase of the noise level within the whole tested scope.

Rubber and rubber-metal vibration isolators are widely used vibration isolation systems in marine applications. For naval application, shock absorber mounting systems must fulfil two functions. The first one supports the suspended mass in the absence of waving or detonation while providing isolation from vibrations and shock impact. In the second case, during the machine operation, it reduces the force of movement to an acceptable value. Moreover, it returns the insulated mass to the position output without plastic deformation or residual buckling after removing shock stresses or harmonic vibrations. The environment in which marine vibration isolators are to be used strongly influences the selection of a shock absorber. The main environmental problem is the temperature range in marine power plants, which ranges from 20 °C to 55 °C. Temperature fluctuations may cause changes in the physical properties of typical vibration/shock insulators. Both rubbers and elastomers used for shock absorbers tend to stiffen, gain low-temperature damping, and soften and lose damping at elevated temperatures. Factors such as moisture, ozone and changes in atmospheric pressure are usually ignored in shipbuilding. The main environmental factors influencing the ageing of insulators are liquid saturated hydrocarbons, i.e., oils, fuels, coolants, etc., which may come into contact with the surface of the insulators. This work presents the results of the research carried out to determine the effect of overload and the impact of petroleum products on the materials of metal-rubber shock absorbers made of three different rubbers and one polyurethane mixture. For each of the materials, shock absorbers with three different degrees of hardness were tested.

This article deals with the modeling of the processes of operating both marine main and auxiliary engines. The paper presents a model of changes in operating conditions of ship’s internal combustion engine. The semi-Markov decision process was used to mathematically describe the process model of the engine. The developed model describes the effect of engine damage on the characteristics of its operation. A change in the input parameters of the model can simulate the influence of internal and external factors on the course of the analyzed process. A simplified calculation example is also presented for illustration purposes. The presented method together with developed algorithms and IT tools can be used to solve a wide range of problems related to the operation of marine main engines and other marine equipment as well as maritime and port facilities. This concerns primarily the economic, risk management and operational security issues of complex technical systems, as well as the readiness and reliability analysis of technical facilities.