Fundamental investigations of marine engines turbochargers diagnostic with use acceleration vibration signals

Monieta, J.

doi:10.1063/1.5066506

Cited by 5 publications

(6 citation statements)

References 8 publications

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“…The damage detection issue is critical in this system since the blade wears off 90 % of the time and may occur and lead to catastrophic failure. According to statistics, blades are involved in 65 % of centrifugal compressor unfitness conditions [20].…”

Section: Air Supply Systemmentioning

confidence: 99%

Development of a New Expert System for Diagnosing Marine Diesel Engines Based on Real-Time Diagnostic Parameters

Gharib¹,

Kovács²

2022

sv-jme

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Implementing adequate diagnostic strategies for marine engines offers a good possibility to focus on the early recognition of potentialproblems and prevent catastrophic and costly consequences. The successful and increasing application of diagnostic systems and devices for machines depends significantly on the precision of the diagnostic approaches. This research aims to develop an improved diagnosis expert system for determining the real-time technical condition of marine diesel engines. The adequate selection of the diagnostic parameters is crucial in detecting early-stage defects and failures since each parameter responds to the changes in structural parameters of the engine in different modes and degrees. This result provides valuable information on the accurate location of the fault and describes the relationship between operational and structural parameters. Firstly, this article introduces the relevant literature relating to the selection of the diagnostic parameters for marine engines and their subsystems through different statistical methods. The next part contains the description of marine diesel engine subsystems and the selected marine diesel engine’s diagnostic parameters. After that, a newly developed expert system for diagnosing marine diesel engines’ technical conditions is introduced. Finally, a case study of the operation of the developed diagnostic system is presented. The main contribution of the article is the introduction of the newly developed diagnosis expert system, which can be offered to inexperienced users on ships to effectively manage abnormal situations. Furthermore, this diagnostic tool can be applied to the engines’ subsystems to improve the reliability and efficiency of the marine diesel engines’ operation and maintenance.

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Section: Air Supply Systemmentioning

confidence: 99%

Development of a New Expert System for Diagnosing Marine Diesel Engines Based on Real-Time Diagnostic Parameters

Gharib¹,

Kovács²

2022

sv-jme

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“…Adamkiewicz [8] analyzed the relations between cause and effect of operation faults in a few turbocharger models with a method based on expert knowledge and operational diagnostic experience. Monieta [9] used a method with acceleration vibration signals for assessing the technical condition of turbochargers in three four-stroke engines. The research has shown that the diagnostic parameters of technical condition are more reliable with this method than the resource of the operating hours of the engine.…”

Section: Literature Overviewmentioning

confidence: 99%

“…Fouling of the air filter and air flow ducts will significantly affect the quality of energy conversion and also it could cause an increase in fuel consumption. During operation, the air filter will eventually get contaminated and display the following inefficiencies [9]:…”

Section: Air Filter Faultmentioning

confidence: 99%

Fault Tree Analysis and Failure Diagnosis of Marine Diesel Engine Turbocharger System

Knežević

Orović

Stazić

et al. 2020

JMSE

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The reliability of marine propulsion systems depends on the reliability of several sub-systems of a diesel engine. The scavenge air system is one of the crucial sub-systems of the marine engine with a turbocharger as an essential component. In this paper, the failures of a turbocharger are analyzed through the fault tree analysis (FTA) method to estimate the reliability of the system and to predict the cause of failures. The quantitative method is used for assessing the probability of faults occurring in the turbocharger system. The main failures of a scavenge air sub-system, such as air filter blockage, compressor fouling, turbine fouling (exhaust side), cooler tube blockage and cooler air side blockage, are simulated on a Wärtsilä-Transas engine simulator for a marine two-stroke diesel engine. The results obtained through the simulation can provide improvement in the maintenance plan, reliability of the propulsion system and optimization of turbocharger operation during exploitation time.

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“…In this paper, we consider the vibration signal data of marine turbocharges [19][20]. We start from a raw vibration signal of a short duration.…”

Section: Introductionmentioning

confidence: 99%

Virtual Data Generation for Marine Turbochargers Using GANs

Du¹,

Ho²

2022

eJNDT

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A large amount and diversity of data is required for training an effective and robust deep learning or machine learning model. However, obtaining sufficient and various real-time data is difficult for bulky equipment such as marine turbochargers in practical working conditions, since exhaustive acquisition and annotation is hard and time-consuming. In this paper, the proposed methods use Generative Adversarial Networks (GANs) to generate virtual numerical data from limited number of real data. Two GAN architectures, which are basic GAN and conditional GAN, are utilized to develop the methods. The resultant virtual data can be either unlabelled or labelled. It shows that GANs can generate numerical data which is similar enough and not significantly different from the real data. Furthermore, GAN-based domain adaptation approach will be developed to generate synthetic data for predictive maintenance of a turbocharger, given by some healthy data of itself and laboratory testing data of other turbochargers.

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Fundamental investigations of marine engines turbochargers diagnostic with use acceleration vibration signals

Cited by 5 publications

References 8 publications

Development of a New Expert System for Diagnosing Marine Diesel Engines Based on Real-Time Diagnostic Parameters

Development of a New Expert System for Diagnosing Marine Diesel Engines Based on Real-Time Diagnostic Parameters

Fault Tree Analysis and Failure Diagnosis of Marine Diesel Engine Turbocharger System

Virtual Data Generation for Marine Turbochargers Using GANs

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