RADIS: A real-time anomaly detection intelligent system for fault diagnosis of marine machinery

Velasco-Gallego, Christian; Lazakis, Iraklis

doi:10.1016/j.eswa.2022.117634

Cited by 37 publications

(22 citation statements)

References 39 publications

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“…where n cycle denotes the revolutions per engine cycle (two for four-stroke engines), whereas fmep is the friction mean effective pressure given by the Chen-Flynn model 53 according to equation (11).…”

Section: Single-cylinder Thermodynamics Model Descriptionmentioning

confidence: 99%

Health assessment framework of marine engines enabled by digital twins

Tsitsilonis

Theotokatos

Patil

et al. 2023

International Journal of Engine Research

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The advancements in digital twins when combined with the use of the machine learning tools can facilitate the effective health assessment and diagnostics of safety critical systems. This study aims at developing a framework to address the health assessment of marine engines utilising digital twins based on first-principles. This framework follows four distinct stages, with the former two including the marine engine digital-twin set up by customising the required thermodynamic models, as well as its calibration using tests trials data representing the engine healthy conditions. In the third stage, measurements from actual operating conditions are corrected and subsequently employed to develop the digital twin representing the prevailing conditions. The fourth stage deals with the engine health assessment by assessing health metrics derived from the developed digital twins. This framework is demonstrated in a case study of a large marine four-stroke nine-cylinder propulsion engine. The results demonstrate that three cylinders are identified to be underperforming leading to an average increase of the engine Brake Specific Fuel Consumption (BSFC) by 2.1%, whereas an average decreases of 6.8% in Indicated Mean Effective Pressure (IMEP) and 6.1% in the Exhaust Gas Temperature (EGT) are exhibited for the underperforming cylinders across the entire operating envelope. The developed digital twins facilitate the effective mapping of the engine performance for the entire operating envelope under several health conditions, providing enhanced insights for the current engine health status. The advantages of the proposed framework include the use of easily obtained data, and its application to several engine types including two and four-stroke engines for both propulsion and auxiliary use.

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Section: Single-cylinder Thermodynamics Model Descriptionmentioning

confidence: 99%

Health assessment framework of marine engines enabled by digital twins

Tsitsilonis

Theotokatos

Patil

et al. 2023

International Journal of Engine Research

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“…where A is any subset of the discriminative framework and m(A) is the fundamental probability of A. Since the decision level of multi-source information fusion needs to fuse the basic probabilities generated by multiple sensors to obtain the final diagnosis according to the DS fusion rules, the fusion rules are described in the following Equation (6).…”

Section: Ds Evidence Theorymentioning

confidence: 99%

“…In the field of fault diagnosis, Soother D.K et al [5] used a soft real-time fault diagnosis system for edge equipment based on domain adaptive training strategy using long-and short-term memory networks for remote and real-time detection of bearing faults from vibration data in order to reduce faults. Christian V.G et al [6] made use of a combination of long-and short-term memory networks with multi-level Qtsu threshold segmentation for real-time fault diagnosis of marine machinery, in order to provide intelligent maintenance for the maritime industry. To improve weld quality, Miao et al [7] established a convolutional neural network combined with 3D laser scanning technology in an imaginative approach to extract weld edge regions for real-time detection of weld defects.…”

Section: Introductionmentioning

confidence: 99%

Multi-Source Information Fusion Fault Diagnosis for Gearboxes Based on SDP and VGG

Chen

Liu

et al. 2022

Applied Sciences

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A decision-level approach using multi-sensor-based symmetry dot pattern (SDP) analysis with a Visual Geometry Group 16 network (VGG16) fault diagnosis model for multi-source information fusion was proposed to realize accurate and comprehensive fault diagnosis of gearbox gear teeth. Firstly, the SDP technique was used to perform a feature-level fusion of the fault states of gearbox gear collected by multiple sensors, which could initially visualize the vibration states of the gear teeth in different states. Secondly, the SDP images obtained were combined with the deep learning VGG16. In this way, the local diagnostic results of each sensor can be easily obtained. Finally, the local diagnostic results of each sensor were combined with the DS evidence theory to achieve decision-level fusion, which can better realize comprehensive fault detection for gearbox gear teeth. Before fusion, the accuracies of the three sensors were 96.43%, 93.97%, and 93.28%, respectively. When sensor 1 and sensor 2 were fused, the accuracy reached 99.93%, which is 3.52% and 6.34% better than when using sensors 1 and 2, respectively, alone. When sensor 1 and sensor 3 were fused, the accuracy reached 99.96%, marking an improvement of 3.36% and 6.85% over individual use of sensors 1 and 3, respectively. When sensor 2 and sensor 3 were fused, the accuracy reached 99.40%, which is 5.78% and 6.56% better than individual use of sensors 2 and 3, respectively. When the three sensors were fused simultaneously, the accuracy reached 99.98%, which is 3.68%, 6.40%, and 7.18% better than individual use of sensors 1, 2, and 3, respectively.

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“…Such methods are used on the basis of the study of the internal properties of elements of complex systems and assemblies and take into account the peculiarities of constructing equations that characterize various processes in specific operational modes of a particular system [5]. In turn, the development of principles for constructing regression models according to experimental studies are determined by the principle of combining input on the basis of experiment data of only typical sensors for operation in a limited spectral range without taking into account the characteristics and individual technical requirements of EPI [9][10][11];…”

Section: Literature Review and Problem Statementmentioning

confidence: 99%

Improving tools for diagnosing technical condition of ship electric power installations

Sandler

Budashko

2022

EEJET

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Existing information-measuring systems (IMS) do not fully correspond to the tasks of monitoring electric power installations (EPI) in terms of their characteristics. The capabilities of IMS have certain limitations regarding the probability of measurement results and the degree of invariance to the influence of operational factors. This proves that for modern failure-free EPI technical operation, new diagnostic tools are in demand. Such means should be seamlessly integrated in IMS to enable high operational efficiency and performance reliability. Therefore, it is of particular relevance to tackle the scientific and technical issue of rational combination of protection and preservation of the characteristics of fiber-optic sensors of relative humidity control systems in ship EPI. To solve the problem, the chosen object of this study is the processes of formation and transformation of the diagnostic signal in the means of humidity control. It has been established that the improvement of the characteristics of the control means can be achieved through the synthesis of known optical circuits and the latest materials. To register the parameters of relative humidity, a new circuitry solution was proposed for the sensor based on fiber-optic and elements made of nanomaterials. The main feature of the proposed monitoring tool is invariance to operational destabilizing factors. The scope of application of the obtained research results involves distributed fiber-optic systems for monitoring the technical condition of ship electric power systems. The introduction of a new means for measuring humidity will make it possible to achieve an increase in the efficiency of use and reliability of EPI by reducing the accident rate by 6...11 %, as well as a decrease in operating costs by USD 8...10 per 1 kWh of generated power per year of operation with an average load

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RADIS: A real-time anomaly detection intelligent system for fault diagnosis of marine machinery

Cited by 37 publications

References 39 publications

Health assessment framework of marine engines enabled by digital twins

Health assessment framework of marine engines enabled by digital twins

Multi-Source Information Fusion Fault Diagnosis for Gearboxes Based on SDP and VGG

Improving tools for diagnosing technical condition of ship electric power installations

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