Statistical Filter based Sensor and DAQ Fault Detection for Onboard Ship Performance and Navigation Monitoring Systems

Perera, Lokukaluge P.

doi:10.1016/j.ifacol.2016.10.362

Cited by 17 publications

(7 citation statements)

References 7 publications

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“…23,25,26 Furthermore, hazardous situations may also be associated with either the engine sensors and/or actuators faulty operation or the engine control hardware malfunctioning, demonstrating more severe impact when the engine operates at high loads. With regard to the engine sensors, common issues may be associated with the charge air/exhaust gases pressure or temperature sensors, 27 the engine speed and crank angle sensors, [27][28][29] as well as the engine lubricating oil and charge air coolant pressure or temperature sensors. The actuators faults may be related to the diesel fuel rack actuator and the diesel fuel injectors (misfire issues) 30 as well as the valves clearance.…”

Section: Marine Diesel/df Engines Design and Operational Hazardsmentioning

confidence: 99%

Safety performance assessment of a marine dual fuel engine by integrating failure mode, effects and criticality analysis with simulation tools

Stoumpos

Bolbot

Theotokatos

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part M:

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Marine Dual Fuel engines have been proved an attractive solution to improve the shipping industry sustainability and environmental footprint. Compared to the conventional diesel engines, the use of additional components to accommodate the natural gas feeding is associated with several safety implications. To ensure the engine safe operation, appropriate engine control and safety systems are of vital importance, whilst potential safety implications due to sensors and actuators faults or failures must be considered. This study aims at investigating the safety issues of a marine dual fuel (DF) engine considering critical operating scenarios, which are identified by employing a Failure Mode, Effects and Criticality Analysis. An existing verified digital twin (DT) of the investigated DF engine, capable of predicting the engine response at steady state and transient conditions with sufficient accuracy is employed to simulate the engine operation for the identified scenarios. The simulated scenarios results analysis is used to support the risk priority number assessment and identify the potential safety implications by considering the manufacturer alarm limits. Appropriate measures are recommended for the investigated DF engine safety performance improvement. This study demonstrates a methodology integrating existing safety methods with state-of-the-art simulation tools for facilitating and enhancing the safety assessment process of marine DF engines considering both steady state conditions and transient operation with main focus on switching operating modes.

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Section: Marine Diesel/df Engines Design and Operational Hazardsmentioning

confidence: 99%

Safety performance assessment of a marine dual fuel engine by integrating failure mode, effects and criticality analysis with simulation tools

Stoumpos

Bolbot

Theotokatos

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part M:

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“…Aoyama et al [10] proposed new methods of extracting and utilizing monitoring data by introducing two different monitoring technologies and considering the reliability of each for advanced shipbuilding construction management. Perera et al [11] analyzed large ship performance datasets to propose a model for evaluating ship performance under various seagoing conditions in the operations field.…”

Section: A Bd In the Marine Fieldmentioning

confidence: 99%

Exploiting Marine BD to Develop MLDB and Its Application to Ship Basic Planning Support

Arifin

Octaviani²

2021

IJMEIR

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⎯ recently, the global marine logistics industry has changed significantly because of the global movement of goods. Where the amount of available data and attention paid to extensive data analysis in various topics exponentially grows, it is possible to obtain vast amounts of marine BD. However, the collection of BD groups is difficult to organize and frequently redundant. This is why the database can be so important. If these BD are effectively utilized, great innovation can be achieved in the marine industry. In this study, we develop a marine logistics database to ship basic planning support in the future. The database under study consists of BD sets, i.e. port, ship, route, international trade, and ship operation information from automatic identification system data. As a result, the relational database was developed. The effectiveness of the database is evaluated and extracted data from the database necessary for ship basic planning is discussed.

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“…The significant outliers (i.e. high dimensional boundaries) beyond the respective data structure are classified as data anomalies in a high dimensional space [9,10]. However, data anomalies can be further divided into sensor and DAQ faults and system abnormal events, therefore the domain knowledge in shipping should be used to make the respective classification.…”

Section: Figure 1 Data Handling Frameworkmentioning

confidence: 99%

Ship performance and navigation information under high-dimensional digital models

Perera

2019

J Mar Sci Technol

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Future vessels will be facilitated by modern internet of things (IoT) to collect various ship performance and navigation information. Such information is collected as large-scale data sets, so called Big Data and that should be utilized towards digitalization of the shipping industry. However, various data handling challenges are encountered by the shipping industry during the phase of digitalization, onboard as well as onshore. Data driven models, so called digital models, to support data handling frameworks of the shipping industry are proposed by this study. Such models can overcome the respective data handling challenges in shipping, where conventional mathematical models may fail to facilitate. These models can be derived from ship performance and navigation data sets by considering the high dimensional parameter space. Such high dimensional models consist of several data clusters and each data cluster may consist of a possible unique data structure. These data clusters often relate to sub-operational conditions of vessels and ship systems. The identification of the distribution of data clusters and the structure of each data cluster in relation to ship performance and navigation conditions have been done under this study for a selected vessel as the main contribution. Furthermore, the domain knowledge in shipping (i.e. vessel operational and navigation conditions) is also considered during this analysis to interpret the meaning in such digital models.Index Terms-Digitalization, Shipping industry, big data, digital models, data analytics, machine leaning and artificial intelligence.

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Statistical Filter based Sensor and DAQ Fault Detection for Onboard Ship Performance and Navigation Monitoring Systems

Cited by 17 publications

References 7 publications

Safety performance assessment of a marine dual fuel engine by integrating failure mode, effects and criticality analysis with simulation tools

Safety performance assessment of a marine dual fuel engine by integrating failure mode, effects and criticality analysis with simulation tools

Exploiting Marine BD to Develop MLDB and Its Application to Ship Basic Planning Support

Ship performance and navigation information under high-dimensional digital models

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