NDLI: Using artificial neural network-self-organising map for data clustering of marine engine condition monitoring applications

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Using artificial neural network-self-organising map for data clustering of marine engine condition monitoring applications

Content Provider	Scilit
Author	Raptodimos, Yiannis Lazakis, Iraklis
Copyright Year	2018
Description	Journal: Ships and Offshore Structures Condition monitoring is the process of monitoring parameters expressing machinery condition, interpreting them for the identification of change which could indicate developing faults. Data processing is important in a ship condition monitoring software tool, as misinterpretation of data can significantly affect the accuracy and performance of the predictions made. Data for key performance parameters for a PANAMAX container ship main engine cylinder are clustered using a two-stage approach. Initially, the data is clustered using the artificial neural network (ANN)-self-organising map (SOM) and then the clusters are interclustered using the Euclidean distance metric into groups. The case study results demonstrate the capability of the SOM to monitor the main engine condition by identifying clusters containing data which are diverse compared to data representing normal engine operating conditions. The results obtained can be further expanded for application in diagnostic purposes, identifying faults, their causes and effects to the ship main engine.
Related Links	https://strathprints.strath.ac.uk/63498/1/Raptodimos_Lazakis_SOS_2018_Using_artificial_neural_network_self_organising_map_for_data_clustering.pdf
Ending Page	656
Page Count	8
Starting Page	649
ISSN	17445302
e-ISSN	1754212X
DOI	10.1080/17445302.2018.1443694
Journal	Ships and Offshore Structures
Issue Number	6
Volume Number	13
Language	English
Publisher	Informa UK Limited
Publisher Date	2018-08-18
Access Restriction	Open
Subject Keyword	Journal: Ships and Offshore Structures Marine Engineering Ship Condition Monitoring Data Clustering Self-organising Maps Ship Machinery
Content Type	Text
Subject	Ocean Engineering Mechanical Engineering

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