Real-time data-driven missing data imputation for short-term sensor data of marine systems. A comparative study
Velasco, Christian and Lazakis, Iraklis (2020) Real-time data-driven missing data imputation for short-term sensor data of marine systems. A comparative study. Ocean Engineering, 218. 108261. ISSN 0029-8018 (https://doi.org/10.1016/j.oceaneng.2020.108261)
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Abstract
In the maritime industry, sensors are utilised to implement condition-based maintenance (CBM) to assist decision-making processes for energy efficient operations of marine machinery. However, the employment of sensors presents several challenges including the imputation of missing values. Data imputation is a crucial pre-processing step, the aim of which is the estimation of identified missing values to avoid under-utilisation of data that can lead to biased results. Although various studies have been developed on this topic, none of the studies so far have considered the option of imputing incomplete values in real-time to assist instant data-driven decision-making strategies. Hence, a methodological comparative study has been developed that examines a total of 20 widely implemented machine learning and time series forecasting algorithms. Moreover, a case study on a total of 7 machinery system parameters obtained from sensors installed on a cargo vessel is utilised to highlight the implementation of the proposed methodology. To assess the models’ performance seven metrics are estimated (Execution time, MSE, MSLE, RMSE, MAPE, MedAE, Max Error). In all cases, ARIMA outperforms the remaining models, yielding a MedAE of 0.08 r/min and a Max Error of 2.4 r/min regarding the main engine rotational speed parameter
ORCID iDs
Velasco, Christian and Lazakis, Iraklis ORCID: https://orcid.org/0000-0002-6130-9410;-
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Item type: Article ID code: 74456 Dates: DateEvent15 December 2020Published24 October 2020Published Online18 October 2020AcceptedSubjects: Naval Science > Naval architecture. Shipbuilding. Marine engineering Department: Faculty of Engineering > Naval Architecture, Ocean & Marine Engineering Depositing user: Pure Administrator Date deposited: 30 Oct 2020 11:16 Last modified: 12 Sep 2024 00:55 URI: https://strathprints.strath.ac.uk/id/eprint/74456