Cargando…
An Ensemble-Based Approach to Anomaly Detection in Marine Engine Sensor Streams for Efficient Condition Monitoring and Analysis
This study proposes an unsupervised anomaly detection method using sensor streams from the marine engine to detect the anomalous system behavior, which may be a possible sign of system failure. Previous works on marine engine anomaly detection proposed a clustering-based or statistical control chart...
Autores principales: | Kim, Donghyun, Lee, Sangbong, Lee, Jihwan |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7765970/ https://www.ncbi.nlm.nih.gov/pubmed/33353051 http://dx.doi.org/10.3390/s20247285 |
Ejemplares similares
-
Explainable Anomaly Detection Framework for Maritime Main Engine Sensor Data
por: Kim, Donghyun, et al.
Publicado: (2021) -
Effective Sensor Selection and Data Anomaly Detection for Condition Monitoring of Aircraft Engines
por: Liu, Liansheng, et al.
Publicado: (2016) -
Data-Driven Prediction of Vessel Propulsion Power Using Support Vector Regression with Onboard Measurement and Ocean Data
por: Kim, Donghyun, et al.
Publicado: (2020) -
Feature Attribution Analysis to Quantify the Impact of Oceanographic and Maneuverability Factors on Vessel Shaft Power Using Explainable Tree-Based Model
por: Kim, Donghyun, et al.
Publicado: (2023) -
Anomaly Detection Using an Ensemble of Multi-Point LSTMs
por: Lee, Geonseok, et al.
Publicado: (2023)