An Innovative Machine Learning System for Real Time Condition Monitoring of Ship Machinery

Lecture Notes in Civil Engineering - Practical Design of Ships and Other Floating Structures ◽

10.1007/978-981-15-4672-3_47 ◽

2020 ◽

pp. 753-768

Author(s):

Stylianos Oikonomou ◽

Iraklis Lazakis ◽

George Papadakis

Keyword(s):

Machine Learning ◽

Real Time ◽

Condition Monitoring ◽

Learning System ◽

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Application of Machine Learning and Vision for real-time condition monitoring and acceleration of product development cycles

Procedia Manufacturing ◽

10.1016/j.promfg.2020.11.012 ◽

2020 ◽

Vol 52 ◽

pp. 61-66

Author(s):

Wjatscheslav Baumung ◽

Viktor Baumung

Keyword(s):

Machine Learning ◽

Product Development ◽

Real Time ◽

Condition Monitoring ◽

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Development of Real-time Condition Monitoring System Based on Machine Learning for Winch Equipment of Floating Crane

Korean Journal of Computational Design and Engineering ◽

10.7315/cde.2020.445 ◽

2020 ◽

Vol 25 (4) ◽

pp. 445-454

Author(s):

Se-Yun Hwang ◽

Jang-Hyun Lee ◽

Kwang-Sik Kim ◽

Jae-Won Oh ◽

Cheon-Hong Min

Keyword(s):

Machine Learning ◽

Real Time ◽

Monitoring System ◽

Condition Monitoring ◽

Time Condition ◽

Floating Crane ◽

Condition Monitoring System

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Real Time Condition Monitoring on Brakes using Machine Learning Techniques

2020 International Conference on Artificial Intelligence and Signal Processing (AISP) ◽

10.1109/aisp48273.2020.9073173 ◽

2020 ◽

Author(s):

J. Jayakrishnan ◽

Alamelu Manghai T.M. ◽

R. Jegadeeshwaran

Keyword(s):

Machine Learning ◽

Real Time ◽

Condition Monitoring ◽

Machine Learning Techniques ◽

Time Condition ◽

Learning Techniques

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Real-time condition monitoring and fault detection of components based on machine-learning reconstruction model

Renewable Energy ◽

10.1016/j.renene.2018.10.062 ◽

2019 ◽

Vol 133 ◽

pp. 433-441 ◽

Author(s):

Chunzhen Yang ◽

Jingquan Liu ◽

Yuyun Zeng ◽

Guangyao Xie

Keyword(s):

Machine Learning ◽

Fault Detection ◽

Real Time ◽

Condition Monitoring ◽

Time Condition ◽

Reconstruction Model

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A Novel Online Machine Learning Approach for Real-Time Condition Monitoring of Rotating Machines

10.1109/icrom54204.2021.9663495 ◽

2021 ◽

Author(s):

Alireza Mostafavi ◽

Ali Sadighi

Keyword(s):

Machine Learning ◽

Real Time ◽

Condition Monitoring ◽

Learning Approach ◽

Rotating Machines ◽

Time Condition ◽

Machine Learning Approach

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Real time condition monitoring system for industrial motors

2015 2nd Asia-Pacific World Congress on Computer Science and Engineering (APWC on CSE) ◽

10.1109/apwccse.2015.7476232 ◽

2015 ◽

Author(s):

S. S. Goundar ◽

M. R. Pillai ◽

K. A. Mamun ◽

F. R. Islam ◽

R. Deo

Keyword(s):

Real Time ◽

Monitoring System ◽

Condition Monitoring ◽

Time Condition ◽

Condition Monitoring System

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Real-time condition monitoring of thermal power plants feed-pumps by rolling bearings supports vibration

Journal of Physics Conference Series ◽

10.1088/1742-6596/364/1/012131 ◽

2012 ◽

Vol 364 ◽

pp. 012131 ◽

Author(s):

V N Kostyukov ◽

E V Tarasov

Keyword(s):

Real Time ◽

Condition Monitoring ◽

Power Plants ◽

Thermal Power ◽

Thermal Power Plants ◽

Rolling Bearings ◽

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Real-time condition monitoring of a gearbox using Hall effect sensor

2021 4th Biennial International Conference on Nascent Technologies in Engineering (ICNTE) ◽

10.1109/icnte51185.2021.9487667 ◽

2021 ◽

Author(s):

Nitesh P. Yelve ◽

Yohann Lobo ◽

Aditi Deogire ◽

Joel Mathew Varghese ◽

Mohammed Talha

Keyword(s):

Hall Effect ◽

Real Time ◽

Condition Monitoring ◽

Time Condition ◽

Hall Effect Sensor

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Real-time condition monitoring approach of pantograph-catenary system using FPGA

2016 IEEE 14th International Conference on Industrial Informatics (INDIN) ◽

10.1109/indin.2016.7819209 ◽

2016 ◽

Author(s):

Mehmet Karakose ◽

Orhan Yaman ◽

Ilhan Aydin ◽

Ebru Karakose

Keyword(s):

Real Time ◽

Condition Monitoring ◽

Time Condition ◽

Catenary System

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Application of Hierarchical Colored Petri Nets for Real-Time Condition Monitoring of Internal Blowout Prevention (IBOP) in Top Drive Assembly System

2019 IEEE International Systems Conference (SysCon) ◽

10.1109/syscon.2019.8836875 ◽

2019 ◽

Author(s):

Nadia Saad Noori ◽

Tor Inge Waag

Keyword(s):

Real Time ◽

Condition Monitoring ◽

Colored Petri Nets ◽

Assembly System ◽

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