Monitoring and Diagnosis of Fermentation Processes

2000 ◽  
pp. 517-546
Author(s):  
Kouamana Bousson ◽  
Jean-Philippe Steyer ◽  
Boutaib Dahhou ◽  
Louise Travé-Massuyès
Keyword(s):  
Fermentation Processes ◽  
Monitoring And Diagnosis

Automated beam monitoring and diagnosis for CO2 lasers

2001 ◽  
Author(s):  
L. Böske ◽  
S. Mann ◽  
S. Kaierle ◽  
E. W. Kreutz ◽  
R. Poprawe
Keyword(s):  
Co2 Lasers ◽  
Monitoring And Diagnosis ◽  
Beam Monitoring

Implementation of a research prototype onboard fault monitoring and diagnosis system

1987 ◽  
Author(s):  
MICHAEL PALMER ◽  
KATHY ABBOTT ◽  
PAUL SCHUTTE ◽  
WENDELL RICKS
Keyword(s):  
Diagnosis System ◽  
Monitoring And Diagnosis ◽  
Fault Monitoring ◽  
Research Prototype

Remote Monitoring and Diagnosis Technology of Kawasaki Heavy Industries, “Techno Net”

2019 ◽  
Vol 73 (3) ◽  
pp. 194-199
Author(s):  
Naoki Noguchi ◽  
So Kurosaka
Keyword(s):  
Remote Monitoring ◽  
Monitoring And Diagnosis

Intelligent Online Monitoring and Diagnosis of a DC Superconducting Current Limiters

2021 ◽  
Author(s):  
Yingdun Hei ◽  
Xingmei Zhou ◽  
Yaxiong Tan ◽  
Jiajun Pan ◽  
Wei Chen ◽  
...  
Keyword(s):  
Online Monitoring ◽  
Monitoring And Diagnosis ◽  
Superconducting Current

Research on transformer vibration monitoring and diagnosis based on Internet of things

2021 ◽  
Vol 30 (1) ◽  
pp. 677-688
Author(s):  
Zhenzhuo Wang ◽  
Amit Sharma
Keyword(s):  
Internet Of Things ◽  
Power Distribution ◽  
Vibration Analysis ◽  
Vibration Monitoring ◽  
Power Transformers ◽  
Normal Operation ◽  
Analysis Method ◽  
Power Distribution Network ◽  
Monitoring And Diagnosis ◽  
Distribution Transformers

Abstract A recent advent has been seen in the usage of Internet of things (IoT) for autonomous devices for exchange of data. A large number of transformers are required to distribute the power over a wide area. To ensure the normal operation of transformer, live detection and fault diagnosis methods of power transformers are studied. This article presents an IoT-based approach for condition monitoring and controlling a large number of distribution transformers utilized in a power distribution network. In this article, the vibration analysis method is used to carry out the research. The results show that the accuracy of the improved diagnosis algorithm is 99.01, 100, and 100% for normal, aging, and fault transformers. The system designed in this article can effectively monitor the healthy operation of power transformers in remote and real-time. The safety, stability, and reliability of transformer operation are improved.

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