scholarly journals Transformer Oil Leakage Detection Based on Loop Training Method

2021 ◽  
Vol 33 (3) ◽  
pp. 431-438
Author(s):  
Weichao Bao ◽  
Li Gu ◽  
Jinsong He ◽  
Yong Kuai ◽  
Wei Liu ◽  
...  
Keyword(s):  
Transformer Oil ◽  
Training Method ◽  
Leakage Detection ◽  
Oil Leakage

Oil Leakage Detection in Automobile Shock Absorber using Machine Learning Classifiers

2021 ◽  
Author(s):  
Hayeon Park ◽  
Rut Diane Cuebas ◽  
Kyoung-Soo We ◽  
Sung Hoon Kim ◽  
Chang-Gun Lee
Keyword(s):  
Machine Learning ◽  
Shock Absorber ◽  
Leakage Detection ◽  
Machine Learning Classifiers ◽  
Oil Leakage ◽  
Learning Classifiers

Wireless Sensor for Oil Leakage Detection of Depots

2013 ◽  
Vol 336-338 ◽  
pp. 244-247 ◽  
Author(s):  
Chao Yin ◽  
Shao Qiang Liu ◽  
Yong Zhou Li ◽  
Xiang Yong Chen
Keyword(s):  
Low Power ◽  
Low Voltage ◽  
Aviation Fuel ◽  
Wireless Sensor ◽  
Leakage Detection ◽  
Integrated Sensor ◽  
Oil Leakage ◽  
Communication Module ◽  
Power Mode ◽  
Fuel Leakage

This paper presents a low-power wireless sensor system scheme for monitoring aviation fuel leakage of depots. Based on MSP430 microcontroller and powered by a combination of lithium battery and solar energy, the system employs the photoionization detection (PID) technology to detect the oil leakage and wirelessly reports the detection results by CC2520 radio-frequency communication module. With a low-voltage PID integrated sensor and a specialized active gas-collecting device, the system can effectively measure the concentration of leakage in low power mode. Furthermore, an integrated temperature sensor is used to compensate environmental temperature influence on the PID sensor. The effectiveness analysis and power estimation of the system show that the proposed scheme is suitable for detecting aviation fuel leakage of depots.

scholarly journals Networking-Aware IoT Application Development

Sensors ◽  
2020 ◽  
Vol 20 (3) ◽  
pp. 897
Author(s):  
Arne Bröring ◽  
Jan Seeger ◽  
Manos Papoutsakis ◽  
Konstantinos Fysarakis ◽  
Ahmad Caracalli
Keyword(s):  
Wind Turbines ◽  
Data Models ◽  
Leakage Detection ◽  
Business Logic ◽  
Application Development ◽  
Oil Leakage ◽  
Iot Applications ◽  
The Creation ◽  
Application Developers ◽  
Associated Data

Various tools support developers in the creation of IoT applications. In general, such tools focus on the business logic, which is important for application development, however, for IoT applications in particular, it is crucial to consider the network, as they are intrinsically based on interconnected devices and services. IoT application developers do not have in depth expertise in configuring networks and physical connections between devices. Hence, approaches are required that automatically deduct these configurations. We address this challenge in this work with an architecture and associated data models that enable networking-aware IoT application development. We evaluate our approach in the context of an application for oil leakage detection in wind turbines.

Sign in / Sign up

Export Citation Format

Share Document