Development of an Automatic Incident Detection Algorithm for Freeway Based on Multi-Level Alarming System and Artificial Neural Networks

2002 ◽  
Author(s):  
Guiyan Jiang ◽  
Francis Navin ◽  
Tarek Sayed ◽  
Ruoqi Zhang
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Detection Algorithm ◽  
Incident Detection ◽  
Multi Level ◽  
Artificial Neural ◽  
Automatic Incident Detection

scholarly journals Fault Detection of Wind Turbine Sensors Using Artificial Neural Networks

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Ayse Gokcen Kavaz ◽  
Burak Barutcu
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Fault Detection ◽  
Wind Turbine ◽  
High Performance ◽  
Detection Algorithm ◽  
Sensor Calibration ◽  
Isolation Technique ◽  
Measurement Validation ◽  
Artificial Neural

This paper proposes a method for sensor validation and fault detection in wind turbines. Ensuring validity of sensor measurements is a significant part in overall condition monitoring as sensor faults lead to incorrect results in monitoring a system’s state of health. Although identifying abrupt failures in sensors is relatively straightforward, calibration drifts are more difficult to detect. Therefore, a detection and isolation technique for sensor calibration drifts on the purpose of measurement validation was developed. Temperature sensor measurements from the Supervisory Control and Data Acquisition system of a wind turbine were used for this aim. Low output rate of the measurements and nonlinear characteristics of the system drive the necessity to design an advanced fault detection algorithm. Artificial neural networks were chosen for this purpose considering their high performance in nonlinear environments. The results demonstrate that the proposed method can effectively detect existence of calibration drift and isolate the exact sensor with faulty behaviour.

Automated multi-level pathology identification techniques for abnormal retinal images using artificial neural networks

2011 ◽  
Vol 96 (2) ◽  
pp. 220-223 ◽  
Author(s):  
J Anitha ◽  
C Kezi Selva Vijila ◽  
A Immanuel Selvakumar ◽  
A Indumathy ◽  
D Jude Hemanth
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Retinal Images ◽  
Multi Level ◽  
Artificial Neural ◽  
Identification Techniques

Multi-Level Interval Estimation for Locating damage in Structures by Using Artificial Neural Networks

2010 ◽  
Author(s):  
Pan Dan-guang ◽  
Gao Yan-hua ◽  
Song Jun-lei ◽  
Jane W. Z. Lu ◽  
Andrew Y. T. Leung ◽  
...  
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Interval Estimation ◽  
Multi Level ◽  
Artificial Neural
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