Journal of Quality Engineering and Management

Identification of Defects in Power Distribution Panels Using Spatial Control Charts

Document Type : Original Article

Authors

Bahman Jamshidi Aini 1
Abbas Saghaei 2
Seyed Hossein Hosseini 3
Sahar Alimardani 4

1 Electrical Engineering Department, Alborz Province Power Distribution Company, Karaj, Iran.

2 Islamic Azad University, Tehran Science and Research Branch, Tehran, Iran.

3 Electrical Engineering Department, Manager of Shahr-e-Quds Electricity Area, Alborz Power Distribution Company, Karaj, Iran.

4 Islamic Azad University, Qazvin Branch, Iran

Abstract
In image monitoring, the information contained in an image is evaluated using control charts. A spatial control chart is a type of control chart in which the horizontal axis represents the position within the image. These charts are used to detect abnormal points in an image. Thermovision is a branch of machine vision that deals with the analysis of infrared images. Although infrared cameras have long been used in preventive maintenance to identify faulty equipment, overloads, and loose connections, the images captured by these cameras are usually analyzed only through empirical methods, and the few quantitative studies conducted in this area have not utilized control charts. In identifying defects in power distribution panels, several challenges must be considered, including the variety of equipment used in electrical panels, the lack of sufficient data to train pattern recognition models, autocorrelation, and the complex behavior of heat transfer by radiation, convection, and conduction. The insufficient data for training pattern recognition models such as neural networks makes spatial control charts relatively more advantageous than these methods. In this study, a combination of spatial control charts and robust regression is employed to detect defects in power distribution panels, and the detection capabilities of various control charts for identifying these defects are compared.

Keywords

Spatial Control Chart
Image Processing
Infrared
Preventive Maintenance
Robust Regression
Journal of Quality Engineering and Management
Volume 2, Issue 2
Summer 2012
Pages 89-96

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