Aerospace and Electronic Systems - August 2018 - 62
UAV System for Photovoltaic Plants Inspection
In this work, the proposed Computer Vision Algorithm, whose flowchart
is shown in Figure 3, is based on the
template matching technique, a highlevel machine vision procedure for
identification of the parts on an image
that match a predefined template [11].
The algorithm is implemented using the OpenCV library, an open source
project that started in 1999 by the computer-vision community [12], and it
uses a Normalized Cross Correlation
as a similarity measure for template
matching [13].
EXPERIMENTAL SETUP AND
RESULTS
Figure 3.
Flowchart of the Computer Vision algorithm.
PV defects, infrared imaging represents one of the most diffused
techniques first of all because it is a noninvasive method for detection of thermal anomalies, and secondly because this technique
has reached very high levels of performance in defect detection
concerning other methodologies. Infrared imaging is suitable to
detect many defects on PV plants, such as faults in bypass diodes,
mechanically damaged cells, hot spots, and fault contact points,
that represent the main PV plant defect typologies [10]. An example of visible and thermal imaging of the same panels is shown
in Figure 4; it is evident the effectiveness of using thermal imaging
for defects detection with respect to visible.
As already underlined, the images
captured by the onboard thermal camera need an accurate positioning to
enable the automation of the entire
process allowing to correctly geo-referencing the defective panel. Images
have to be tagged using fixed positions provided by the GNSS receiver.
At the beginning, the use of an RTK receiver was scheduled for
the collection of geo-referenced data. Unfortunately, when employed, it presented electromagnetic interference problems with
the devices on board the UAV, due to the magnet which the RTK
antenna is provided with. For this reason, it has been ordered
a specially customized antenna whose specifications have been
properly designed and sent to the manufacturer for its fabrication. Meanwhile, it has been decided to begin data acquisition
through the use of the U-blox NEO-M8N GNSS receiver in conjunction with the Differential GNSS mode, as explained previously.
Figure 4.
Example of healthy and broken panels in visible (left) and thermal (right) images (panel defect in light blue).
62
IEEE A&E SYSTEMS MAGAZINE
AUGUST 2018
Aerospace and Electronic Systems - August 2018
Table of Contents for the Digital Edition of Aerospace and Electronic Systems - August 2018
Contents
Aerospace and Electronic Systems - August 2018 - Cover1
Aerospace and Electronic Systems - August 2018 - Cover2
Aerospace and Electronic Systems - August 2018 - Contents
Aerospace and Electronic Systems - August 2018 - 2
Aerospace and Electronic Systems - August 2018 - 3
Aerospace and Electronic Systems - August 2018 - 4
Aerospace and Electronic Systems - August 2018 - 5
Aerospace and Electronic Systems - August 2018 - 6
Aerospace and Electronic Systems - August 2018 - 7
Aerospace and Electronic Systems - August 2018 - 8
Aerospace and Electronic Systems - August 2018 - 9
Aerospace and Electronic Systems - August 2018 - 10
Aerospace and Electronic Systems - August 2018 - 11
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Aerospace and Electronic Systems - August 2018 - 18
Aerospace and Electronic Systems - August 2018 - 19
Aerospace and Electronic Systems - August 2018 - 20
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Aerospace and Electronic Systems - August 2018 - 28
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Aerospace and Electronic Systems - August 2018 - 68
Aerospace and Electronic Systems - August 2018 - Cover3
Aerospace and Electronic Systems - August 2018 - Cover4
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