An adaptive fault diagnosis approach using pipeline implementation for   railway inspection

YUNUS SANTUR; Mehmet KARAKÖSE; ERHAN AKIN

Makale detayları

An adaptive fault diagnosis approach using pipeline implementation for railway inspection

Yazarlar:

YUNUS SANTUR | Mehmet KARAKÖSE | ERHAN AKIN

Yayıncı:

TUBITAK

Dergi:

Turkish Journal of Electrical Engineering and Computer Science 2018 Vol.26 Issue 2, pp.987-998

Belge Tipi:

Makale

Yayın Tarihi:

3/2018

Belge Dili:

Türkçe

Document ID (Org No.):

2000735312

Sıklık:

İki Aylık

eISSN:

1303-6203

pISSN:

1300-0632

Özet:

 

Railway tracks must be periodically inspected. This study   proposes a new approach for eliminating two major disadvantages experienced   during rail inspection applications performed via computer vision. The first   is the blurring effect on images, resulting from physical vibration during   movement on the rail lines. This effect significantly reduces the high   accuracy rate expected from anomaly inspection algorithms. The second   disadvantage is the need to operate in real time. This study presents a new   three-stage computer vision method approach that eliminates both   disadvantages. First, a three-stage pipeline architecture is implemented and   IMU-assisted blur detection is performed on images taken from the left and   right rail lines. Next, a convolutional neural network is used for learning.   In the third test stage, anomaly detection and classification training are   conducted. By performing the implementation with parallel programming on   graphic processing units, a highly accurate, cost-effective computer vision   rail inspection, based on image processing and capable of operating in real   time, is successfully carried out.

Makale detayları

An adaptive fault diagnosis approach using pipeline implementation for railway inspection

Yazarlar: YUNUS SANTUR | Mehmet KARAKÖSE | ERHAN AKIN

Yayıncı: TUBITAK

Dergi: Turkish Journal of Electrical Engineering and Computer Science 2018 Vol.26 Issue 2, pp.987-998

Belge Tipi: Makale

Yayın Tarihi: 3/2018

Belge Dili: Türkçe

Document ID (Org No.): 2000735312

Sıklık: İki Aylık

eISSN: 1303-6203

pISSN: 1300-0632

Sayı

Yazarlar:

YUNUS SANTUR | Mehmet KARAKÖSE | ERHAN AKIN

Yayıncı:

TUBITAK

Dergi:

Turkish Journal of Electrical Engineering and Computer Science 2018 Vol.26 Issue 2, pp.987-998

Belge Tipi:

Makale

Yayın Tarihi:

3/2018

Belge Dili:

Türkçe

Document ID (Org No.):

2000735312

Sıklık:

İki Aylık

eISSN:

1303-6203

pISSN:

1300-0632