Next Article in Journal
TrackCC: A Practical Wireless Indoor Localization System Based on Less-Expensive Chips
Next Article in Special Issue
Study of a Compression-Molding Process for Ultraviolet Light-Emitting Diode Exposure Systems via Finite-Element Analysis
Previous Article in Journal
A Novel Approach to Measuring Muscle Mechanics in Vehicle Collision Conditions
Previous Article in Special Issue
Inspection and Reconstruction of Metal-Roof Deformation under Wind Pressure Based on Bend Sensors
Article Menu
Issue 6 (June) cover image

Export Article

Open AccessArticle
Sensors 2017, 17(6), 1403; doi:10.3390/s17061403

Development of an Automatic Testing Platform for Aviator’s Night Vision Goggle Honeycomb Defect Inspection

Department of Aeronautics and Astronautics, National Cheng Kung University, Tainan 70101, Taiwan
*
Author to whom correspondence should be addressed.
Received: 6 May 2017 / Revised: 10 June 2017 / Accepted: 12 June 2017 / Published: 15 June 2017
(This article belongs to the Special Issue Innovative Sensing Control Scheme for Advanced Materials)
View Full-Text   |   Download PDF [3294 KB, uploaded 15 June 2017]   |  

Abstract

Due to the direct influence of night vision equipment availability on the safety of night-time aerial reconnaissance, maintenance needs to be carried out regularly. Unfortunately, some defects are not easy to observe or are not even detectable by human eyes. As a consequence, this study proposed a novel automatic defect detection system for aviator’s night vision imaging systems AN/AVS-6(V)1 and AN/AVS-6(V)2. An auto-focusing process consisting of a sharpness calculation and a gradient-based variable step search method is applied to achieve an automatic detection system for honeycomb defects. This work also developed a test platform for sharpness measurement. It demonstrates that the honeycomb defects can be precisely recognized and the number of the defects can also be determined automatically during the inspection. Most importantly, the proposed approach significantly reduces the time consumption, as well as human assessment error during the night vision goggle inspection procedures. View Full-Text
Keywords: night vision goggles; military avionics systems; defect detection; auto focus; passive focusing night vision goggles; military avionics systems; defect detection; auto focus; passive focusing
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Jian, B.-L.; Peng, C.-C. Development of an Automatic Testing Platform for Aviator’s Night Vision Goggle Honeycomb Defect Inspection. Sensors 2017, 17, 1403.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top