Non-intrusive Flight Test Instrumentation using Video Recognition

Abstract

The National Research Council of Canada has conducted feasibility studies into the development of non-intrusive flight test instrumentation methods with the goal of reducing the cost and time-to-market for certified aerospace products. Video recognition for the collection of flight test time history data was one such non-intrusive method. Compared to traditional instrumentation alternatives the use of machine vision techniques for flight data collection can reduce the instrumentation, airworthiness, and installation efforts required for flight test data collection, and is particularly advantageous when access to the aircraft is limited. This paper details the development of flight test video recognition software, the necessary calibration algorithms, hardware, and the accuracy of data collected by video via full flight simulator data benchmarks. This work has shown that video recognition is a convenient means of collecting cockpit flight test data for model development and certification of full flight simulator devices.