Flight data recorders (FDRs) play a critical role in determining root causes of aviation mishaps. Some aircraft record limited amounts of information during flight (e.g. T-1A Jayhawk), while others have no FDR on board (B-52 Stratofortress). This study explores the use of image-based flight data acquisition to overcome a lack of available digitally-recorded FDR data. In this work, images of cockpit gauges were unwrapped vertically, and 2-D cross-correlation was performed on each image of the unwrapped gauge versus a template of the unwrapped gauge needle. Points of high correlation between the unwrapped gauge and needle template were used to locate the gauge needle, and interpolation and extrapolation were performed (based on locations of gauge tick marks) to quantify the value to which the gauge needle pointed. Results suggest that image-based flight data acquisition could provide key support to mishap investigations when aircraft lack sufficient FDR data.

Modern aircraft are capable of recording hundreds of parameters during flight. This fact not only facilitates the investigation of an accident or a serious incident, but also provides the opportunity to use the recorded data to predict future aircraft behavior. It is believed that, by analyzing the recorded data, one can identify precursors to hazardous behavior and develop procedures to mitigate the problems before they actually occur. Because of the enormous amount of data collected during each flight, it becomes necessary to identify the segments of data that contain useful information. The objective is to distinguish between typical data points, that are present in the majority of flights, and unusual data points that can be only found in a few flights. The distinction between typical and unusual data points is achieved by using classification procedures. In this dissertation, the application of classification procedures to flight data is investigated. It is proposed to use a Bayesian classifier that tries to identify the flight from which a particular data point came. If the flight from which the data point came is identified with a high level of confidence, then the conclusion that the data point is unusual within the investigated flights can be made. The Bayesian classifier uses the overall and conditional probability density functions together with a priori probabilities to make a decision. Estimating probability density functions is a difficult task in multiple dimensions. Because many of the recorded signals (features) are redundant or highly correlated or are very similar in every flight, feature selection techniques are applied to identify those signals that contain the most discriminatory power. In the limited amount of data available to this research, twenty five features were identified as the set exhibiting the best discriminatory power. Additionally, the number of signals is reduced by applying feature generation techniques to similar signals. To make the approach applicable in practice, when many flights are considered, a very efficient and fast sequential data clustering algorithm is proposed. The order in which the samples are presented to the algorithm is fixed according to the probability density function value. Accuracy and reduction level are controlled using two scalar parameters: a distance threshold value and a maximum compactness factor. / Ph. D.

No description available.

M. Tech. (Engineering: Electrical; Department of Electronic Engineering, Faculty of Engineering and Technology )-- Vaal University of Technology / In the ever growing sport of model aircraft, pilots are challenged with many obstacles. In the division of gliders, one of the biggest problems is the loss of model aircraft. Pilots launch their aircraft off mountain tops and if the aircraft crashes below, the pilot must make use of his best estimates in order to locate the aircraft. This either takes several hours, or the aircraft is never recovered. Pilots are also at a loss with regard to real time data, such as, but not limited to, battery levels, fuel levels, altitude and speed. Model aircraft competitions are also limited to the best estimate of officials. In this work an attempt has been made to design and develop a remote tracking device for model aircraft. This device will retrieve Global Positioning System (GPS) co-ordinates from the aircraft and relay them to the pilot on the ground. In the event of a crash, the pilot will retrieve the last GPS co-ordinates and then proceed to the location to collect the aircraft. An attempt will also be made to design add-on telemetry components that will allow for measurement and transmission of battery levels, fuel levels, altitude, G-Force, orientation, acceleration, wind and ground speed. Some of the data retrieved from the Flight Data Recorder (FDR) in trial 1 are: maximum altitude above sea level of 2139.20 m, maximum speed over ground which was 57.34 m/s and the average battery voltage for transceiver and servos was 15.2 v.

General Aviation (GA) accidents constitute the majority of aviation related accidents. In the United States, there have been over 7,000 GA accidents compared to 190 airline accidents in the last 8 years. Flight data analysis has helped reduce the accident rate in commercial aviation. Similarly, safety analysis based on flight data can help GA be safer. The FAA mandates flight data recorders for multi-engine and turbine powered aircraft, but nearly 80% of General Aviation consists of single engine, of which only a small portion contain any form of data recording device. GA aircraft flight data recorders are costly for operating pilots. Low-cost flight recorders are few and rarely used in GA safety analysis due to lack of accuracy compared to the certified on-board equipment. In this thesis, I investigate the feasibility of using a low-cost Attitude and Heading Reference System (AHRS) to detect hazardous states in GA aircraft. I considered the case of roll angles and found that the low-cost device has significant measurement errors. I developed models to correct the roll angle error as well as methods to improve the detection of hazardous roll angles. I devised a method to evaluate the time accuracy along with the angle accuracy and showed that despite the errors, the low-cost device can provide partial hazardous state detection information.

<p>The main purpose of a Flight Data Recorder (FDR) is to facilitate the investigation of incidents. In order to interpret the data that has been recorded in the FDR the data has to be visualized in some way. This can be done with software on a computer or with hardware that is specific for the model of aircraft that the data originates from.</p><p>The aim of this project is to visualize data for six parameters from the FDR of Saab 2000 in an avionics rig. The avionics rig resembles the cockpit of Saab 2000 and the displays in it are identical to the ones found in the plane. All six parameters are shown on the same display.</p><p>Due to safety regulation vital systems in aircraft are doubled, with one system on the left side and one on the right. Because of the architecture of the rig it was decided that data from the right-hand side systems were to be visualized on the right-hand side display. It is not possible to guarantee that no incorrect values are shown for the parameter altitude when values are taken from the right-hand side, but it can be done for values from the left side. This is the reason why values are taken from the left-hand side for altitude. In the rig a computer with an ARINC429-card and the software Data Bus Analyzer was accessible to transmit data to the displays. DBA can save received data in ASCII-files and also open and transmit the data in such files. Data that has been extracted from an FDR can be converted to the format which DBA can read with macros that have been written in the project. After conversion the data can be transmitted to the display on which it is supposed to be visualized.</p>

The main purpose of a Flight Data Recorder (FDR) is to facilitate the investigation of incidents. In order to interpret the data that has been recorded in the FDR the data has to be visualized in some way. This can be done with software on a computer or with hardware that is specific for the model of aircraft that the data originates from. The aim of this project is to visualize data for six parameters from the FDR of Saab 2000 in an avionics rig. The avionics rig resembles the cockpit of Saab 2000 and the displays in it are identical to the ones found in the plane. All six parameters are shown on the same display. Due to safety regulation vital systems in aircraft are doubled, with one system on the left side and one on the right. Because of the architecture of the rig it was decided that data from the right-hand side systems were to be visualized on the right-hand side display. It is not possible to guarantee that no incorrect values are shown for the parameter altitude when values are taken from the right-hand side, but it can be done for values from the left side. This is the reason why values are taken from the left-hand side for altitude. In the rig a computer with an ARINC429-card and the software Data Bus Analyzer was accessible to transmit data to the displays. DBA can save received data in ASCII-files and also open and transmit the data in such files. Data that has been extracted from an FDR can be converted to the format which DBA can read with macros that have been written in the project. After conversion the data can be transmitted to the display on which it is supposed to be visualized.

The only aeroballistic laboratory of Turkey is the Flight Mechanics Laboratory, FML of T&Uuml / BITAK - SAGE. In FML, flight profiles of projectiles are reconstructed using their tear marks on paper sheets, called yaw cards. Tear marks are created on yaw cards as projectiles pass through them. These yaw cards are tightly stretched to metal frames which are positioned normal to the direction of projectile flight path. The use of yaw cards for flight profile reconstruction is a low cost and reliable solution. However, the yaw card method requires a heavy workload for the analysis of tear marks. Yaw cards collected from the frames are fed through an optical scanner and converted to digital images. These digital images are then processed by operators to calculate the projectile&rsquo / s flight position and angles. To automate this manual process, an algorithm is developed by using histogram based segmentation techniques, custom search algorithms, and Radon transform. This algorithm identifies and locates the projectile marks and finds angle of attack, angle of side slip and roll angle at each frame station by conducting the necessary transformations. Using this automated algorithm, a considerable amount of improvement is accomplished in terms of both decreasing the analysis time and increasing the accuracy of flight profile reconstruction.

This diploma thesis deals with analysis of existing solutions for collecting maintenance data and technical condition of the aircraft. Based on this analysis, it proposes a trend monitoring system based on the existing structure and data from the flight data recorder.

International Telemetering Conference Proceedings / October 20-23, 2003 / Riviera Hotel and Convention Center, Las Vegas, Nevada / The Interactive Analysis and Display System (IADS) provides the test engineer with enhanced test-data processing, management and display capabilities necessary to perform critical data monitoring in near real-time during a test mission. The IADS provides enhanced situational awareness through a display capability designed to increase the confidence of the engineer in making clearance decisions within a Mission Control Room (MCR) environment. The engineer achieves this confidence level through IADS’ real-time display capability (every data point) and simultaneous near real-time processing capability consisting of both time and frequency domain analyses. The system displays real-time data while performing interactive and automated near real-time analyses; alerting the engineer when displayed data exceed predefined threshold limits. The IADS provides a post-test capability at the engineer’s project area desktop, with a user interface common with the real-time system. The IADS promotes teamwork by allowing engineers to share data and test results during a mission and in the post-test environment. The IADS was originally developed for the government’s premier flight test programs. IADS has set the standard for MCR advancements in data acquisition and monitoring and is currently being integrated into all the existing MCR disciplines.