Visual Mining and Statistics for a Turbofan Engine Fleet

International audienceSnecma, as a turbofan manufacturer, needs to deal with a wide eet of more than thousands of engines. Every day, data from aircraft engines are broadcas- ted to the ground. Some airlines companies rely on their engine manufacturer to control the engines' behavior and help prepare for maintenance scheduling. The goal of the manufacturer is to detect abnormalities to help schedule main- tenance operations. The advantage of the manufacturer as MRO operator is the registered memory of all past events that appears on its eet of engines. If one opens the possibility to look in this huge amount of data for corresponding similar behaviors, which may have append in the past (for all engines of all customer companies), it becomes possible to make some targeted statistics of the future

Sudden change detection in turbofan engine behavior

International audienceSnecma, as a turbofan manufacturer, needs to deal with a wide eet of more than thousands of engines. Every day, data from aircraft engines are broadcas- ted to the ground. Some airlines companies rely on their engine manufacturer to control the engines' behavior and help prepare for maintenance scheduling. The goal of the manufacturer is to detect abnormalities to help schedule main- tenance operations. The advantage of the manufacturer as MRO operator is the registered memory of all past events that appears on its eet of engines. If one opens the possibility to look in this huge amount of data for corresponding similar behaviors, which may have append in the past (for all engines of all customer companies), it becomes possible to make some targeted statistics of the future

Aeronautical Engineering: A continuing bibliography with indexes, supplement 137, July 1981

This bibliography lists 483 reports, articles, and other documents introduced into the NASA scientific and technical information system in June 1981

Fiscal year 1973 scientific and technical reports, articles, papers, and presentations

Formal NASA technical reports, papers published in technical journals, and presentations by MSFC personnel in FY73 are presented. Papers of MSFC contractors are also included

Machine vision applications in UAVs for autonomous aerial refueling and runway detection

This research focuses on the application of Machine Vision (MV) techniques and algorithms to the problems of Autonomous Aerial Refueling (AAR) and Runway Detection. In particular, real laboratory based hardware was used in a simulated environment to emulate real-life conditions for AAR. It was shown that the K-Means Clustering Algorithm solution to the Marker Detection problem could be executed at a frame rate of 30 Hz and it averaged a tracking error of less than one pixel while utilizing only 0.16% of the image. It was also shown that the solution to the Runway Detection problem could be executed at a frame rate of 20 Hz which is acceptable for use in an UAV performing reconnaissance work. Data from these tests suggest that both software schemes are suitable for applications in moving vehicles and that the accuracy of the measurements produced by the schemes make them suitable for UAV applications