ABSTRACT
The paper presents the development of the IMUMETER sensor, designed to study the dynamics of aircraft movement, in particular, to measure the ground performance of the aircraft. A motivation of this study was to develop a sensor capable of airplane motion measurement, especially for airfield performance, takeoff and landing. The IMUMETER sensor was designed on the basis of the method of artificial neural networks. The use of a neural network is justified by the fact that the automation of the measurement of the airplane's ground distance during landing based on acceleration data is possible thanks to the recognition of the touchdown and stopping points, using artificial intelligence. The hardware is based on a single-board computer that works with the inertial navigation platform and a satellite navigation sensor. In the development of the IMUMETER device, original software solutions were developed and tested. The paper describes the development of the Convolution Neural Network, including the learning process based on the measurement results during flight tests of the PZL 104 Wilga 35A aircraft. The ground distance of the test airplane during landing on a grass runway was calculated using the developed neural network model. Additionally included are exemplary measurements of the landing distance of the test airplane during landing on a grass runway. The results obtained in this study can be useful in the development of artificial intelligence-based sensors, especially those for the measurement and analysis of aircraft flight dynamics.
Subject(s)
Artificial Intelligence , Neural Networks, Computer , Acceleration , AircraftABSTRACT
The performance of a PZL 104 Wilga 35A airplane was determined and analyzed in this work. Takeoff and landing distances were determined by means of two different methods: one which utilized a Global Navigation Satellite System/Inertial Navigation System (GNSS/INS) sensor and another in which airplane ground speed was measured with the use of an optical non-contact sensor. Based on the airfield measurements, takeoff and landing distances as well as rolling resistance coefficients were determined for the used airplane on a grassy runway at the Radawiec airfield, located near Lublin, southeast Poland. The study was part of the "GARFIELD" project that is expected to deliver an online information system on grassy airfield conditions. It was concluded that both sensors were suitable for the aimed research. The results obtained in this study showed the effects of high grass upon the takeoff and landing performances of the test airplane. Also, the two methods were compared against each other, and the final results were compared to calculations of ground distances by means of the chosen analytical models.
ABSTRACT
This paper describes airfield measurement of forces and moments that act on a landing gear wheel. For the measurement, a wheel force sensor was used. The sensor was designed and built based on strain gage technology and was embedded in the left landing gear wheel of a test aircraft. The sensor is capable of measuring simultaneously three perpendicular forces and three moments and sends data to a handheld device wirelessly. For the airfield tests, the sensor was installed on a PZL 104 Wilga 35A multipurpose aircraft. The aircraft was towed at a "marching man" speed and the measurements were performed at three driving modes: Free rolling, braking, and turning. The paper contains results obtained in the field measurements performed on a grassy runway of the Rzeszów Jasionka Aerodrome, Poland. Rolling resistance of aircraft tire, braking friction, as well as aligning moment were analyzed and discussed with respect to surface conditions.
