A New Aircraft Taxiing Model Based on Filtering White Noise Method

Abstract

The conversion relationship between power spectral density (PSD) and international roughness index (IRI) was studied based on the filtering white noise method with variable sampling frequency using a quarter vehicle model. Six-degree-of-freedom dynamic equations of the whole aircraft taxiing were obtained considering the lift, upstream and downward bump, roll and pitch motion of the airframe. And then the dynamic load factors of the aircraft wheels under different pavement roughness and various airspeeds were solved by SIMULINK toolbox. The results shown that the mean dynamic load is independent of the pavement roughness, whose values are approximately equal to the load when the aircraft glided on the smooth pavement. The worse the pavement roughness, the greater the maximum dynamic load factor. There are approximately linear relationships between IRI and the maximum dynamic load. When the aircraft glides at low airspeed, the dynamic load increases as the increasing of airspeed. Then the maximum dynamic load factor decreases with the increase of running velocity. Moreover, the formulas for calculating the wheel dynamic load factor under the coupling action of pavement roughness and airspeed were proposed, which could be used to calculated the distribution of the dynamic load in longitudinal direction of the runway and determine the dynamic load values in airport pavement design.

Analysis of Taxiing Performance of Single Strut Landing Gear Based on ISD

“…When excited by the road surface, the two masses vibrate up and down respectively at their equilibrium positions. Therefore, the effects of lift and gravity cannot be considered when the aircraft starts at a constant speed taxiing state [15,18]. According to Newton's second law, the differential equation of motion of the aircraft at the equilib-rium position can be obtained as:…”

“…The time domain model of road roughness shown in formula ( 6) is used as road surface excitation [18]:…”

Phase Congruential White Noise Generator

“…It is assumed that if the information signal is closely approximated to the white noise signal, then it should have the same amplitudes at all frequencies ω k = kω 1 . However, in Expression (18), each frequency is accompanied by two amplitudes a k and b k with possibly separate distributions. This approach leads to a significant complication of the algorithm for their calculations.…”

“…An analysis of the literature shows that most of the articles describe different applications of white noise, as well as its recognition in transmitted signals. This includes the areas such as theoretical and applied mathematics [5][6][7][8][9], physical research [3,4,[10][11][12][13], electronic and radio engineering [14][15][16][17][18][19][20][21][22][23], acoustics and noise phenomena [1][2][3][4]24,25], computer algorithms [26,27], geological prospecting and exploration [28,29], medical and biological research [30][31][32][33][34][35][36], psychology and psychiatry [37,38], and others. It is worth noting that significant results have been achieved in those fields.…”

Fire Risk Analysis of Runway Excursion Accidents in High-Plateau Airport

“…The wind speed and temperature of the high-plateau airport have great uncertainty. We use the white Gaussian noise [52,53] to represent the effect of random changes in wind speed and temperature. Limited to the altitude of the high-plateau airport, the take-off and landing performance needs to be guaranteed.…”