Aerodynamic modeling and parameter estimation from quick accesses recorder （QAR） data is an important technical way to analyze the effects of highland weather conditions upon aerodynamic characteristics of airplane....Aerodynamic modeling and parameter estimation from quick accesses recorder （QAR） data is an important technical way to analyze the effects of highland weather conditions upon aerodynamic characteristics of airplane. It is also an essential content of flight accident analysis. The related techniques are developed in the present paper, including the geometric method for angle of attack and sideslip angle estimation, the extended Kalman filter associated with modified Bryson-Frazier smoother （EKF-MBF） method for aerodynamic coefficient identification, the radial basis function （RBF） neural network method for aerodynamic mod- eling, and the Delta method for stability/control derivative estimation. As an application example, the QAR data of a civil air- plane approaching a high-altitude airport are processed and the aerodynamic coefficient and derivative estimates are obtained. The estimation results are reasonable, which shows that the developed techniques are feasible. The causes for the distribution of aerodynamic derivative estimates are analyzed. Accordingly, several measures to improve estimation accuracy are put forward.展开更多
Flight data of a twin-jet transport aircraft in revenue flight are analyzed for potential safety problems. Data from the quick access recorder （QAR） are first filtered through the kinematic compatibility analysis. T...Flight data of a twin-jet transport aircraft in revenue flight are analyzed for potential safety problems. Data from the quick access recorder （QAR） are first filtered through the kinematic compatibility analysis. The filtered data are then organized into longitudinal- and lateral-directional aerodynamic model data with dynamic ground effect. The dynamic ground effect requires the radio height and sink rate in the models. The model data are then refined into numerical models through a fuzzy logic algorithm without data smoothing in advance. These numerical models describe nonlinear and unsteady aerodynamics and are used in nonlinear flight dynamics simulation. For the jet transport under study, it is found that the effect of crosswind is significant enough to excite the Dutch roll motion. Through a linearized analysis in flight dynamics at every instant of time, the Dutch roll motion is found to be in nonlinear oscillation without clear damping of the amplitude. In the analysis, all stability derivatives vary with time and hence are nonlinear functions of state variables. Since the Dutch roll motion is not damped despite the fact that a full-time yaw damper is engaged, it is concluded that the design data for the yaw damper is not sufficiently realistic and the contribution of time derivative of sideslip angle to damping should be considered. As a result of nonlinear flight simulation, the vertical wind acting on the aircraft is estimated to be mostly updraft which varies along the flight path before touchdown. Varying updraft appears to make the descent rate more difficult to control to result in a higher g-load at touchdown.展开更多
As the risks associated with air turbulence are intensified by climate change and the growth of the aviation industry,it has become imperative to monitor and mitigate these threats to ensure civil aviation safety.The ...As the risks associated with air turbulence are intensified by climate change and the growth of the aviation industry,it has become imperative to monitor and mitigate these threats to ensure civil aviation safety.The eddy dissipation rate(EDR)has been established as the standard metric for quantifying turbulence in civil aviation.This study aims to explore a universally applicable symbolic classification approach based on genetic programming to detect turbulence anomalies using quick access recorder(QAR)data.The detection of atmospheric turbulence is approached as an anomaly detection problem.Comparative evaluations demonstrate that this approach performs on par with direct EDR calculation methods in identifying turbulence events.Moreover,comparisons with alternative machine learning techniques indicate that the proposed technique is the optimal methodology currently available.In summary,the use of symbolic classification via genetic programming enables accurate turbulence detection from QAR data,comparable to that with established EDR approaches and surpassing that achieved with machine learning algorithms.This finding highlights the potential of integrating symbolic classifiers into turbulence monitoring systems to enhance civil aviation safety amidst rising environmental and operational hazards.展开更多
This article studies the fault recorder in power system and introduces the Comtrade format. Andituses C++ programming to read recorded fault data and adopts Fourier analysis and symmetrical component method to filter ...This article studies the fault recorder in power system and introduces the Comtrade format. Andituses C++ programming to read recorded fault data and adopts Fourier analysis and symmetrical component method to filter and extract fundamental waves. Finally the effectiveness of the data processing method introduced in this paper is verified by CAAP software.展开更多
基金National Natural Science Foundation of China(60832012)
文摘Aerodynamic modeling and parameter estimation from quick accesses recorder （QAR） data is an important technical way to analyze the effects of highland weather conditions upon aerodynamic characteristics of airplane. It is also an essential content of flight accident analysis. The related techniques are developed in the present paper, including the geometric method for angle of attack and sideslip angle estimation, the extended Kalman filter associated with modified Bryson-Frazier smoother （EKF-MBF） method for aerodynamic coefficient identification, the radial basis function （RBF） neural network method for aerodynamic mod- eling, and the Delta method for stability/control derivative estimation. As an application example, the QAR data of a civil air- plane approaching a high-altitude airport are processed and the aerodynamic coefficient and derivative estimates are obtained. The estimation results are reasonable, which shows that the developed techniques are feasible. The causes for the distribution of aerodynamic derivative estimates are analyzed. Accordingly, several measures to improve estimation accuracy are put forward.
基金Foundation item： National Natural Science Foundation of China （60832012）
文摘Flight data of a twin-jet transport aircraft in revenue flight are analyzed for potential safety problems. Data from the quick access recorder （QAR） are first filtered through the kinematic compatibility analysis. The filtered data are then organized into longitudinal- and lateral-directional aerodynamic model data with dynamic ground effect. The dynamic ground effect requires the radio height and sink rate in the models. The model data are then refined into numerical models through a fuzzy logic algorithm without data smoothing in advance. These numerical models describe nonlinear and unsteady aerodynamics and are used in nonlinear flight dynamics simulation. For the jet transport under study, it is found that the effect of crosswind is significant enough to excite the Dutch roll motion. Through a linearized analysis in flight dynamics at every instant of time, the Dutch roll motion is found to be in nonlinear oscillation without clear damping of the amplitude. In the analysis, all stability derivatives vary with time and hence are nonlinear functions of state variables. Since the Dutch roll motion is not damped despite the fact that a full-time yaw damper is engaged, it is concluded that the design data for the yaw damper is not sufficiently realistic and the contribution of time derivative of sideslip angle to damping should be considered. As a result of nonlinear flight simulation, the vertical wind acting on the aircraft is estimated to be mostly updraft which varies along the flight path before touchdown. Varying updraft appears to make the descent rate more difficult to control to result in a higher g-load at touchdown.
基金supported by the Meteorological Soft Science Project(Grant No.2023ZZXM29)the Natural Science Fund Project of Tianjin,China(Grant No.21JCYBJC00740)the Key Research and Development-Social Development Program of Jiangsu Province,China(Grant No.BE2021685).
文摘As the risks associated with air turbulence are intensified by climate change and the growth of the aviation industry,it has become imperative to monitor and mitigate these threats to ensure civil aviation safety.The eddy dissipation rate(EDR)has been established as the standard metric for quantifying turbulence in civil aviation.This study aims to explore a universally applicable symbolic classification approach based on genetic programming to detect turbulence anomalies using quick access recorder(QAR)data.The detection of atmospheric turbulence is approached as an anomaly detection problem.Comparative evaluations demonstrate that this approach performs on par with direct EDR calculation methods in identifying turbulence events.Moreover,comparisons with alternative machine learning techniques indicate that the proposed technique is the optimal methodology currently available.In summary,the use of symbolic classification via genetic programming enables accurate turbulence detection from QAR data,comparable to that with established EDR approaches and surpassing that achieved with machine learning algorithms.This finding highlights the potential of integrating symbolic classifiers into turbulence monitoring systems to enhance civil aviation safety amidst rising environmental and operational hazards.
文摘This article studies the fault recorder in power system and introduces the Comtrade format. Andituses C++ programming to read recorded fault data and adopts Fourier analysis and symmetrical component method to filter and extract fundamental waves. Finally the effectiveness of the data processing method introduced in this paper is verified by CAAP software.
