Table of Content

26 April 2019, Volume 37 Issue 2

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Civil Aviation

Empirical analysis on air traffic flow long phase correlation based on Hurst exponent

WANG Fei

2019, 37(2):  1-4. 

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Air traffic system is a complex nonlinear dynamic system, air traffic flow shows obvious nonlinear fractal characteristics with long phase correlation as one of the key features of which. For accurate modeling, prediction and control of air traffic flow, air traffic flow time series are constructed using operation data in ATM sectors,calculating the Hurst exponent by rescaled range method and conducting empirical analysis on traffic flow long phase correlation. Results show that the local and global Hurst exponent of traffic flow time series are both more than 0.5, indicating that these time series are non-random and have a positive correlation, meanwhile, the past state of traffic flow has an influence on the current and future states, further verifying the fractal characteristics of air traffic flow, providing scientific criteria for traffic flow prediction based on fractal theory.

Design and application of satellite based ADS-B track display terminal

LIU Haitao, JIN Xin

2019, 37(2):  5-10. 

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Compared with traditional ground-based monitoring system, satellite based ADS-B has the ability of flight monitoring and tracking in wide area. Satellite based ADS-B data has the characteristics of large surveillance range,scattered track information, high data frequency and large amount. According to the characteristics of satellitebased ADS-B data, a satellite-based ADS-B track display terminal software for global flight tracking is designed with its functions and system architecture. Key techniques of this software are introduced including satellite based ADS-B information receiving, analyzing and processing procedures, database management, target track display process and GIS implementation scheme. Practical data of Tiantuo experimental satellite are used to test the current terminal software, proving its practical value for effective flight monitoring and tracking using satellite based ADS-B data.

Aerodynamic efficiency calculation method of solar powered micro-UAV

LU Xiang, XU Xianchao, ZENG Qiongzhi

2019, 37(2):  11-16. 

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AimingatthelowReynoldsnumberandlargecruisingspeedrangeofsolarenergy-lithiumhybridbatterymicro-UAV,data fitting for possible airfoil is conducted; Relation function between Reynolds number and airfoil resistance is built through statistical analysis. Calculating method of the low Reynolds number爷s influence on aerodynamic force is obtained. Meanwhile, the influence of corrected cruising speed change on aerodynamic force is calculated through empennage trim resistance calculation. FLUENT simulation and actual flight test prove the feasibility of the proposed method.

Wind turbine clutter suppression for weather radar based on echo data

HE Weikun, GAO Li, WANG Xiaoliang

2019, 37(2):  17-22. 

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Over the past decade, the global cumulative installed capacity of wind turbines has increased rapidly. Research shows that wind farms have serious affect on the performance of nearby weather radars. Wind farm clutter suppression can greatly improve the estimation accuracy of meteorological target parameters for weather radar,therefore it is necessary to study the wind farm clutter suppression technology for weather radar. Based on the traditional periodic characteristics suppression algorithm, the uncontaminated echoes around wind farm is used to dispose the results obtained by traditional method using characteristics of meteorological target parameters distributed uniformly with the distance. The suppression results are improved for the same frequency range of the clutter as meteorological target. Based on the above findings, quantitative performance analysis of the current method is given by the proposed performance indices, verifying the effectiveness of the algorithm.

Engine unit performance research based on thermal model

CAO Huiling, LIU Naibin,XUE Peng, YU Tianhao

2019, 37(2):  23-28. 

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According to the working principle and composition of aircraft engine, as well as the similar thermal equations of each module, equal flow between engine modules and rotor power balance, the relationship mathematical model of performance parameters between engine and components is established by applying small deviation theory.Through performance separation, the model only represents the change of module performance parameters when faults occur, without the change of performance parameters when each module is re-matched after faults. Finally,the variation of engine performance parameters is calculated by collecting the decay of module performance parameters in aero-engine finger print. The model effectiveness is verified by comparing with the changes of acquired engine performance parameters. The impact of engine module performance changes on the performance of whole engine is confirmed by the current model, providing theoretical reference for engine fault diagnoses and troubleshooting.

Basic Research

Aero-engine fault diagnosis based on ensemble learning algorithm

XU Meng, XI Zexi, WANG Yongyun, LI Xiaolu

2019, 37(2):  29-33,42. 

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Complex internal structure and high coupling of faults make it difficult for precise fault diagnosis of aero-engine,in which the typical machine learning model and ensemble learning model cannot meet the rising flight safety requirements. In order to solve this problem, a fault diagnosis method of aero-engine based on Stacking ensemble learning is proposed. Firstly, four key parameters of aero-engine gas path are selected and the flight cycle observation window is set basing on fault reports provided by OEM. Then, the training data set is built and normalized preprocessing is conducted. Finally, according to the difference degree and typical model performance, the optimal base models and meta model are selected. A two-layer Stacking ensemble learning model is established to realize the intelligent diagnosis of four typical gas path faults of aeroengine. Experimental results show that compared with the typical model, the current model improves both of the accuracy and recall ratio by 3%~16%, which can be better applied to the aeroengine fault diagnosis.

Civil Aviation

Fault recognition of complex system based on improved SDAE algorithm

SHI Yongsheng, HENG Huijuan

2019, 37(2):  34-37. 

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Aiming at the low fault recognition rate and large error loss of traditional SDAE algorithm, an improved algorithm is proposed. Data quantification and fault code matching are introduced in order to reduce the input/output error loss and raise the fault recognition accuracy. Results show that the reconstruction error of the improved SDAE algorithm is decreased by 1.5% on average, and the fault recognition rate is increased by 9% on average, the fault recognition accuracy of complex system has been improved.

Numerical simulation of aircraft cabin thermal comfort under heating operation of bridge load air conditioner

LIN Jiaquan, LIU Mingliang

2019, 37(2):  38-42. 

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The 3D models of B737 aircraft second class cabin and human body are established using CFD, simulating the air flow field inside cabin under heating operation of bridge load air conditioner in cold winter. The influence of air supply velocity on temperature field, wind velocity field and thermal comfort are analyzed. Take ADPI as the evaluating indicator of thermal comfort in cabin, calculating the inside ADPI using values of temperature and wind velocity at sample points. Point tracking and Gaussian curve fitting of ADPI under different air supply velocities are conducted, obtaining the function relationship between ADPI and air supply velocity, confirming the range of air supply velocity with the requirement of thermal comfort, providing theoretical basis for the control and adjustment of bridge load air conditioner.

Multi-objective airport gate assignment based on stratified sequencing method

SHEN Xiaoyun, YU Huiwen

2019, 37(2):  43-48. 

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In order to solve the airport gate pre-assignment problem, stratified sequencing method in multi-objective programming is adopted to divide the gate assignment into two stages, and a gate assignment optimization model which coordinates different targets by priority is established. In the first stage, the optimization model is constructed with the objective of minimum number of soft conflicts under hard constraints. In the second stage, the soft constraint conditions are relaxed by the first stage assignment results, and the model is built with the highest gate occupancy rate and the best robustness of the pre-assignment scheme. A hybrid genetic algorithm for solving the assignment model is designed by combining genetic algorithm with greedy algorithm. According to the actual operation data of a large domestic airport, validity of the model and algorithm is verified by comparing with the results of CPLEX optimization, providing theoretical reference for coordinating various optimization objectives to solve the problem of gate assignment by priority.

Cleaning process parameter optimization for embedded navigation lamps

GAO Qingji, WANG Wenzhou, WANG Shen, ZHU Wangzhen

2019, 37(2):  49-52. 

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The emitting surface of airport embedded navigation lamp is easy to deposit pollutants, resulting in lower luminous intensity of the lamp and negative influence on flight safety. An automatic cleaning process controlling method is necessary for efficient and environment-friendly automatic cleaning. Through research on the influence of five cleaning parameters of sand blasting cleaning such as pressure, duration, distance, angle and medium content on cleaning effect, fuzzy,rules between cleaning parameters and cleaning effect are established, and the multi-objective cleaning process optimization function is built. Genetic algorithm is used to optimize the parameters. The optimal cleaning parameter range is obtained basing on experimental data and the optimized cleaning parameters, providing theoretical basis for the automatic cleaning control of navigation light.

Engineering and Technology

Fractal feature extracting method of finger vein image

YANG Jinfeng, LI Qiansimao, JIA Guimin

2019, 37(2):  53-58. 

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The main vascular network of finger vein image is enhanced and extracted by Gabor filter. Three fractal dimension calculating methods are investigated and compared, analyzing the fractal feature extracted by the best calculation method. Furthermore, a fractal geometric feature extracting method is proposed basing on binary tree model to extract the fractal geometric features of finger vascular network such as bifurcation angle, vascular length and bifurcation layer feature and obtain general rules of the network, building foundation for finger vascular network modeling and recognition.

Free vibration analysis of composite laminated plates based on XLWM

XU Jianxin, XU Dong, GUO Qiaorong, WU Yaogang

2019, 37(2):  59-64. 

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XLWM combines the advantages of layerwise method and XFEM, which is capable to analyze composite laminated structure problems with multiple delamination and matrix crack. XLWM is applied to the dynamic analysis of laminated composite plates to investigate the free vibration of isotropic and laminated composite plates with damage. Free vibration convergence rate of XLWM is investigated through numerical examples,comparing the numerical results with those of previous researches and 3D elastic model, proving the validity of XLMW in composite laminates free vibration analyses with/without matrix crack. In addition, the effects of orthotropy degree, number of layers and crack length on free vibration are investigated.