Transactions of Nanjing University of Aeronautics & Astronautics
Volume 37,Issue S,2020 Table of Contents
2020, 37(S):1-8.
DOI: 10.16356/j.1005-1120.2020.S.001
Abstract:
Aiming at the complex tilting process of quad tilt-rotor （QTR） transition mode， this paper studies the manipulation strategy in transition mode to solve the problem of manipulation redundancy and coupling in transition mode of quad tilt rotor. The variations of the manipulation derivative are analyzed in the tilting process. Through the flight control simulation and flight test of the quad tilt-rotor， the validity of the control system and the rationality of the manipulation strategy are verified.
Aiming at the complex tilting process of quad tilt-rotor （QTR） transition mode， this paper studies the manipulation strategy in transition mode to solve the problem of manipulation redundancy and coupling in transition mode of quad tilt rotor. The variations of the manipulation derivative are analyzed in the tilting process. Through the flight control simulation and flight test of the quad tilt-rotor， the validity of the control system and the rationality of the manipulation strategy are verified.
2020, 37(S):9-17.
DOI: 10.16356/j.1005-1120.2020.S.002
Abstract:
The performance of slowed-rotor compound aircraft， particularly at high-speed flight condition， is examined. The forward flight performance calculation model of the composite helicopter is established， and the appropriate wing and propeller parameters are determined. The predicted performance of isolated propeller， wing and rotor combination is examined. Three kinds of tip speed and a range of load share setting are investigated. Propeller bearing 80% of the thrust with wing sharing lift is found to be the best condition to have better performance and the maximum L/D for maximum forward speed. Detailed rotor， propeller， and wing performance are examined for sea level， 1 000 m， and 2 000 m cruise altitude. Rotor， propeller， and wing power are found to be largely from profile drag， except at low speed where the wing is near stall. Increased elevation offloads lift from the rotor to the wing， dropping the total power required and increasing the maximum speed limit over 400 km/h.
The performance of slowed-rotor compound aircraft， particularly at high-speed flight condition， is examined. The forward flight performance calculation model of the composite helicopter is established， and the appropriate wing and propeller parameters are determined. The predicted performance of isolated propeller， wing and rotor combination is examined. Three kinds of tip speed and a range of load share setting are investigated. Propeller bearing 80% of the thrust with wing sharing lift is found to be the best condition to have better performance and the maximum L/D for maximum forward speed. Detailed rotor， propeller， and wing performance are examined for sea level， 1 000 m， and 2 000 m cruise altitude. Rotor， propeller， and wing power are found to be largely from profile drag， except at low speed where the wing is near stall. Increased elevation offloads lift from the rotor to the wing， dropping the total power required and increasing the maximum speed limit over 400 km/h.
2020, 37(S):18-27.
DOI: 10.16356/j.1005-1120.2020.S.003
Abstract:
Spray performance downward the plain orifice injector was numerically simulated by using Fluent. The primary breakup and the secondary breakup were both focused. To capture the instantaneous interface of two-phase flow and multiscale structure of liquid spray more accurately， an adaptive mesh refinement （AMR） method was adopted. Firstly， the velocity distribution and jet structure were obtained. Then， with different coupled VOF （Volume of Fluid）-DPM （Discrete Phase model） strategies， the jet trajectory， the column breakup point， and the time-average SMD distribution were analyzed and compared. Meanwhile， the experimental data and several empirical formulas were applied to verify the numerical value. The results suggested that the numerical simulation could accord well with experimental data and a certain formula.
Spray performance downward the plain orifice injector was numerically simulated by using Fluent. The primary breakup and the secondary breakup were both focused. To capture the instantaneous interface of two-phase flow and multiscale structure of liquid spray more accurately， an adaptive mesh refinement （AMR） method was adopted. Firstly， the velocity distribution and jet structure were obtained. Then， with different coupled VOF （Volume of Fluid）-DPM （Discrete Phase model） strategies， the jet trajectory， the column breakup point， and the time-average SMD distribution were analyzed and compared. Meanwhile， the experimental data and several empirical formulas were applied to verify the numerical value. The results suggested that the numerical simulation could accord well with experimental data and a certain formula
2020, 37(S):28-34.
DOI: 10.16356/j.1005-1120.2020.S.004
Abstract:
Local defected resonance （LDR） is a recently-developed non-destructive testing method， which identifies damage by detecting the vibrational response of the structural surface under the wideband ultrasonic excitation. The concept of LDR is studied and applied for damage imaging of delamination in composite laminates. Aiming at the problem of poor anti-noise ability and inaccurate damage identification in traditional detection process， an LDR-based multi-frequency method is proposed. Experimental results show that the proposed method can realize the localization and imaging of delamination damage in composite materials.
Local defected resonance （LDR） is a recently-developed non-destructive testing method， which identifies damage by detecting the vibrational response of the structural surface under the wideband ultrasonic excitation. The concept of LDR is studied and applied for damage imaging of delamination in composite laminates. Aiming at the problem of poor anti-noise ability and inaccurate damage identification in traditional detection process， an LDR-based multi-frequency method is proposed. Experimental results show that the proposed method can realize the localization and imaging of delamination damage in composite materials.
2020, 37(S):35-40.
DOI: 10.16356/j.1005-1120.2020.S.005
Abstract:
Due to the electrical anisotropy of carbon fiber reinforced polymer （CFRP）， this paper presents a method to inverse the anisotropic conductivity of unidirectional CFRP laminate using eddy current testing （ECT）. The relationship between the conductivity and probe signal of ECT is studied by means of numerical simulation. Finally， the accuracy of inversion result is improved by optimizing the initial conductivity by use of experimental data.
Due to the electrical anisotropy of carbon fiber reinforced polymer （CFRP）， this paper presents a method to inverse the anisotropic conductivity of unidirectional CFRP laminate using eddy current testing （ECT）. The relationship between the conductivity and probe signal of ECT is studied by means of numerical simulation. Finally， the accuracy of inversion result is improved by optimizing the initial conductivity by use of experimental data.
2020, 37(S):41-48.
DOI: 10.16356/j.1005-1120.2020.S.006
Abstract:
Drilling carbon fiber reinforced polymer （CFRP） composites is liable to generate serious defects including burrs， delamination， fiber pullouts and matrix cracking because of their inherent anisotropy in mechanical properties. Therefore， studies on drilling quality during composites processing is necessary. The thrust force of different material drill bits in composites drilling process was measured by the dynamometer and the surface quality of the hole wall was observed by scanning electron microscope （SEM）， moreover， the tool wear and its effects on the hole wall quality were also taken into account.
Drilling carbon fiber reinforced polymer （CFRP） composites is liable to generate serious defects including burrs， delamination， fiber pullouts and matrix cracking because of their inherent anisotropy in mechanical properties. Therefore， studies on drilling quality during composites processing is necessary. The thrust force of different material drill bits in composites drilling process was measured by the dynamometer and the surface quality of the hole wall was observed by scanning electron microscope （SEM）， moreover， the tool wear and its effects on the hole wall quality were also taken into account.
2020, 37(S):49-57.
DOI: 10.16356/j.1005-1120.2020.S.007
Abstract:
Silicon carbide particle reinforced aluminum matrix composites （SiCp/Al composites） are widely used in aviation， aerospace and electronic package. However， low machining efficiency， severe tool wear and poor surface quality are severe during the machining of SiCp/Al composites. Laser-induced oxidation is capable to improve the machinability of SiCp/Al composites. The material response of 55% （volume fraction） SiCp/Al composites induced by a nanosecond pulsed laser is studied. A metamorphic layer which is composed of an oxide layer and sub-layer is produced. The effects of reaction surrounding and laser average power on the microstructure and thickness of the oxide layer and sub-layer are investigated. Experimental results show that： A thicker oxide layer and a sub-layer are formed in an oxygen-rich atmosphere. The oxides are mainly composed of 2Al2O3·SiO2 （mullite）. A positive correlation between the laser average power and thicknesses of oxide layers and sub-layers is found. A loose oxide layer of 138 μm and a sub-layer of 21 μm are formed at the laser average power of 6 W， laser scanning pitch of 10 μm， and laser scanning speed of 1 mm/s under an oxygen-rich atmosphere. The high efficient machining of SiCp/Al composites can be realized by laser-induced oxidation.
Silicon carbide particle reinforced aluminum matrix composites （SiCp/Al composites） are widely used in aviation， aerospace and electronic package. However， low machining efficiency， severe tool wear and poor surface quality are severe during the machining of SiCp/Al composites. Laser-induced oxidation is capable to improve the machinability of SiCp/Al composites. The material response of 55% （volume fraction） SiCp/Al composites induced by a nanosecond pulsed laser is studied. A metamorphic layer which is composed of an oxide layer and sub-layer is produced. The effects of reaction surrounding and laser average power on the microstructure and thickness of the oxide layer and sub-layer are investigated. Experimental results show that： A thicker oxide layer and a sub-layer are formed in an oxygen-rich atmosphere. The oxides are mainly composed of 2Al2O3·SiO2 （mullite）. A positive correlation between the laser average power and thicknesses of oxide layers and sub-layers is found. A loose oxide layer of 138 μm and a sub-layer of 21 μm are formed at the laser average power of 6 W， laser scanning pitch of 10 μm， and laser scanning speed of 1 mm/s under an oxygen-rich atmosphere. The high efficient machining of SiCp/Al composites can be realized by laser-induced oxidation.
2020, 37(S):58-66.
DOI: 10.16356/j.1005-1120.2020.S.008
Abstract:
Behavior-based flocking has got remarkable attention in the recent past. The flocking algorithms can have inherent properties like organizing， healing and re-configuring for a distributed system. In this research we presented the emergent flocking behavior-based control. We defined the basis behavior and with variety of combination， and obtained a complex group behavior flocking. Unlike classical flocking， we implemented additional rules obstacle avoidance， formation and seek target which results in V-formation flocking while avoiding obstacles. We performed the visual simulation of our flocking algorithm using MATLAB. The results concluded that the multi-boid flock could successfully navigate to the target while avoiding collisions. This can be applied to areas where we need to maximize the coverage of sensors or minimize the risk of combative attack， both in military and civilian scenarios.
Behavior-based flocking has got remarkable attention in the recent past. The flocking algorithms can have inherent properties like organizing， healing and re-configuring for a distributed system. In this research we presented the emergent flocking behavior-based control. We defined the basis behavior and with variety of combination， and obtained a complex group behavior flocking. Unlike classical flocking， we implemented additional rules obstacle avoidance， formation and seek target which results in V-formation flocking while avoiding obstacles. We performed the visual simulation of our flocking algorithm using MATLAB. The results concluded that the multi-boid flock could successfully navigate to the target while avoiding collisions. This can be applied to areas where we need to maximize the coverage of sensors or minimize the risk of combative attack， both in military and civilian scenarios.
2020, 37(S):67-75.
DOI: 10.16356/j.1005-1120.2020.S.009
Abstract:
The problems of attachment failure and detachment impact within gecko-like robots’ locomotion control are considered in this paper. A real-time foot-end force intelligent sensing module with integrated sensing and structure is developed to help the robot get the foot-end force information in time and realize stable locomotion in an uncertain environment. Firstly， a structure/sensing integrated elastomer based on a Maltese cross /cantilever beam structure is completed by designing and finite element analysis. Secondly， a real-time data acquisition and transmission system is designed to obtain the foot-end reaction force which is miniaturized and distributed. Thirdly， based on this system， a force sensor calibration platform is built to complete the calibration， decoupling， and performance testing of the sensing module. Finally， the experiment of single-leg attachment performance is carried out. The results indicate that the three-axis sensing module can detect robot’s weight， measure the reaction force with high precision and provide real-time force from robot’s foot end.
The problems of attachment failure and detachment impact within gecko-like robots’ locomotion control are considered in this paper. A real-time foot-end force intelligent sensing module with integrated sensing and structure is developed to help the robot get the foot-end force information in time and realize stable locomotion in an uncertain environment. Firstly， a structure/sensing integrated elastomer based on a Maltese cross /cantilever beam structure is completed by designing and finite element analysis. Secondly， a real-time data acquisition and transmission system is designed to obtain the foot-end reaction force which is miniaturized and distributed. Thirdly， based on this system， a force sensor calibration platform is built to complete the calibration， decoupling， and performance testing of the sensing module. Finally， the experiment of single-leg attachment performance is carried out. The results indicate that the three-axis sensing module can detect robot’s weight， measure the reaction force with high precision and provide real-time force from robot’s foot end.
2020, 37(S):76-87.
DOI: 10.16356/j.1005-1120.2020.S.010
Abstract:
For many real-world multiobjective optimization problems， the evaluations of the objective functions are computationally expensive. Such problems are usually called expensive multiobjective optimization problems （EMOPs）. One type of feasible approaches for EMOPs is to introduce the computationally efficient surrogates for reducing the number of function evaluations. Inspired from ensemble learning， this paper proposes a multiobjective evolutionary algorithm with an ensemble classifier （MOEA-EC） for EMOPs. More specifically， multiple decision tree models are used as an ensemble classifier for the pre-selection， which is be more helpful for further reducing the function evaluations of the solutions than using single inaccurate model. The extensive experimental studies have been conducted to verify the efficiency of MOEA-EC by comparing it with several advanced multiobjective expensive optimization algorithms. The experimental results show that MOEA-EC outperforms the compared algorithms.
For many real-world multiobjective optimization problems， the evaluations of the objective functions are computationally expensive. Such problems are usually called expensive multiobjective optimization problems （EMOPs）. One type of feasible approaches for EMOPs is to introduce the computationally efficient surrogates for reducing the number of function evaluations. Inspired from ensemble learning， this paper proposes a multiobjective evolutionary algorithm with an ensemble classifier （MOEA-EC） for EMOPs. More specifically， multiple decision tree models are used as an ensemble classifier for the pre-selection， which is be more helpful for further reducing the function evaluations of the solutions than using single inaccurate model. The extensive experimental studies have been conducted to verify the efficiency of MOEA-EC by comparing it with several advanced multiobjective expensive optimization algorithms. The experimental results show that MOEA-EC outperforms the compared algorithms.
2020, 37(S):88-94.
DOI: 10.16356/j.1005-1120.2020.S.011
Abstract:
In order to improve the detail preservation and target information integrity of different sensor fusion images， an image fusion method of different sensors based on non-subsampling contourlet transform （NSCT） and GoogLeNet neural network model is proposed. First， the different sensors images， i.e.， infrared and visible images， are transformed by NSCT to obtain a low frequency sub-band and a series of high frequency sub-bands respectively. Then， the high frequency sub-bands are fused with the max regional energy selection strategy， the low frequency sub-bands are input into GoogLeNet neural network model to extract feature maps， and the fusion weight matrices are adaptively calculated from the feature maps. Next， the fused low frequency sub-band is obtained with weighted summation. Finally， the fused image is obtained by inverse NSCT. The experimental results demonstrate that the proposed method improves the image visual effect and achieves better performance in both edge retention and mutual information.
In order to improve the detail preservation and target information integrity of different sensor fusion images， an image fusion method of different sensors based on non-subsampling contourlet transform （NSCT） and GoogLeNet neural network model is proposed. First， the different sensors images， i.e.， infrared and visible images， are transformed by NSCT to obtain a low frequency sub-band and a series of high frequency sub-bands respectively. Then， the high frequency sub-bands are fused with the max regional energy selection strategy， the low frequency sub-bands are input into GoogLeNet neural network model to extract feature maps， and the fusion weight matrices are adaptively calculated from the feature maps. Next， the fused low frequency sub-band is obtained with weighted summation. Finally， the fused image is obtained by inverse NSCT. The experimental results demonstrate that the proposed method improves the image visual effect and achieves better performance in both edge retention and mutual information.
2020, 37(S):95-101.
DOI: 10.16356/j.1005-1120.2020.S.012
Abstract:
We propose the trench-assisted multimode fiber （TA-OM4） as a novel sensing fiber in forward Brillouin scattering （FBS）-based temperature sensor， due to its higher temperature sensitivity， better bending resistance and lower propagation loss， compared with the single mode fiber （SMF） and other sensing fibers. The FBS effect and acousto-optic interaction in TA-OM4 are the first time to be demonstrated and characterized at 1 550 nm theoretically and experimentally. A 2.0 km long TA-OM4 is put into an oven to measure its temperature sensitivity， which can reach up to 80.3 kHz/℃， exceeding 53% of SMF （52.4 kHz/℃）. The simulated and experimental results verify that the TA-OM4 may be a good candidate as the sensing fiber for the FBS-based temperature sensor.
We propose the trench-assisted multimode fiber （TA-OM4） as a novel sensing fiber in forward Brillouin scattering （FBS）-based temperature sensor， due to its higher temperature sensitivity， better bending resistance and lower propagation loss， compared with the single mode fiber （SMF） and other sensing fibers. The FBS effect and acousto-optic interaction in TA-OM4 are the first time to be demonstrated and characterized at 1 550 nm theoretically and experimentally. A 2.0 km long TA-OM4 is put into an oven to measure its temperature sensitivity， which can reach up to 80.3 kHz/℃， exceeding 53% of SMF （52.4 kHz/℃）. The simulated and experimental results verify that the TA-OM4 may be a good candidate as the sensing fiber for the FBS-based temperature sensor.
2020, 37(S):102-108.
DOI: 10.16356/j.1005-1120.2020.S.013
Abstract:
This paper presents the isotropic optimization of a Stewart-type six-component force sensor. First， the static model of the sensor is built by the screw theory and the forward isotropy indexes and the inverse isotropy indexes are further presented. Second， a comprehensive evaluation function is established to evaluate the isotropic performance of the sensor. By compromising all the isotropy indexes and solving the extreme value of the function， the sensor optimization process is completed and an optimal solution of a set of sensor structure parameters is obtained. Finally， the design of the components and the assembly of the prototype are established by 3D modeling software Pro-E. The verification of the isotropic performance of the sensor is conducted by the finite element analysis software ANSYS. The results obtained by our research can provide useful reference to the isotropic performance evaluation and structure design of the stewart-type six-component force sensor.
This paper presents the isotropic optimization of a Stewart-type six-component force sensor. First， the static model of the sensor is built by the screw theory and the forward isotropy indexes and the inverse isotropy indexes are further presented. Second， a comprehensive evaluation function is established to evaluate the isotropic performance of the sensor. By compromising all the isotropy indexes and solving the extreme value of the function， the sensor optimization process is completed and an optimal solution of a set of sensor structure parameters is obtained. Finally， the design of the components and the assembly of the prototype are established by 3D modeling software Pro-E. The verification of the isotropic performance of the sensor is conducted by the finite element analysis software ANSYS. The results obtained by our research can provide useful reference to the isotropic performance evaluation and structure design of the stewart-type six-component force sensor.
2020, 37(S):109-114.
DOI: 10.16356/j.1005-1120.2020.S.014
Abstract:
Soil properties and water content vary from place to place. The calibration method based on capacitive soil moisture and humidity sensor is carried out. The sensor readings are compared with the mass water content measured by the oven dried method， and the calibration formula of sensor reading and mass moisture content is established. Results show that the sensor reading has a good linear relationship with the mass water content measured by the oven dried method， and has high precision. It can calibrate the mass moisture content of the data obtained from the moisture migration test in the soil column.
Soil properties and water content vary from place to place. The calibration method based on capacitive soil moisture and humidity sensor is carried out. The sensor readings are compared with the mass water content measured by the oven dried method， and the calibration formula of sensor reading and mass moisture content is established. Results show that the sensor reading has a good linear relationship with the mass water content measured by the oven dried method， and has high precision. It can calibrate the mass moisture content of the data obtained from the moisture migration test in the soil column.
2020, 37(S):115-123.
DOI: 10.16356/j.1005-1120.2020.S.015
Abstract:
Since traditional whale optimization algorithms have slow convergence speed， low accuracy and are easy to fall into local optimal solutions， an improved whale optimization algorithm based on mirror selection （WOA-MS） is proposed. Specific improvements includes：（1） An adaptive nonlinear inertia weight based on Branin function was introduced to balance global search and local mining. （2） A mirror selection method is proposed to improve the individual quality and speed up the convergence. By optimizing several test functions and comparing the experimental results with other three algorithms， this study verifies that WOA-MS has an excellent optimization performance.
Since traditional whale optimization algorithms have slow convergence speed， low accuracy and are easy to fall into local optimal solutions， an improved whale optimization algorithm based on mirror selection （WOA-MS） is proposed. Specific improvements includes：（1） An adaptive nonlinear inertia weight based on Branin function was introduced to balance global search and local mining. （2） A mirror selection method is proposed to improve the individual quality and speed up the convergence. By optimizing several test functions and comparing the experimental results with other three algorithms， this study verifies that WOA-MS has an excellent optimization performance.
2020, 37(S):124-132.
DOI: 10.16356/j.1005-1120.2020.S.016
Abstract:
From the mathematical point of view， the flexible inventory control model is proved in the practical problem application and the rationality of the capacity parameter selection and calculation. The purpose is to actively respond to demand fluctuations when there is a demand forecast error or a missing part of the demand information， and to avoid the risk of passive variable demand forecasting to set the immutable inventory capacity. At the same time， the game is controlled by the flexible and variable inventory control strategy and the customer’s willingness to demand. The paper mainly studies the influence of the setting of capacity parameters on the booking-limit decision and its benefits under the control of flexible space with variable total capacity. Through the two trends of capacity increase flexibility and capacity reduction flexibility in the flexible inventory control model， the mathematical performance and marginal utility methods are introduced to change the performance of the booking-limit control decision model under different scenarios. The correlation analysis between the capacity limit level and the return under the optimal Booking-limit decision， and the above two flexibility parameters are obtained.
From the mathematical point of view， the flexible inventory control model is proved in the practical problem application and the rationality of the capacity parameter selection and calculation. The purpose is to actively respond to demand fluctuations when there is a demand forecast error or a missing part of the demand information， and to avoid the risk of passive variable demand forecasting to set the immutable inventory capacity. At the same time， the game is controlled by the flexible and variable inventory control strategy and the customer’s willingness to demand. The paper mainly studies the influence of the setting of capacity parameters on the booking-limit decision and its benefits under the control of flexible space with variable total capacity. Through the two trends of capacity increase flexibility and capacity reduction flexibility in the flexible inventory control model， the mathematical performance and marginal utility methods are introduced to change the performance of the booking-limit control decision model under different scenarios. The correlation analysis between the capacity limit level and the return under the optimal Booking-limit decision， and the above two flexibility parameters are obtained.
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