This paper introduces the background, aim, experimental design, configuration and data processing for an airborne test flight of the HY-2 Microwave scatterometer(HSCAT). The aim was to evaluate HSCAT performance and a...This paper introduces the background, aim, experimental design, configuration and data processing for an airborne test flight of the HY-2 Microwave scatterometer(HSCAT). The aim was to evaluate HSCAT performance and a developed data processing algorithm for the HSCAT before launch. There were three test flights of the scatterometer, on January 15, 18 and 22, 2010, over the South China Sea near Lingshui, Hainan. The test flights successfully generated simultaneous airborne scatterometer normalized radar cross section(NRCS), ASCAT wind, and ship-borne-measured wind datasets, which were used to analyze HSCAT performance. Azimuthal dependence of the NRCS relative to the wind direction was nearly cos(2w), with NRCS minima at crosswind directions, and maxima near upwind and downwind. The NRCS also showed a small difference between upwind and downwind directions, with upwind crosssections generally larger than those downwind. The dependence of airborne scatterometer NRCS on wind direction and speed showed favorable consistency with the NASA scatterometer geophysical model function(NSCAT GMF), indicating satisfactory HSCAT performance.展开更多
In this paper,to study the mechanical responses of a solid propellant subjected to ultrahigh acceleration overload during the gun-launch process,specifically designed projectile flight tests with an onboard measuremen...In this paper,to study the mechanical responses of a solid propellant subjected to ultrahigh acceleration overload during the gun-launch process,specifically designed projectile flight tests with an onboard measurement system were performed.Two projectiles containing dummy HTPB propellant grains were successfully recovered after the flight tests with an ultrahigh acceleration overload value of 8100 g.The onboard-measured time-resolved axial displacement,contact stress and overload values were successfully obtained and analysed.Uniaxial compression tests of the dummy HTPB propellant used in the gunlaunched tests were carried out at low and intermediate strain rates to characterize the propellant's dynamic properties.A linear viscoelastic constitutive model was employed and applied in finite-element simulations of the projectile-launching process.During the launch process,the dummy propellant grain exhibited large deformation due to the high acceleration overload,possibly leading to friction between the motor case and propellant grain.The calculated contact stress showed good agreement with the experimental results,though discrepancies in the overall displacement of the dummy propellant grain were observed.The dynamic mechanical response process of the dummy propellant grain was analysed in detail.The results can be used to estimate the structural integrity of the analysed dummy propellant grain during the gun-launch process.展开更多
This paper proposes an autopilot system that can be used to control the small scale rotorcraft during the flight test for linear-frequency-domain system identification. The input frequency-sweep is generated automatic...This paper proposes an autopilot system that can be used to control the small scale rotorcraft during the flight test for linear-frequency-domain system identification. The input frequency-sweep is generated automatically as part of the autopilot control command. Therefore the bandwidth coverage and consistency of the frequency-sweep are guaranteed to produce high quality data for system identification. Beside that, we can set the safety parameters during the flight test （maximum roll/pitch value, minimum altitude, etc.） so the safety of the whole flight test is guaranteed. This autopilot system is validated using hardware in the loop simulator for hover flight condition.展开更多
Plasma flow control（PFC） is a promising active flow control method with its unique advantages including the absence of moving components, fast response, easy implementation, and stable operation. The effectiveness o...Plasma flow control（PFC） is a promising active flow control method with its unique advantages including the absence of moving components, fast response, easy implementation, and stable operation. The effectiveness of plasma flow control by microsecond dielectric barrier discharge（μs-DBD）, and by nanosecond dielectric barrier discharge（NS-DBD） are compared through the wind tunnel tests, showing a similar performance between μs-DBD and NS-DBD. Furthermore, theμs-DBD is implemented on an unmanned aerial vehicle（UAV）, which is a scaled model of a newly developed amphibious plane. The wingspan of the model is 2.87 m, and the airspeed is no less than 30 m/s. The flight data, static pressure data,and Tufts images are recorded and analyzed in detail. Results of the flight test show that the μs-DBD works well on board without affecting the normal operation of the UAV model. When the actuators are turned on, the stall angle and maximum lift coefficient can be improved by 1.3° and 10.4%, and the static pressure at the leading edge of the wing can be reduced effectively in a proper range of angle of attack, which shows the ability of μs-DBD to act as plasma slats. The rolling moment produced by left-side μs-DBD actuation is greater than that produced by the maximum deflection of ailerons,which indicates the potential of μs-DBD to act as plasma ailerons. The results verify the feasibility and efficacy of μs-DBD plasma flow control in a real flight and lay the foundation for the full-sized airplane application.展开更多
为了提高无人机俯仰角故障数据处理和预测的精确性和可靠性,避免增加无人机试飞成本,利用长短期记忆网络(long short term memory,LSTM)、注意力机制+LSTM模型和差分自回归移动平均模型(autoregressive integrated moving average model...为了提高无人机俯仰角故障数据处理和预测的精确性和可靠性,避免增加无人机试飞成本,利用长短期记忆网络(long short term memory,LSTM)、注意力机制+LSTM模型和差分自回归移动平均模型(autoregressive integrated moving average model,ARIMA)模型预测无人机试飞俯仰角故障数据。结果表明,ARIMA预测结果:平均绝对误差(mean absolute error,MAE)为0.35,均方根误差(root mean square error,RMSE)为0.73,平均绝对百分比误差(mean absolute percentage error,MAPE)为23.80%;LSTM模型预测结果:MAE=0.49,RMSE=0.74,MAPE=45.20%;注意力机制+LSTM模型预测结果:MAE=0.17,RMSE=0.53,MAPE=18.93%。可见注意力机制+LSTM模型比其余两种模型更适合于试飞俯仰角的数据预测,以上3种方法对无人机故障数据预测都具有实际意义,有效的预测可以推进自动飞行器和移动机器人的异常检测或外国直接投资研究的最新进展,以进一步提高自动和远程飞行操作的安全性。展开更多
基金Supported by the National Natural Science Foundation of China(No.41106152)the National Science and Technology Support Program of China(No.2013BAD13B01)+3 种基金the National High Technology Research and Development Program of China(863 Program)(No.2013AA09A505)the International Science&Technology Cooperation Program of China(No.2011DFA22260)the National High Technology Industrialization Project(No.[2012]2083)the Marine Public Projects of China(Nos.201105032,201305032,201105002-07)
文摘This paper introduces the background, aim, experimental design, configuration and data processing for an airborne test flight of the HY-2 Microwave scatterometer(HSCAT). The aim was to evaluate HSCAT performance and a developed data processing algorithm for the HSCAT before launch. There were three test flights of the scatterometer, on January 15, 18 and 22, 2010, over the South China Sea near Lingshui, Hainan. The test flights successfully generated simultaneous airborne scatterometer normalized radar cross section(NRCS), ASCAT wind, and ship-borne-measured wind datasets, which were used to analyze HSCAT performance. Azimuthal dependence of the NRCS relative to the wind direction was nearly cos(2w), with NRCS minima at crosswind directions, and maxima near upwind and downwind. The NRCS also showed a small difference between upwind and downwind directions, with upwind crosssections generally larger than those downwind. The dependence of airborne scatterometer NRCS on wind direction and speed showed favorable consistency with the NASA scatterometer geophysical model function(NSCAT GMF), indicating satisfactory HSCAT performance.
文摘In this paper,to study the mechanical responses of a solid propellant subjected to ultrahigh acceleration overload during the gun-launch process,specifically designed projectile flight tests with an onboard measurement system were performed.Two projectiles containing dummy HTPB propellant grains were successfully recovered after the flight tests with an ultrahigh acceleration overload value of 8100 g.The onboard-measured time-resolved axial displacement,contact stress and overload values were successfully obtained and analysed.Uniaxial compression tests of the dummy HTPB propellant used in the gunlaunched tests were carried out at low and intermediate strain rates to characterize the propellant's dynamic properties.A linear viscoelastic constitutive model was employed and applied in finite-element simulations of the projectile-launching process.During the launch process,the dummy propellant grain exhibited large deformation due to the high acceleration overload,possibly leading to friction between the motor case and propellant grain.The calculated contact stress showed good agreement with the experimental results,though discrepancies in the overall displacement of the dummy propellant grain were observed.The dynamic mechanical response process of the dummy propellant grain was analysed in detail.The results can be used to estimate the structural integrity of the analysed dummy propellant grain during the gun-launch process.
文摘This paper proposes an autopilot system that can be used to control the small scale rotorcraft during the flight test for linear-frequency-domain system identification. The input frequency-sweep is generated automatically as part of the autopilot control command. Therefore the bandwidth coverage and consistency of the frequency-sweep are guaranteed to produce high quality data for system identification. Beside that, we can set the safety parameters during the flight test （maximum roll/pitch value, minimum altitude, etc.） so the safety of the whole flight test is guaranteed. This autopilot system is validated using hardware in the loop simulator for hover flight condition.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.51336011 and 51607188)the China Postdoctoral Science Foundation(Grant No.2014M562446)the PhD Research Startup Foundation of Xi’an University of Technology(Grant No.256081802)
文摘Plasma flow control（PFC） is a promising active flow control method with its unique advantages including the absence of moving components, fast response, easy implementation, and stable operation. The effectiveness of plasma flow control by microsecond dielectric barrier discharge（μs-DBD）, and by nanosecond dielectric barrier discharge（NS-DBD） are compared through the wind tunnel tests, showing a similar performance between μs-DBD and NS-DBD. Furthermore, theμs-DBD is implemented on an unmanned aerial vehicle（UAV）, which is a scaled model of a newly developed amphibious plane. The wingspan of the model is 2.87 m, and the airspeed is no less than 30 m/s. The flight data, static pressure data,and Tufts images are recorded and analyzed in detail. Results of the flight test show that the μs-DBD works well on board without affecting the normal operation of the UAV model. When the actuators are turned on, the stall angle and maximum lift coefficient can be improved by 1.3° and 10.4%, and the static pressure at the leading edge of the wing can be reduced effectively in a proper range of angle of attack, which shows the ability of μs-DBD to act as plasma slats. The rolling moment produced by left-side μs-DBD actuation is greater than that produced by the maximum deflection of ailerons,which indicates the potential of μs-DBD to act as plasma ailerons. The results verify the feasibility and efficacy of μs-DBD plasma flow control in a real flight and lay the foundation for the full-sized airplane application.
文摘为了提高无人机俯仰角故障数据处理和预测的精确性和可靠性,避免增加无人机试飞成本,利用长短期记忆网络(long short term memory,LSTM)、注意力机制+LSTM模型和差分自回归移动平均模型(autoregressive integrated moving average model,ARIMA)模型预测无人机试飞俯仰角故障数据。结果表明,ARIMA预测结果:平均绝对误差(mean absolute error,MAE)为0.35,均方根误差(root mean square error,RMSE)为0.73,平均绝对百分比误差(mean absolute percentage error,MAPE)为23.80%;LSTM模型预测结果:MAE=0.49,RMSE=0.74,MAPE=45.20%;注意力机制+LSTM模型预测结果:MAE=0.17,RMSE=0.53,MAPE=18.93%。可见注意力机制+LSTM模型比其余两种模型更适合于试飞俯仰角的数据预测,以上3种方法对无人机故障数据预测都具有实际意义,有效的预测可以推进自动飞行器和移动机器人的异常检测或外国直接投资研究的最新进展,以进一步提高自动和远程飞行操作的安全性。
