Transactions of Nanjing University of Aeronautics & Astronautics
Volume 38,Issue 6,2021 Table of Contents
2021, 38(6):901-913.
DOI: 10.16356/j.1005-1120.2021.06.001
Abstract:
Along with the rapid development of air traffic， the contradiction between conventional air traffic management （ATM） and the increasingly complex air traffic situations is more severe， which essentially reduces the operational efficiency of air transport systems. Thus， objectively measuring the air traffic situation complexity becomes a concern in the field of ATM. Most existing studies focus on air traffic complexity assessment， and rarely on the scientific guidance of complex traffic situations. According to the projected time of aircraft arriving at the target sector boundary， we formulated two control strategies to reduce the air traffic complexity. The strategy of entry time optimization was applied to the controllable flights in the adjacent upstream sectors. In contrast， the strategy of flying dynamic speed optimization was applied to the flights in the target sector. During the process of solving complexity control models， we introduced a physical programming method. We transformed the multi-objective optimization problem involving complexity and delay to single-objective optimization problems by designing different preference function. Actual data validated the two complexity control strategies can eliminate the high-complexity situations in reality. The control strategy based on the entry time optimization was more efficient than that based on the speed dynamic optimization. A basic framework for studying air traffic complexity management was preliminarily established. Our findings will help the implementation of a complexity-based ATM.
Along with the rapid development of air traffic， the contradiction between conventional air traffic management （ATM） and the increasingly complex air traffic situations is more severe， which essentially reduces the operational efficiency of air transport systems. Thus， objectively measuring the air traffic situation complexity becomes a concern in the field of ATM. Most existing studies focus on air traffic complexity assessment， and rarely on the scientific guidance of complex traffic situations. According to the projected time of aircraft arriving at the target sector boundary， we formulated two control strategies to reduce the air traffic complexity. The strategy of entry time optimization was applied to the controllable flights in the adjacent upstream sectors. In contrast， the strategy of flying dynamic speed optimization was applied to the flights in the target sector. During the process of solving complexity control models， we introduced a physical programming method. We transformed the multi-objective optimization problem involving complexity and delay to single-objective optimization problems by designing different preference function. Actual data validated the two complexity control strategies can eliminate the high-complexity situations in reality. The control strategy based on the entry time optimization was more efficient than that based on the speed dynamic optimization. A basic framework for studying air traffic complexity management was preliminarily established. Our findings will help the implementation of a complexity-based ATM.
2021, 38(6):914-926.
DOI: 10.16356/j.1005-1120.2021.06.002
Abstract:
In recent years， the number of incidents involved with unmanned aerial vehicles （UAVs） has increased conspicuously， resulting in an increasingly urgent demand for developing anti-UAV systems. The vast requirements of high detection accuracy with respect to low altitude UAVs are put forward. In addition， the methods of UAV detection based on deep learning are of great potential in low altitude UAV detection. However， such methods need high-quality datasets to cope with the problem of high false alarm rate （FAR） and high missing alarm rate （MAR） in low altitude UAV detection， special high-quality low altitude UAV detection dataset is still lacking. A handful of known datasets for UAV detection have been rejected by their proposers for authorization and are of poor quality. In this paper， a comprehensive enhanced dataset containing UAVs and jamming objects is proposed. A large number of high-definition UAV images are obtained through real world shooting， web crawler， and data enhancement. Moreover， to cope with the challenge of low altitude UAV detection in complex backgrounds and long distance， as well as the puzzle caused by jamming objects， the noise with jamming characteristics is added to the dataset. Finally， the dataset is trained， validated， and tested by four mainstream deep learning models. The results indicate that by using data enhancement， adding noise contained jamming objects and images of UAV with complex backgrounds and long distance， the accuracy of UAV detection can be significantly improved. This work will promote the development of anti-UAV systems deeply，and more convincing evaluation criteria are provided for models optimization for UAV detection.
In recent years， the number of incidents involved with unmanned aerial vehicles （UAVs） has increased conspicuously， resulting in an increasingly urgent demand for developing anti-UAV systems. The vast requirements of high detection accuracy with respect to low altitude UAVs are put forward. In addition， the methods of UAV detection based on deep learning are of great potential in low altitude UAV detection. However， such methods need high-quality datasets to cope with the problem of high false alarm rate （FAR） and high missing alarm rate （MAR） in low altitude UAV detection， special high-quality low altitude UAV detection dataset is still lacking. A handful of known datasets for UAV detection have been rejected by their proposers for authorization and are of poor quality. In this paper， a comprehensive enhanced dataset containing UAVs and jamming objects is proposed. A large number of high-definition UAV images are obtained through real world shooting， web crawler， and data enhancement. Moreover， to cope with the challenge of low altitude UAV detection in complex backgrounds and long distance， as well as the puzzle caused by jamming objects， the noise with jamming characteristics is added to the dataset. Finally， the dataset is trained， validated， and tested by four mainstream deep learning models. The results indicate that by using data enhancement， adding noise contained jamming objects and images of UAV with complex backgrounds and long distance， the accuracy of UAV detection can be significantly improved. This work will promote the development of anti-UAV systems deeply，and more convincing evaluation criteria are provided for models optimization for UAV detection.
2021, 38(6):927-936.
DOI: 10.16356/j.1005-1120.2021.06.003
Abstract:
A data-driven method for arrival pattern recognition and prediction is proposed to provide air traffic controllers （ATCOs） with decision support. For arrival pattern recognition， a clustering-based method is proposed to cluster arrival patterns by control intentions. For arrival pattern prediction， two predictors are trained to estimate the most possible command issued by the ATCOs in a particular traffic situation. Training the arrival pattern predictor could be regarded as building an ATCOs simulator. The simulator can assign an appropriate arrival pattern for each arrival aircraft， just like real ATCOs do. Therefore， the simulator is considered to be able to provide effective advice for part of the work of ATCOs. Finally， a case study is carried out and demonstrates that the convolutional neural network （CNN）-based predictor performs better than the radom forest （RF）-based one.
A data-driven method for arrival pattern recognition and prediction is proposed to provide air traffic controllers （ATCOs） with decision support. For arrival pattern recognition， a clustering-based method is proposed to cluster arrival patterns by control intentions. For arrival pattern prediction， two predictors are trained to estimate the most possible command issued by the ATCOs in a particular traffic situation. Training the arrival pattern predictor could be regarded as building an ATCOs simulator. The simulator can assign an appropriate arrival pattern for each arrival aircraft， just like real ATCOs do. Therefore， the simulator is considered to be able to provide effective advice for part of the work of ATCOs. Finally， a case study is carried out and demonstrates that the convolutional neural network （CNN）-based predictor performs better than the radom forest （RF）-based one.
2021, 38(6):937-947.
DOI: 10.16356/j.1005-1120.2021.06.004
Abstract:
A point-to-point iterative learning control method with the current-cycle feedback is proposed to enable aircraft to achieve an accurate four-dimensional（4D） trajectory tracking. To this end， the 4D trajectory tracking control problem is formulated into a point-to-point tracking control issue with an external disturbance. Then， the optimal point-to-point iterative learning control law is derived based on the successive projection method. Further， the current-cycle feedback error is added to the control law， so that the tracking error is reduced in both time and iteration domains. Finally， a numerical simulation is carried out using the kinematic model of an unmanned aerial vehicle and 4D trajectory data. Obtained results demonstrate that the proposed method can quickly reduce the trajectory tracking error even in the presence of gust interferences. Compared with the commonly used average velocity method and the velocity correction method， the proposed method makes full use of the past and current running data， and can continuously improve the accuracy of 4D trajectory tracking with the repetitive operation of aircraft between city pairs.
A point-to-point iterative learning control method with the current-cycle feedback is proposed to enable aircraft to achieve an accurate four-dimensional（4D） trajectory tracking. To this end， the 4D trajectory tracking control problem is formulated into a point-to-point tracking control issue with an external disturbance. Then， the optimal point-to-point iterative learning control law is derived based on the successive projection method. Further， the current-cycle feedback error is added to the control law， so that the tracking error is reduced in both time and iteration domains. Finally， a numerical simulation is carried out using the kinematic model of an unmanned aerial vehicle and 4D trajectory data. Obtained results demonstrate that the proposed method can quickly reduce the trajectory tracking error even in the presence of gust interferences. Compared with the commonly used average velocity method and the velocity correction method， the proposed method makes full use of the past and current running data， and can continuously improve the accuracy of 4D trajectory tracking with the repetitive operation of aircraft between city pairs.
2021, 38(6):948-958.
DOI: 10.16356/j.1005-1120.2021.06.005
Abstract:
The flight departure process is affected by various uncertain factors， such as flight delays， scheduling delays and taxi time etc. A reliable and robust departure sequence is very important to the safe and efficient operation for airports. An optimal scheduling model for multi-runway departure considering the arrival aircraft crossing departure runway is developed. A genetic algorithm encoding flight numbers is designed to find a near-optimal solution. After that， further establish a multi-objective dynamic scheduling model and design a hybrid algorithm to solve it， and compare and analyze the results of the two models. A quantitative analysis of departure time based on the kernel density estimation is performed， and Monte Carlo simulations are carried out to explore the impact of flight departure time’s uncertainty on departure scheduling. The results based on historical data from Guangzhou Baiyun Airport are presented， showing the advantage of the proposed model and algorithm.
The flight departure process is affected by various uncertain factors， such as flight delays， scheduling delays and taxi time etc. A reliable and robust departure sequence is very important to the safe and efficient operation for airports. An optimal scheduling model for multi-runway departure considering the arrival aircraft crossing departure runway is developed. A genetic algorithm encoding flight numbers is designed to find a near-optimal solution. After that， further establish a multi-objective dynamic scheduling model and design a hybrid algorithm to solve it， and compare and analyze the results of the two models. A quantitative analysis of departure time based on the kernel density estimation is performed， and Monte Carlo simulations are carried out to explore the impact of flight departure time’s uncertainty on departure scheduling. The results based on historical data from Guangzhou Baiyun Airport are presented， showing the advantage of the proposed model and algorithm.
2021, 38(6):959-966.
DOI: 10.16356/j.1005-1120.2021.06.006
Abstract:
As the main body of air traffic control safety， the air traffic controller is an important part of the whole air traffic control system. According to the relevant data of civil aviation over the years， a mapping model between flight support sorties and air traffic controller demand is constructed by using the prediction algorithm of support vector regression （SVR） based on grid search and cross-validation. Then the model predicts the demand for air traffic controllers in seven regions. Additionally， according to the employment data of civil aviation universities， the future training scale of air traffic controller is predicted. The forecast results show that the average relative error of the number of controllers predicted by the algorithm is 1.73%， and the prediction accuracy is higher than traditional regression algorithms. Under the influence of the epidemic， the demand for air traffic controllers will decrease in the short term，but with the control of the epidemic，the demand of air traffic controllers will return to the pre-epidemic level and gradually increase. It is expected that the controller increment will be about 816 by 2028. The forecast results of the demand for air traffic controllers provide a theoretical basis for the introduction and training of medium and long-term air traffic controllers， and also provide method guidance and decision support for the establishment of professional reserve and dynamic control mechanism in the air traffic control system.
As the main body of air traffic control safety， the air traffic controller is an important part of the whole air traffic control system. According to the relevant data of civil aviation over the years， a mapping model between flight support sorties and air traffic controller demand is constructed by using the prediction algorithm of support vector regression （SVR） based on grid search and cross-validation. Then the model predicts the demand for air traffic controllers in seven regions. Additionally， according to the employment data of civil aviation universities， the future training scale of air traffic controller is predicted. The forecast results show that the average relative error of the number of controllers predicted by the algorithm is 1.73%， and the prediction accuracy is higher than traditional regression algorithms. Under the influence of the epidemic， the demand for air traffic controllers will decrease in the short term，but with the control of the epidemic，the demand of air traffic controllers will return to the pre-epidemic level and gradually increase. It is expected that the controller increment will be about 816 by 2028. The forecast results of the demand for air traffic controllers provide a theoretical basis for the introduction and training of medium and long-term air traffic controllers， and also provide method guidance and decision support for the establishment of professional reserve and dynamic control mechanism in the air traffic control system.
2021, 38(6):967-974.
DOI: 10.16356/j.1005-1120.2021.06.007
Abstract:
The combined gradient representations for generalized Birkhoffian systems in event space are studied. Firstly， the definitions of six kinds of combined gradient systems and corresponding differential equations are given. Secondly， the conditions under which generalized Birkhoffian systems become combined gradient systems are obtained. Finally， the characteristics of combined gradient systems are used to study the stability of generalized Birkhoffian systems in event space. Seven examples are given to illustrate the results.
The combined gradient representations for generalized Birkhoffian systems in event space are studied. Firstly， the definitions of six kinds of combined gradient systems and corresponding differential equations are given. Secondly， the conditions under which generalized Birkhoffian systems become combined gradient systems are obtained. Finally， the characteristics of combined gradient systems are used to study the stability of generalized Birkhoffian systems in event space. Seven examples are given to illustrate the results.
2021, 38(6):975-983.
DOI: 10.16356/j.1005-1120.2021.06.008
Abstract:
The discontinuous Galerkin（DG） method is established and innovatively conducted on accurately simulating the evolution of blade-tip vortex and the aerodynamic characteristics of helicopter rotor. Firstly， the Reynolds-Averaged Navier-Stokes（RANS） equations in rotating reference frame are employed， and the embedded grid system is developed with the finite volume method （FVM） and the DG method conducted on the blade grid and background grid respectively. Besides， the Harten-Lax-Van Leer contact （HLLC） scheme with high-resolution and low-dissipation is employed for spatial discretization， and the explicit third-order Runge-Kutta scheme is used to accomplish the temporal discretization. Secondly， the aerodynamic characteristics and the evolution of blade-tip vortex for Caradonna-Tung rotor are simulated by the established CFD method， and the numerical results are in good agreement with experimental data， which well validates the accuracy of the DG method and shows the advantages of DG method on capturing the detailed blade-tip vortex compared with the FVM method. Finally， the evolution of tip vortex at different blade tip Mach numbers and collective pitches is discussed.
The discontinuous Galerkin（DG） method is established and innovatively conducted on accurately simulating the evolution of blade-tip vortex and the aerodynamic characteristics of helicopter rotor. Firstly， the Reynolds-Averaged Navier-Stokes（RANS） equations in rotating reference frame are employed， and the embedded grid system is developed with the finite volume method （FVM） and the DG method conducted on the blade grid and background grid respectively. Besides， the Harten-Lax-Van Leer contact （HLLC） scheme with high-resolution and low-dissipation is employed for spatial discretization， and the explicit third-order Runge-Kutta scheme is used to accomplish the temporal discretization. Secondly， the aerodynamic characteristics and the evolution of blade-tip vortex for Caradonna-Tung rotor are simulated by the established CFD method， and the numerical results are in good agreement with experimental data， which well validates the accuracy of the DG method and shows the advantages of DG method on capturing the detailed blade-tip vortex compared with the FVM method. Finally， the evolution of tip vortex at different blade tip Mach numbers and collective pitches is discussed.
2021, 38(6):984-992.
DOI: 10.16356/j.1005-1120.2021.06.009
Abstract:
To improve the comfortability and safety of aircraft， the demand of rectangular submerged inlets （RSIs） with low resistance is proposed to increase the inlet flow rate of ram air. A theoretical model is built to numerically analyze the effects of geometric parameters on the inlet mass flow rate of RSIs. The geometric parameters in question here encompass the aspect ratio of 2—4， the ramp angle of 6°—7°， the characteristic parameter of the throat of 0.20 —0.30， the ramp length of 939—1 337 mm， and the cone angle of 0° —3°. Simulation results demonstrate that the mass flow rate （MFR）is positively correlated with the aspect ratio， ramp angle， ramp length， and cone angle， and negatively correlated with characteristic parameter of the throat. Within the range of the geometric parameters considered， the RSI with the aspect ratio of 3， the ramp angle of 6°， the characteristic parameter of the throat of 0.20， the ramp length of 1 337 mm， and the cone angle of 3° obtains the largest MFR value of about 2.251 kg/s.
To improve the comfortability and safety of aircraft， the demand of rectangular submerged inlets （RSIs） with low resistance is proposed to increase the inlet flow rate of ram air. A theoretical model is built to numerically analyze the effects of geometric parameters on the inlet mass flow rate of RSIs. The geometric parameters in question here encompass the aspect ratio of 2—4， the ramp angle of 6°—7°， the characteristic parameter of the throat of 0.20 —0.30， the ramp length of 939—1 337 mm， and the cone angle of 0° —3°. Simulation results demonstrate that the mass flow rate （MFR）is positively correlated with the aspect ratio， ramp angle， ramp length， and cone angle， and negatively correlated with characteristic parameter of the throat. Within the range of the geometric parameters considered， the RSI with the aspect ratio of 3， the ramp angle of 6°， the characteristic parameter of the throat of 0.20， the ramp length of 1 337 mm， and the cone angle of 3° obtains the largest MFR value of about 2.251 kg/s.
2021, 38(6):993-1002.
DOI: 10.16356/j.1005-1120.2021.06.010
Abstract:
A piezoelectric pump with flexible valve has been developed to pump high viscosity cooling liquid in the nanosats thermal control system. The structure of the flexible valve is designed according to the characteristics of the human aortic shape with the aim to simulate the bionic pumping function of the human heart. Dynamic stress-strain features of the flexible valve are analyzed by the finite element method， and the results show that the proposed flexible valve is suitable and functional for the piezoelectric pump. Then the cylinder and diffuser/nozzle piezoelectric pumps based on flexible valves have been developed and fabricated. Experimental results of the output performance indicate that the maximum flow rate of the cylinder piezoelectric pump with flexible valve is 15.38 mL/min， 170.77% higher than the diffuser/nozzle piezoelectric pump with flexible valve. The ability of the cylinder piezoelectric pump with flexible valve for transmitting high viscosity liquid has been validated. The piezoelectric pump with flexible valve has potential applications in the nanosats thermal control system.
A piezoelectric pump with flexible valve has been developed to pump high viscosity cooling liquid in the nanosats thermal control system. The structure of the flexible valve is designed according to the characteristics of the human aortic shape with the aim to simulate the bionic pumping function of the human heart. Dynamic stress-strain features of the flexible valve are analyzed by the finite element method， and the results show that the proposed flexible valve is suitable and functional for the piezoelectric pump. Then the cylinder and diffuser/nozzle piezoelectric pumps based on flexible valves have been developed and fabricated. Experimental results of the output performance indicate that the maximum flow rate of the cylinder piezoelectric pump with flexible valve is 15.38 mL/min， 170.77% higher than the diffuser/nozzle piezoelectric pump with flexible valve. The ability of the cylinder piezoelectric pump with flexible valve for transmitting high viscosity liquid has been validated. The piezoelectric pump with flexible valve has potential applications in the nanosats thermal control system.
11 Effects of Gas Flow Field on Clogging Phenomenon in Close-Coupled Vortical Loop Slit Gas Atomization
2021, 38(6):1003-1019.
DOI: 10.16356/j.1005-1120.2021.06.011
Abstract:
In order to study the basic characteristics of gas flow field in the atomizing chamber near the nozzle outlet of the vortical loop slit atomizer and its influence mechanism on clogging phenomenon， the computational fluid dynamics （CFD） software Fluent is used to conduct a numerical simulation of the gas flow field in the atomizing chamber near the nozzle outlet of this atomizer under different annular slit widths， different atomization gas pressures and different protrusion lengths of the melt delivery tube. The results show that under atomization gas pressure p = 4.5 MPa， the greater the annular slit width D， the lower the static temperature near the central hole outlet at the front end of the melt delivery tube， and the smaller the aspirating pressure at the front end of the melt delivery tube. These features can effectively prevent the occurrence of the clogging phenomenon of metallic melt. Under an annular slit width of D = 1.2 mm， when the atomization gas pressure satisfies 1 MPa ≤ p ≤ 2 MPa and increases gradually， the aspirating pressure at the front end of the melt delivery tube will decline rapidly. This can prevent the clogging phenomenon of metallic melt. However， when the atomization gas pressure p >2 MPa， the greater the atomization gas pressure， the lower the static temperature near the central hole outlet at the front end of the melt delivery tube， and the greater the aspirating pressure at the front end of the melt delivery tube. Hence， the effect of preventing the solidification-induced clogging phenomenon of metallic melt is restricted. When atomization gas pressure is p = 4.5 MPa and annular slit width is D = 1.2 mm， the greater the protrusion length H of the melt delivery tube， and the smaller the aspirating pressure at its front end. The static temperature near the central hole that can be observed in its front end is approximate to effectively prevent the occurrence of clogging phenomenon of metallic melt. However， because of the small aspirating pressure， the metallic melt flows into the atomizing chamber from the central hole at the front end of the melt delivery tube at an increasing speed and the gas-melt ratio in the mass flow rate is reduced， which is not conducive to the improvement of atomization performance.
In order to study the basic characteristics of gas flow field in the atomizing chamber near the nozzle outlet of the vortical loop slit atomizer and its influence mechanism on clogging phenomenon， the computational fluid dynamics （CFD） software Fluent is used to conduct a numerical simulation of the gas flow field in the atomizing chamber near the nozzle outlet of this atomizer under different annular slit widths， different atomization gas pressures and different protrusion lengths of the melt delivery tube. The results show that under atomization gas pressure p = 4.5 MPa， the greater the annular slit width D， the lower the static temperature near the central hole outlet at the front end of the melt delivery tube， and the smaller the aspirating pressure at the front end of the melt delivery tube. These features can effectively prevent the occurrence of the clogging phenomenon of metallic melt. Under an annular slit width of D = 1.2 mm， when the atomization gas pressure satisfies 1 MPa ≤ p ≤ 2 MPa and increases gradually， the aspirating pressure at the front end of the melt delivery tube will decline rapidly. This can prevent the clogging phenomenon of metallic melt. However， when the atomization gas pressure p >2 MPa， the greater the atomization gas pressure， the lower the static temperature near the central hole outlet at the front end of the melt delivery tube， and the greater the aspirating pressure at the front end of the melt delivery tube. Hence， the effect of preventing the solidification-induced clogging phenomenon of metallic melt is restricted. When atomization gas pressure is p = 4.5 MPa and annular slit width is D = 1.2 mm， the greater the protrusion length H of the melt delivery tube， and the smaller the aspirating pressure at its front end. The static temperature near the central hole that can be observed in its front end is approximate to effectively prevent the occurrence of clogging phenomenon of metallic melt. However， because of the small aspirating pressure， the metallic melt flows into the atomizing chamber from the central hole at the front end of the melt delivery tube at an increasing speed and the gas-melt ratio in the mass flow rate is reduced， which is not conducive to the improvement of atomization performance.
2021, 38(6):1020-1027.
DOI: 10.16356/j.1005-1120.2021.06.012
Abstract:
Combining the mutual information theory and the sequential hypothesis testing （SHT） method， a self-adapting radio frequency （RF） stealth signal design method is proposed. The channel information is gained through the radar echo and feeds back to the radar system， and then the radar system adaptively designs the transmission waveform. So the close-loop system is formed. The correlations between these transmission waveforms are decreased because of the adaptive change of these transmission waveforms， and the number of illuminations is reduced for adopting the SHT， which lowers the transmission power of the radar system. The radar system using the new method possesses the RF stealth performance. Aiming at the application of radar automatic target recognition （RATR）， experimental simulations show the effectiveness and feasibility of the proposed method.
Combining the mutual information theory and the sequential hypothesis testing （SHT） method， a self-adapting radio frequency （RF） stealth signal design method is proposed. The channel information is gained through the radar echo and feeds back to the radar system， and then the radar system adaptively designs the transmission waveform. So the close-loop system is formed. The correlations between these transmission waveforms are decreased because of the adaptive change of these transmission waveforms， and the number of illuminations is reduced for adopting the SHT， which lowers the transmission power of the radar system. The radar system using the new method possesses the RF stealth performance. Aiming at the application of radar automatic target recognition （RATR）， experimental simulations show the effectiveness and feasibility of the proposed method.
2021, 38(6):1028-1036.
DOI: 10.16356/j.1005-1120.2021.06.013
Abstract:
The performance of uplink distributed massive multiple-input multiple-output （MIMO） systems with cross-layer design （CLD） is investigated over Rayleigh fading channel， which combines the discrete rate adaptive modulation with truncated automatic repeat request. By means of the performance analysis， the closed-form expressions of average packet error rate （APER） and overall average spectral efficiency （ASE） of distributed massive MIMO systems with CLD are derived based on the conditional probability density function of each user’s approximate effective signal-to-noise ratio （SNR） and the switching thresholds under the target packet loss rate （PLR） constraint. With these results， using the approximation of complementary error functions， the approximate APER and overall ASE are also deduced. Simulation results illustrate that the obtained theoretical ASE and APER can match the corresponding simulations well. Besides， the target PLR requirement is satisfied， and the distributed massive MIMO systems offer an obvious performance gain over the co-located massive MIMO systems.
The performance of uplink distributed massive multiple-input multiple-output （MIMO） systems with cross-layer design （CLD） is investigated over Rayleigh fading channel， which combines the discrete rate adaptive modulation with truncated automatic repeat request. By means of the performance analysis， the closed-form expressions of average packet error rate （APER） and overall average spectral efficiency （ASE） of distributed massive MIMO systems with CLD are derived based on the conditional probability density function of each user’s approximate effective signal-to-noise ratio （SNR） and the switching thresholds under the target packet loss rate （PLR） constraint. With these results， using the approximation of complementary error functions， the approximate APER and overall ASE are also deduced. Simulation results illustrate that the obtained theoretical ASE and APER can match the corresponding simulations well. Besides， the target PLR requirement is satisfied， and the distributed massive MIMO systems offer an obvious performance gain over the co-located massive MIMO systems.
2021, 38(6):1037-1047.
DOI: 10.16356/j.1005-1120.2021.06.014
Abstract:
Visual inspection of the key components of nuclear power plants （NPPs） is important for NPP operation and maintenance. However， the underwater environment and existing radiation will lead to image degradation， thus making it difficult to identify surface defects. In this study， a method for improving the quality of underwater images is proposed. By analyzing the degradation characteristics of underwater detection image， the image enhancement technology is used to improve the color richness of the image， and then the improved dark channel prior （DCP） algorithm is used to restore it. By modifying the estimation formula of transmittance and background light， the correction of insufficient brightness in DCP restored image is realized. The proposed method is compared with other state-of-the-art methods. The results show that the proposed method can achieve higher scores and improve the image quality by correcting the color and restoring local details， thus effectively enhancing the reliability of visual inspection of NPPs.
Visual inspection of the key components of nuclear power plants （NPPs） is important for NPP operation and maintenance. However， the underwater environment and existing radiation will lead to image degradation， thus making it difficult to identify surface defects. In this study， a method for improving the quality of underwater images is proposed. By analyzing the degradation characteristics of underwater detection image， the image enhancement technology is used to improve the color richness of the image， and then the improved dark channel prior （DCP） algorithm is used to restore it. By modifying the estimation formula of transmittance and background light， the correction of insufficient brightness in DCP restored image is realized. The proposed method is compared with other state-of-the-art methods. The results show that the proposed method can achieve higher scores and improve the image quality by correcting the color and restoring local details， thus effectively enhancing the reliability of visual inspection of NPPs.
2021, 38(6):1048-1057.
DOI: 10.16356/j.1005-1120.2021.06.015
Abstract:
A flexible calibration method based on a front-coated flat mirror is proposed for a laser light-sectioning three-dimensional （3D） measurement system. Since the calibration target and its mirror image are spatially separated and can be recorded in an image by a camera， the proposed method requires only a single composite image that contains a non-planar checkerboard pattern， a laser strip projected on the target and their mirror images to complete the calibration of the camera and the laser plane in one step. Levenberg-Marquardt （LM） algorithm is used to optimize the system parameters， and the measurement accuracy and speed are improved to enable online 3D inspection. Static and dynamic online 3D measurements are carried out on a cup and a triple stepped shaft， respectively， to validate the proposed method. The shaft has two steps with the depth of （0.5±0.01） mm and （2±0.01） mm to be measured online when the shaft is rotated and translated at the same time. The measurement results can be output at a frequency of 7 to 11 readings per second with standard deviations of 0.040 mm and 0.051 mm. The experimental results verify the effectiveness and flexibility of the proposed method.
A flexible calibration method based on a front-coated flat mirror is proposed for a laser light-sectioning three-dimensional （3D） measurement system. Since the calibration target and its mirror image are spatially separated and can be recorded in an image by a camera， the proposed method requires only a single composite image that contains a non-planar checkerboard pattern， a laser strip projected on the target and their mirror images to complete the calibration of the camera and the laser plane in one step. Levenberg-Marquardt （LM） algorithm is used to optimize the system parameters， and the measurement accuracy and speed are improved to enable online 3D inspection. Static and dynamic online 3D measurements are carried out on a cup and a triple stepped shaft， respectively， to validate the proposed method. The shaft has two steps with the depth of （0.5±0.01） mm and （2±0.01） mm to be measured online when the shaft is rotated and translated at the same time. The measurement results can be output at a frequency of 7 to 11 readings per second with standard deviations of 0.040 mm and 0.051 mm. The experimental results verify the effectiveness and flexibility of the proposed method.
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