Transactions of Nanjing University of Aeronautics & Astronautics
Volume 38,Issue 5,2021 Table of Contents
2021, 38(5):713-725.
DOI: 10.16356/j.1005-1120.2021.05.001
Abstract:
Aiming at the problem of large AC copper loss caused by skin effects and proximity effects， and low efficiency at high speed of the hairpin-winding permanent magnet synchronous motor （PMSM） for electric vehicles （EVs）， this paper firstly established the electromagnetic analytical model of the hairpin winding to calculate AC resistance. And the finite element model （FEM） of the hairpin-winding driving motor is established to calculate the AC characteristic of the hairpin winding at different speeds and temperatures. Then， combining modified particle swarm optimization （MPSO） and FEM， a 60 kW hairpin-winding PMSM is optimized under driving cycle conditions， and the electromagnetic performance and heat dissipation performance are compared with that of the traditional strand-winding motor. Finally， a prototype is made and an experimental platform is built to test the efficiency Map and temperature rise of the hairpin-winding motor over the whole speed range and verify the accuracy of the proposed optimization design method. The results show that the hairpin-winding PMSM not only has higher slot filling rate， high-efficiency range and power density， but also has better heat dissipation performance， which is suitable for application in the field of electric vehicles.
Aiming at the problem of large AC copper loss caused by skin effects and proximity effects， and low efficiency at high speed of the hairpin-winding permanent magnet synchronous motor （PMSM） for electric vehicles （EVs）， this paper firstly established the electromagnetic analytical model of the hairpin winding to calculate AC resistance. And the finite element model （FEM） of the hairpin-winding driving motor is established to calculate the AC characteristic of the hairpin winding at different speeds and temperatures. Then， combining modified particle swarm optimization （MPSO） and FEM， a 60 kW hairpin-winding PMSM is optimized under driving cycle conditions， and the electromagnetic performance and heat dissipation performance are compared with that of the traditional strand-winding motor. Finally， a prototype is made and an experimental platform is built to test the efficiency Map and temperature rise of the hairpin-winding motor over the whole speed range and verify the accuracy of the proposed optimization design method. The results show that the hairpin-winding PMSM not only has higher slot filling rate， high-efficiency range and power density， but also has better heat dissipation performance， which is suitable for application in the field of electric vehicles.
2021, 38(5):726-736.
DOI: 10.16356/j.1005-1120.2021.05.002
Abstract:
With the increasing requirement for the mechanical vibration and acoustic noise of the permanent magnet synchronous motor （PMSM） drive system， the demand for cogging torque reduction of PMSM has been considerably increased. To solve the problem of oversized cogging torque of axial flux PMSM， a rotor topology with hybrid permanent magnet is proposed to weaken the cogging torque. Firstly， the expression of the cogging torque of the axial flux motor is derived， and the influence of the pole-arc ratio of the permanent magnet on the cogging torque is analyzed. Secondly， the rotor structure with hybrid permanent magnet is adopted to reduce the cogging torque. According to the analytical analysis， the constraints of the size and pole-arc ratio between the hybrid permanent magnets are obtained， and the two permanent magnets related to the minimum cogging torque are determined. And the analysis results are verified by the finite element simulation. Furthermore， the motor performance with and without the hybrid permanent magnet is compared with each other. Finally， the cogging torque is significantly reduced by adopting a rotor structure with hybrid permanent magnets.
With the increasing requirement for the mechanical vibration and acoustic noise of the permanent magnet synchronous motor （PMSM） drive system， the demand for cogging torque reduction of PMSM has been considerably increased. To solve the problem of oversized cogging torque of axial flux PMSM， a rotor topology with hybrid permanent magnet is proposed to weaken the cogging torque. Firstly， the expression of the cogging torque of the axial flux motor is derived， and the influence of the pole-arc ratio of the permanent magnet on the cogging torque is analyzed. Secondly， the rotor structure with hybrid permanent magnet is adopted to reduce the cogging torque. According to the analytical analysis， the constraints of the size and pole-arc ratio between the hybrid permanent magnets are obtained， and the two permanent magnets related to the minimum cogging torque are determined. And the analysis results are verified by the finite element simulation. Furthermore， the motor performance with and without the hybrid permanent magnet is compared with each other. Finally， the cogging torque is significantly reduced by adopting a rotor structure with hybrid permanent magnets.
2021, 38(5):737-746.
DOI: 10.16356/j.1005-1120.2021.05.003
Abstract:
Electrifying the on-board subsystems of aircraft becomes an inevitable process as being faced with the environmental pollution， along with the proposed concept called more electric aircraft （MEA）. With the increasing number of on-board power electronic based devices， the distribution system of the aircraft can be regarded as an on-board microgrid. As it is known that the load power electronic converters can exhibit constant power load（CPL） characteristics and reduce the system stability， it is necessary to accurately predict and enhance the system stability in designing process. This paper firstly analyzes the stability of an on-board DC microgrid with the presence of CPL. Then， discusses the reasons behind instability and proposes a control strategy to enhance system stability. Finally， the simulation results are worked out to validate the analysis and the effect of the proposed control strategy.
Electrifying the on-board subsystems of aircraft becomes an inevitable process as being faced with the environmental pollution， along with the proposed concept called more electric aircraft （MEA）. With the increasing number of on-board power electronic based devices， the distribution system of the aircraft can be regarded as an on-board microgrid. As it is known that the load power electronic converters can exhibit constant power load（CPL） characteristics and reduce the system stability， it is necessary to accurately predict and enhance the system stability in designing process. This paper firstly analyzes the stability of an on-board DC microgrid with the presence of CPL. Then， discusses the reasons behind instability and proposes a control strategy to enhance system stability. Finally， the simulation results are worked out to validate the analysis and the effect of the proposed control strategy.
2021, 38(5):747-757.
DOI: 10.16356/j.1005-1120.2021.05.004
Abstract:
To improve the living standards， economical efficiency and environmental protection of isolated islands， remote areas and other areas with weak electric power facilities construction， a multi-source independent microgrid system is studied， including diesel generators， photovoltaic power generation system， wind power generation system and energy storage unit. Meanwhile， in order to realize the voltage and frequency stability control of AC bus of multi-source microgrid， the virtual synchronous generator technology is introduced into the energy storage unit， and the charge and discharge control of the energy storage battery are simulated as the control behavior characteristics of synchronous motors， so as to provide damping and inertia support for the microgrid. The operation mode and control principle of each energy subsystem are expounded and analyzed. The algorithm principle of virtual synchronous generator and the control method of energy storage unit are given. Then， the working modes of the microgrid system under different environmental conditions are analyzed， and the multi-source microgrid system simulation model is built based on MATLAB /Simulink. The simulation results show that the microgrid system can run stably under different working modes and the energy storage unit using the virtual synchronous generator technology can provide good voltage and frequency support for the microgrid system. Finally， experiments verify the supporting function of energy storage unit on the voltage and frequency of the microgrid system.
To improve the living standards， economical efficiency and environmental protection of isolated islands， remote areas and other areas with weak electric power facilities construction， a multi-source independent microgrid system is studied， including diesel generators， photovoltaic power generation system， wind power generation system and energy storage unit. Meanwhile， in order to realize the voltage and frequency stability control of AC bus of multi-source microgrid， the virtual synchronous generator technology is introduced into the energy storage unit， and the charge and discharge control of the energy storage battery are simulated as the control behavior characteristics of synchronous motors， so as to provide damping and inertia support for the microgrid. The operation mode and control principle of each energy subsystem are expounded and analyzed. The algorithm principle of virtual synchronous generator and the control method of energy storage unit are given. Then， the working modes of the microgrid system under different environmental conditions are analyzed， and the multi-source microgrid system simulation model is built based on MATLAB /Simulink. The simulation results show that the microgrid system can run stably under different working modes and the energy storage unit using the virtual synchronous generator technology can provide good voltage and frequency support for the microgrid system. Finally， experiments verify the supporting function of energy storage unit on the voltage and frequency of the microgrid system.
2021, 38(5):758-768.
DOI: 10.16356/j.1005-1120.2021.05.005
Abstract:
When using traditional drive circuits， the enhancement-mode GaN （eGaN） HEMT will be affected by high switching speed characteristics and parasitic parameters leading to worse crosstalk problems. Currently， the existing crosstalk suppression drive circuits often have the disadvantages of increased switching loss， control complexity， and overall electromagnetic interference （EMI）. Therefore， this paper combines the driving loop impedance control and the active Miller clamp method to propose an improved active Miller clamp drive circuit. First， the crosstalk mechanism is analyzed， and the crosstalk voltage model is established. Through the crosstalk voltage evaluation platform， the influencing factors are evaluated experimentally. Then， the operating principle of the improved active Miller clamp drive circuit is discussed， and the optimized parameter design method is given. Finally， the effect of the improved active Miller clamp method for suppressing crosstalk is experimentally verified. The crosstalk voltage was suppressed from 3.5 V and -3.5 V to 1 V and -1.3 V， respectively， by the improved circuit.
When using traditional drive circuits， the enhancement-mode GaN （eGaN） HEMT will be affected by high switching speed characteristics and parasitic parameters leading to worse crosstalk problems. Currently， the existing crosstalk suppression drive circuits often have the disadvantages of increased switching loss， control complexity， and overall electromagnetic interference （EMI）. Therefore， this paper combines the driving loop impedance control and the active Miller clamp method to propose an improved active Miller clamp drive circuit. First， the crosstalk mechanism is analyzed， and the crosstalk voltage model is established. Through the crosstalk voltage evaluation platform， the influencing factors are evaluated experimentally. Then， the operating principle of the improved active Miller clamp drive circuit is discussed， and the optimized parameter design method is given. Finally， the effect of the improved active Miller clamp method for suppressing crosstalk is experimentally verified. The crosstalk voltage was suppressed from 3.5 V and -3.5 V to 1 V and -1.3 V， respectively， by the improved circuit.
6 Influence of Refractive Index Distribution on Brillouin Gain Spectrum in GeO2-Doped Optical Fibers
2021, 38(5):769-787.
DOI: 10.16356/j.1005-1120.2021.05.006
Abstract:
GeO2 is commonly used as dopant to adjust the refractive index profile （RIP） and the acoustic velocity profile （AVP） in the fiber， thereby forming different Brillouin gain spectrum （BGS） characteristics such as Brillouin gain， acoustic mode number and peak intensity difference. When an optical fiber is used in optical fiber sensing or communication system， its BGS characteristics may play an important role in determining the performance of the system. In this paper， finite element analysis（FEA） method is used to study the influence of refractive index distribution and its corresponding AVP on the BGS in step-index， graded-index， and complex-index optical fibers. A new method has also been proposed to efficiently discriminate acoustic mode solution and obtain the new and full images of total Brillouin gain and acoustic modes number of the fiber as a function of the refractive index distribution， considering the influence of changing the refractive index difference and the geometric size simultaneously. For each type of optical fiber， the recommended parameter range is provided for optical fiber sensing and optical fiber communication. Moreover， the suitable optical fiber with close peak intensity in its multi-peak BGS is explored and achieved， which can be used in Brillouin beat spectrum detection systems to improve sensing accuracy.
GeO2 is commonly used as dopant to adjust the refractive index profile （RIP） and the acoustic velocity profile （AVP） in the fiber， thereby forming different Brillouin gain spectrum （BGS） characteristics such as Brillouin gain， acoustic mode number and peak intensity difference. When an optical fiber is used in optical fiber sensing or communication system， its BGS characteristics may play an important role in determining the performance of the system. In this paper， finite element analysis（FEA） method is used to study the influence of refractive index distribution and its corresponding AVP on the BGS in step-index， graded-index， and complex-index optical fibers. A new method has also been proposed to efficiently discriminate acoustic mode solution and obtain the new and full images of total Brillouin gain and acoustic modes number of the fiber as a function of the refractive index distribution， considering the influence of changing the refractive index difference and the geometric size simultaneously. For each type of optical fiber， the recommended parameter range is provided for optical fiber sensing and optical fiber communication. Moreover， the suitable optical fiber with close peak intensity in its multi-peak BGS is explored and achieved， which can be used in Brillouin beat spectrum detection systems to improve sensing accuracy.
2021, 38(5):788-799.
DOI: 10.16356/j.1005-1120.2021.05.007
Abstract:
In order to obtain the image of airframe damage region and provide the input data for aircraft intelligent maintenance， a multi-dimensional and multi-threshold airframe damage region division method based on correlation optimization is proposed. On the basis of airframe damage feature analysis， the multi-dimensional feature entropy is defined to realize the full fusion of multiple feature information of the image， and the division method is extended to multi-threshold to refine the damage division and reduce the impact of the damage adjacent region’s morphological changes on the division. Through the correlation parameter optimization algorithm， the problem of low efficiency of multi-dimensional multi-threshold division method is solved. Finally， the proposed method is compared and verified by instances of airframe damage image. The results show that compared with the traditional threshold division method， the damage region divided by the proposed method is complete and accurate， and the boundary is clear and coherent， which can effectively reduce the interference of many factors such as uneven luminance， chromaticity deviation， dirt attachment， image compression， and so on. The correlation optimization algorithm has high efficiency and stable convergence， and can meet the requirements of aircraft intelligent maintenance.
In order to obtain the image of airframe damage region and provide the input data for aircraft intelligent maintenance， a multi-dimensional and multi-threshold airframe damage region division method based on correlation optimization is proposed. On the basis of airframe damage feature analysis， the multi-dimensional feature entropy is defined to realize the full fusion of multiple feature information of the image， and the division method is extended to multi-threshold to refine the damage division and reduce the impact of the damage adjacent region’s morphological changes on the division. Through the correlation parameter optimization algorithm， the problem of low efficiency of multi-dimensional multi-threshold division method is solved. Finally， the proposed method is compared and verified by instances of airframe damage image. The results show that compared with the traditional threshold division method， the damage region divided by the proposed method is complete and accurate， and the boundary is clear and coherent， which can effectively reduce the interference of many factors such as uneven luminance， chromaticity deviation， dirt attachment， image compression， and so on. The correlation optimization algorithm has high efficiency and stable convergence， and can meet the requirements of aircraft intelligent maintenance.
2021, 38(5):800-806.
DOI: 10.16356/j.1005-1120.2021.05.008
Abstract:
By applying meander-line for electrical loss and magnetic material for magnetic loss， we present a metamaterial absorber which is wide-spaced and dual-band （1.35—2.24 GHz and 10.37—12.37 GHz）. The novelty of this study mainly lies in a combination of two kinds of losses to consume electromagnetic energy， which can get better dual-band absorption. In the electrical loss layer， meander-line structures are printed on both surfaces of the substrate and the structure series with resistors. Considering the need for miniaturization， we connect eight metallic vias with these meander-line areas to form a compact 2.5-dimensional （2.5D） structure. The dimension of the unit cell is miniaturized to be 5.94 mm×5.94 mm， about 0.035λ at the center frequency of the lower absorption band. In the magnetic loss layer， the 0.4 mm thick magnetic material is employed on a metallic ground plane. In addition， the complex permittivity and complex permeability of the magnetic material are given. Finally， we fabricate a prototype of the proposed absorber and obtain a measurement result which is in good agreement with the full-wave simulation result.
By applying meander-line for electrical loss and magnetic material for magnetic loss， we present a metamaterial absorber which is wide-spaced and dual-band （1.35—2.24 GHz and 10.37—12.37 GHz）. The novelty of this study mainly lies in a combination of two kinds of losses to consume electromagnetic energy， which can get better dual-band absorption. In the electrical loss layer， meander-line structures are printed on both surfaces of the substrate and the structure series with resistors. Considering the need for miniaturization， we connect eight metallic vias with these meander-line areas to form a compact 2.5-dimensional （2.5D） structure. The dimension of the unit cell is miniaturized to be 5.94 mm×5.94 mm， about 0.035λ at the center frequency of the lower absorption band. In the magnetic loss layer， the 0.4 mm thick magnetic material is employed on a metallic ground plane. In addition， the complex permittivity and complex permeability of the magnetic material are given. Finally， we fabricate a prototype of the proposed absorber and obtain a measurement result which is in good agreement with the full-wave simulation result.
2021, 38(5):807-815.
DOI: 10.16356/j.1005-1120.2021.05.009
Abstract:
In view of the fact that the traditional Hausdorff image matching algorithm is very sensitive to the image size as well as the unsatisfactory real-time performance in practical applications， an image matching algorithm is proposed based on the combination of Yolov3. Firstly， the features of the reference image are selected for pre-training， and then the training results are used to extract the features of the real images before the coordinates of the center points of the feature area are used to complete the coarse matching. Finally， the Hausdorff algorithm is used to complete the fine image matching. Experiments show that the proposed algorithm significantly improves the speed and accuracy of image matching. Also， it is robust to rotation changes.
In view of the fact that the traditional Hausdorff image matching algorithm is very sensitive to the image size as well as the unsatisfactory real-time performance in practical applications， an image matching algorithm is proposed based on the combination of Yolov3. Firstly， the features of the reference image are selected for pre-training， and then the training results are used to extract the features of the real images before the coordinates of the center points of the feature area are used to complete the coarse matching. Finally， the Hausdorff algorithm is used to complete the fine image matching. Experiments show that the proposed algorithm significantly improves the speed and accuracy of image matching. Also， it is robust to rotation changes.
2021, 38(5):816-828.
DOI: 10.16356/j.1005-1120.2021.05.010
Abstract:
Accurately solving transient nonlinear inverse heat conduction problems in complex structures is of great importance to provide key parameters for modeling coupled heat transfer process and the structure’s optimization design. The finite element method in ABAQUS is employed to solve the direct transient nonlinear heat conduction problem. Improved particle swarm optimization （PSO） method is developed and used to solve the transient nonlinear inverse problem. To investigate the inverse performances， some numerical tests are provided. Boundary conditions at inaccessible surfaces of a scramjet combustor with the regenerative cooling system are inversely identified. The results show that the new methodology can accurately and efficiently determine the boundary conditions in the scramjet combustor with the regenerative cooling system. By solving the transient nonlinear inverse problem， the improved particle swarm optimization for solving the transient nonlinear inverse heat conduction problem in a complex structure is verified.
Accurately solving transient nonlinear inverse heat conduction problems in complex structures is of great importance to provide key parameters for modeling coupled heat transfer process and the structure’s optimization design. The finite element method in ABAQUS is employed to solve the direct transient nonlinear heat conduction problem. Improved particle swarm optimization （PSO） method is developed and used to solve the transient nonlinear inverse problem. To investigate the inverse performances， some numerical tests are provided. Boundary conditions at inaccessible surfaces of a scramjet combustor with the regenerative cooling system are inversely identified. The results show that the new methodology can accurately and efficiently determine the boundary conditions in the scramjet combustor with the regenerative cooling system. By solving the transient nonlinear inverse problem， the improved particle swarm optimization for solving the transient nonlinear inverse heat conduction problem in a complex structure is verified.
2021, 38(5):829-839.
DOI: 10.16356/j.1005-1120.2021.05.011
Abstract:
This paper proposes an optimization model for the airport ground movement problem （GMP） based on bilevel programming to address taxi conflicts on the airport ground and to improve the operating safety and efficiency. To solve GMP， an iterative heuristic algorithm is designed. Instead of separately investigating each problem， this model simultaneously coordinates and optimizes the aircraft routing and scheduling. A simulation test is conducted on Nanjing Lukou International Airport （NKG） and the results show that the bilevel programming model can clearly outperform the widely used first-come-first-service （FCFS） scheduling scheme in terms of aircraft operational time under the precondition of none conflict. The research effort demonstrates that with the reduced operating cost and the improved overall efficiency， the proposed model can assist operations of the airports that are facing increasing traffic demand and working at almost maximum capacity.
This paper proposes an optimization model for the airport ground movement problem （GMP） based on bilevel programming to address taxi conflicts on the airport ground and to improve the operating safety and efficiency. To solve GMP， an iterative heuristic algorithm is designed. Instead of separately investigating each problem， this model simultaneously coordinates and optimizes the aircraft routing and scheduling. A simulation test is conducted on Nanjing Lukou International Airport （NKG） and the results show that the bilevel programming model can clearly outperform the widely used first-come-first-service （FCFS） scheduling scheme in terms of aircraft operational time under the precondition of none conflict. The research effort demonstrates that with the reduced operating cost and the improved overall efficiency， the proposed model can assist operations of the airports that are facing increasing traffic demand and working at almost maximum capacity.
2021, 38(5):840-851.
DOI: 10.16356/j.1005-1120.2021.05.012
Abstract:
The timely and accurately detection of abnormal aircraft trajectory is critical to improving flight safety. However， the existing anomaly detection methods based on machine learning cannot well characterize the features of aircraft trajectories. Low anomaly detection accuracy still exists due to the high-dimensionality， heterogeneity and temporality of flight trajectory data. To this end， this paper proposes an abnormal trajectory detection method based on the deep mixture density network （DMDN） to detect flights with unusual data patterns and evaluate flight trajectory safety. The technique consists of two components： Utilization of the deep long short-term memory （LSTM） network to encode features of flight trajectories effectively， and parameterization of the statistical properties of flight trajectory using the Gaussian mixture model （GMM）. Experiment results on Guangzhou Baiyun International Airport terminal airspace show that the proposed method can effectively capture the statistical patterns of aircraft trajectories. The model can detect abnormal flights with elevated risks and its performance is superior to two mainstream methods. The proposed model can be used as an assistant decision-making tool for air traffic controllers.
The timely and accurately detection of abnormal aircraft trajectory is critical to improving flight safety. However， the existing anomaly detection methods based on machine learning cannot well characterize the features of aircraft trajectories. Low anomaly detection accuracy still exists due to the high-dimensionality， heterogeneity and temporality of flight trajectory data. To this end， this paper proposes an abnormal trajectory detection method based on the deep mixture density network （DMDN） to detect flights with unusual data patterns and evaluate flight trajectory safety. The technique consists of two components： Utilization of the deep long short-term memory （LSTM） network to encode features of flight trajectories effectively， and parameterization of the statistical properties of flight trajectory using the Gaussian mixture model （GMM）. Experiment results on Guangzhou Baiyun International Airport terminal airspace show that the proposed method can effectively capture the statistical patterns of aircraft trajectories. The model can detect abnormal flights with elevated risks and its performance is superior to two mainstream methods. The proposed model can be used as an assistant decision-making tool for air traffic controllers.
2021, 38(5):852-866.
DOI: 10.16356/j.1005-1120.2021.05.013
Abstract:
Most of the traditional taxi path planning studies assume that the aircraft is in uniform speed， and the optimization goal is the shortest taxi time. Although it is easy to solve， it does not consider the changes in the speed profile of the aircraft when turning， and the shortest taxi time does not necessarily bring the best taxi fuel consumption. In this paper， the number of turns is considered， and the improved A* algorithm is used to obtain the P static paths with the shortest sum of the straight-line distance and the turning distance of the aircraft as the feasible taxi paths. By balancing taxi time and fuel consumption， a set of Pareto optimal speed profiles are generated for each preselected path to predict the 4-D trajectory of the aircraft. Based on the 4-D trajectory prediction results， the conflict by the occupied time window in the taxiing area is detected. For the conflict aircraft， based on the priority comparison， the waiting or changing path is selected to solve the taxiing conflict. Finally， the conflict free aircraft taxiing path is generated and the area occupation time window on the path is updated. The experimental results show that the total taxi distance and turn time of the aircraft are reduced， and the fuel consumption is reduced. The proposed method has high practical application value and is expected to be applied in real-time air traffic control decision-making in the future.
Most of the traditional taxi path planning studies assume that the aircraft is in uniform speed， and the optimization goal is the shortest taxi time. Although it is easy to solve， it does not consider the changes in the speed profile of the aircraft when turning， and the shortest taxi time does not necessarily bring the best taxi fuel consumption. In this paper， the number of turns is considered， and the improved A* algorithm is used to obtain the P static paths with the shortest sum of the straight-line distance and the turning distance of the aircraft as the feasible taxi paths. By balancing taxi time and fuel consumption， a set of Pareto optimal speed profiles are generated for each preselected path to predict the 4-D trajectory of the aircraft. Based on the 4-D trajectory prediction results， the conflict by the occupied time window in the taxiing area is detected. For the conflict aircraft， based on the priority comparison， the waiting or changing path is selected to solve the taxiing conflict. Finally， the conflict free aircraft taxiing path is generated and the area occupation time window on the path is updated. The experimental results show that the total taxi distance and turn time of the aircraft are reduced， and the fuel consumption is reduced. The proposed method has high practical application value and is expected to be applied in real-time air traffic control decision-making in the future.
2021, 38(5):867-875.
DOI: 10.16356/j.1005-1120.2021.05.014
Abstract:
In order to directly construct the mapping between multiple state parameters and remaining useful life （RUL）， and reduce the interference of random error on prediction accuracy， a RUL prediction model of aeroengine based on principal component analysis （PCA） and one-dimensional convolution neural network （1D-CNN） is proposed in this paper. Firstly， multiple state parameters corresponding to massive cycles of aeroengine are collected and brought into PCA for dimensionality reduction， and principal components are extracted for further time series prediction. Secondly， the 1D-CNN model is constructed to directly study the mapping between principal components and RUL. Multiple convolution and pooling operations are applied for deep feature extraction， and the end-to-end RUL prediction of aeroengine can be realized. Experimental results show that the most effective principal component from the multiple state parameters can be obtained by PCA， and the long time series of multiple state parameters can be directly mapped to RUL by 1D-CNN， so as to improve the efficiency and accuracy of RUL prediction. Compared with other traditional models， the proposed method also has lower prediction error and better robustness.
In order to directly construct the mapping between multiple state parameters and remaining useful life （RUL）， and reduce the interference of random error on prediction accuracy， a RUL prediction model of aeroengine based on principal component analysis （PCA） and one-dimensional convolution neural network （1D-CNN） is proposed in this paper. Firstly， multiple state parameters corresponding to massive cycles of aeroengine are collected and brought into PCA for dimensionality reduction， and principal components are extracted for further time series prediction. Secondly， the 1D-CNN model is constructed to directly study the mapping between principal components and RUL. Multiple convolution and pooling operations are applied for deep feature extraction， and the end-to-end RUL prediction of aeroengine can be realized. Experimental results show that the most effective principal component from the multiple state parameters can be obtained by PCA， and the long time series of multiple state parameters can be directly mapped to RUL by 1D-CNN， so as to improve the efficiency and accuracy of RUL prediction. Compared with other traditional models， the proposed method also has lower prediction error and better robustness.
WANG Liping
,
TANG Dunbing
,
SUN Hongwei
,
LIAO Liangchuang
,
ZHANG Zequn
,
ZHOU Tong
,
NIE Qingwei
,
SONG Jiaye
2021, 38(5):876-892.
DOI: 10.16356/j.1005-1120.2021.05.015
Abstract:
As the manufacturing mode focuses more on network and community， the orders and production processes are becoming highly dynamic and unpredictable. The traditional manufacturing system cannot handle those exceptional events such as rush orders and machine breakdowns. Nevertheless， the multiagent manufacturing system （MAMS） becomes a critical pattern to deal with these disturbances in a real-time way. However， due to the lack of universality， MAMS is difficult to be applied to industrial sites. A new multiagent architecture and the relay cooperation model based on a positive process relation matrix are proposed to address this paper’s issue. An optimized contract net protocol （CNP）-based negotiation mechanism is developed to improve the efficiency of collaboration in the proposed architecture. Finally， a case study of self-organizing internet of things （IoT） manufacturing system is used to test the feasibility and effectiveness of the method. It is shown that the proposed self-organizing IoT manufacturing mode outperforms the traditional manufacturing system in terms of makespan and critical machine workload balancing under disturbances through comparison.
As the manufacturing mode focuses more on network and community， the orders and production processes are becoming highly dynamic and unpredictable. The traditional manufacturing system cannot handle those exceptional events such as rush orders and machine breakdowns. Nevertheless， the multiagent manufacturing system （MAMS） becomes a critical pattern to deal with these disturbances in a real-time way. However， due to the lack of universality， MAMS is difficult to be applied to industrial sites. A new multiagent architecture and the relay cooperation model based on a positive process relation matrix are proposed to address this paper’s issue. An optimized contract net protocol （CNP）-based negotiation mechanism is developed to improve the efficiency of collaboration in the proposed architecture. Finally， a case study of self-organizing internet of things （IoT） manufacturing system is used to test the feasibility and effectiveness of the method. It is shown that the proposed self-organizing IoT manufacturing mode outperforms the traditional manufacturing system in terms of makespan and critical machine workload balancing under disturbances through comparison.
2021, 38(5):893-900.
DOI: 10.16356/j.1005-1120.2021.05.016
Abstract:
Ti-4Al-1.5Mn dual phase titanium alloy sheet was spot welded by pneumatic resistance spot welder. The effects of different welding parameters on shear load and nugget diameter were studied. The results show that the maximum shear load of solder joint increases first and then decreases with the increase of electrode pressure and welding current， while the nugget diameter increases with the increase of electrode pressure and welding current. Electrode pressure of 0.20 MPa and welding current of 46 A are the optimal process parameters， under which the maximum shear load of solder joint reaches 8.80 kN. The microstructure of nugget zone is coarse acicular martensite， and the solder joints fail in a mixed mode of intergranular brittle-ductile fracture.
Ti-4Al-1.5Mn dual phase titanium alloy sheet was spot welded by pneumatic resistance spot welder. The effects of different welding parameters on shear load and nugget diameter were studied. The results show that the maximum shear load of solder joint increases first and then decreases with the increase of electrode pressure and welding current， while the nugget diameter increases with the increase of electrode pressure and welding current. Electrode pressure of 0.20 MPa and welding current of 46 A are the optimal process parameters， under which the maximum shear load of solder joint reaches 8.80 kN. The microstructure of nugget zone is coarse acicular martensite， and the solder joints fail in a mixed mode of intergranular brittle-ductile fracture.
CHINA AERO-SCIENCES
Mobile website
Transactions of Nanjing University of Aeronautics & Astronautics ® 2024 All Rights Reserved