Transactions of Nanjing University of Aeronautics & Astronautics
Volume 31,Issue 4,2014 Table of Contents
2014, 31(4):345-361.
Abstract:
Ultra-high-speed grinding (UHSG) is a significant and powerful machining method in view of the enhanced productivity and precision demands. Previous researches regarding formation mechanisms and crucial technologies are comprehensively and thoroughly summarized to highlight state-of-art technology of UHSG. On the basis of the interdependence between process and machine innovations, theoretically,grinding mechanisms in strain hardening, strain rate strengthening, thermal softening, size effect and process characteristics need more in-depth studies to clarify the dominance of UHSG. Technically, CFRP wheel integrating with the brazed bonding has a prominent advantage in bonding strength and grit's configuration over vitrified bonding, which would be superior in UHSG. Furthermore, external high pressure cooling combining with inner jet cooling methods, accompanied by scraper plates to alleviate the effect of air boundary, are crucial and practical measures for realizing effective cooling in UHSG. Grinding processes, especially those being related to grinding parameters and precise in-process measuring approaches, are also prerequisite for fitting and investigation of UHSG.
Ultra-high-speed grinding (UHSG) is a significant and powerful machining method in view of the enhanced productivity and precision demands. Previous researches regarding formation mechanisms and crucial technologies are comprehensively and thoroughly summarized to highlight state-of-art technology of UHSG. On the basis of the interdependence between process and machine innovations, theoretically,grinding mechanisms in strain hardening, strain rate strengthening, thermal softening, size effect and process characteristics need more in-depth studies to clarify the dominance of UHSG. Technically, CFRP wheel integrating with the brazed bonding has a prominent advantage in bonding strength and grit's configuration over vitrified bonding, which would be superior in UHSG. Furthermore, external high pressure cooling combining with inner jet cooling methods, accompanied by scraper plates to alleviate the effect of air boundary, are crucial and practical measures for realizing effective cooling in UHSG. Grinding processes, especially those being related to grinding parameters and precise in-process measuring approaches, are also prerequisite for fitting and investigation of UHSG.
2 Threshold Selection Method Based on Reciprocal Gray Entropy and Artificial Bee Colony Optimization
2014, 31(4):362-369.
Abstract:
Since the logarithmic form of Shannon entropy has the drawback of undefined value at zero points, and most existing threshold selection methods only depend on the probability information, ignoring the within-class uniformity of gray level, a method of reciprocal gray entropy threshold selection is proposed based on two-dimensional(2-D) histogram region oblique division and artificial bee colony (ABC) optimization. Firstly, the definition of reciprocal gray entropy is introduced. Then on the basis of one-dimensional (1-D) method, 2-D threshold selection criterion function based on reciprocal gray entropy with histogram oblique division is derived. To accelerate the progress of searching the optimal threshold, the recently proposed ABC optimization algorithm is adopted. The proposed method not only avoids the undefined value points in Shannon entropy, but also achieves high accuracy and anti-noise performance due to reasonable 2-D histogram region division and the consideration of within-class uniformity of gray level. A large number of experimental results show that, compared with the maximum Shannon entropy method with 2-D histogram oblique division and the reciprocal entropy method with 2-D histogram oblique division based on niche chaotic mutation particle swarm optimization (NCPSO), the proposed method can achieve better segmentation results and can satisfy the requirement of real-time processing.
Since the logarithmic form of Shannon entropy has the drawback of undefined value at zero points, and most existing threshold selection methods only depend on the probability information, ignoring the within-class uniformity of gray level, a method of reciprocal gray entropy threshold selection is proposed based on two-dimensional(2-D) histogram region oblique division and artificial bee colony (ABC) optimization. Firstly, the definition of reciprocal gray entropy is introduced. Then on the basis of one-dimensional (1-D) method, 2-D threshold selection criterion function based on reciprocal gray entropy with histogram oblique division is derived. To accelerate the progress of searching the optimal threshold, the recently proposed ABC optimization algorithm is adopted. The proposed method not only avoids the undefined value points in Shannon entropy, but also achieves high accuracy and anti-noise performance due to reasonable 2-D histogram region division and the consideration of within-class uniformity of gray level. A large number of experimental results show that, compared with the maximum Shannon entropy method with 2-D histogram oblique division and the reciprocal entropy method with 2-D histogram oblique division based on niche chaotic mutation particle swarm optimization (NCPSO), the proposed method can achieve better segmentation results and can satisfy the requirement of real-time processing.
2014, 31(4):370-376.
Abstract:
In order to analyze the influence of setting error of tool on both tooth profile and contact characteristic of orthogonal face gear drive, the coordinate systems with and without setting error are established. Moreover, the equations of tooth profile and contact points of face gear drive are derived by envelope principle. According to the equations, the change of tooth profile and the contact points position on face gear are analyzed. The tooth surface and contact points are obtained by numerical simulation. Results show that the tooth profile and contact characteristic of face gear drive are not sensitive to the setting error of tool.
In order to analyze the influence of setting error of tool on both tooth profile and contact characteristic of orthogonal face gear drive, the coordinate systems with and without setting error are established. Moreover, the equations of tooth profile and contact points of face gear drive are derived by envelope principle. According to the equations, the change of tooth profile and the contact points position on face gear are analyzed. The tooth surface and contact points are obtained by numerical simulation. Results show that the tooth profile and contact characteristic of face gear drive are not sensitive to the setting error of tool.
2014, 31(4):377-385.
Abstract:
The forward kinematics of the general Stewart mechanism is studied and a fast numerical method is presented. Quaternion is utilized to model the forward kinematics and the equations are merely a system of quadratic ones. The numerical method is a nice simplification of the Newton-Raphson method when applied to this system. A simulation of the movement control of the Stewart mechanism is accomplished, confirming the effectiveness of the proposed algorithm in real-time conditions.
The forward kinematics of the general Stewart mechanism is studied and a fast numerical method is presented. Quaternion is utilized to model the forward kinematics and the equations are merely a system of quadratic ones. The numerical method is a nice simplification of the Newton-Raphson method when applied to this system. A simulation of the movement control of the Stewart mechanism is accomplished, confirming the effectiveness of the proposed algorithm in real-time conditions.
5 Optimal Power Management for Antagonizing Between Radar and Jamming Based on Continuous Game Theory
2014, 31(4):386-393.
Abstract:
To solve the problem of dynamic power resource allocation for cooperative penetration combat, the continuous game theory is introduced and a two-person general-sum continuous-game-based model is put forward with a common payoff function named collaborative detection probability of netted radar countermeasures. Comparing with traditional optimization methods, an obvious advantage of game-based model is an adequate consideration of the opposite potential strategy. This model guarantees a more effective allocation of the both sides′ power resource and a higher combat efficiency during a combat. Furthermore, an analysis of the complexity of the proposed model is given and a hierarchical processing method is presented to simplify the calculating process. Simulation results show the validity of the proposed scheme.
To solve the problem of dynamic power resource allocation for cooperative penetration combat, the continuous game theory is introduced and a two-person general-sum continuous-game-based model is put forward with a common payoff function named collaborative detection probability of netted radar countermeasures. Comparing with traditional optimization methods, an obvious advantage of game-based model is an adequate consideration of the opposite potential strategy. This model guarantees a more effective allocation of the both sides′ power resource and a higher combat efficiency during a combat. Furthermore, an analysis of the complexity of the proposed model is given and a hierarchical processing method is presented to simplify the calculating process. Simulation results show the validity of the proposed scheme.
2014, 31(4):394-404.
Abstract:
To learn from evolutionary experimental data points effectively, an evolutionary Gaussian mixture model based on constraint consistency (EGMM) is proposed and the corresponding method of parameter optimization is presented.Here, the Gaussian mixture model (GMM) is adopted to describe the data points, and the differences between the posterior probabilities of pairwise points under the current parameters are introduced to measure the temporal smoothness. Then, parameter optimization of EGMM can be realized by evolutionary clustering. Compared with most of the existing data analysis methods by evolutionary clustering, both the whole features and individual differences of data points are considered in the clustering framework of EGMM. It decreases the algorithm sensitivity to noises and increases the robustness of evaluated parameters. Experimental result shows that the clustering sequence really reflects the shift of data distribution, and the proposed algorithm can provide better clustering quality and temporal smoothness.
To learn from evolutionary experimental data points effectively, an evolutionary Gaussian mixture model based on constraint consistency (EGMM) is proposed and the corresponding method of parameter optimization is presented.Here, the Gaussian mixture model (GMM) is adopted to describe the data points, and the differences between the posterior probabilities of pairwise points under the current parameters are introduced to measure the temporal smoothness. Then, parameter optimization of EGMM can be realized by evolutionary clustering. Compared with most of the existing data analysis methods by evolutionary clustering, both the whole features and individual differences of data points are considered in the clustering framework of EGMM. It decreases the algorithm sensitivity to noises and increases the robustness of evaluated parameters. Experimental result shows that the clustering sequence really reflects the shift of data distribution, and the proposed algorithm can provide better clustering quality and temporal smoothness.
2014, 31(4):405-412.
Abstract:
The selection pressure of genetic algorithm reveals the degree of balance between the global exploration and local optimization. A novel algorithm called the hybrid multi-population cellular genetic algorithm (HCGA) is proposed, which combines population segmentation with particle swarm optimization (PSO). The control parameters are the number of individuals in the population and the number of subpopulations. By varying these control parameters, changes in selection pressure can be investigated. Population division is found to reduce the selection pressure. In particular, low selection pressure emerges in small and highly divided populations. Besides, slight or mild selection pressure reduces the convergence speed, and thus a new mutation operator accelerates the system. HPCGA is tested in the optimization of four typical functions and the results are compared with those of the conventional cellular genetic algorithm. HPCGA is found to significantly improve global convergence rate, convergence speed and stability. Population diversity is also investigated by HPCGA. Appropriate numbers of subpopulations not only achieve a better tradeoff between global exploration and local exploitation, but also greatly improve the optimization performance of HPCGA. It is concluded that HPCGA can elucidate the scientific basis for selecting the efficient numbers of subpopulations.
The selection pressure of genetic algorithm reveals the degree of balance between the global exploration and local optimization. A novel algorithm called the hybrid multi-population cellular genetic algorithm (HCGA) is proposed, which combines population segmentation with particle swarm optimization (PSO). The control parameters are the number of individuals in the population and the number of subpopulations. By varying these control parameters, changes in selection pressure can be investigated. Population division is found to reduce the selection pressure. In particular, low selection pressure emerges in small and highly divided populations. Besides, slight or mild selection pressure reduces the convergence speed, and thus a new mutation operator accelerates the system. HPCGA is tested in the optimization of four typical functions and the results are compared with those of the conventional cellular genetic algorithm. HPCGA is found to significantly improve global convergence rate, convergence speed and stability. Population diversity is also investigated by HPCGA. Appropriate numbers of subpopulations not only achieve a better tradeoff between global exploration and local exploitation, but also greatly improve the optimization performance of HPCGA. It is concluded that HPCGA can elucidate the scientific basis for selecting the efficient numbers of subpopulations.
2014, 31(4):413-419.
Abstract:
The solution of normal least squares support vector regression (LSSVR) is lack of sparseness, which limits the real-time and hampers the wide applications to a certain degree. To overcome this obstacle, a scheme, named I2FSA-LSSVR, is proposed. Compared with the previously approximate algorithms, it not only adopts the partial reduction strategy but considers the influence between the previously selected support vectors and the will-selected support vector during the process of computing the supporting weights. As a result, I2FSA-LSSVR reduces the number of support vectors and enhances the real-time. To confirm the feasibility and effectiveness of thｅ proposed algorithm, experiments on benchmark data sets are conducted, whose results support the presented I2FSA-LSSVR.
The solution of normal least squares support vector regression (LSSVR) is lack of sparseness, which limits the real-time and hampers the wide applications to a certain degree. To overcome this obstacle, a scheme, named I2FSA-LSSVR, is proposed. Compared with the previously approximate algorithms, it not only adopts the partial reduction strategy but considers the influence between the previously selected support vectors and the will-selected support vector during the process of computing the supporting weights. As a result, I2FSA-LSSVR reduces the number of support vectors and enhances the real-time. To confirm the feasibility and effectiveness of thｅ proposed algorithm, experiments on benchmark data sets are conducted, whose results support the presented I2FSA-LSSVR.
2014, 31(4):420-430.
Abstract:
A network-coding-based multisource LDPC-coded cooperative MIMO scheme is proposed, where multiple sources transmit their messages to the destination with the assistance from a single relay. The relay cooperates with multiple sources simultaneously via network-coding. It avoids the issues of imperfect frequency/timing synchronization and large transmission delay which may be introduced by frequency-division multiple access (FDMA)/code-division multiple access (CDMA) and time-division multiple access (TDMA) manners. The proposed joint ″Min-Sum″ iterative decoding is effectively carried out in the destination. Such a decoding algorithm agrees with the introduced equivalent joint Tanner graph which can be used to fully characterize LDPC codes employed by the sources and relay. Theoretical analysis and numerical simulation show that the proposed scheme with joint iterative decoding can achieve significant cooperation diversity gain. Furthermore, for the relay, compared with the cascade scheme, the proposed scheme has much lower complexity of LDPC-encoding and is easier to be implemented in the hardware with similar bit error rate (BER) performance.
A network-coding-based multisource LDPC-coded cooperative MIMO scheme is proposed, where multiple sources transmit their messages to the destination with the assistance from a single relay. The relay cooperates with multiple sources simultaneously via network-coding. It avoids the issues of imperfect frequency/timing synchronization and large transmission delay which may be introduced by frequency-division multiple access (FDMA)/code-division multiple access (CDMA) and time-division multiple access (TDMA) manners. The proposed joint ″Min-Sum″ iterative decoding is effectively carried out in the destination. Such a decoding algorithm agrees with the introduced equivalent joint Tanner graph which can be used to fully characterize LDPC codes employed by the sources and relay. Theoretical analysis and numerical simulation show that the proposed scheme with joint iterative decoding can achieve significant cooperation diversity gain. Furthermore, for the relay, compared with the cascade scheme, the proposed scheme has much lower complexity of LDPC-encoding and is easier to be implemented in the hardware with similar bit error rate (BER) performance.
2014, 31(4):431-439.
Abstract:
A cross-layer design (CLD) scheme with combination of power allocation, adaptive modulation (AM) and automatic repeat request (ARQ) is presented for space-time coded MIMO system under imperfect feedback, and the corresponding system performance is investigated in a Rayleigh fading channel. Based on imperfect feedback information, a suboptimal power allocation (PA) scheme is derived to maximize the average spectral efficiency (SE) of the system. The scheme is based on a so-called compressed SNR criterion, and has a closed-form expression for positive power allocation, thus being computationally efficient. Moreover, it can improve SE of the presented CLD. Besides, due to better approximation, it obtains the performance close to the existing optimal approach which requires numerical search. Simulation results show that the proposed CLD with PA can achieve higher SE than the conventional CLD with equal power allocation scheme, and has almost the same performance as CLD with optimal PA. However, it has lower calculation complexity.
A cross-layer design (CLD) scheme with combination of power allocation, adaptive modulation (AM) and automatic repeat request (ARQ) is presented for space-time coded MIMO system under imperfect feedback, and the corresponding system performance is investigated in a Rayleigh fading channel. Based on imperfect feedback information, a suboptimal power allocation (PA) scheme is derived to maximize the average spectral efficiency (SE) of the system. The scheme is based on a so-called compressed SNR criterion, and has a closed-form expression for positive power allocation, thus being computationally efficient. Moreover, it can improve SE of the presented CLD. Besides, due to better approximation, it obtains the performance close to the existing optimal approach which requires numerical search. Simulation results show that the proposed CLD with PA can achieve higher SE than the conventional CLD with equal power allocation scheme, and has almost the same performance as CLD with optimal PA. However, it has lower calculation complexity.
2014, 31(4):440-444.
Abstract:
A conformal Runge-Kutta multi-resolution time-domain (C-RKMRTD) method is present and applied to model and analyze curved objects. Compared with the non-conformal method, the proposed method is more accurate. The scattering analyses of the cylinder and ellipsoid are presented to validate the proposed method. The numerical results demonstrate that the proposed scheme perform better than the MRTD method and other higher order methods with a higher accuracy.
A conformal Runge-Kutta multi-resolution time-domain (C-RKMRTD) method is present and applied to model and analyze curved objects. Compared with the non-conformal method, the proposed method is more accurate. The scattering analyses of the cylinder and ellipsoid are presented to validate the proposed method. The numerical results demonstrate that the proposed scheme perform better than the MRTD method and other higher order methods with a higher accuracy.
2014, 31(4):445-451.
Abstract:
To better understand the formation of H2O2 in the ozonation of nitrobenzene and its role for the oxidation, a batch reactor of nitrobenzene ozonation was set up. The variables such as pH value, ozone dosage, and the presence of hydroxyl radical scavenger were investigated. The results showed that high accumulations of H2O2 were generally formed at low pH values and low ozone dosages. Moreover, H2O2 mainly formed after nitrobenzene was oxidized by hydroxyl radical during ozonation of the intermediates, such as p-nitrophenol, which reacted with ozone quickly in water. A small amount of additional H2O2 enhanced the nitrobenzene removal slightly. The kinetic study showed that nitrobenzene degradation fitted with pseudo-second-order kinetics well in the experiment. The kinetic constant values correlated linearly with the concentrations of H2O2 added. Thus, it is expected that the H2O2 formed in oxidation of nitrobenzene may initiate ozone decomposition to form hydroxyl radical and finally enhance the degradation of aromatic compounds to a certain extent.
To better understand the formation of H2O2 in the ozonation of nitrobenzene and its role for the oxidation, a batch reactor of nitrobenzene ozonation was set up. The variables such as pH value, ozone dosage, and the presence of hydroxyl radical scavenger were investigated. The results showed that high accumulations of H2O2 were generally formed at low pH values and low ozone dosages. Moreover, H2O2 mainly formed after nitrobenzene was oxidized by hydroxyl radical during ozonation of the intermediates, such as p-nitrophenol, which reacted with ozone quickly in water. A small amount of additional H2O2 enhanced the nitrobenzene removal slightly. The kinetic study showed that nitrobenzene degradation fitted with pseudo-second-order kinetics well in the experiment. The kinetic constant values correlated linearly with the concentrations of H2O2 added. Thus, it is expected that the H2O2 formed in oxidation of nitrobenzene may initiate ozone decomposition to form hydroxyl radical and finally enhance the degradation of aromatic compounds to a certain extent.
2014, 31(4):452-462.
Abstract:
Cyber physical system (CPS) provides more powerful service by cyber and physical features through the wireless communication. As a kind of social organized network system, a fundamental question of CPS is to achieve service self-organization with its nodes autonomously working in both physical and cyber environments. To solve the problem, the social nature of nodes in CPS is firstly addressed, and then a formal social semantic descriptions is presented for physical environment, node service and task in order to make the nodes communicate automatically and physical environment sensibly. Further, the Horn clause is introduced to represent the reasoning rules of service organizing. Based on the match function, which is defined for measurement between semantics, the semantic aware measurement is presented to evaluate whether environment around a node can satisfy the task requirement or not. Moreover, the service capacity evaluation method for nodes is addressed to find out the competent service from both cyber and physical features of nodes. According to aforementioned two measurements, the task semantic decomposition algorithm and the organizing matrix are defined and the service self-organizing mechanism for CPS is proposed. Finally, examinations are given to further verify the efficiency and feasibility of the proposed mechanism.
Cyber physical system (CPS) provides more powerful service by cyber and physical features through the wireless communication. As a kind of social organized network system, a fundamental question of CPS is to achieve service self-organization with its nodes autonomously working in both physical and cyber environments. To solve the problem, the social nature of nodes in CPS is firstly addressed, and then a formal social semantic descriptions is presented for physical environment, node service and task in order to make the nodes communicate automatically and physical environment sensibly. Further, the Horn clause is introduced to represent the reasoning rules of service organizing. Based on the match function, which is defined for measurement between semantics, the semantic aware measurement is presented to evaluate whether environment around a node can satisfy the task requirement or not. Moreover, the service capacity evaluation method for nodes is addressed to find out the competent service from both cyber and physical features of nodes. According to aforementioned two measurements, the task semantic decomposition algorithm and the organizing matrix are defined and the service self-organizing mechanism for CPS is proposed. Finally, examinations are given to further verify the efficiency and feasibility of the proposed mechanism.
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