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| 1 | A reliability assessment method based on support vector machines for CNC equipment显示文摘With the applications of high technology,a catastrophic failure of CNC equipment rarely occurs at normal operation conditions.So it is difficult for traditional reliability assessment methods based on time-to-failure distributions to deduce the reliability level.This paper presents a novel reliability assessment methodology to estimate the reliability level of equipment with machining performance degradation data when only a few samples are available.The least squares support vector machines(LS-SVM) are introduced to analyze the performance degradation process on the equipment.A two-stage parameter optimization and searching method is proposed to improve the LS-SVM regression performance and a reliability assessment model based on the LS-SVM is built.A machining performance degradation experiment has been carried out on an OTM650 machine tool to validate the effectiveness of the proposed reliability assessment methodology. | WU Jun DENG Chao SHAO XinYu XIE S Q | 2009 | Science China(Technological Sciences)2009，52，7： | 14 |
| 2 | Parameter Optimization of Interval Type-2 Fuzzy Neural Networks Based on PSO and BBBC Methods显示文摘Interval type-2 fuzzy neural networks(IT2FNNs)can be seen as the hybridization of interval type-2 fuzzy systems(IT2FSs) and neural networks(NNs). Thus, they naturally inherit the merits of both IT2 FSs and NNs. Although IT2 FNNs have more advantages in processing uncertain, incomplete, or imprecise information compared to their type-1 counterparts, a large number of parameters need to be tuned in the IT2 FNNs,which increases the difficulties of their design. In this paper,big bang-big crunch(BBBC) optimization and particle swarm optimization(PSO) are applied in the parameter optimization for Takagi-Sugeno-Kang(TSK) type IT2 FNNs. The employment of the BBBC and PSO strategies can eliminate the need of backpropagation computation. The computing problem is converted to a simple feed-forward IT2 FNNs learning. The adoption of the BBBC or the PSO will not only simplify the design of the IT2 FNNs, but will also increase identification accuracy when compared with present methods. The proposed optimization based strategies are tested with three types of interval type-2 fuzzy membership functions(IT2FMFs) and deployed on three typical identification models. Simulation results certify the effectiveness of the proposed parameter optimization methods for the IT2 FNNs. | Jiajun Wang Tufan Kumbasar | 2019 | IEEE/CAA Journal of Automatica Sinica2019，6，1： | 14 |
| 3 | Design of a novel 3-DOF hybrid mechanical arm显示文摘Parameter optimization for a novel 3-DOF hybrid mechanical arm was presented by using a statistics method called the statistics parameters optimization method based on index atlases.Several kinematics and mechanics performance evaluation indices were proposed and discussed,according to the kinematics and mechanics analyses of the mechanical arm.Considering the assembly technique,a prototype of the 3-DOF hybrid mechanical arm was developed,which provided a basis for applications of the 3-DOF hybrid mechanical arm.The novel 3-DOF hybrid mechanical arm can be applied to the modern industrial fields requiring high stiffness,lower inertia and good technological efficiency.A novel 6-DOF hybrid humanoid mechanical arm was built,in which the present mechanical arm was connected with a spherical 3-DOF parallel manipulator. | LI YanBiao JIN ZhenLin JI ShiMing | 2009 | Science China(Technological Sciences)2009，52，12： | 8 |
| 4 | Parameters Optimization of a Novel 5-DOF Gasbag Polishing Machine Tool显示文摘The research on the parameters optimization for gasbag polishing machine tools, mainly aims at a better kinematics performance and a design scheme. Serial structural arm is mostly employed in gasbag polishing machine tools at present, but it is disadvantaged by its complexity, big inertia, and so on. In the multi-objective parameters optimization, it is very difficult to select good parameters to achieve excellent performance of the mechanism. In this paper, a statistics parameters optimization method based on index atlases is presented for a novel 5-DOF gasbag polishing machine tool. In the position analyses, the structure and workspace for a novel 5-DOF gasbag polishing machine tool is developed, where the gasbag polishing machine tool is advantaged by its simple structure, lower inertia and bigger workspace. In the kinematics analyses, several kinematics performance evaluation indices of the machine tool are proposed and discussed, and the global kinematics performance evaluation atlases are given. In the parameters optimization process, considering the assembly technique, a design scheme of the 5-DOF gasbag polishing machine tool is given to own better kinematics performance based on the proposed statistics parameters optimization method, and the global linear isotropic performance index is 0.5, the global rotational isotropic performance index is 0.5, the global linear velocity transmission performance index is 1.012 3 m/s in the case of unit input matrix, the global rotational velocity transmission performance index is 0.102 7 rad/s in the case of unit input matrix, and the workspace volume is 1. The proposed research provides the basis for applications of the novel 5-DOF gasbag polishing machine tool, which can be applied to the modern industrial fields requiring machines with lower inertia, better kinematics transmission performance and better technological efficiency. | LI Yanbiao TAN Dapeng WEN Donghui JI Shiming CAI Donghai | 2013 | Chinese Journal of Mechanical Engineering2013，26，4： | 7 |
| 5 | Study of probability integration method parameter inversion by the genetic algorithm显示文摘In order to obtain accurate probability integration method(PIM) parameters for surface movement of multi-panel mining, a genetic algorithm(GA) was used to optimize the parameters. As the measured surface movement is affected by more than one mining panel, traditional PIM parameter inversion model is difficult to ensure the reliability of the results due to the complexity of rock movement. With crossover,mutation and selection operators, GA can perform a global optimization search and has high computation efficiency. Compared with the pattern search algorithm, the fitness function can avoid falling into local minima traps. GA reduces the risk of local minima traps which improves the accuracy and reliability with the mutation mechanism. Application at Xuehu colliery shows that GA can be used to inverse the PIM parameters for multi-panel surface movement observation, and reliable results can be obtained. The research provides a new way for back-analysis of PIM parameters for mining subsidence under complex conditions. | Li Peixian Peng Di Tan Zhixiang Deng Kazhong | 2017 | International Journal of Mining Science and Technology2017，27，6： | 5 |
| 6 | On the effective inversion by imposing a priori information for retrieval of land surface parameters显示文摘The anisotropy of the land surface can be best described by the bidirectional reflectance distribution function (BRDF). As the field of multiangular remote sensing advances, it is increasingly probable that BRDF models can be inverted to estimate the important biological or climatological parameters of the earth surface such as leaf area index and albedo. The state-of-the-art of BRDF is the use of the linear kernel-driven models, mathematically described as the linear combination of the isotropic kernel, volume scattering kernel and geometric optics kernel. The computational stability is characterized by the algebraic operator spectrum of the kernel-matrix and the observation errors. Therefore, the retrieval of the model coefficients is of great importance for computation of the land surface albedos. We first consider the smoothing solution method of the kernel-driven BRDF models for retrieval of land surface albedos. This is known as an ill-posed inverse problem. The ill-posedness arises from that the linear kernel driven BRDF model is usually underdetermined if there are too few looks or poor directional ranges, or the observations are highly dependent. For example, a single angular observation may lead to an under-determined system whose solution is infinite (the null space of the kernel operator contains nonzero vectors) or no solution (the rank of the coefficient matrix is not equal to the augmented matrix). Therefore, some smoothing or regularization technique should be applied to suppress the ill-posedness. So far, least squares error methods with a priori knowledge, QR decomposition method for inversion of the BRDF model and regularization theories for ill-posed inversion were developed. In this paper, we emphasize on imposing a priori information in different spaces. We first propose a gen-eral a priori imposed regularization model problem, and then address two forms of regularization scheme. The first one is a regularized singular value decomposition method, and then we propose a retrieval method in l1 space. We show that the proposed method is suitable for solving land surface parameter retrieval problem if the sampling data are poor. Numerical experiments are also given to show the efficiency of the proposed methods. | WANG YanFei MA ShiQian YANG Hua WANG JinDi LI XiaoWen | 2009 | Science China Earth Sciences2009，52，4： | 4 |
| 7 | Investigation and optimization of sampling characteristics of light field camera for flame temperature measurement显示文摘It is essential to investigate the light field camera parameters for the accurate flame temperature measurement because the sampling characteristics of the flame radiation can be varied with them. In this study, novel indices of the light field camera were proposed to investigate the directional and spatial sampling characteristics of the flame radiation. Effects of light field camera parameters such as focal length and magnification of the main lens, focal length and magnification of the microlens were investigated. It was observed that the sampling characteristics of the flame are varied with the different parameters of the light field camera. The optimized parameters of the light field camera were then proposed for the flame radiation sampling. The larger sampling angle(23 times larger) is achieved by the optimized parameters compared to the commercial light field camera parameters. A non-negative least square(NNLS) algorithm was used to reconstruct the flame temperature. The reconstruction accuracy was also evaluated by the optimized parameters. The results suggested that the optimized parameters can provide higher reconstruction accuracy for axisymmetric and non-symmetric flame conditions in comparison to the commercial light field camera. | 刘煜东 Md.Moinul Hossain 孙俊 张彪 许传龙 | 2019 | Chinese Physics B2019，28，3： | 4 |
| 8 | Dynamics analysis of chaotic maps: From perspective on parameter estimation by meta-heuristic algorithm显示文摘Chaotic encryption is one of hot topics in cryptography, which has received increasing attention. Among many encryption methods, chaotic map is employed as an important source of pseudo-random numbers(PRNS). Although the randomness and the butterfly effect of chaotic map make the generated sequence look very confused, its essence is still the deterministic behavior generated by a set of deterministic parameters. Therefore, the unceasing improved parameter estimation technology becomes one of potential threats for chaotic encryption, enhancing the attacking effect of the deciphering methods. In this paper, for better analyzing the cryptography, we focus on investigating the condition of chaotic maps to resist parameter estimation. An improved particle swarm optimization(IPSO) algorithm is introduced as the estimation method. Furthermore, a new piecewise principle is proposed for increasing estimation precision. Detailed experimental results demonstrate the effectiveness of the new estimation principle, and some new requirements are summarized for a secure chaotic encryption system. | 彭越兮 孙克辉 贺少波 | 2020 | Chinese Physics B2020，29，3： | 4 |
| 9 | Dynamic modeling and parameter identification of a gun saddle ring显示文摘In this study,a theoretical nonlinear dynamic model was established for a saddle ring based on a dynamic force analysis of the launching process and the structure according to contact-impact theory.The ADAMS software was used to build a parameterized dynamic model of the saddle ring.A parameter identification method for the ring was proposed based on the particle swarm optimization algorithm.A loading test was designed and performed several times at different elevation angles.The response histories of the saddle ring with different loads were then obtained.The parameters of the saddle ring dynamic model were identified from statistics generated at a 500 elevation angle to verify the feasibility and accuracy of the proposed method.The actual loading history of the ring at a 70°elevation angle was taken as the model input.The response histories of the ring under these working conditions were obtained through a simulation.The simulation results agreed with the actual response.Thus,the effectiveness and applicability of the proposed dynamic model were verified,and it provides an effective method for modeling saddle rings. | Tong Lin Lin-fang Qian Qiang Yin Shi-yu Chen Tai-su Liu | 2020 | Defence Technology(防务技术)2020，16，2： | 3 |
| 10 | Fault Diagnosis Model Based on Fuzzy Support Vector Machine Combined with Weighted Fuzzy Clustering显示文摘A fault diagnosis model is proposed based on fuzzy support vector machine (FSVM) combined with fuzzy clustering (FC).Considering the relationship between the sample point and non-self class,FC algorithm is applied to generate fuzzy memberships.In the algorithm,sample weights based on a distribution density function of data point and genetic algorithm (GA) are introduced to enhance the performance of FC.Then a multi-class FSVM with radial basis function kernel is established according to directed acyclic graph algorithm,the penalty factor and kernel parameter of which are optimized by GA.Finally,the model is executed for multi-class fault diagnosis of rolling element bearings.The results show that the presented model achieves high performances both in identifying fault types and fault degrees.The performance comparisons of the presented model with SVM and distance-based FSVM for noisy case demonstrate the capacity of dealing with noise and generalization. | 张俊红 马文朋 马梁 何振鹏 | 2013 | Transactions of Tianjin University2013，19，3： | 3 |
| 11 | Design of mixed H-two/H-infinity optimal control systems using multiobjective differential evolution algorithm显示文摘In this paper, the mixed H-two/H-infinity control synthesis problem is stated as a multiobjective opti-mization problem, with objectives of minimizing the H-two and H-infinity norms simultaneously. Instead of building a LMIs-based synthesis algorithm, a self-adaptive control parameter multiobjective differential evolution algorithm is developed directly in the controller parameters space. In the case of systems with polytopic uncertainties, the worst case norm computation is formulated as an implicit optimization problem, and the proposed self-adaptive differential evolution is employed to calculate the worst case H-two and H-infinity norms. The numerical examples illustrate the power and validity of the proposed approach for the mixed H-two/H-infinity control multiobjective optimal design. | Lianghong WU Yaonan WANG Shaowu ZHOU Xiaofang YUAN | 2013 | 控制理论与应用(英文版)2013，11，3： | 2 |
| 12 | A Piecewise Linear Isotropic-Kinematic Hardening Model with Semi-Implicit Rules for Cyclic Loading and Its Parameter Identification显示文摘A simple constitutive model,called semi-implicit model,for cyclic loading is proposed for steel materials used for structures such as building frames in civil engineering.The constitutive model is implemented in the E-Simulator,which is a software package for large-scale seismic response analysis.The constitutive relation is defined in an algorithmic manner based on the piecewise linear combined isotropic-kinematic hardening.Different rules are used for the first and subsequent loading states to incorporate characteristics such as yield plateau and Bauschinger effect of rolled mild steel materials.An optimization method is also presented for parameter identification from the results of cyclic and monotonic loading tests.Therefore,the proposed model is readily applicable to practical elastoplastic analysis of building frames.Accuracy of the model is demonstrated in an example of a cantilever subjected to various types of cyclic loading. | M.Ohsaki T.Miyamura J.Y.Zhang | 2016 | Computer Modeling in Engineering & Sciences2016，，4： | 2 |
| 13 | MULTIVARIABLE FINITE ELEMENTS:CONSISTENCY AND OPTIMIZATION显示文摘A nonlinear analysis of the energy consistency of multivariable finite elements based onincompatible trial functions is presented. The nonlinear forms of the convergence and opti-mization condition are set up. The relevant optimization approach for hybrid elements andthe optimal parameter matching is suggested and applied to the 3-dimensional problem ofelasticity. | 吴长春 HANS BUFLER | 1991 | Science China Mathematics1991，34，3： | 2 |
| 14 | Parameter Optimization of Linear Quadratic Controller Based on Genetic Algorithm显示文摘The selection of weighting matrix in design of the linear quadratic optimal controller is an important topic in the control theory. In this paper, an approach based on genetic algorithm is presented for selecting the weighting matrix for the optimal controller. Genetic algorithm is adaptive heuristic search algorithm premised on the evolutionary ideas of natural selection and genetic. In this algorithm, the fitness function is used to evaluate individuals and reproductive success varies with fitness. In the design of the linear quadratic optimal controller, the fitness function has relation to the anticipated step response of the system. Not only can the controller designed by this approach meet the demand of the performance indexes of linear quadratic controller, but also satisfy the anticipated step response of close-loop system. The method possesses a higher calculating efficiency and provides technical support for the optimal controller in engineering application. The simulation of a three-order single-input single-output (SISO) system has demonstrated the feasibility and validity of the approach. | 李纪敏 尚朝轩 邹明虎 | 2007 | Tsinghua Science and Technology2007，12，S1： | 2 |
| 15 | Application of the asynchronous advantage actor–critic machine learning algorithm to real-time accelerator tuning显示文摘This paper describes a real-time beam tuning method with an improved asynchronous advantage actor–critic(A3C)algorithm for accelerator systems.The operating parameters of devices are usually inconsistent with the predictions of physical designs because of errors in mechanical matching and installation.Therefore,parameter optimization methods such as pointwise scanning,evolutionary algorithms(EAs),and robust conjugate direction search are widely used in beam tuning to compensate for this inconsistency.However,it is difficult for them to deal with a large number of discrete local optima.The A3C algorithm,which has been applied in the automated control field,provides an approach for improving multi-dimensional optimization.The A3C algorithm is introduced and improved for the real-time beam tuning code for accelerators.Experiments in which optimization is achieved by using pointwise scanning,the genetic algorithm(one kind of EAs),and the A3C-algorithm are conducted and compared to optimize the currents of four steering magnets and two solenoids in the low-energy beam transport section(LEBT)of the Xi’an Proton Application Facility.Optimal currents are determined when the highest transmission of a radio frequency quadrupole(RFQ)accelerator downstream of the LEBT is achieved.The optimal work points of the tuned accelerator were obtained with currents of 0 A,0 A,0 A,and 0.1 A,for the four steering magnets,and 107 A and 96 A for the two solenoids.Furthermore,the highest transmission of the RFQ was 91.2%.Meanwhile,the lower time required for the optimization with the A3C algorithm was successfully verified.Optimization with the A3C algorithm consumed 42%and 78%less time than pointwise scanning with random initialization and pre-trained initialization of weights,respectively. | Yun Zou Qing-Zi Xing Bai-Chuan Wang Shu-Xin Zheng Cheng Cheng Zhong-Ming Wang Xue-Wu Wang | 2019 | Nuclear Science and Techniques2019，30，10： | 2 |
| 16 | Transfer function based equivalent modeling method for wind farm显示文摘To effectively study the dynamics of power systems with large-scale wind farms(WFs), an equivalent model needs to be developed. It is well known that back-toback converters and their controllers are important for the dynamic responses of the wind turbine(WT) under disturbances. However, the detailed structure and parameters of the back-to-back converters and their controllers are usually unknown to power grid operators. Hence, it is difficult to build an accurate equivalent model for the WF using the component model-based equivalent modeling method. In this paper, a transfer function based equivalent modeling method for the WF is proposed. During modeling, the detailed structure and parameters of the WF are not required. The objective of the method is reproducing the output dynamics of the WF under the variation of the wind speed and power grid faults. A decoupled parameter-estimation strategy is also developed to estimate the parameters of the equivalent model. A WF that consists of 16 WTs is used to test the proposed equivalent model. Additionally,the proposed equivalent modeling method is applied to build the equivalent model for a real WF in Northwest China. The effectiveness of the proposed method is validated by the real measurement data. | Feng WU Junxia QIAN Ping JU Xiaoping ZHANG Yuqing JIN Dan XU Michael STERLING | 2019 | Journal of Modern Power Systems and Clean Energy2019，7，3： | 2 |
| 17 | Gabor Filter Optimization Design for Iris Texture Analysis显示文摘This paper deals with an optimization design method for the Gabor filters based on the analysis of an iris texture model. By means of analyzing the properties of an iris texture image, the energy distribution regularity of the iris texture image measured by the average power spectrum density is exploited, and the theoretical ranges of the efficient valued frequency and orientation parameters can also be deduced. The analysis shows that the energy distribution of the iris texture is generally centralized around lower frequencies in the spatial frequency domain. Accordingly, an iterative algorithm is designed to optimize the Gabor parameter field. The experimental results indicate the validity of the theory and efficiency of the algorithm. | Tao Xu 1, Xing Ming 2, Xiaoguang Yang 3 1.College of Mechanical Science and Engineering, Jilin University, Changchun 130022, P.R.China 2.College of Computer Science and Technology, Jilin University, Changchun 130022, P.R.China 3.Dept of Mathematics and Physics, Dalian Maritime University, Dalian 116026,P.R.China | 2004 | Journal of Bionic Engineering2004，1，1： | 1 |
| 18 | Trajectory online optimization for unmanned combat aerial vehicle using combined strategy显示文摘This paper presents a combined strategy to solve the trajectory online optimization problem for unmanned combat aerial vehicle(UCAV). Firstly, as trajectory directly optimizing is quite time costing, an online trajectory functional representation method is proposed. Considering the practical requirement of online trajectory, the 4-order polynomial function is used to represent the trajectory, and which can be determined by two independent parameters with the trajectory terminal conditions; thus, the trajectory online optimization problem is converted into the optimization of the two parameters, which largely lowers the complexity of the optimization problem. Furthermore, the scopes of the two parameters have been assessed into small ranges using the golden section ratio method. Secondly, a multi-population rotation strategy differential evolution approach(MPRDE) is designed to optimize the two parameters; in which, 'current-to-best/1/bin', 'current-torand/1/bin' and 'rand/2/bin' strategies with fixed parameter settings are designed, these strategies are rotationally used by three subpopulations. Thirdly, the rolling optimization method is applied to model the online trajectory optimization process. Finally, simulation results demonstrate the efficiency and real-time calculation capability of the designed combined strategy for UCAV trajectory online optimizing under dynamic and complicated environments. | Kangsheng Dong Hanqiao Huang Changqiang Huang Zhuoran Zhang | 2017 | Journal of Systems Engineering and Electronics2017，28，5： | 1 |
| 19 | Machine learning the Hubbard U parameter in DFT+U using Bayesian optimization显示文摘Within density functional theory(DFT),adding a Hubbard U correction can mitigate some of the deficiencies of local and semi-local exchange-correlation functionals,while maintaining computational efficiency.However,the accuracy of DFT+U largely depends on the chosen Hubbard U values.We propose an approach to determining the optimal U parameters for a given material by machine learning.The Bayesian optimization(BO)algorithm is used with an objective function formulated to reproduce the band structures produced by more accurate hybrid functionals.This approach is demonstrated for transition metal oxides,europium chalcogenides,and narrow-gap semiconductors.The band structures obtained using the BO U values are in agreement with hybrid functional results.Additionally,comparison to the linear response(LR)approach to determining U demonstrates that the BO method is superior. | Maituo Yu Shuyang Yang Chunzhi Wu Noa Marom | 2020 | npj Computational Materials2020，，1： | 1 |
| 20 | 等腰三角形路径扫描声强法测量声功率误差分析及参数优化显示文摘以单极子、偶极子和四极子声源为例,研究了在包围声源的四面体等腰三角形测量面上采用等腰三角形扫描路径应用扫描声强法测量声功率的收敛特性,并以扫描声强测量误差为目标函数,以等腰三角形扫描测量面的大小、测量面到声源的距离和扫描线密度为设计变量,应用遗传算法进行了优化.依此优化方法确定测量面的各几何参数,保证了测量精度,提高了测量效率,为快速准确地测量声功率提供了依据.
Abstract:
To measure the measuring surfaces of isosceles triangle from tetrahedron which surround sound source by the method of isosceles triangle path scanning, the monopole source, dipole source and quadrupole source are taken as examples. The scanning sound intensity method can get the convergent feature of sound power. The convergent feature is studied. The error analysis of scanning sound intensity as objective function, the design variable which made up of the sizeof scanning measuring surfaces of isosceles triangle, the distance between measuring surface and sound source, and the density of scanning line, all of which optimized by GA. This optimization determines the geometry parameters of measuring surface, ensures the measuring accuracy, also improves the measuring efficiency . They lays a solid foundation for swiftly and accurately measuring sound power of sound source. | 周广林 周晃明 Guang-lin Huang-ming | 2009 | 计量学报2009，，6： | 1 |
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