有限元法和退火进化算法相结合分析结构模糊可靠性

结构的失效除了具有随机性，还应具有模糊性。本文在介绍一种修正的联合概率密度函数的基础上，采用有限元法和退火进化算法相结合来研究结构的模糊可靠度。在每一模糊失效水平下，有限元法用来计算荷载效应项，并将荷载效应项代入原联合概率密度函数形成修正的联合概率密度函数。为了解决进化算法的早熟收敛问题，采用模拟退火算法与进化算法相结合，以保证更有效地搜索到最可能失效点(设计点)。解决不存在显式极限状态方程的大部分实际结构的可靠度研究的困难。数例结果表明该法可直接应用现有的确定性的有限元程序，并且具有很好的效率和精度。     

基于模糊神经网络的数据融合结构损伤识别方法

为了有效利用结构健康监测系统中的多源传感器数据信息,提高损伤检测与评估的识别正确率,该文通过构造模糊神经网络分类器,提出了一种基于模糊神经网络的数据融合损伤识别方法并将之应用于结构健康诊断中。它先通过数据预处理,提取原始响应信号中的特征参数,接着将之作为模糊神经网络的输入,构造模糊神经网络模型进行识别决策,最后运用数据融合算法,计算出数据融合后的决策结果。为了验证所提方法的有效性,通过一个7自由度的建筑模型,分别用单一模糊神经网络决策器和数据融合损伤识别方法进行了损伤识别和比较。研究结果表明:该文所提方法比单一决策结果更准确、可靠。     

Output Linearization of Single-Input Single-Output Fuzzy System to Improve Accuracy and Performance

For fuzzy systems to be implemented effectively, the fuzzy membership function (MF) is essential. A fuzzy system (FS) that implements precise input and output MFs is presented to enhance the performance and accuracy of single-input single-output (SISO) FSs and introduce the most applicable input and output MFs protocol to linearize the fuzzy system’s output. Utilizing a variety of non-linear techniques, a SISO FS is simulated. The results of FS experiments conducted in comparable conditions are then compared. The simulated results and the results of the experimental setup agree fairly well. The findings of the suggested model demonstrate that the relative error is abated to a sufficient range (≤ ± 10%) and that the mean absolute percentage error (MPAE) is reduced by around 66.2%. The proposed strategy to reduce MAPE using an FS improves the system’s performance and control accuracy. By using the best input and output MFs protocol, the energy and financial efficiency of every SISO FS can be improved with very little tuning of MFs. The proposed fuzzy system performed far better than other modern days approaches available in the literature.     

Brightness preserving optimized weighted bi-histogram equalization algorithm and its application to MR brain image segmentation

Medical image segmentation is crucial for neuroscience research and computer-aided diagnosis. However, intensity inhomogeneity and existence of noise in magnetic resonance images lead to incorrect segmentation. In this article, an effective method called enhanced fuzzy level set algorithm is presented to segment the white matter, gray matter, and cerebrospinal fluid automatically in contrast-enhanced brain images. In this method, first, exposure threshold is computed to divide the input histogram into two sub-histograms of different gray levels. The input histogram is clipped using a mean gray level to control the excessive enhancement rate. Then, these two sub-histograms are modified and equalized independently to get a better contrast enhanced image. Finally, an enhanced fuzzy level set algorithm is employed to facilitate image segmentation. The extensive experimental results proved the outstanding performance of the proposed algorithm compared with other existing methods. The results conform its effectiveness for MR brain image segmentation.     

Thermoelectromechanically induced stochastic post buckling response of piezoelectric functionally graded beam

This paper deals with the stochastic post buckling response the functionally graded material (FGMs) beam with surface bonded piezoelectric layers subjected to thermoelectromechanical loadings. A C⁰ nonlinear finite element method using higher order shear deformation theory with von-Karman nonlinearity is used for basic formulation. The random system parameter such as material properties of FGM and piezoelectric layers and thermoelectromechanical loadings are modeled as uncorrelated random input variables. The first and second order perturbation method and Monte Carlo sampling (MCS) are proposed to examine the mean, coefficient of variation, probability distribution function and probability of failure of critical post buckling load. Typical numerical results are presented for volume fraction indexes, slenderness ratios, boundary conditions, piezoelectric layers and thermoelectromechanical loadings with random system properties. The present outlined approach is validated with the results available in the literature and by employing MCS.     

温黄平原防汛调度模糊控制方法

 针对温黄平原河网调度所具有的影响因素多、存在范围广、工程难度大、地形复杂、信息采集不完备等特点，提出一种基于数据挖掘的模糊分类算法。该算法极大程度地利用有限的历史数据，对模型输入输出量进行抽象，根据对历史主干河道水位、降雨等记录值的学习并建模，解决了存在的调度问题。通过工程实践，对温黄平原各个主要闸门进行实时调度，调整流域内主要河道水位，取得了较好的工程效果，同时验证了工程的实用性与有效性。     

Identifying the Magnitude and Location of a Load on a Slender Beam Using a Strain Gauge Based Force Transducer

A unique strain gauge based method is developed to identify the magnitude and location of a load on a slender beam with variable cross sections, and pinned, firm rest, soft rest, pinned‐fixed, and fixed boundary conditions. Four uniaxial strain gauges are mounted to the bottom surface of the beam, and the bending moment diagram of the beam can be constructed using measured strains on the beam. By combining individually scaled strain gauge outputs, the magnitude and location of the load can be accurately identified. The strain gauge based force transducer methodology is experimentally validated on prismatic beams with firm rest, soft rest, firm rest‐fixed, and fixed boundary conditions, and a continuously tapered beam with rest boundary conditions. The force transducer methodology is independent of the boundary conditions of the beam, and the error from strain gauge drift due to uniform thermal expansion on a prismatic beam can cancel out.     

大型旋转机械故障诊断专家系统ETHYLENE的理论研究

本文在模糊产生式规则的基础上引入了加权模糊连接算子的概念,并研究了征兆的类型。在此基础上,为旋转机械模糊诊断知识提出了一个灵活的知识表达方法——广义模糊产生式规则。在征兆类型的基础上引入了征兆认可因子的概念.利用这一概念来描述模糊蕴涵关系的语义,基于征兆认可因子提出了一个模糊推理算法。文中还给出了由基于这一广义模糊产生式规则和模糊推理算法建立的透平压缩机组故障诊断专家系统ETHYLENE得到的两个诊断结果。     

Combined particle swarm optimization and heuristic fuzzy inference systems for a smart home one-step-ahead load forecasting

This article presents a hybrid approach that combines particle swarm optimization (PSO) and heuristic fuzzy inference system (HFIS) for smart home one-step-ahead load forecasting. Smart home load forecasting is an important issue in the development of smart grids. Generally, the electricity consumption of a household is inherently nonlinear and dynamic and heavily dependent on the habitual nature of power demand, activities of daily living and on holidays or weekends, so it is often difficult to construct an adequate forecasting model for this type of load. To address this problem, a hybrid model, consisting of two phases, is proposed in this article. In the first phase, the popular PSO algorithm is used to determine the locations of fuzzy membership functions. Then, the proposed HFIS technique is used to develop the one-step-ahead load forecasting model in the second phase. Because of the robust nature of the proposed HFIS technique, which does not need to retrain or re-estimate model parameters, it is very suitable for smart home load forecasting. The proposed method was verified using two different households’ load data. Simulation results indicate that the proposed method produces better forecasting accuracy than existing methods.     

Numerical solution of fuzzy linear equations in engineering analysis

A computational methodology is presented for the solution of simultaneous linear equations that arise in the analysis of engineering systems involving fuzzy input parameters. In addition to a discussion on the existence of solution to the problem, the numerical solution to the fuzzy linear systems is defined and formalized. The framework of the proposed methodology consists of three major aspects involving (1) computerized selection of fuzziness, (2) implementation of fuzzy operations and (3) development and execution of a search-based algorithm. Two numerical examples are presented to illustrate the computational aspects of the proposed methodology. The present results are compared with those given by the combinatorial approach. © 1998 John Wiley & Sons, Ltd.     

自适应变论域模糊控制器在结构振动控制中的应用

大挠性航天结构具有复杂的动力学特性,建立其精确的数学模型是很困难的,模糊控制不需要精确的数学模型,但是模糊控制的主要缺陷是精度不太高,自适应能力有限,易产生振荡现象。变论域自适应模糊控制是改变模糊控制性能的主要方法之一,针对自适应变论域模糊控制器的稳定性设计这一难题,将输入和输出的隶属度函数分别用论域值表示成解析形式,引进李亚谱诺夫函数,设计了输入和输出的隶属度函数论域值的自适应律,针对大型航天桁架结构振动控制的仿真,结果表明设计的变论域模糊控制器是可行的。     

Numerical solution of fuzzy linear equations in engineering analysis

A computational methodology is presented for the solution of simultaneous linear equations that arise in the analysis of engineering systems involving fuzzy input parameters. In addition to a discussion on the existence of solution to the problem, the numerical solution to the fuzzy linear systems is defined and formalized. The framework of the proposed methodology consists of three major aspects involving (1) computerized selection of fuzziness, (2) implementation of fuzzy operations and (3) development and execution of a search-based algorithm. Two numerical examples are presented to illustrate the computational aspects of the proposed methodology. The present results are compared to those given by the combinatorial approach. © 1998 John Wiley & Sons, Ltd.     

对体积位移传感器的研讨

以不同边界条件的振动梁为例,提出通过分部积分方法设计特定形状的PVDF薄膜测量体积位移。这种分部积分方法得到的PVDF传感器形状不但与外激励力的性质（如激励力类型、位置以及频率等）无关,而且不需要振动梁的模态信息。研究表明,可以把振动梁的边界条件分为两类,即一端固定一端任意和两端位移为零,对于每一类边界条件可以用一种特定形状PVDF传感器测量其体积位移。     

DSC analysis of a simply supported anisotropic rectangular plate

The discrete singular convolution (DSC) algorithm is used to analyze the deflection and free vibration behavior of a simply supported anisotropic rectangular plate. A novel approach is proposed to solve the difficulty in using DSC to handle the simply supported boundary conditions with bending–twisting coupling. DSC results are presented for bending under distributed load and a center concentrated load, and natural frequencies of flexural vibrations. It is shown that the DSC with proposed method to apply the simply supported boundary conditions yields very accurate results as compared to exact solutions or results obtained by methods of differential quadrature and finite element with fine meshes. It is also verified that neglecting the bending–twisting coupling in applying the simply supported boundary conditions may result incorrect solutions, especially for the bending analysis of anisotropic plates.     

导管架海洋平台结构模糊优化设计

考虑约束条件边界的模糊性,建立了导管架海洋平台结构模糊优化设计模型。对模糊优化模型中的设计变量、目标函数和约束条件进行了模糊处理。针对导管架海洋平台的特点,用模糊优选法确定约束条件边界容差系数,由界限搜索法求解模糊约束集和模糊目标集之交集的最优水平截集*l,进而求得模糊优化问题的最优解。以胜利油田埕北11#井采油平台为例进行了模糊优化设计,并与确定性优化设计相比较,分析了两种优化设计中设计变量的走向及原因,算例结果还显示目标函数值比确定性优化设计值有较大幅度下降,说明考虑模糊因素进行优化设计的可行性和科学性。     

插值振型函数法求解移动荷载作用下等截面连续梁的动态响应

根据哈密顿原理,应用插值振型函数法,分析了多跨连续梁在移动荷载作用下的车桥耦合振动动态响应。经实例讨论分析,给出了多跨等截面连续梁在不同速度移动荷载作用下的数值结果。实例分析表明,该方法具有很好的收敛性和很高的精度。具通过对结果的分析讨论,得到了多跨连续梁在移动荷载作用下的一些规律。     

Fuzzy entropy‐based MR brain image segmentation using modified particle swarm optimization

This article presents an image segmentation technique based on fuzzy entropy, which is applied to magnetic resonance (MR) brain images in order to detect brain tumors. The proposed method performs image segmentation based on adaptive thresholding of the input MR images. The image is classified into two membership functions (MFs) of the fuzzy region: Z‐function and S‐function. The optimal parameters of these fuzzy MFs are obtained using modified particle swarm optimization (MPSO) algorithm. The objective function for obtaining the optimal fuzzy MF parameters is considered to be the maximum fuzzy entropy. Through a number of examples, The performance is compared with existing entropy based object segmentation approaches and the superiority of the proposed method is demonstrated. The experimental results are compared with the exhaustive search method and Otsu's segmentation technique. The result shows the proposed fuzzy entropy‐based segmentation method optimized using MPSO achieves maximum entropy with proper segmentation of infected areas and with minimum computational time. © 2013 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 23, 281–288, 2013     

基于有限元法的模糊参数二维声场数值分析

为了分析不确定性二维声场,引入模糊集概念描述声场的物理参数、载荷和边界条件的不确定性,推导了分析模糊参数下二维声场问题的相关计算公式。在不同隶属度的截集下通过对模糊动刚度矩阵和模糊载荷矩阵进行泰勒展开,再用纽曼展开对模糊动刚度矩阵泰勒展开式的逆进行转化,采用摄动有限元法求解,最终得到模糊参数下的声压解集。以二维管道声场模型和某轿车二维声腔模型为研究对象分析了模糊参数下的声压响应,结果表明该文方法能有效分析模糊参数下的二维声场,具有重要的工程应用价值。     

Fuzzy rules extraction using a hybrid of base‐n‐number‐coded GA and SVD‐QR

Abstract

A hybrid of a base‐n‐number‐coded genetic algorithm (base‐n‐number‐coded GA) and an SVD‐QR is proposed to construct a fuzzy system directly from some gathered input‐output data of the identified system. Each individual in the base‐n‐number‐coded GA is applied to determine the fuzzy sets in each input variable. However, the grid‐type fuzzy partition by the fuzzy sets associated with each input variable may generate some redundant fuzzy subspaces. Therefore, an SVD‐QR method is applied to remove the redundant fuzzy subspaces to efficiently describe the behavior of the identified system so that the premise part of the fuzzy system is determined. Then, the recursive least‐squares method is used to determine the consequent part of the fuzzy system. Subsequently, a fitness function is defined such that it can guide the search procedure to select an appropriate fuzzy system that not only maintains a good performance but also has relevant fuzzy rules. Finally, two nonlinear system identification problems are used to illustrate the efficiency of the proposed method.     

Analytical solutions for free and forced vibrations of a multiple cracked Timoshenko beam subject to a concentrated moving load

An analytical approach for evaluating the forced vibration response of uniform beams with an arbitrary number of open edge cracks excited by a concentrated moving load is developed in this research. For this purpose, the cracked beam is modeled using beam segments connected by rotational massless linear elastic springs with sectional flexibility, and each segment of the continuous beam is assumed to satisfy Timoshenko beam theory. In this method, the equivalent spring stiffness does not depend on the frequency of vibration and is obtained from fracture mechanics. Considering suitable compatibility requirements at cracked sections and corresponding boundary conditions, characteristic equations of free vibration response are derived. Then, forced vibration response is treated under a moving load with a constant velocity. Using the determined eigenfunctions, the forced vibration response may be obtained by the modal superposition method. Finally, some parametric studies are presented to show the effects of crack parameters and moving load velocity.