Hybrid intelligent method for fuzzy reliability analysis of corroded X100 steel pipelines

Epistemic uncertainties are critical for reliable design of corroded pipes made of high-strength grade steel. In this work, corrosion defects geometries and operating pressure are provided as the epistemic uncertainties in reliability analysis. A framework of an iterative approach-based bi-loop is presented for fuzzy reliability analysis (FRA) of corroded pipelines to evaluate the fuzzy reliability index-based various fuzzy-random variables (FRVs). In the inner loop, the conjugate first-order reliability method using adaptive finite-step size is applied for carried out the reliability analysis. The outer loop is structured based on the fuzzy analysis corresponding to a modified particle swarm optimization as an intelligent tool. The adaptive conjugate fine step size is dynamically computed to adjust the conjugate sensitivity vector in the reliability loop. The sufficient descent condition is satisfied based on three-term conjugate first-order reliability method. The performance function of corroded pipelines is defined based on average shear stress yield-based plastic flow theory, remaining strength factor, and operating pressure. Two applicable examples as corroded pipelines made from X100 high-strength steel are given to illustrate the effects of epistemic uncertainties under corrosion defects. Investigation the results has shown that modeling of epistemic uncertainty in the reliability analysis of high-grade steel pipelines could result more reasonable reliability indexes. In addition, results indicate that FRVs have significant influence on fuzzy reliability index calculations, especially corrosion defect depth and operating pressure (as FRVs). The sensitivity measure of FRA demonstrated that fuzzy reliability index of corroded X100 steel pipelines is more sensitive to the FRVs means.

     

A general RBDO decoupling approach for different reliability analysis methods

There are available in the literature several papers on the development of methods to decouple the reliability analysis and the structural optimization to solve RBDO problems. Most of them focused on strategies that employ the First Order Reliability Method (FORM) to approximate the reliability constraints. Despite of all these developments, one limitation prevailed: the lack of accuracy in the approximation of the reliability constraints due to the use of FORM. Thus, in this paper, a novel approach for RBDO is presented in order to overcome such a limitation. In this approach, we use the concept of shifting vectors, originally developed in the context of the Sequential Optimization and Reliability Assessment (SORA). However, the shifting vectors are found and updated based on a novel strategy. The resulting framework is able to use any technique for the reliability analysis stage, such as Monte Carlo simulation, second order reliability methods, stochastic polynomials, among others. Thus, the proposed approach overcomes the aforementioned limitation of most of RBDO decoupling techniques, which required the use of FORM for reliability analysis. Several examples are analyzed in order to show the effectiveness of the methodology. Focus is given on examples that are poorly solved or even cannot be tackled by FORM based approaches, such as highly nonlinear limit state functions comprised by a maximum operator or problems with discrete random variables. It should be remarked that the proposed approach was not developed to be more computationally efficient than RBDO decoupling strategies based FORM, but to allow the utilization of any, including more accurate, reliability analysis method.     

基于模糊神经网络的静态手语词汇识别

利用数据手套CAS-Glove作为输入设备,提出了一种基于模糊神经网络的中国手语单 手静态词汇的识别方法:首先利用经验知识为每个词汇创建模糊规则,然后通过学习确定各模糊 子集隶属函数中的参数.对于参数的学习,提出了一种适用于分类器的可微经验风险函数,该函 数能够有效地利用梯度下降法进行最小化.在实验中通过比较证实了该方法的有效性和可靠性.     

模糊PID在液压机位置控制系统中的应用

大型模锻液压机活动横梁的位置控制与运行可靠性对产品精度至关重要,针对活动横梁位置控制高精度、大滞后和大惯性等特点,提出了基于位移反馈的五驱动缸主动平衡系统.结合PID和模糊控制的优点,设计开发了基于S7-300 PLC的模糊PID参数自整定控制算法,利用模糊推理对PID参数K<,P>,T<,I>和T<,D>进行在线自整...     

Reliability-based optimum design of a symmetric laminated plate subject to buckling

This study is concerned with the buckling reliability maximization of a symmetric laminated composite plate with respect to the mean ply orientation angle. The reliability is evaluated by modelling the buckling failure as a series system consisting of potential eigenmodes. The mode reliability is obtained by the first-order reliability theory (FORM), where material constants and orientation angles of individual layers, as well as the applied loads are treated as random variables. In order to keep track of the intended buckling mode during the reliability analysis, the mode tracking method is utilized. Then, the failure probability of the series system is approximated by Ditlevsen's upper bound. The reliability maximization problem is formulated as a nested problem with two levels of optimization. Through numerical calculations, the reliability-based design is demonstrated to be important for the structural safety in comparison with the deterministic buckling load maximization design.     

Investigation of actuation voltage for non-uniform serpentine flexure design of RF-MEMS switch

This paper presents an attempt to reduce the actuation voltage of capacitive RF-MEMS switch by introducing the concept of non-uniform serpentine flexure suspensions. The spring constant of non-uniform serpentine flexure with different meander sections have been equated by analytical expression and verified with finite element method (FEM). FEM analysis indicate actuation voltage as low as 5 V with single meander section for the proposed non-uniform serpentine spring design, which is reasonably low as compared to uniform serpentine spring with same span beam length.     

A new directional stability transformation method of chaos control for first order reliability analysis

The HL-RF iterative algorithm of the first order reliability method (FORM) is popularly applied to evaluate reliability index in structural reliability analysis and reliability-based design optimization. However, it sometimes suffers from non-convergence problems, such as bifurcation, periodic oscillation, and chaos for nonlinear limit state functions. This paper derives the formulation of the Lyapunov exponents for the HL-RF iterative algorithm in order to identify these complicated numerical instability phenomena of discrete chaotic dynamic systems. Moreover, the essential cause of low efficiency for the stability transform method (STM) of convergence control of FORM is revealed. Then, a novel method, directional stability transformation method (DSTM), is proposed to reduce the number of function evaluations of original STM as a chaos feedback control approach. The efficiency and convergence of different reliability evaluation methods, including the HL-RF algorithm, STM and DSTM, are analyzed and compared by several numerical examples. It is indicated that the proposed DSTM method is versatile, efficient and robust, and the bifurcation, periodic oscillation, and chaos of FORM is controlled effectively.     

基于改进模糊神经网络的软测量建模方法

提出了一种改进的模糊神经网络软测量建模方法，采用规则化的平均输出隶属度函数作为模糊基函数进行反模糊化运算；在训练网络时,部分参数采用Levenberg-Marquardt算法来训练，另一部分采用一阶梯度下降法．最后用该建模方法建立了聚合反应中熔融指数的软测量模型，并与一般的模糊神经网络软测量模型进行比较．结果表明改进的模糊神经网络对初始值的选择不敏感,具有很好的收敛性，同时还能达到指定的预测精度，很适合工程应用．     

面向数据挖掘的时间序列聚类方法研究

一、引言自然界以及我们社会生活中的各种事物都在运动、变化和发展着,将它们按时间顺序记录下来,我们就可以得到各种各样的“时间序列”数据。对时间序列进行分析,可以揭示事物运动、变化和发展的内在规律,对于人们正确认识事物并据此作出科学的决策具有重要的现实意义。     

System reliability analysis with saddlepoint approximation

System reliability is usually estimated through component reliability, which is commonly computed by the First Order Reliability Method (FORM). The FORM is computationally efficient, but may not be accurate for nonlinear limit-state functions. An alternative system reliability analysis method is proposed based on saddlepoint approximation. Unlike the FORM that linearizes limit-state functions in a transformed random space, the proposed method linearizes the limited-state functions without any transformation. After the linearization, the joint probability density of limit-state functions is estimated by the multivariate saddlepoint approximation. Without the nonnormal-to-normal transformation, the present method is more accurate than the FORM when the transformation increases the nonlinearity of limit-state functions. As demonstrated in the two examples, the new method is also as efficient as the FORM.     

Inverse analysis method using MPP-based dimension reduction for reliability-based design optimization of nonlinear and multi-dimensional systems

There are two commonly used analytical reliability analysis methods: linear approximation - first-order reliability method (FORM), and quadratic approximation - second-order reliability method (SORM), of the performance function. The reliability analysis using FORM could be acceptable in accuracy for mildly nonlinear performance functions, whereas the reliability analysis using SORM may be necessary for accuracy of nonlinear and multi-dimensional performance functions. Even though the reliability analysis using SORM may be accurate, it is not as much used for probability of failure calculation since SORM requires the second-order sensitivities. Moreover, the SORM-based inverse reliability analysis is rather difficult to develop.This paper proposes an inverse reliability analysis method that can be used to obtain accurate probability of failure calculation without requiring the second-order sensitivities for reliability-based design optimization (RBDO) of nonlinear and multi-dimensional systems. For the inverse reliability analysis, the most probable point (MPP)-based dimension reduction method (DRM) is developed. Since the FORM-based reliability index (β) is inaccurate for the MPP search of the nonlinear performance function, a three-step computational procedure is proposed to improve accuracy of the inverse reliability analysis: probability of failure calculation using constraint shift, reliability index update, and MPP update. Using the three steps, a new DRM-based MPP is obtained, which estimates the probability of failure of the performance function more accurately than FORM and more efficiently than SORM. The DRM-based MPP is then used for the next design iteration of RBDO to obtain an accurate optimum design even for nonlinear and/or multi-dimensional system. Since the DRM-based RBDO requires more function evaluations, the enriched performance measure approach (PMA+) with new tolerances for constraint activeness and reduced rotation matrix is used to reduce the number of function evaluations.     

Convergence analysis of first order reliability method using chaos theory

First order reliability method (FORM) for the computation of reliability index has been used widely because of its advantages of the efficiency and effectiveness as well simplicity for many years. There exists the phenomenon of convergent failure in the FORM in calculating the reliability index iteratively for some limit state functions, for which the essential factor is investigated using chaotic dynamics theory in the present paper. The bifurcation plots of reliability index are presented for several typical limit state functions, and the computational results from those mapping functions due to FORM iterations show the complicated dynamics phenomena such as the periodic oscillation, bifurcation and chaos. Moreover, the Lyapunov exponents of non-linear map from FORM are calculated. From the numerical investigation of presented examples, it is concluded that the convergence of FORM does not depend on the curvature of design points of the limit state function, and the quantitative index for identifying the convergence of FORM iterative computation is the Lyapunov exponents of non-linear map corresponding to that limit state function.     

隶属函数分布对Fuzzy-PI控制器动态性能的影响

为研究模糊控制器的隶属函数分布对Fuzzy-PI控制器动态性能的影响,达到优化Fuzzy-PI控制器动态性能的目的,以二阶系统为研究模型,用模糊控制器来修正比例系数Kp及积分系数Ki,根据PI控制器参数自整定原则,通过改变输入变量误差E及误差变化率EC的隶属函数分布,在MatlabSimulink环境下仿真Fuzzy-PI控制器的输出。通过数据分析,得出了变量误差E及误差化率EC的隶属函数分布对上升时间、最大超调量、调整时间影响的规律。     

利用FSART算法实现对时间序列数据的聚类分析

根据时间序列数据进行聚类分析的需要,提出了一人可以描述矢量间形态相似度的模糊隶属度函数表达式,实验表明该表达式除具有较好的矢量形态表达能力外,对呈球形分布的样本空是也有较好的表达能力。通过对FSART（Fuzzy Simplified Adaptive Resonance Theory)算法作进一步的改进,提高了它的计算效率,并将新的隶属度函数表达式与改进后的FSART算法相结合,实现了对非平稳时间序列数据的聚类分析,取得了良好的实验结果。     

Fuzzy PWM based on Genetic Algorithm for battery charging

This paper investigates the use of fuzzy logic control together with Genetic Algorithm (GA) to tune corresponding membership functions in a pulse width modulation voltage (PWM)-based converter for battery charging. For quick charging purposes, a current-charging mode is built on the charging battery series with small impedance resistance. Once the rechargeable battery voltage reaches the preset output voltage value during the current-charging mode, constant voltage-charging mode should take to do the battery charging. No matter what you use a voltage/current mode for battery charging, the PWM converter with tuning duty cycle is necessary to obtain various output voltages to charge battery. The proposed pulse width modulation (PWM) control strategy based on fuzzy logic systems is applied to charge batteries for buck converter. A simulation is proposed to illustrate the efficiency of the design proposed in this paper.     

CFB锅炉汽包水位自校正PID模糊控制研究

通过对CFB锅炉汽包水位动态特性的分析，讨论了一种自校正PID模糊控制对汽包水位进行控制的策略。仿真研究表明，这种方案使汽包水位控制系统具有较强的鲁棒性及良好的控制品质，提高了系统的动静态性能指标。     

Fuzzy system reliability evaluation using time-dependent intuitionistic fuzzy set

In general, fuzzy sets are used to analyse the system reliability. In this article, the concept of fuzzy set is extended by the idea of intuitionistic fuzzy set (IFS) and a new general procedure is proposed to construct the membership and non-membership functions of the fuzzy reliability using time-dependent IFS. Here, failure rate function of the system is represented by a triangular intuitionistic fuzzy number (IFN). Also, using proposed approach, membership and non-membership functions of fuzzy reliability of series and parallel systems are constructed, where the failure rate of each component is taken as a time-dependent triangular IFN. The major advantage of using IFS over fuzzy sets is that IFS separate the positive and negative evidences for membership of an element in the set. Numerical examples are given to illustrate the proposed approach.     

自调整模糊控制除霜系统的研究与开发

本文通过对风冷热泵冷热水机组结霜因素的分析，提出了多参量自调整模糊除霜控制的方法，建立了自调整模糊控制除霜系统的总体结构；在实验的基础上，确定了各输入参数的隶属函数，采用SIEMENS S7—200可编程控制器，设计开发了风冷热泵冷热水机组的自调整模糊除霜控制系统。实验运行表明：本文的研究有效的提高了风冷热泵冷热水机组冬季运行的制热性能，节能效果好。     

NEW METHOD FOR FUZZY SYSTEM RELIABILITY ANALYSIS

This paper presents a new method for fuzzy system reliability analysis based on fuzzy time series and the alpha-cuts arithmetic operations of fuzzy numbers, where we allow the reliabilities of the components of a system at different times t (t= ...,0,1,2,...) to be represented by different membership functions. Because the proposed method allows the reliabilities of the components of a system at different times t to have different membership functions, it is more flexible than the ones presented in Chen 1994 , Cheng and Mon 1993 , and Singer 1990 . Furthermore, because the proposed method uses the simple alpha -cuts arithmetic operations of fuzzy numbers rather than the complicated nonlinear programming techniques mentioned in Mon and Cheng 1994 , it is simpler in calculating fuzzy system reliability than the one presented in that paper.     

一种改进的模糊支持向量机算法

模糊隶属度函数设计是模糊支持向量机中的关键步骤.Lin & Wang提出的基于类中心距离的模糊隶属度设计方法,不能从样本集中有效区分噪声或野值点,而且可能降低支持向量的隶属度.针对上述不足,提出一种改进的隶属度函数设计方法.通过引入一个半径控制因子,充分利用样本间的信息,更加合理地设计样本的模糊隶属度.与基于类中心的隶属度方法相比,该方法在不增加时间复杂度的情况下,通过数值实验表明了方法的优势,大大提高了模糊支持向量机的分类精度.