基于自适应模拟退火遗传算法的传感器优化配置研究

针对传感器优化配置组合优化问题,提出了一种基于模态置信度准则MAC的优化算法——自适应模拟退火遗传算法。以模态置信度MAC矩阵的最大非对角元的值极小为目标函数,针对满足传感器数量不变的约束条件问题,提出了二重结构编码遗传算法,并将传统的模拟退火算法改良后,作为一个独立的算子置于遗传算法进化过程中;为了避免出现过早收敛的现象,引入了自适应交叉和变异概率。算例结果表明该混合算法对传感器数目与位置同时实现了优化,得到了满足不同精度要求的传感器优化配置方案。     

基于整数编码遗传算法的传感器优化配置研究

动态测试中,为了将传感器配置在合理的自由度上,以便充分反映结构的动力特性,需对传感器进行优化配置。本文分别以模态置信度矩阵、Fisher信息阵和它们的组合为优化准则,采用整数编码遗传算法,探讨了单目标和多目标优化的传感器优化配置问题。通过与现有的模态动能法、有效独立法及基于QR分解的逐步累积法进行比较,传感器优化配置的结果表明整数编码遗传算法优于上述三种现有方法。     

基于结构部分结点振动响应信息的海洋平台损伤诊断研究

利用结构的前三阶频率和部分结点的响应信息构建适应度函数和目标函数,采用改进的CHC遗传算法对结构进行损伤诊断,在相同的收敛精度条件下,大大减少了遗传代数和结构分析时间,因而提高了计算速度。数值算例表明:在不同的传感器配置条件下,对固定式导管架平台的损伤诊断均具有较高的损伤定位和损伤程度估计精度。     

基于不完备损伤指标和遗传算法的特大桥损伤识别和传感器布点优化

特大桥健康监测系统不可能在所有自由度安放传感器,该文讨论了用由不完备振型建立的损伤指标的损伤识别和传感器布点优化方法。与过去用遗传算法优化传感器布点的适应度函数不同,该文用损伤指标最灵敏来建立适应度函数。对桥梁的单个损伤,该文用不完备模态柔度矩阵差和截断模态应变能变化率两个不完备损伤指标作为适应度函数来优化传感器布点,并与传统的COMAC指标对比,还改进了多种群遗传算法,以提高收敛速度和全局寻优能力。并以西堠门悬索桥有限元模型为例,识别不同部位的损伤。算例表明:该方法在损伤识别和传感器布点优化方面不仅可行而且有效。     

机车柴油机活塞连杆组的组合优化研究

对活塞连杆组的选配进行数学建模,并用遗传算法对活塞连杆组的组合优化进行了研究.在用遗传算法进行组合优化时,提出了采用惩罚函数法把约束条件转移到目标函数上,从而使整个问题转化为无约束问题.通过系统模拟,比较了基本遗传算法、进化规划法和精英保留遗传算法三种遗传算法,并最终确定进化规划算法为最适合活塞连杆组组合优化的算法.     

基于模态应变能分布的压电致动器/传感器位置优化遗传算法

本文由线弹性压电结构有限元动力方程,推导了压电智能结构的振动控制方程。建立了准确模拟层合压电结构动力行为的有限元模型。基于主结构模态应变能分布提出了一种新的优化目标函数,将压电致动器/传感器位置编号作为优化变量,建立了离散变量表示的智能结构优化问题,并通过二进制编码的遗传算法（GA）求解了该最优问题。以四边固支复合层合压电智能板为数值算例,采用比例反馈控制, 研究了最优位置配置致动器/传感器智能结构目标模态的控制效果。数值结果表明基于模态应变能分布的遗传算法所得优化解具有较好的振动控制效果。     

作动器／传感器配置优化的遗传算法应用

针对空间柔性结构,研究了振动主动控制中作动器/传感器的配置和控制器增益的全局优化问题。首先采用空间柔性结构的状态空间模型建立了以最大耗能准则为基础的目标函数,将优化问题归结为一个有约束的非线性优化问题,然后根据其特点,采用了一种十进制浮点数编码的遗传算法,并融合、设计了一些简单且优良的遗传操作,使得优化过程不依赖于初值,而且可以快速可靠地求得全局最优解。通过一个悬臂梁单点同位配置算例,证明了该算法的可行性和优越性。     

基于频响函数和遗传算法的结构损伤识别研究

提出一种基于频响函数和遗传算法的结构损伤识别方法.以单元刚度折减因子为遗传算法的优化变量,以测试频响函数和计算频响函数的形状相关系数来构造遗传算法的优化目标函数和适应度函数;为克服二进制编码的缺点,采用浮点数编码方案;最后通过一个桁架结构模型进行数值模拟,计算结果表明,即使在考虑一定测量噪声水平的情况下,仍然能够准确识别出结构的多处损伤,验证了该方法的有效性和可行性.     

基于信息熵与谱有限元法的传感器优化布置

为从测量数据中获得尽可能多信息,减少待识别模型参数的不确定性,提出面向结构模型参数识别的传感器优化布置方法。为避免用静态形函数传统有限元方法建模对结构动力特性及传感器优化布置影响,采用高精确动力学法即谱有限元法对结构进行动力学建模。以结构模型参数识别结果的不确定性最小作为传感器优化布置准则,该不确定性程度通过信息熵标量指标量化,用贝叶斯统计系统识别法进行识别。采用整数编码遗传算法在所有可能的传感器配置组合中极小化信息熵指标,获得给定数目的传感器最优布置位置。通过弹性地基带弹性接头的周期管梁模型数值仿真及模型试验验证所提方法。     

缓冲区容量约束下发动机混流装配线排序研究

为解决缓冲区容量约束下发动机混流装配排序问题,以关键部件消耗均匀化和最大完工时间最小化为目标,建立了优化数学模型,设计了一种多目标遗传算法,采用了混合交叉算子和启发式变异方法,并设计了基于帕累托分级和共享函数的适应度函数,将多目标遗传算法和多目标模拟退火算法的优化结果进行了比较。研究结果表明,多目标遗传算法在满意度和计算效率方面均优于多目标模拟退火算法,是一种有效的混流装配线排序问题求解算法。     

基于多目标遗传算法的传感器优化布点研究

针对目前桥梁模态试验中传感器布点优化都是基于单一准则下的研究的局限性,提出采用双准则或多准则下的传感器优化布点研究,该方法改进了以往布点优化中单一目标最优的限制,转而寻求多准则下的优化布点的满意解,而非真正严格数学意义上的最优解。采用Pareto遗传算法,设计了相应的遗传算子和编码方案,成功求解了双准则下传感器最优布点问题,优化结束时,成功给出了一组pareto最优解的前沿面,进而证明了提出的方法是可行的。     

Optimal sensor placement for enhancing sensitivity to change in stiffness for structural health monitoring

This paper focuses on optimal sensor placement for structural health monitoring (SHM), in which the goal is to find an optimal configuration of sensors that will best predict structural damage. The problem is formulated as a bound constrained mixed variable programming (MVP) problem, in which the discrete variables are categorical; i.e., they may only take on values from a pre-defined list. The problem is particularly challenging because the objective function is computationally expensive to evaluate and first-order derivatives may not be available. The problem is solved numerically using the generalized mixed variable pattern search (MVPS) algorithm. Some new theoretical convergence results are proved, and numerical results are presented, which show the potential of our approach.     

基于自适应引力算法的桥梁监测传感器优化布置

针对桥梁健康监测中传感器布置优化问题,提出了一种基于自适应引力算法的传感器优化布置方法。以模态置信准则为基础,构造满足传感器优化布置的适应度函数;针对引力搜索算法开发能力不足,对衰减因子α进行了自适应改进。搜索初期α较小,粒子以较大步长进行全局搜索,增强了算法的搜索效率;搜索后期α较大,粒子以较小的步长进行局部搜索,提高了算法的搜索能力,避免落入局部极值点。改进后的自适应引力算法通过双重编码的方式,使算法可以解决离散型的传感器布置问题;以马水河大桥为例,验证算法的可行性。结果表明,改进后的算法有很好的寻优能力,能够准确高效的确定传感器优化位置。     

大跨空间钢结构模态参数测试传感器优化布置

为了有效选择监控模态振型阶数,并使振型向量间夹角和测点振动能量同时尽可能大,提出了基于模态能量和白适应遗传算法的多目标传感器优化布置方法.首先,根据结构模态应变能的大小挑选出环境激励下结构的主要贡献模态,即优化时所取的监控模态.然后,根据单位刚度的模态运动能以及模态置信度矩阵构造新的适应度函数,利用自适应遗传算法对布点...     

Optimization of piezoelectric sensor location for delamination detection in composite laminates

The optimal placement of sensors is a critical issue in detecting damage in laminated composite structures. The aim is to use a minimum number of sensors, placed at the correct locations, so that the voltage signals received from the sensor set can be used to detect both the presence and the extent of damage. In this study, an optimization procedure is developed to detect arbitrarily located discrete delamination in composite plates using distributed piezoelectric sensors. The probability of damage distribution in the plate is determined using a statistical model. A genetic algorithm (GA) is used to detect the number and location of the sensors. The analysis uses a Monte Carlo method to generate the initial population. The simulation and signal processing is performed using a finite element procedure based on the refined layer-wise theory, which is capable of modelling ply-level stresses, and seeded delaminations are modelled with Heaviside step functions. A two-way electromechanical coupled field formulation is used to describe the induced strain. The objective function is a damage index which compares the voltage signals from a healthy (no delamination) and a statistically determined delaminated model. The voltage signals are affected by the local changes in the strain induced by the presence of delamination. The optimization solutions are verified by numerical simulation as well as with experiments conducted using customized piezoelectric sensors and a laser scanning vibrometer. The results presented show that the optimum sensor pattern is capable of detecting discrete seeded delaminations in moderately thick composite plates.     

A Bayesian network approach for fixture fault diagnosis in launch of the assembly process

Verification and correction of faults related to tooling design and tooling installation are important in the auto body assembly process launch. This paper introduces a Bayesian network (BN) approach for quick detection and localisation of assembly fixture faults based on the complete measurement data set. Optimal sensor placement for effective diagnosis of multiple faults, structure learning of the Bayesian network and the diagnostic procedure are incorporated in the proposed approach. The effective independence sensor placement method is used to reach the desired number of optimal sensor locations, which provide the concise and effective sensor nodes to build the diagnostic Bayesian network. A new algorithm based on conditional mutual information tests is put forward to learn the Bayesian network structure. The body side assembly case was used to illustrate the suggested method and the simulation analysis was performed to evaluate the effectiveness of the diagnostic network. The work demonstrated that the proposed methodology composes a feasible and powerful tool for fixture fault diagnosis in launch of the assembly process.     

沉管隧道健康监测试验中传感器位置的优选

基于单节沉管隧道缩比模型在地震激励作用下的健康监测试验,借助商业有限元软件ANSYS对单节隧道缩比模型进行等代地震荷载下的平面应变分析和整体模态分析,得到传感器优化布置初选点.再利用遗传算法对初选点进行优化排序,得到传感器优化布置的最终方案.该方法与EFI法传感器优化布置结果吻合较好.该方法对于大型结构的传感器优化布局有一定的借鉴作用.     

Optimal coordinate sensor placements for estimating mean and variance components of variation sources

In-process optical coordinate measuring machines offer the potential to diagnose the sources of the variations that are responsible for product quality defects. Such a sensor system can thus help manufacturers to improve product quality and reduce process downtime. The effective use of sensor data in the diagnosis of the sources of variations depends on the optimal design of the sensor system, which is often also called the problem of sensor placement. This paper addresses coordinate sensor placement for the diagnosis of dimensional variation sources in assembly processes. Sensitivity indices for the detection of the process mean and variance components are defined as the design criteria and are derived in terms of process layout and sensor deployment information. Exchange algorithms, originally developed for optimal experimental design, are revised and then used to maximize the detection sensitivity. A sort-and-cut procedure is proposed, which is able to significantly improve the algorithm efficiency of the current exchange routine. The resulting optimal sensor layout and its implications are illustrated in the specific context of a panel assembly process.     

复合材料胶层光纤布格光栅应变监测优化配置研究

航空航天用复合材料粘接胶层在制造和服役过程中不可避免会产生各种缺陷和损伤。针对其粘接胶层缺陷和损伤检测,基于光纤光栅应变传感原理,提出一种针对复合材料胶接层结构应变监测的光纤光栅传感网络优化配置的方法。通过仿真和实验研究了埋入复合材料构件胶接层的光纤布拉格光栅传感器在静载作用下的敏感区域分布特性,分析了载荷位移与布拉格波长漂移的关系,建立符合光纤布拉格光栅传感器实际特点的探测模型,采用粒子群优化算法进行光纤光栅传感网络的优化布置,研究结果表明光纤布拉格光栅传感器位置经优化后,覆盖率得到明显提高。