板料成形优化技术进展与质量工程研究

板料成形过程的优化研究对于改进模具设计、提高产品质量具有重要意义。综述了板料成形工艺优化的研究现状。考虑到在有约束的设计优化中,最优结果常位于约束边界附近,随机因素的波动易导致产品质量不稳定甚至失效,难以保持产品的可靠性和稳健性。为此,本文应用质量工程学中的6σ理念,提出了基于数值模拟的板料成形6σ稳健设计优化方法。     

Reliability-based robust design optimization: A general methodology using genetic algorithm

In this paper, we present an improved general methodology including four stages to design robust and reliable products under uncertainties. First, as the formulation stage, we consider reliability and robustness simultaneously to propose the new formulation of reliability-based robust design optimization (RBRDO) problems. In order to generate reliable and robust Pareto-optimal solutions, the combination of genetic algorithm with reliability assessment loop based on the performance measure approach is applied as the second stage. Next, we develop two criteria to select a solution from obtained Pareto-optimal set to achieve the best possible implementation. Finally, the result verification is performed with Monte Carlo Simulations and also the quality improvement during manufacturing process is considered by identifying and controlling the critical variables. The effectiveness and applicability of this new proposed methodology is demonstrated through a case study.     

Augment low-field intra-operative MRI with preoperative MRI using a hybrid non-rigid registration method

Background

Preoperatively acquired diffusion tensor image (DTI) and blood oxygen level dependent (BOLD) have been proved to be effective in providing more anatomical and functional information; however, the brain deformation induced by brain shift and tumor resection severely impairs the correspondence between the image space and the patient space in image-guided neurosurgery.

Method

To address the brain deformation, we developed a hybrid non-rigid registration method to register high-field preoperative MRI with low-field intra-operative MRI in order to recover the deformation induced by brain shift and tumor resection. The registered DTI and BOLD are fused with low-field intra-operative MRI for image-guided neurosurgery.

Results

The proposed hybrid registration method was evaluated by comparing the landmarks predicted by the hybrid registration method with the landmarks identified in the low-field intra-operative MRI for 10 patients. The prediction error of the hybrid method is 1.92 ± 0.54 mm, and the compensation accuracy is 74.3 ± 5.0%. Compared to the landmarks far from the resection region, those near the resection region demonstrated a higher compensation accuracy (P-value = .003) although these landmarks had larger initial displacements.

Conclusions

The proposed hybrid registration method is able to bring preoperatively acquired BOLD and DTI into the operating room and compensate for the deformation to augment low-field intra-operative MRI with rich anatomical and functional information.     

超磁致伸缩作动器的率相关Hammerstein模型与H∞鲁棒跟踪控制

利用Hammerstein模型对超磁致伸缩作动器（Giant magnetostrictive actuators,GMA）的率相关迟滞非线性进行建模,分别以改进的 Prandtl-Ishlinskii（Modified Prandtl-Ishlinskii）模型和外因输入自回归模型（Autoregressive model with exogenous input,ARX）代表Hammerstein模型中的静态非线性部分和线性动态部分,并给出了模型的辨识方法. 此模型能在1～100Hz频率范围内较好地描述GMA的率相关迟滞非线性. 提出了带有逆补偿器和H∞鲁棒控制器的二自由度跟踪控制策略,实时跟踪控制实验结果证明了所提策略的有效性.     

Robust control of variable speed autonomous underwater vehicle

Set point tracking control of autonomous underwater vehicle (AUV) via robust model predictive control (RMPC) is considered. Input-constrained RMPC with integral action, which has been developed in our previous work, is used to control the AUV in this study. In order to derive a RMPC control rule, non-linear dynamics of AUV with six degree of freedom is linearized at certain operating points. So, horizontal and vertical plane dynamics of system are represented by linear models which have polytopic uncertainties. Since the derived control rule will be used in real time, the computation time should be reduced. To overcome this computational time problem and get rid of trial–error step of Algorithm 1, a new algorithm is proposed here. The simulations are carried out using the control rule based on this algorithm and these results are presented.     

融合Hu矩与BoF-SURF支持向量机的手势识别

基于尺度不变特征变换的特征包（BoF-SIFT）支持向量机的分类方法具有较好的手势识别效果, 但是计算复杂度高、实时性较差。为此, 提出了融合Hu矩与基于快速鲁棒特征的特征包（BoF-SURF）支持向量机（SVM）的手势识别方法。特征包模型中用快速鲁棒性特征（SURF）算法替换尺度不变特征变换（SIFT）算法提取特征, 提高了实时性, 并引入Hu矩描述手势全局特征, 进一步提高识别率。实验结果表明, 算法无论是实时性还是识别率都要高于BoF-SIFT支持向量机方法。     

基于全网能量均衡的WirelessHART图路由算法

如何均衡使用网络节点能量并生成高可靠路由是WirelessHART网络研究的一个难题,为此提出了一种GRAEB（graph routing algorithm based on energy balancing）图路由算法。首先,网络被初始化为连通的图结构,能够提高丰富的冗余路径。网络管理器根据全网节点剩余能量、通信周期、链路分布等因子生成节点鲁棒系数矩阵,节点通过比较邻居的鲁棒系数来选择最优路径。另外,规定了邻居节点数的上限阈值,每次路由更新只保留鲁棒系数最优的邻居。仿真结果表明GRAEB不仅提高了网络可靠性,而且延长了网络寿命。     

压电作动器的动态迟滞建模与H∞鲁棒控制

压电作动器具有率相关动态迟滞非线性特性,给传统建模和控制技术提出了挑战.本文针对压电作动器,提出了一种基于Bouc-Wen的Hammerstein率相关迟滞非线性模型,其中Bouc-Wen模型和线性动态模块分别用于描述系统的静态迟滞非线性特性和率相关特性.同时,构造了一个基于Bouc-Wen模型的迟滞补偿器,将迟滞补偿器与被控对象串联使系统线性化;并建立了不确定性系统模型,提出了一种H∞鲁棒跟踪控制方案,可以实现给定频率范围内单频率和复合频率参考信号的良好跟踪.实验结果表明,所建动态模型具有良好的泛化能力,跟踪控制相对误差小于8%,证明了所提出方法的有效性.     

具有自适应噪声边界的Tube可达集鲁棒预测控制

针对过程噪声设定边界与真实噪声边界失配的有界干扰离散线性不确定系统,提出一种具有自适应噪声边界的Tube可达集鲁棒模型预测控制方法.首先,该算法引入基于MIT规则的自适应集员滤波在线估计系统状态和噪声边界.其次,基于估计值,通过迭代自适应集员滤波的时间更新部分计算出预测时域内闭环不确定系统状态的可达集.最后,用可达集代替不变集并根据Tube鲁棒模型预测控制策略,给出了实际不确定系统的控制律,确保系统状态鲁棒渐近稳定,并收敛于终端干扰不变集.仿真结果验证了该控制方法的有效性.     

航空有源滤波器自适应谐波检测仿真研究

介绍了基于自适应滤波理论的谐波检测原理,分析了自适应神经元算法用于谐波检测的可行性,设计了基于自适应谐波检测的并联型航空混合有源滤波器,对滤波特性进行了仿真研究。结果表明,基于自适应滤波理论的谐波检测方法能够快速、精确地检测相电流谐波含量,在相电压波形发生畸变的情况下,也具有较好的自适应能力、快速补偿能力和跟踪性能。