基于改进型自抗扰控制的永磁同步电机伺服控制

目的 解决传统包装机械存在的包装速度慢、包装质量堪忧等问题,满足包装机械的高效率、高精度等要求,提高食品包装的自动化水平和包装企业的经济效益。方法 对具有较大潜力的永磁同步电机,进行控制器和控制方法的研究与改进,并最终选定自抗扰控制器,对自抗扰控制器中非光滑函数fal进行改进得到连续平滑的tal函数,使其减小在原点周围的颤振,并且基于tal函数重新设计非线性状态误差反馈率和扩张状态观测器,以取得对永磁同步电机更好的控制效果。结果 仿真表明,tal函数比fal函数具有更好的平滑性和连续性。基于改进型自抗扰控制的永磁同步电机具有更好的动态性能、稳态精度、抗扰能力和跟踪能力。结论 文中优化后的永磁同步电机伺服控制系统,适用于高精度、负载变动频繁的场合,能够有效地提高包装自动化水平,满足高效率、高精度的包装行业要求。     

Simulation of a non-Gaussian stochastic process based on a combined distribution of the UHPM and the GBD

To simulate non-Gaussian stochastic processes based on the first four moments, various simulation methods are presented, in which the determination of the transformation model and the calculation of the correlation coefficients between non-Gaussian stochastic processes and Gaussian stochastic processes are the critical procedures in these simulation methods. However, some existing simulation methods are limited to specific ranges. Furthermore, their practical applications are affected negatively due to the expensive cost of determining the transformation model and the correlation coefficients between non-Gaussian and Gaussian stochastic processes. Therefore, an accurate and efficient simulation method of a non-Gaussian stochastic process with a broader range is proposed in this article. Since the simulation of non-Gaussian processes and the Nataf transformation of non-Gaussian variables have some similar characteristics, a new combined distribution is proposed based on the unified Hermite polynomial model (UHPM) and the generalized beta distribution (GBD). Then, the combined distribution is employed in the simulation of non-Gaussian stochastic processes, in which the transformation model is deduced by the combined distribution. The correlation coefficient transformation function (CCTF) between the Gaussian and non-Gaussian stochastic processes can be evaluated through the interpolation method. Furthermore, numerical examples are presented to show the accuracy and effectiveness of the proposed simulation method for non-Gaussian stochastic processes.     

Sample regeneration algorithm for structural failure probability function estimation

An efficient strategy to approximate the failure probability function in structural reliability problems is proposed. The failure probability function (FPF) is defined as the failure probability of the structure expressed as a function of the design parameters, which in this study are considered to be distribution parameters of random variables representing uncertain model quantities. The task of determining the FPF is commonly numerically demanding since repeated reliability analyses are required. The proposed strategy is based on the concept of augmented reliability analysis, which only requires a single run of a simulation-based reliability method. This paper introduces a new sample regeneration algorithm that allows to generate the required failure samples of design parameters without any additional evaluation of the structural response. In this way, efficiency is further improved while ensuring high accuracy in the estimation of the FPF. To illustrate the efficiency and effectiveness of the method, case studies involving a turbine disk and an aircraft inner flap are included in this study.     

Transient response of Bouc–Wen hysteretic system under random excitation via RBFNN method

Hysteresis normally exhibited by mechanical systems and materials is so prevalent that its response prediction under random excitation has been extensively investigated for decades. Nevertheless, the transient solution of the response, which is crucial for assessing the system’s reliability, is still a challenging topic that requires additional development. To this regard, this work proposes a semi-analytical method using the radial basis function neural network (RBFNN) to attain the transient probability density distribution of the randomly excited Bouc–Wen system. Specifically, the trial solution of the corresponding FPK equation is configured as the RBFNN with undetermined time-varying weight coefficients. By discretizing the time derivative with the Euler difference method, a loss function with time recurrence is derived and minimized to yield the time-varying optimal weight coefficients through the optimization method. Additionally, an optimized sampling strategy is adopted to reduce the burden of calculation. Finally, the Bouc–Wen hysteretic systems with softening and hardening nonlinearity are considered to investigate the performance of the adopted technique. The numerical results have shown that the evaluation process of the probability density functions(PDFs) can be captured well with sufficient accuracy and efficiency. The proposed efficient sampling technique can provide considerable efficiency improvement for the medium dimension system. The work of the paper will contribute to the reliability design of hysteretic structures in engineering.     

Medical image contrast enhancement based on improved sparrow search algorithm

The collection or transmission of medical images is often disturbed by various factors, such as insufficient brightness and noise pollution, which will result in the deterioration of image quality and significantly affect the clinical diagnosis. To improve the quality of medical images, a contrast enhancement method based on improved sparrow search algorithm is proposed in this paper. The method is divided into two steps to enhance the medical images. First, a new transform function is introduced to improve the brightness or contrast of medical images, and two parameters in the transform function are optimized by the improved sparrow search algorithm. Second, adaptive histogram equalization method with contrast limited is used to equalize the result image of the previous step to make the pixel distribution of the image more uniform. Finally, a large number of experiments and qualitative and quantitative analyses were conducted on the common data sets. The analysis results demonstrate that the presented approach outperforms some existing medical image processing approaches.     

Rational Filters for Passive Depth from Defocus

A fundamental problem in depth from defocus is the measurement of relative defocus between images. The performance of previously proposed focus operators are inevitably sensitive to the frequency spectra of local scene textures. As a result, focus operators such as the Laplacian of Gaussian result in poor depth estimates. An alternative is to use large filter banks that densely sample the frequency space. Though this approach can result in better depth accuracy, it sacrifices the computational efficiency that depth from defocus offers over stereo and structure from motion. We propose a class of broadband operators that, when used together, provide invariance to scene texture and produce accurate and dense depth maps. Since the operators are broadband, a small number of them are sufficient for depth estimation of scenes with complex textural properties. In addition, a depth confidence measure is derived that can be computed from the outputs of the operators. This confidence measure permits further refinement of computed depth maps. Experiments are conducted on both synthetic and real scenes to evaluate the performance of the proposed operators. The depth detection gain error is less than 1%, irrespective of texture frequency. Depth accuracy is found to be 0.51.2% of the distance of the object from the imaging optics.     

一种用于立体匹配的改进的神经网络方法

实现了一种用于静态视觉立体匹配的神经网络方法。文献［１］提出了一种用于静态体视匹配的神经网络方案,其方案用于随机点图对时存在严重的缺陷。针对随机点图对的特点,对神经网络的偏置输入进行了修正,改进的神经网络能够有效地提取随机点图对中的立体深度信息。为了进一步提高收敛速度和平滑边缘特征,又在偏置输入中引入射线特征,改进了神经元的初始化。在工作站上进行的大量实验模拟表明,我们所做的改进提高了网络的迭代速度和视差图的边缘特征平滑性。     

第二次管理革命——企业再造及其特征显示

通过对传统的企业管理和第二次管理革命———企业再造的比较,揭示了第二次管理革命———企业再造的特征,阐明了第二次管理革命———企业再造过程对企业的影响,并对未来经济与组织管理进行展望     

产品形态设计的思考

产品形态设计怎样才能顺应时代的发展？根据我国国情,从国际流行趋势、功能、性能优化、人本性、新技术以及产品周期六个方面进行了探讨。     

Valuations,regular expressions,and fractal geometry

Valuations — morphisms from ( _n ^* ,·,) to ((0, ), ·, 1) — are a simple generalization of so-called Bernoulli morphisms. In this paper, we show a characterization of strongly unambiguous regular expressions with the help of valuations and formal power series. We apply these algebraic results to the determination of Hausdorff dimensions of fractals described by regular expressions.