一种自适应改进曲率扩散超声图像滤波方法

针对图像尤其是医学超声图像的边缘模糊或者缺失对图像进一步处理带来的影响,同时由于传统改进曲率扩散方程无法自适应以及迭代时间长,本文提出了一种结合高斯滤波的参数自适应的改进曲率扩散方法,并且使用统计学中的绝对偏差中值自动调整梯度阈值参数。该方法能在保留改进曲率扩散方程去噪能力的同时有效地保留图像边缘细节信息,同时减少了滤波过程中的迭代次数,从时间复杂度的方面提高了方法的效率。另外,自适应梯度阈值的采用进一步提高了改进曲率扩散方程保留图像细节信息的能力。实验结果表明,结合高斯滤波的参数自适应改进曲率扩散方法继承了改进曲率扩散的优点,同时又减少了人工干预,提高了去噪效率。     

Designing biomass supply chains within planetary boundaries

The design of sustainable supply chains, which recently emerged as an active area of research in process systems engineering, is vital to ensure sustainable development. Despite past and ongoing efforts, the available methods often overlook impacts beyond climate change or incorporate them via standard life cycle assessment metrics that are hard to interpret from an absolute sustainability viewpoint. We here address the design of biomass supply chains considering critical ecological limits of the Earth—planetary boundaries—which should never be surpassed by anthropogenic activities. Our method relies on a mixed-integer linear program that incorporates a planetary boundaries-based damage model to quantify absolute sustainability precisely. We apply this approach to the sugarcane-to-ethanol industry in Argentina, identifying the optimal combination of technologies and network layout that minimize the impact on these ecological boundaries. Our framework can find applications in a wide range of supply chain problems related to chemicals and fuels production, energy systems, and agriculture planning.     

基于C8051F352单片机的弹道参数测量系统设计

为提高弹道辨识精度和弹道解算速度,设计了一种基于C8051F352单片机的弹道参数测量系统.通过对弹丸飞行中动压和静压信息的采集、存储和处理,完成弹道参数(初速和射角)辨识.该系统以C8051F352单片机作为处理单元,结合差压传感器和绝压传感器设计而成,采用基于动压-静压的弹道辨识方法,有效地提高了弹道参数测量的精度.实验测试表明:该系统测量精度高,解算速度快,满足弹道辨识的设计要求.     

用两层分类算法进行视频烟雾检测

为提高视频烟雾检测的准确性,提出一种基于概率的两层最近邻自适应度量分类算法(PTLNN)来进行烟雾检测.该算法以最小化平均绝对误差为原则,结合AdaBoost和KNN算法的优势,充分考虑局部和全局的样本分布,能明显提升分类精度.采用离散余弦变换(DCT)和离散小波变换(DWT)两种方式对烟雾特征进行提取,并验证算法性能.通过与传统算法的对比实验发现,采用离散余弦变换并结合PTLNN算法在视频烟雾检测方面具有更好的效果,既满足实时性要求又提高了检测精度.     

多功能工业定时器设计

主要设计了以STC89C51单片机为核心的多功能工业定时器设计,并且使用了万年历芯片DS1302、液晶显示器TS1620、蜂鸣器等器件.该没计采用C语言编程,包括液晶显示程序、万年历程序、按键扫描程序.该工业定时器应能够实现绝对时间和相对时间的定时,定时范围广,并且有信号输出.     

On absolute (robust) stability: slope restrictions andstability multipliers

Absolute stability for systems with several sector‐restricted and slope‐restricted nonlinearities is studied in this paper. A critical analysis of the multipliers is performed and the multipliers of Yakubovich type are chosen because the stability inequality is obtained with a minimum of technical assumptions. The main part of the paper is devoted to obtaining the Yakubovich‐type criterion in the unified context of stable, critical, and unstable cases for the linear part. The paper is motivated by the problem of pilot in‐the‐loop oscillations of the aircrafts where critical and unstable cases appear and the saturation nonlinearity is both sector and slope restricted. The paper contains some applications of the frequency domain inequalities. The conclusions show a ‘parsimony principle’: using as few free parameters as possible to obtain the largest possible domain of stability. The paper ends with conclusions and hints for further development. Copyright © 2011 John Wiley & Sons, Ltd.     

利用图像传感器的光电轴角编码器编码研究

研究了绝对式角度编码器的编码原理及解码方法.在分析国内外已有编码原理的基础上,提出了一种以位移连续码为基础的新型码盘图案,该码盘在背景光照射下,由图像传感器进行光学图像采集,快速数字化后经代码识别算法获取绝对位置信息.该图形简单,制作方便,类似于增量式编码器图案,但实现了绝对式编码,易于实现编码器的小型化.实验结果表明该系统设计及理论依据是完全正确的.     

并行通讯格雷码多圈旋转编码器和S7-200型PLC在石灰炉提升机上的应用

本文系统分析了各种旋转编码器和S7-200型PLC的特点,解决了用S7-200型PLC将格雷码翻译成二进制码等难题,选用并行通讯格雷码旋转编码器、S7-200型PLC和中文TD200人机界面组成控制系统,成功实现石灰炉提升机自动控制,控制系统必将在小规模精度定位领域中得到广泛应用。     

大坝变形预测的最优因子长短期记忆网络模型

面对海量的大坝安全监测数据,快速合理地确定大坝变形预测模型的变量因子能够有效提高模型预测的效率和精度。为此,本文提出一种基于最小绝对值收缩和选择算子（least absolute shrinkage and selection operation,LASSO）变量选择和长短期记忆（long short-term memory,LSTM）网络的大坝变形预测模型。首先,通过大坝变形机理分析确定影响大坝变形的相关影响因子集。然后,通过LASSO算法剔除不显著的因子,筛选出最优影响因子作为模型输入变量,并利用LSTM网络建立大坝变形预测模型。最后,以皂市水利枢纽工程的碾压混凝土重力坝为例,对本文方法进行了验证和讨论。结果表明,本文方法具有较高的预测精度,其平均绝对误差（MAE）、均方误差（MSE）与均方根误差（RMSE）均相对较小;与常规预测模型相比,基于LASSO算法的变量选择使模型建立过程更加简单高效,有利于海量监测数据的处理分析。     

Robust integrated sequential covariance intersection fusion Kalman filters and their convergence and stability for networked sensor systems with five uncertainties

For networked sensor systems (NSSs) with hard and soft sensors including five uncertainties, two universal approaches of solving the robust fusion estimation problems are presented. It includes an integrated sequential covariance intersection (SCI) fusion minimax robust Kalman filtering approach with cross-covariance information and a generalized Lyapunov equation approach with four pairs of Lyapunov equations. Applying them, the robust local and SCI fused time-varying and steady-state Kalman filters are presented in the sense that their actual estimation error variances are guaranteed to have the corresponding minimal upper bounds. The equivalent batch SCI fusers are also presented. Their robustness and accuracy relations are proved, and the sensitivity of the SCI fuser with respect to the fused orders of sensors is analyzed. Applying the dynamic error system analysis method and the dynamic variance error system analysis method, a new convergence and absolute asymptotic stability theory of robust fusion Kalman filtering is presented. The classical Kalman filtering convergence and stability theory is developed. Compared with the original covariance intersection fuser, they significantly reduced the computational complexity and burden. Compared with the optimal and conservative SCI fusers, they significantly improved the robust accuracies. They are suitable to deal with asynchronous or random delayed data and are suitable for real-time applications. A simulation applied to the two-mass spring damper mechanical system shows their effectiveness.