单片机控制泄漏电流测试仪

以8031单片机为核心的泄漏电流测试仪的硬件结构和软件设计。     

Uncertainty of Predictions of Embankment Dam Breach Parameters

Risk assessment studies considering the failure of embankment dams often require the prediction of basic geometric and temporal parameters of a breach, or the estimation of peak breach outflows. Many of the relations most commonly used to make these predictions were developed from statistical analyses of data collected from historic dam failures. The prediction uncertainties of these methods are widely recognized to be very large, but have never been specifically quantified. This paper presents an analysis of the uncertainty of many of these breach parameter and peak flow prediction methods. Application of the methods and the uncertainty analysis are illustrated through a case study of a risk assessment recently performed by the Bureau of Reclamation for a large embankment dam in North Dakota.     

标准椅全身计数器对不同年龄组均匀体模源全能峰效率的刻度

本文介绍了用标准液体源均匀充入聚氯乙烯制的体模,刻度标准椅全身计数器〔φ8″×4″(NaI)〕的方法和结果。分别就代表6个年龄组的体模,测定了标准椅全身计数器对5种能量(364,637,898,1460和1836keV)γ射线的全能峰效率;给出了全能峰效率与γ射线能量和被测对象体重的关系曲线。     

燃气空调的优势及对燃气和电力调峰的意义

分析了天然气季节性调峰的各种手段，指出燃气空调的技术经济优势，以及发展燃气空调对于电力和燃气系统季节性调峰的作用。     

基于氢能的风-火耦合多能系统设计与综合评估

为了提高火电机组深度调峰极限,挖掘其提升新能源消纳能力的潜力,构建了基于氢能的风-火耦合多能系统.建立了风-火耦合多能系统的设计框架,包括设计原则、系统组成及评价指标体系等,提出了富裕风电制氢支撑的风-火耦合多能系统的总体结构;考虑经济性、能源利用、"双碳"目标、可靠性这4个方面的影响因素,提出了风-火耦合多能系统的多尺度评价指标及其数学模型,并基于模糊层次分析-熵权法确定各指标的权重占比;以某地区拟建的风-火耦合多能系统结构设计为例,验证了所提方法的有效性,可为实际工程建设提供了一定的参考.     

普通快走丝线切割机间隙电压取样电路浅析

介绍了传统的间隙电压取样电路，指出了它存在的问题，简述了取样电路的发展方向。     

年最大洪峰流量群居蜘蛛优化投影寻踪预测模型

年最大洪峰流量预测,受较多的复杂因素的影响,不确定性较强,用常规统计方法做出准确预报具有较大困难。从水文序列本身出发,提出将投影回归模型应用于年最大洪峰流量预测,为了更好获得投影寻踪模型参数和预测精度,提出了运用延迟相关系数法确定回归预测因子、群居蜘蛛算法优化投影寻踪模型最佳投影方向参数a、利用最小二乘法确定多项式的权系数c、岭函数个数M的群居蜘蛛优化投影寻踪年最大洪峰流量预测模型,结合长江宜昌站(1882年-2004年)的年最大洪峰流量资料进行实例预测,训练阶段平均绝对相对误差为8.61%,预测阶段平均绝对相对误差为10.51%,该模型预测效果较好,模型结果稳定,可有效应用于年最大洪峰流量预测。     

Automatic moment segmentation and peak detection analysis of heart sound pattern via short-time modified Hilbert transform

This paper proposes a novel automatic method for the moment segmentation and peak detection analysis of heart sound (HS) pattern, with special attention to the characteristics of the envelopes of HS and considering the properties of the Hilbert transform (HT). The moment segmentation and peak location are accomplished in two steps. First, by applying the Viola integral waveform method in the time domain, the envelope (E_T) of the HS signal is obtained with an emphasis on the first heart sound (S1) and the second heart sound (S2). Then, based on the characteristics of the E_T and the properties of the HT of the convex and concave functions, a novel method, the short-time modified Hilbert transform (STMHT), is proposed to automatically locate the moment segmentation and peak points for the HS by the zero crossing points of the STMHT. A fast algorithm for calculating the STMHT of E_T can be expressed by multiplying the E_T by an equivalent window (W_E). According to the range of heart beats and based on the numerical experiments and the important parameters of the STMHT, a moving window width of N = 1 s is validated for locating the moment segmentation and peak points for HS. The proposed moment segmentation and peak location procedure method is validated by sounds from Michigan HS database and sounds from clinical heart diseases, such as a ventricular septal defect (VSD), an aortic septal defect (ASD), Tetralogy of Fallot (TOF), rheumatic heart disease (RHD), and so on. As a result, for the sounds where S2 can be separated from S1, the average accuracies achieved for the peak of S1 (AP₁), the peak of S2 (AP₂), the moment segmentation points from S1 to S2 (AT₁₂) and the cardiac cycle (ACC) are 98.53%, 98.31% and 98.36% and 97.37%, respectively. For the sounds where S1 cannot be separated from S2, the average accuracies achieved for the peak of S1 and S2 (AP₁₂) and the cardiac cycle ACC are 100% and 96.69%.     

基于轮廓波变换的织物疵点图像消噪新方法

为了实现织物疵点图像的有效消噪,使其更有利于特征提取和疵点检测,提出了基于轮廓波变换的织物疵点图像消噪新方法。综合考虑轮廓波方向子带能量的大小与织物疵点图像轮廓细节之间的关系,对Donoho多尺度分解阈值进行修正,改进了Donoho多尺度分解阈值对图像细节"过扼杀"的缺点。实验结果表明,对织物疵点图像进行基于轮廓波变换改进阈值消噪时,该方法更好地保留了织物疵点图像的轮廓细节,峰值信噪比显著提高。采用改进的轮廓波Donoho多尺度分解阈值消噪后的图像,可以更好地应用于织物疵点图像的特征提取和疵点识别。