基于EEMD和多元多尺度熵的变压器故障检测方法

对EEMD算法进行了理论分析,介绍了多尺度样本熵特征提取方法,提出了一种基于EEMD和多元多尺度熵的故障检测算法,并进行了仿真对比试验。     

浅议集团检测单元技术创新管理与实践

检测部门是集团公司重要的辅助单元,履行着集团公司“产品质量守护神”、“集团海关”和“生产的眼睛”的神圣职责,在外购原料把关和产品出产检验等方面发挥着重要的作用。创新在检测进步的过程中发挥了越来越重的作用,基于这-.现状,本文从创新的目的和方向、创新的思维、激励机制、创新手段创新团队五个方面,结合检测中心近年来技术进步管理工作,就如何强化检测的技术创新管理提出了几点浅见。     

Discussion on the determination of sail residue in silk fibroin solution with a water quality testing pen北大核心CSCD

the salt residue is one of the quality indexes of silk fibroin products.The products with low salt residue are not only healthier for human body, hut also more stable in exterior qualities, such as color and smell.Instrumental analysis and chemical analysis are currently methods to accurately determine salt residues in silk fibroin products, but they still need to be supplemented by real-time and quick detection methods in practical production.This paper discusses the determination method with a water quality testing pen and investigates the response of the water quality pen to the changes in the concentration of a variety of solutions, and associates with application examples.The results show that the TDS measured by the water quality pen is highly linearly correlated with the changes in the concentrations of CaCU , NaCl, and fibroin-CaCU solutions.The principle and method of the TDS water quality testing pen have an application prospect in the field of real-time and rapid approximate evaluation of salt residue in silk fibroin solution. © 2021 China Silk Association. All rights reserved.     

2000m~3液化气球罐的TOFD检测

由于现场施工队伍多、施工工期短等原因,采用100%TOFD+100%UT组合方式取代100%射线检测方式对现场组焊的球罐焊缝进行检测,并编制了检测技术方案。按照该方案对一台球罐进行了TOFD检测,发现了许多圆形、条形缺陷。经超声检测验证,其检测结果与TOFD检测出的缺陷位置基本吻合。     

基于声信号处理的窨井盖盗毁检测方法

为遏制偷盗和毁坏窨井盖行为,提出一种利用声信号对窨井盖偷盗和毁坏进行检测的方法。因不同声信号的能量基于频率的分布存在差异,将窨井盖产生的振动声信号进行FFT变换,将变换后的频谱转化为能量谱,利用统计方法确定窨井盖振动声信号能量在频率上的特征分布区间和分布阈值,计算其他干扰声信号的20个最大能量点在该特征区间的概率分布数并与阈值对比,判断窨井盖的振动声是否是遭受盗毁时敲击引起的。实验结果显示:窨井盖敲击声的能量分布与其他声信号具有明显不同,其能量分布的特征频率为48～504 Hz,分布阈值为85%。该方法能够有效识别盗毁窨井盖声音,且在一定信噪比环境下具有较强鲁棒性。     

Increasing X-ray image interpretation competency of cargo security screeners

X-ray screening of containers and unit load devices in the area of cargo shipping is becoming an essential and common feature at ports and airports all over the world. The detection of prohibited items in X-ray images is a challenging task for screening officers as they need to know which items are prohibited and what they look like in X-ray images. The main aim of this study was to investigate whether X-ray image interpretation competency of cargo security screeners can be increased by computer-based training. More specifically, effects of training were investigated by conducting tests before training started and after approximately three months of training. Moreover, it was examined whether viewing X-ray images in pseudo color would lead to a better detection performance compared to when X-ray images are shown in greyscale. Recurrent computer-based training resulted in large performance increases after three months. No significant difference in detection performance could be found for tests when using X-ray images in greyscale vs. pseudo color.     

现代检测技术在数控机床中的应用

介绍现代检测技术及检测装置在数控机床中的应用,详细分析位置检测装置在数控机床中的重要作用,归纳总结检测元件发生故障的原因,以达到经验共享的目的。     

双频载波相位平滑码伪距差分技术研究

本文针对载波相位平滑伪距差分技术在高精度测量的应用,推导了单频和双频载波相位平滑伪距的原理,分别给出了单频和双频载波相位平滑伪距差分模型。通过试验分析,比较了单频和双频差分导航定位精度,分析了双频载波相位平滑伪距差分定位的优点,且其差分定位精度可达亚米级。     

A Procedure to Estimate the Population Mean In Random Effects Models

A general procedure for estimating the population mean in random effects models of the nested and/of classification type is considered. The suggested estimator is unbiased and consistent (with respect to the structure of the experimental design). It is also optimal with respect to a particular quadratic, location-sensitive criterion. Finally, for experimental designs which contain a certain degree of structural balance, the suggested estimator coincides with the sample mean.     

Bayesian changepoint and time-varying parameter learning in regime switching volatility models

This paper proposes a combined state and piecewise time-varying parameter learning technique in regime switching volatility models using multiple changepoint detection. This approach is a Sequential Monte Carlo method for estimating GARCH & EGARCH based volatility models with an unknown number of changepoints. Modern auxiliary particle filtering techniques are used to calculate the posterior densities and online forecasts. This approach also automatically deals with the common ancestral path dependence problem faced in these type volatility models. The model is tested on Borsa Istanbul (BIST) formerly known as Istanbul Stock Exchange (ISE) market data using daily log returns. A full structural changepoint specification is defined in which all parameters of the conditional variance of the volatility models are dynamic. Finally, it is shown with simulation experiments that the proposed approach partitions the series into several regimes and learns the parameters of each regime's volatility model in parallel with the multiple changepoint detection process.