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.     

Comparison of the RAPID-B® flow cytometer and the BAX® system for the detection of non-O157 shiga toxin-producing Escherichia coli (STEC) in beef products

The beef industry continues to be interested in reliable rapid detection technologies for shiga toxin-producing Escherichia coli (STEC). Current rapid technologies require several hours of pre-enrichment and additional time on the rapid technology instrument. A flow cytometer-based system (RAPID-B^®) has been shown to improve the turn-around for results with a more rapid pre-enrichment requiring only 6.5 h pre-enrichment for a 25 g and 8.5 h for a 375 g sample, followed by an additional 30 min time to achieve final results using the screening technology. The purpose of this study was to validate the RAPID-B^® technology for non-O157 STEC detection as compared to the USDA-FSIS reference method which utilizes the BAX^® system. A total of 180 STEC isolates from various sources and 20 non-STEC strains were used to evaluate specificity and sensitivity using the RAPID-B^® flow cytometer. Also, three different weights (25, 325 and 375 g) of beef trim and ground beef samples were spiked with each STEC to verify detection sensitivity of BAX^® system and RAPID-B^® flow cytometer. For both methods, samples were confirmed by culturing using the USDA-FSIS reference method regardless of the screening result. The RAPID-B^® flow cytometer showed that 180 isolates were all positive and the 20 non-STEC strains were all negative. For spiked beef samples, overall detection sensitivity was the same for both the BAX^® system and RAPID-B^® flow cytometer. When detection sensitivity was based on sample weight, there was no differences in 25 and 375 g samples between RAPID-B^® flow cytometer and USDA-FSIS reference method. The RAPID-B^® system yielded the same sensitivity as the reference method with a decrease of over 10 h of pre-enrichment time and 3 h of rapid screening detection time. In conclusion, the RAPID-B^® flow cytometer based on whole cell detection generated similar results as BAX^® system therefore the RAPID-B^® flow cytometer system could be a valuable rapid method for the detection of non-O157 STEC in beef products.     

A modified lateral flow immunoassay for the detection of trace aflatoxin M1 based on immunomagnetic nanobeads with different antibody concentrations

A modified lateral flow immunoassay (two-step assay) was developed to detect trace aflatoxin M1 (AFM1) in raw milk. In contrast to conventional LFIA, two kinds of immunomagnetic nanobeads (IMNBs) were used. One IMNB with high antibody concentration was used to capture AFM1 in the test sample, whereas the other IMNB with low antibody concentration was used to elucidate the results of the test. Critical factors, such as antibody concentration of IMNBs and size of IMNBs, were investigated. The two-step assay exhibited an ideal sensitivity to screen trace AFM1 in milk samples without extra sample pretreatment. The cutoff value of the naked eye was 0.02 μg/L and satisfied the European Union's maximum limit of AFM1 in raw milk, heat-treated milk, and milk used to manufacture milk-based products and even in baby foods. With the same antibody, sensitivity was enhanced approximately 25 and 50 times when compared with conventional IMNB-based LFIA and gold-based LFIA, respectively. Corresponding results of 13 raw milk samples were obtained between this two-step assay and referenced enzyme-linked immunosorbent assay.     

一种矿用二氧化氮传感器的检测方法

矿用二氧化氮传感器是煤矿常用的气体检测仪表，针对煤矿需求开发的矿用二氧化氮传感器，需要满足煤矿矿用产品要求。文章提出一种矿用二氧化氮传感器检测方法，说明矿用二氧化氮传感器需要满足的技术参数，供实验室检测人员借鉴，也为设计制造矿用二氧化氮传感器提供了参考。