时间分辨荧光免疫一步法检测微囊藻毒素的研究

利用稀土元素Eu³⁺ 标记微囊藻毒素偶联物MCLR-BSA,在固相包被二抗的微孔板上建立了微囊藻毒素的直接竞争时间分辨荧光免疫法.条件优化后Eu³⁺ 标记物的稀释度为1∶50,微囊藻毒素单抗的合适浓度为100 ng/mL.该法对微囊藻毒素检测的灵敏度为0.02 ng/mL,试剂的测量范围是0.05～10 ng/mL,回收率达到94％以上.     

水环境中微囊藻毒素分析技术进展

微囊藻毒素将成为衡量水质好坏的指标之一。水体中微囊藻毒素的检测是了解水体污染和毒素控制的基础,因此微囊藻毒素的检测变得尤其重要。文章综述了目前微囊藻毒素的来源、化学结构和性质的研究成果,重点评述国内外微囊藻毒素检测方法进展。     

基于Hilbert-Huang变换理论的结构损伤检测

详细介绍了一种适合分析非线性非平稳数据的新方法——Hilbert-Huang变换,并将此方法应用于结构损伤检测。仿真实验是某三层剪切型建筑结构受两种不同地震烈度的地震动激励,结构在此过程中出现的损伤由层间刚度衰减的方法近似模拟,用巴特沃斯低通滤波器对得到的每层加速度数据进行滤波,然后对滤波后的数据进行Hilbert-Huang变换分析,得到其Hilbert谱,并对Hilbert谱进行了分析。结果表明,此方法能有效地提取结构的损伤特征,从而对结构的健康状况做出诊断。     

基于交流电磁场裂纹缺陷识别仿真研究

为了研究基于交流电磁场裂纹缺陷识别问题,调研了交流电磁场检测的国内外现状,结合交流电磁场技术,利用有限元分析软件ANSYS Maxwell构建常见的裂纹缺陷模型,进行仿真分析。研究了缺陷尺寸的识别以及不同缺陷簇群对交流电磁场(Alternating Current Field Measurement,ACFM）检测信号特征的影响,对提取的Bx和Bz（沿坐标轴X方向和Z方向的磁感应强度）特征信号的影响进行了分析与探讨,得到影响ACFM技术的核心参数,并建立了缺陷深度和长度的测量评估方法。研究结果表明:通过测量Bz曲线的峰谷间距可初步确定缺陷长度; Bx曲线检测同时受缺陷深度和缺陷长度的影响,对于缺陷深度检测灵敏度较低;ACFM技术虽能够实现对缺陷个数的识别,但难以准确识别缺陷尺寸的大小,当缺陷间的距离足够大时,才能准确实现缺陷的定量识别。     

VOCs快速检测在某化工企业搬迁遗留污染场地调查中的应用

以天津市某化工企业搬迁遗留污染场地为例,采用VOCs快速检测法辅助现场钻孔取样,以初步判断土壤污染深度,同时将现场样品送实验室检测。试验表明,VOCs快速检测法与实验室检测法结果基本一致。将452个样品测定结果做比对,结果表明实验室检测数据VOCs加和值与快速检测法现场检测数据存在显著相关,R2为0.803 7。污染物主要集中于场地5 m~9 m的粉土层中。其中,13种VOCs检出,4种VOCs超过《场地土壤环境风险评价筛选值》(DB11/T 811—2011)商业用地筛选值。     

储罐底板维修决策方法研究

储罐底板腐蚀是储罐失效的主要原因之一,对底板的腐蚀检测方法目前有很多种。每种方法都有自己的优势,但同时也存在着相应的弊端。通过在实践应用中对比漏磁检测与超声测厚检测方法,分别指出两种检测方法的优势与实践应用中存在的问题,提出应综合应用两种方法来提高效率和确保准确性。为更好地利用检测技术保障储罐安全提出参考建议。     

高压管汇磁致伸缩导波缺陷检测模拟研究

针对高压管汇导波缺陷检测问题,基于磁致伸缩效应,借助COMSOL有限元仿真软件,建立高压管汇直管段的导波缺陷检测模型,探究导波的激励条件及缺陷检测效果,分析不同参数对缺陷附近磁感应强度分布的影响。研究结果表明:在频率为10 kHz的正弦电流信号激励下,可产生沿管道轴向传播的T（0,1）模态导波,并能辨别缺陷处的回波信号。改变缺陷的尺寸参数时,缺陷附近的磁感应强度随着缺陷深度增加呈增大趋势,随轴向宽度增加呈减小趋势,不同形状的缺陷对应的磁感应强度存在一定的差异;改变激励条件,磁感应强度均随激励电流、激励频率的增加呈不断增加趋势。     

Model-based information fusion investigation on fault isolation of subsea systems considering the interaction among subsystems and sensors

The offshore oil industry has expanded to deep water and Arctic. The harsh operating conditions (e.g., ice and strong wind) and increasing complicated system raise the occurrence likelihood of system faults. This requires timely fault isolation and management in the subsea system. However, the offshore oil industry mainly relies on humans to isolate faults based on alarms. With harsh operating conditions and increasing complicated system, this industry urgently needs research on more efficient fault isolation and cause diagnosis methods. Unfortunately, limited research is conducted on fault isolation method in the offshore oil industry. Furthermore, in industry 4.0 era, large amounts of information are obtained. This provides precondition for the application of information fusion technique which aims to improve diagnosis results. However, to the authors’ knowledge, information fusion has not been much studied in the fault isolation of the offshore oil industry. Moreover, the interaction of different subsystems contains valuable information. How the interaction of different subsystems can influence the fault diagnosis has not been explored. This paper proposes a Bayesian network (BN) based method for timely fault isolation and cause diagnosis for the offshore oil industry. The work fuses different information, and it also includes the dependency among different subsystems in the fault diagnosis. As an important alarm source, false alarms are also taken into account in the model. A case study on the subject of the subsea wellhead and chemical injection systems is conducted to demonstrate the functions and merits of the proposed method.     

农村环境保护与环境检测技术的结合

我国经济快速发展的同时加剧了环境污染问题。无论是城市还是农村都存在一定的环境污染问题。在进行环境污染治理过程中,环境检测技术发挥了重要的作用。我国的农村在发展经济的同时也对环境带来很大的影响,而农村作为我国粮食的重要产地,一旦发生环境污染问题将会对全国人民的健康带来一定的威胁,因此必须引起高度重视。本文将对农村环境保护与环境检测技术的结合进行深入分析,希望可以促进我国农村生态环境的可持续发展。     

Safety assessment of natural gas storage tank using similarity aggregation method based fuzzy fault tree analysis (SAM-FFTA) approach

Fault tree analysis (FTA) is an important method to analyze the failure causes of engineering systems and evaluate their safety and reliability. In practical application, the probabilities of bottom events in FTA are usually estimated according to the opinions of experts or engineers because it is difficult to obtain sufficient probability data of bottom events in fault tree. However, in many cases, there are many experts with different opinions or different forms of opinions. How to reasonably aggregate expert opinions is a challenge for the engineering application of fault tree method. In this study, a fuzzy fault tree analysis approach based on similarity aggregation method (SAM-FFTA) has been proposed. This method combines SAM with fuzzy set theory and can handled comprehensively diverse forms of opinions of different experts to obtain the probabilities of bottom events in fault tree. Finally, for verifying the applicability and flexibility of the proposed method, a natural gas spherical storage tank with a volume of 10,000 m³ was analyzed, and the importance of each bottom event was determined. The results show that flame, lightning spark, electrostatic spark, impact spark, mechanical breakdown and deformation/breakage have the most significant influence on the explosion of the natural gas spherical storage tank.