油-气管道检测机器人技术现状及展望

为提高油-气管道检测的效果,结合国内外典型管道机器人的特点,综合分析了管道机器人运动控制技术、定位技术和实时检测技术3个方面的现状,并指出了核心技术的不足;针对石油化工行业高温带压管道环境,提出管道检测机器人的研究重点为分层模糊神经网络运动控制技术、CCD视觉定位技术、低频电磁定位技术和分层图像分割的优化方法等。为进一步提高化工油-气管道内检测机器人的检测效果提供了理论依据。     

Recent Advances in the Detection of Antibiotic and Multi-Drug Resistant Salmonella: An Update

Antibiotic and multi-drug resistant (MDR) Salmonella poses a significant threat to public health due to its ability to colonize animals (cold and warm-blooded) and contaminate freshwater supplies. Monitoring antibiotic resistant Salmonella is traditionally costly, involving the application of phenotypic and genotypic tests over several days. However, with the introduction of cheaper semi-automated devices in the last decade, strain detection and identification times have significantly fallen. This, in turn, has led to efficiently regulated food production systems and further reductions in food safety hazards. This review highlights current and emerging technologies used in the detection of antibiotic resistant and MDR Salmonella.     

Defect classification using a new feature for pulsed eddy current sensors

The objective of this study is to identify defects such as surface cracks, subsurface defects and metal losses using feature based pulsed eddy current sensors. A new feature, termed as the rising point, related to the propagation time of electromagnetic waves in metallic targets is proposed for defect classification. Experimental studies of the validation, robustness of the new feature of rising time are reported. In addition to other features, defects can be detected and quantified robustly and lift-off can also be derived from the rising time. Conclusion and further work are derived on the basis of the findings.     

焊缝X射线照相中以透照距离为参变量的管电压计算方法

针对钛、钢焊缝X射线照相探伤中,要通过实验来确定管电压值,存在低效、浪费的问题,作者总结大量探伤工作中的数据,找出了对于不同透照方式和不同透照条件下,管电压值与试样厚度和透照距离之间的关系,建立了计算管电压值的经验公式,并对计算值与实验值作了对比分析,证实经验公式简便可靠。文中给出了适用于国内广泛采用的几种X光探伤机和通用的几种感光胶片的管电压计算公式及有关数据,可供钛、钢X光探伤工作者参考应用。     

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 多传感器信息融合是一个新的研究领域，它应用到故障诊断领域还是近几年的事。文章主要论述了多传感器信息融合技术的基本概念、工作原理及常用方法，同时还介绍了其在故障诊断中的应用实例。     

脱硫塔501-EA的焊接修复

脱硫分厂脱硫塔焊缝缺陷威胁生产，修复后有效消除了隐患，延长设备使用寿命，现系统运行良好。     

Determination of tetrachloroethylene—Results of a collaborative study and the standardized method

The development, by collaborative study, of a standardized method for the determination of tetrachloroethylene in olive oils is described. The results of the study, which was carried out in 1989 under the direction of the International Olive Oil Council (IOOC), are presented and show that tetrachloroethylene can be readily determined, to an acceptable degree of precision, by gas-liquid chromatography with electron capture detection. A limited number of results obtained for the determination of trichloroethylene and chloroform by the same method indicate that a similar precision could be obtained with the method when determining these solvents also.     

两性离子表面活性剂在分析化学中的应用

综述了两性离子表面活性剂在分析检测尤其在色谱分离和毛细管电泳技术中的应用。在色谱分离中,两性表面活性剂首先被用作固定相,能很好地分离海水及雨水中的阴离子;后来随着色谱技术在生物领域的应用,两性表面活性剂又被用作流动相,即把其溶解于电解质溶液中,此流动相能很好地分离含蛋白质的生物样品。两性表面活性剂还被广泛地用于毛细管电泳中,即作毛细管壁上的动态或静态的涂层,此法既可控制电渗流,提高分离效果,又可避免蛋白质等一些样品粘在壁上,是一种较理想的生物分离技术。     

引调水工程实体质量检测技术及其应用

针对引调水工程建设和运行设施特点,应在工程建设期直至运营管理期对引调水工程适时进行无损检测,并对其建筑物质量进行评价和监督。详细介绍了工程设施实体质量无损检测的主要内容、适用方法及检测结论等,为工程实体质量控制以及工程建设整体质量保证进行了有益的探索。通过工程应用实例验证,说明工程建设和安全运行期间的实体质量检测可判定所检测出的工程质量问题缺陷是否应及时进行修复和处理,从而为质量控制和质量保证提供了可靠的科学依据。     

Data-mining based SQL injection attack detection using internal query trees

Detecting SQL injection attacks (SQLIAs) is becoming increasingly important in database-driven web sites. Until now, most of the studies on SQLIA detection have focused on the structured query language (SQL) structure at the application level. Unfortunately, this approach inevitably fails to detect those attacks that use already stored procedure and data within the database system. In this paper, we propose a framework to detect SQLIAs at database level by using SVM classification and various kernel functions. The key issue of SQLIA detection framework is how to represent the internal query tree collected from database log suitable for SVM classification algorithm in order to acquire good performance in detecting SQLIAs. To solve the issue, we first propose a novel method to convert the query tree into an n-dimensional feature vector by using a multi-dimensional sequence as an intermediate representation. The reason that it is difficult to directly convert the query tree into an n-dimensional feature vector is the complexity and variability of the query tree structure. Second, we propose a method to extract the syntactic features, as well as the semantic features when generating feature vector. Third, we propose a method to transform string feature values into numeric feature values, combining multiple statistical models. The combined model maps one string value to one numeric value by containing the multiple characteristic of each string value. In order to demonstrate the feasibility of our proposals in practical environments, we implement the SQLIA detection system based on PostgreSQL, a popular open source database system, and we perform experiments. The experimental results using the internal query trees of PostgreSQL validate that our proposal is effective in detecting SQLIAs, with at least 99.6% of the probability that the probability for malicious queries to be correctly predicted as SQLIA is greater than the probability for normal queries to be incorrectly predicted as SQLIA. Finally, we perform additional experiments to compare our proposal with syntax-focused feature extraction and single statistical model based on feature transformation. The experimental results show that our proposal significantly increases the probability of correctly detecting SQLIAs for various SQL statements, when compared to the previous methods.