金属材料超声无损检测技术应用研究

为了提高石油工业装备检测水平,促使石油生产工业健康、可持续发展,现提出一套行之有效的金属材料超声无损检测技术应用方案。首先,针对超声无损检测技术、算法与研究概况,研究了连续波透射法、共振法、脉冲反射法、脉冲透射法四种超声无损检测方法。其次,从灵活选择超声无损检测技术方法、在对的时间段内实施无损检测工作、对超声无损检测方式加以升级等方面入手,将超声无损检测技术科学地应用到石油行业金属材料中。结果表明：本文所提出的超声无损检测技术应用方案具有较高的可靠性和可行性,不仅可以精确化检测石油行业金属材料内部缺陷,还能实现对材料微观部分的精细化检查,有效地提高了金属材料把控质量。希望通过这次研究,为相关人员提供有效的借鉴和参考。     

大棒材电磁超声探伤的技术特点

介绍了大棒材电磁超声探伤仪的设备结构、功能和工作原理,与常规压电超声相比,电磁超声探伤仪具有调整简便、适应温度范围广、无需耦合剂等优点,在大棒材自动无损检测领域逐渐占据重要地位。     

深冲钢板r值在线检测技术评述

ｒ值是评价深冲钢板成型性能的重要指标之一。ｒ值的在线无损连续检测对沿整个板卷长度方向实行质量监控极为有益。通过对目前的Ｘ射线法和电磁超声法ｒ值在线检测技术各自特点的讨论，提出了电磁超声法更具发展前途的结论。     

无损检测技术在轧辊质量控制方面的应用

本文叙述了几种常见的无损检测方法的工作原理,并结合在冷轧薄板厂的工作实际,介绍了无损检测技术在在轧辊质量控制中的应用。实践证明,综合运用涡流、超声、渗透、磁粉等方法对轧辊进行无损检测,可有效预防轧辊服役过程中的剥落、断辊等事故的发生。     

连铸坯集肤表层电磁激励超声场模拟

为研究连铸二次冷却区凝固坯壳厚度电磁超声无损检测机理,分析了连铸坯表面振痕对超声波信号的影响.利用有限元分析方法,建立螺旋线圈电磁超声换能器在连铸坯表面的电场、磁场、力场和声场的耦合模型.并以贝塞尔曲线方程模拟表面振痕,分析了表面振痕对连铸坯集肤表层的涡流、磁场、力场等分布规律的影响.实验结果验证了仿真分析中模型和仿真结果的正确性,为设计连铸过程凝固坯壳厚度电磁超声无损检测装置提供了理论参考依据.     

钢材含碳量电磁无损检测方法

钢材含碳量在线无损检测技术在钢铁工业精确过程控制中起着至关重要的作用。电磁方法广泛应用于离线钢材含碳量的无损检测,但多数传统方法只是利用了电磁特性对含碳量敏感的特点,而忽视了电磁特性对温度敏感的特点。最近,利用电磁计算技术的多物理场软测量方法克服了这一缺点,取得了良好的效果。本文介绍采用涡流法、Barkhausen噪声法、宏观磁性能法和感应加热法4种钢铁材料中含碳量电磁无损检测方法的基本原理,阐述它们的研究现状及发展方向。通过比较分析各种测量方法的原理,分析了应用这些方法进行在线检测的可能性。     

基于DSP小波变换在钢铁材质无损检测中的应用

针对钢铁材质电磁无损检测中使用传统信号处理方法检测分选率偏低的问题,利用电磁无损检测信号特点,将小波分析引入钢铁材质无损检测。根据小波分析算法对硬件系统的要求,充分利用DSP芯片优越的数字信号处理功能和快速的运算速度,完成了钢铁材质电磁无损检测装置。试验表明,该方法可以有效地提取检测信号,可应用于钢铁材质裂纹的无损探伤。     

无损检测技术在冶金设备机械安检中的应用

分析了超声波检测、红外热像无损检测、超声红外热像检测、激光全息检测等几种无损检测技术在冶金机械设备安检中的应用情况。无损检测技术能够为安检操作人员提供快速准确的决策依据,是冶金生产消除故障隐患、保证安全生产的重要手段。     

铁磁性金属材料电磁无损检测中优化磁化场设计的研究

利用电磁原理进行无损检测的方法在铁磁性金属材料的探伤中得到广泛应用.本文介绍了应用永久磁铁、电磁铁所形成的几种外加磁化场的特点,及其适用于不同检测要求的优化设计及合理使用的一般原则.     

组合无损检测技术及其在无缝钢管在线自动检验中的应用

分析了常规无损检测方法的特点及其局限性,讨论了以热轧无缝钢管为检测对象时检出各类缺陷的组合原则。在此基础上介绍一种由电磁分钢、涡流探伤、漏磁探伤及超声测量组成的钢管在线组合检测技术及其应用结果。实践证明,它能够有效地在钢管生产流水线上起到质量把关的作用     

无损检测技术在日本冶金工业中的应用（上）

介绍日本的无损检测技术现况、发展及应用概况,并着重讨论日钢等日本冶金企业中使用的各种无损检测及其自动化实时检测技术。     

金属基复合材料的无损检测

对可用于某些金属基复合我损检测的一些主要方法进行介绍和评价,分析了它们的特点和适用性,所涉及的方法有：超声波反射法,速度法,衰减法,软Ｘ射线法,工业ＣＴ法,声学振动法和声发射检测法。     

Exploring the Bidding Situation for Economically Most Advantageous Tender Projects Using a Bidding Game

Most open tendering procedures in the real world are highly complex, uncertain, and costly. With an increasing emphasis on the quality and value of procurement, economically most advantageous tender (EMAT) has been widely adopted as an alternative contract-awarding criteria, which has changed competitive strategies in the construction industry. A conceptual model of competitive bidding in EMAT is first established to reflect the credibility of the bidding situation. A bidding game for EMAT projects is performed by 24 participants to partially test the conceptual model. The result reveals that the game has the potential to reveal important factors in the bidding situation, simulate competitive bidding behaviors, and explore competitive advantages in the EMAT bidding process. The learning effect from the game should be useful for contractors who are preparing to deliver optimal tenders in EMAT projects.     

Damage Localization and Finite-Element Model Updating Using Multiresponse NDT Data

New techniques for both finite-element model updating and damage localization are presented using multiresponse nondestructive test (NDT) data. A new protocol for combining multiple parameter estimation algorithms for model updating is presented along with an illustrative example. This approach allows for the simultaneous use of both static and modal NDT data to perform model updating at the element level. A new damage index based on multiresponse NDT data is presented for damage localization of structures. This index is based on static and modal strain energy changes in a structure as a result of damage. This method depicts changes in physical properties of each structural element compared to its initial state using NDT data. Deficient or potentially damaged structural elements are then selected as the unknown parameters to be updated by parameter estimation. Error function normalization, error function stacking, and multiresponse parameter estimation methods are proposed for using multiple data types for simultaneous stiffness and mass parameter estimation. Also, multiple sets of measurements with various sizes and missing data points can be utilized. This paper uses a laboratory grid model of a bridge deck built at the University of Cincinnati Infrastructure Institute and the corresponding NDT data for validation of the above damage localization and model updating methods. Multiresponse parameter estimation has been utilized to update the stiffness of bearing pads, and both the stiffness and mass of the connections, using static and dynamic NDT data. The static and modal responses of the updated grid model presented a closer match with the NDT data than the responses from the initial model.     

The Neurocognitive Driving Test: Applying Technology to the Assessment of Driving Ability Following Brain Injury.

Objective: To compare the Neurocognitive Driving Test (NDT) with an established driving assessment method. Study Design: A prospective matched-control study. Participants: Fifteen adult volunteers with acquired brain injury (ABI), aged 21-59 years, referred for a driving evaluation and 15 healthy control (HC) participants. Methods: Individuals with ABI were administered the NDT and a traditional hospital-based driving evaluation. An overall performance score was calculated and used to rank order driving ability. HCs were administered the NDT to establish NDT performance range. Main Outcome Measures: Overall performance on the NDT; overall performance on a comprehensive hospital-based evaluation. Results: Comparison of the rank orders of driving ability for participants with ABI revealed a significant Spearman correlation. NDT scores discriminated between individuals with ABI who passed the driving evaluation and those who failed. Conclusions: Results help establish the potential utility of the NDT for evaluating driving ability in persons with ABI. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Role of Learning Algorithm in Neural Network-Based Backcalculation of Flexible Pavements

Nondestructive testing (NDT) methods are widely used for the performance evaluation of flexible pavements. Falling weight deflectometer (FWD), which measures time-domain deflections resulting from applied impulse loads, is the most popular technique among all NDT methods. The evaluation of the FWD data requires the inversion of mechanical pavement properties using a backcalculation tool that includes both a forward pavement response model and an optimization algorithm. Neural networks (NNs) have also emerged as alternative tools that can be employed for pavement backcalculation problems relative to their real-time processing abilities. However, there have been no comprehensive analyses in previous studies that focus on the learning algorithm and the architecture of a NN model, which considerably affect backcalculation results. In this study, 284 different NN models were developed using synthetic training and testing databases obtained by layered elastic theory. Results indicated that both the learning algorithm and network architecture play important roles in the performance of the NN based backcalculation process.     

热处理工艺对超高强度海洋平台用钢板E690组织和NDT性能的影响

研究了不同热处理工艺对超高强度海洋平台用钢F690组织及NDT性能的影响.结果表明,Q-P-T工艺得到的组织为板条贝氏体＋粒状贝氏体＋残余奥氏体,其NDT温度为-55℃;Q-T工艺得到的组织为板条贝氏体＋粒状贝氏体,其NDT温度为-40℃.Q-P-T工艺得到的残余奥氏体软相及取向混乱的贝氏体板条束能有效阻碍裂纹的扩展,NDT性能得到提高.     

钢丝绳无损检测技术的应用与开发

简述钢丝绳无损检测的意义,并简介ＬＭＡ型钢丝绳无损检测系统的原理与特点。提出其现场应用解决方案：（１）传感器的现场安装方法;（２）钢丝绳劣化断定准的确定;（３）钢丝绳数据管理。该技术在宝钢的应用实例表明：利用ＬＭＡ型钢丝绳无损检测系统对在役钢丝绳进行无损检测,可以保证钢丝绳丝运行的安全及可靠性。