钢丝绳定量检测系统的研制

介绍了钢丝绳损伤定量检测系统的组成及检测原理，对损伤检测信号处理电路及随机瞬态信号的捕捉方法进行了探讨，实现了对钢丝绳损伤的在线、实时、无损定量检测。     

钢丝绳定量检测系统的研制

介绍了钢丝绳损伤定量检测系统的组成及检测原理，对损伤检测信号处理电路及随机瞬态信号的捕捉方法进行了探讨，实现了对钢丝绳损伤的在线、实时、无损定量检测。     

基于GMR磁传感器的钢丝绳励磁结构设计

为实现钢丝绳无损检测设备对钢丝绳局部缺陷（LF）和截面损失（LMA）的检测,在基于GMR传感器的基础上设计钢丝绳励磁装置。通过高灵敏度GMR传感器的多层排布方式来减小漏磁信号中的干扰。对励磁方式提出永磁励磁法与直流励磁法相结合的复合励磁法,可很好地调整励磁强度,同时分析了励磁装置中各参数对励磁性能的影响,给出信号检测电路,总体设计可满足钢丝绳无损检测设备对LF和LMA的检测要求。     

钢丝绳在线不间断检测报警系统研究

钢丝绳的安全使用关系到企业财产和人民生命安全,针对钢丝绳在线不间断检测和对断丝进行实时报警的问题,采用虚拟仪器的方法,设计了钢丝绳在线不间断检测报警系统;系统传感器采用了磁性无损检测的方法,对钢丝绳进行无损探伤检测,检测系统能够在线地进行人工监控和自动监控,对断丝做出报警,其中,自动监控能够进行在线不间断检测;另外,系统能够进行局部损伤和金属截面积损耗的定量评估,并产生相应的报告;实验证明,该系统检测准确,操作方便,适合工况需求。     

矿井提升机钢丝绳在线无损检测系统的设计及应用

介绍了钢丝绳弱磁检测原理,阐述了矿井提升机钢丝绳在线无损检测系统的构成及工作原理。应用结果表明,该系统能够精确地检测出矿井提升机钢丝绳的内、外断丝及损伤状况,检测效率高,且有效节约了用绳成本,大大降低了检测能耗。     

基于X射线的钢丝绳芯无损探伤系统研究

设计了一种基于X射线的钢丝绳芯无损探伤系统。该系统利用X射线的良好穿透性检测钢丝绳芯输送带中的钢丝绳缺陷,采用光纤将现场采集的图像信息传输到远程上位机中进行分析处理,实现了钢丝绳芯缺陷图像的在线智能识别和分析等功能。原理样机测试结果表明,该系统能够检测出切断、凿穿、接头抽动、撕裂等钢丝绳缺陷,在保证X射线安全工作的前提下,提高了检测效率和准确性。     

基于ARM-Linux的钢丝绳损伤检测系统设计

针对现有钢丝绳检测系统实时性与适应性差、自动化程度低的问题,提出了一种基于ARM-Linux的高性能钢丝绳损伤检测系统的设计方案,详细介绍了该系统的硬件组成、工作原理、软件实现方法及实时采样曲线绘制的设计与实现。该系统结合嵌入式Linux技术和漏磁无损检测技术,可独立完成检测任务,实时显示检测波形,提高了检测效率。     

电梯钢丝绳漏磁检测及断丝信号采集系统设计

作为电梯系统的重要组成部分,钢丝绳的主要作用是牵引轿厢,由于钢丝绳的工作环境复杂且工作强度大,很容易出现锈蚀、磨损,若不及时处理可能引发安全事故。为保障电梯运行安全,相关工作人员需要定期检测钢丝绳,但常用的检测方式检测精度不高、检测设备体积过大。因此,相关工作人员尝试利用漏磁检测法对电梯钢丝绳进行无损检测,并基于该技术设计一整套钢丝绳断丝信号采集系统。     

基于USB接口的钢丝绳无损检测数据采集系统设计

针对钢丝绳无损检测数据采集系统设计了一种基于USB的数据通讯接口,该接口使用了Philips公司的ISP1362技术,在S3CA4BOX处理器的管理和USB1．1协议框架下,实现了数据采集系统与PC机之间的高速可靠通讯,试验结果表明该系统满足无损检测系统的快速性和实时性要求,适于便携式采集。     

基于无线射频传输的钢丝绳无损检测系统设计

针对复杂环境下钢丝绳无损检测的要求,设计和建立了一种基于无线射频传输的分布式检测系统。首先,各数据采集节点将钢丝绳的漏磁信号通过无线射频方式传送到数据接收节点;然后,由数据接收节点将信号通过串口传送给主机;最后,由主机对各点采集的信号进行集中处理。实验结果表明:系统能准确地检测到钢丝绳附近的漏磁信号。     

面向对象的无损检测工艺设计专家系统

无损检测工艺确定在压力容器制造中占有重要地位,基于面向对象技术建立X射线、超声波、磁粉、渗透等检测技术的综合无损检测工艺专家系统,系统由主控模块、规范设计模块、监测管理模块以及知识库等组成。开发结果表明,采用面向对象技术不仅保证了系统运行的有效性,同时也显著提高了系统开发效率和系统可维护性和扩充性。     

机敏混凝土ERT实验系统设计

机敏混凝土电阻率层析成像(ERT,electrical resistance tomography)是新近发展起来的一种可视性无损检测技术.为了对其深入研究,设计并实现了一个机敏混凝土ERT实验系统.系统的各功能模块都采用参数化设计技术,能够进行不同试件、不同电极数下ERT成像研究.实现了多种ERT成像算法,各算法参数和成像显示参数也可直接修改.介绍了该系统的主要功能及其实现方法,给出了部分ERT实验图.     

Case-based reasoning for interpretation of data from non-destructive testing

Non-destructive testing (NDT) is a name for a range of methods and procedures used to determine fitness of industrial products for further use. The use of NDT testing techniques results in data in the form of signals, images, or sequences of these, which have to be analysed in order to determine if they contain any indications of defects in the inspected objects. This analysis is often quite complex. In the past, systems have been built which used neural networks (and other statistical classifiers) as well as expert systems to interpret NDT data; however, successful uses of these systems in inspection practice are rare. This article presents how the case-based reasoning methodology (where interpretation of new data is based on previous data-interpretation cases) can be used to tackle the problem of NDT data interpretation. The article presents the characteristics of CBR, which make it an interesting alternative to statistical classifiers and to expert systems. Suitability of CBR for NDT data interpretation is illustrated based on examples of two applications: a CBR system for ultrasonic rail inspection and a CBR system for eddy-current inspection of heat exchangers.     

变精度邻域等价粒的邻域决策树构造算法

针对现有决策树算法对连续性数据分类的信息丢失、效果不佳等缺点,提出一种邻域决策树(NDT)构造算法.首先,挖掘了邻域决策信息系统上的变精度邻域等价粒,并探讨了相关性质;然后基于变精度邻域等价粒构建邻域基尼指数度量,以度量邻域决策信息系统的不确定性;最后,用邻域基尼指数度量诱导出树节点的选取条件,并以变精度邻域等价粒为树...     

基于AT89S51单片机的PWM专用信号发生器的设计

介绍一种脉冲涡流无损检测系统所使用的多波形专用PWM信号发生器的设计。该信号发生器以单片机为核心控制单元,通过对外围芯片的控制来实现对输出波形的频率、电压幅值、占空比的连续调节,并能对运行信号参数进行实时显示。经实验验证,该信号发生器便于观察和调节,完全满足脉冲涡流检测系统所需激励信号的要求。     

SOPC技术在钢材检测上的应用

片上可编程系统（SOPC,System On Programmable Chip）是一种新的系统设计方法,它不仅提高系统内部的集成度,提升了抗干扰能力;还具有很大的灵活性。利用SOPC技术的特点,本文介绍了一种制造钢材无损检测设备的方案。     

无损检测中基于模糊逻辑的多传感器数据融合

模糊逻辑在多传感器数据融合中得到广泛的应用，但是基于模糊逻辑的多传感器数据融合在无损检测中的应用还是一个崭新的课题，本文给出了一种新的用于无损检测数据融合的模糊逻辑结构，并且给出了隶度函数以及运算符的定义，最后给出了例子阐明了这种结构在无损检测中的应用。     

Coverage path planning for eddy current inspection on complex aeronautical parts

Non-destructive testing (NDT) plays a critical role in controlling the structural integrity (therefore the quality) of aeronautical parts, during fabrication as well as during maintenance. Eddy current (EC) testing is one of the most used NDT techniques in the aerospace industry. However, EC testing is still mainly performed by human operators and reliability as well as repeatability is not always guaranteed. To solve these issues, automating this NDT technique with a robotic system is investigated. In this paper, an EC probe equipped with a passive compliant system is assumed to be attached to the end-effector of a 6-DOF manipulator arm to carry on the inspection. Then, assuming that a 3D model of the inspected part is known a priori, a coverage path planning method using a zigzag (or rastering) pattern adapted to EC testing on aeronautical structures with a complex geometry is proposed. To reach this objective, the approach adopted in this work is to adapt existing coverage path planning techniques based on a “divide-and-conquer” strategy used for spraying applications to EC inspection. More precisely, three successive segmentations are applied to the surface to be inspected so that consistent rastering paths can be generated. Simulation results are shown for a complex part of an aeronautical structure to demonstrate the efficiency of the proposed method.     

Data mining corrosion from eddy current non-destructive tests

Quicker, more effective methods of corrosion prediction and classification can help to ensure a safe and operational transportation system for both civilian and military sectors. This is especially critical now as transportation providers attempt to meet the increased expense of repairing aging aircraft with smaller budgets. These budget constraints make it imperative to find corrosion and to correctly determine the appropriate time to replace corroded parts. If the part is replaced too soon, the result is wasted resources. However, if the part is not replaced soon enough, it could cause a catastrophic accident. The discovery of models that limit the possibility of a costly accident while optimizing resource utilization would allow transportation providers to efficiently focus their maintenance efforts. While our concern in this study was with aircraft, the results will also be useful to other transportation providers. This paper describes the discovery and comparison of empirical models to predict corrosion damage from non-destructive test (NDT) data. The NDT data were derived from eddy current (EC) scans of the United States Air Force's (USAF) KC-135 aircraft. While we might suspect a link between NDT results and corrosion, up until now this link has not been formally established. Instead, the NDT data have been converted into false color images that are analyzed visually by maintenance operators. The models we discovered are quite complex and suggest that with the appropriate data mining approaches we can sometimes more effectively handle noisy data through more complex models rather than simpler ones. Our results also show that while a variety of modeling techniques can predict corrosion with reasonable accuracy, regression trees are particularly effective in modeling the complex relationships between the EC measurements and the actual amount of corrosion.