Combining Diagnosis of the Casing and Tooljoint Wear in Mud Fluid While Drilling

A ground monitoring system was developed to diagnose casing and tooljoint wear in a well during drilling by combining the analysis of wear debris with detection of the tooljoints. The result shows that the wear debris concentration in the circulating drilling mud in a well reflects the total wear rate of the triboelements in the well, while the wear detection of a tooljoint can indicate its wear loss between two contiguous times of drill-pipe lifting. A diagnosis method that integrates the two types of information was developed to identify severe wear regions in well casing. Theoretical analyses and field test show that the severe casing wear region can be located relatively accurately by the integrated method. This method presents a new ground casing wear diagnosis approach with good real-time results.     

Wear Debris Identification Using Feature Extraction and Neural Network

IntroductionDuringtheoperationofmachinery ,weardebrisareproducedasaresultofcontactbetweenmovingsurfaces.Thecharacteristicsofweardebris (whichincludeshape ,size,concentration ,surface ,color ,etc .) provideimportantinformationabouttheconditionofmachinery ,in particularthestateofwear .However,thecurrenttechniquesforweardebrisanalysisareusuallytime consumingandcostlyduetotherequirementofanalyst sexpertiseto perform particleinspection ,morphologycharacterizationanddatainterpretation .Thus ,manytec…     

磨粒图像的纹理分析及识别

以磨粒显微图像分析为应用背景，引入方向测度对磨粒图像表面纹理特征进行描述．该方法对磨粒图像各方向的灰度变化规律进行统计分析，提取了8个纹理特征．然后以提取的纹理特征为输入矢量，利用径向基函数神经网络对磨粒纹理进行分类识别．应用实例表明，方向测度综合反映了磨粒纹理的方向性和粗糙性，可用于磨粒纹理特征的描述；所建立的基于神经网络的磨粒纹理分类模型学习速度快，识别率较高．     

基于磨粒显微形态分析的发动机磨损状态监测与故障诊断技术

主要介绍基于形态学方法的磨粒显微分析与综合识别技术,及其在发动机磨损状态监测与故障诊断中的应用．首先应用形态学方法建立了．一套磨粒显微特征描述体系,以提取磨粒特征信息并进行磨粒识别;基于磨粒识别分析的结果,并结合摩擦学理论,实现对发动机磨损状态检测与故障诊断。     

Debris Flow Monitoring System and Observed Event in Taiwan： A Case Study at Aiyuzi River

Since 2002,the Soil and Water Conservation Bureau,which is responsible for the conservation and administrative man-agement of hillside in Taiwan,has been cooperating with Feng Chia University. Together,they have successfully carried out the establishment and maintenance of 13 fixed debris flow monitoring stations over the island and 2 mobile debris flow monitoring sta-tions. During July 2004,a powerful southwest air current brought by Mindulle Typhoon caused serious flood in central and southern Taiwan. This paper aims to describe the establishment of debris flow monitoring systems in Taiwan and the observation of the debris flow event during Mindulle Typhoon at Aiyuzi River in Shenmu Village,Nantou County by the monitoring station.     

支持向量机在刀具磨损多状态监测中的应用

基于多传感器信号、采用多分类支持向量机(support-vector-machine,SVM)实现了刀具监测的多状态辨识.通过对切削过程中的多向切削力和振动信号等多传感器信息进行分析,分别获得时域、频域和小波域的信息作为磨损分类特征;同时,运用基于一对多(one-versus-all,OVA)的多分类支持向量机对刀具不同磨损状态下的特征数据样本进行训练和识别.对切削过程中不同磨损状态的分类结果表明,多分类支持向量机具有出色的学习能力,能够实现在小样本情况下的不同磨损阶段分类,并具有较高的识别精度.     

介质对摩擦副材料磨损性能的影响

通过对两种材料在机械密封常用介质:清水、碱和盐中磨损特性的研究,揭示出介质对材料磨损性能的影响,不同的介质导致不同的磨损类型。     

磨损率方程的比较研究(英)

本文通过具有不同显微组织的1080钢在干滑动条件下的磨损实验，比较和讨论了3种常用的磨损方程．结果表明，磨损系数（K）方程可能得出与磨损体积变化不同或错误的计算结果．其原因在于Archard模型中引入的硬度参数不能反映磨损过程中的动态硬度变化．     

基于声发射监测的砂轮磨损实验

难加工材料的高硬度和高耐磨性使得磨削加工过程中砂轮的损耗变快,目前主要依靠经验判断砂轮的修整和更换周期,很有可能导致修整不及时的情况发生.本文用声发射信号和磨削力信号共同精确监测砂轮磨损状态,通过分析不同磨损状态的砂轮磨削时对应的声发射信号的特征参数以及磨削力和磨削力比的变化情况,综合判断了实验过程中砂轮的磨损状态.结果表明:声发射信号特征参数都与砂轮磨损状态有一定相关性,且磨削力比与砂轮磨损程度的相关性最大,证明了声发射监测技术在砂轮修整中的有效性,为实际生产加工提供了理论指导.     

摩擦配偶材料对Cr12MoV钢耐磨性能的影响

本文总结了干摩擦及低粘度润滑两种条件下的滑动磨损试验结果。当摩擦速度为0.2～1.0m/s,载荷为50～100N时,干摩擦呈现出粘着磨损机制,摩擦配偶对Cr12MOV钢的比磨损显示出显著的影响;而低粘度润滑条件下的低速磨损主要是磨粒磨损机制,摩擦配偶的影响甚微。     

论针织内衣的发展

阐述内衣的消费趋势，指出内衣产业将是2I世纪我国最具发展前景的服装领域之一；通过对针织内衣发展的分析，得出针织内衣会在品牌知名化．市场细分化、材料功能化及品种多元化等方面发展的结论。