【作者】 薛海涛；

【导师】 李俊岳； 宋永伦；

【作者基本信息】 天津大学 ， 材料加工工程， 2004， 博士

【摘要】 近年来,由于对能源和环境的高度关注,铝合金被广泛用于航空航天、汽车、船舶、列车、建筑,国防等领域。在各种加工方法中,点焊由于其质量轻、成本低、效率高、易于自动化等优点已成为铝合金最主要的加工方法。然而,与钢相比铝合金具有优良的导电导热性能,这使得铝合金的点焊焊接性很差,容易出现各种焊接缺陷。目前在生产线上还没有一种可靠的无损检测手段对每一个焊点进行质量检测,而是凭借操作者的经验对焊点的质量状况进行判断。显然,这种方法是不科学的,也无法满足工业化发展对点焊质量提出的高可靠性、低成本的要求。此外,在现代化的质量管理体系中,明确规定了对生产过程中的每个部件产品质量的可记录性和可追溯性,这在传统的生产方式下是很难实现的。为了改变这种现状,有必要将信息技术引入到铝合金点焊制造过程中来,建立点焊过程质量信息检测与评定系统,在线逐检焊点质量,及时检出不合格的焊点,使操作者能够及时进行在线补救,以有效提高和稳定点焊的质量。同时将相关信息记录到数据库中,使得每一个焊点的质量情况都有据可查。本文的目的就是针对铝合金冲击波点焊制造过程,建立铝合金点焊质量信息化系统。论文的研究工作可从质量信息的获取技术、分析技术以及应用技术三个方面加以认识和实践。采用了基于智能终端的数据采集系统,采集了电极电压、焊接电流、电极位移和电极压力四个参数。智能终端可以单独完成数据的采集、模数转换以及数据的本地存储,各个智能终端通过数字处理模块实现与计算机的通信。基于智能终端的数据采集系统可以保证采集的信号具有较高的实时性、信噪比和抗干扰性。针对铝合金冲击波点焊中易于发生的喷溅、未熔合及未完全熔合缺陷,研究了缺陷发生时的各个信号特征,提出用电压信号台阶状突变、电极压力信号的躁动突变作为判读喷溅缺陷的特征信息;用位移信号的膨胀差和最大落差作为判读未熔合及未完全熔合缺陷的特征信息;用能量值作为同时判读喷溅和未熔合及未完全熔合缺陷的特征信息;研究还发现,用于判读未熔合及未完全熔合缺陷的特征信息蕴涵着熔核直径大小的丰富信息。根据特征信息建立了判读缺陷的相应判据,研究表明,所建立的判据能够反映和决定焊接质量的本质特征,能够准确反映铝合金冲击波点焊过程中常见的喷溅、未熔合及未完全熔合缺陷。根据信号上特征信息的特点,建立了基于小波变换信号奇异性检测方法的喷更多还原

【Abstract】 For heightened awareness of energy and environmental concerns, aluminum alloys are recently finding increased application in aerospace, automobile, shipping, train, construction and national defenses industries. Resistance spot welding (RSW) is a major aluminum alloys sheet joining process for its many advantages of lower cost, high production and adaptability for automation. Despite these advantages, spot-welding of aluminum alloys suffers from a major problem of tend to weld defects. This problem results from both higher conductivity for heat and higher conductivity for electric compared to steel. In the past, commonly used quality monitoring method is that depends the operator’s experience to determinate whether is a fault spot weld. The method is unscientific and not meets the need of high reliable and low cost to development of industrialization. On the other hand, it is impossible that spot weld quality information could be recordable and traceable required in the modernization quality control system for conventional method. Until recently there is still not a reliable quality monitoring method to check the quality of every spot weld on-line. In order to change the present status, it is necessary to induce the information technology into spot welding process of aluminum alloys and develop a spot welding of aluminum alloys on-line quality monitoring and assessing system. The system should be monitoring every spot weld quality and record related information so as to improve the manufacturer’s confidence level and help to reduce the cost of the welded structures. The goal of this dissertation is to develop a quality information system used in blast wave direct current resistance spot welding (BWDCRSW) of aluminum alloys. The research effort could be understand and experience from following three aspects: acquirement technology, analysis technology and application technology of spot welding of aluminum alloys quality information. The data acquisition system based intelligent terminal used in this dissertation measured four variables: tip voltage, welding current, electrode force, and displacement. The intelligent terminal could complete independently data acquisition, A/D transfer, and data local storage. Each intelligent terminal communicates with computer by digital management module. The collected signal that come from data acquisition system based intelligent terminal are real-time, high signal-to-noise ratio and anti-interference. Expulsion and incomplete fusion are major defect in the weld quality with BWDCRSW of aluminum alloys. When expulsion or incomplete fusion occurs, signal such as tip voltage, electrode force and displacement all show abrupt changes. Through the studied the feature of the abrupt changes in signals, the dissertation presents the idea of using the step abrupt change of tip voltage signal and restlessness abrupt change of electrode force signal to identify expulsion, using Expansion Differential Value (EDV) and Maximum Drop Value (MDV) of displacement to identify incomplete fusion, using energy value calculated from tip voltage and welding current to identify expulsion and incomplete fusion simultaneously. The study proved that there is abundant nugget size information in EDV, MDV and energy value. It is show experimentally that criterions built in this dissertation could recognize weld defects and reflect the essence of spot weld quality. According to the feature of abrupt changes in tip voltage and displacement signals, the dissertation presents extracted method of expulsion characteristic information based wavelet transfer singularity detection algorithm. The dissertation also presents the methods to extract the EDV and MDV from displacement signal based on range analysis and time-domain analysis. The energy value was calculated from tip voltage and welding current. So, the six dimension characteristic vector that is used to quality assessment and defect diagnosis was built according above analysis and calculation. The dissertation firstly presents a multiple spot weld defect detection algorithm developed based on a Fuzzy Support Vector Machine (FSVM) theory using tip voltage and electrode force signal. Compared to other algorithm, Support Vector Machine (SVM) is good to solve problem of small sample, nonlinear, and higher dimensional because of its advantages such as independent empirical knowledge, global optimal, and outstanding generalization capability. FSVM could ignore the effect on that isolated point and noise point in training samples influenced. Therefore, the Optimal Hyperplane (OH) trained by FSVM has largest margin so as to enhance the capability of generalization. The FSVM classifier built in this dissertation shows good diagnosis capability and higher accuracy under the relatively limited samples come from production line. The dissertation firstly presents an accurate nugget size estimation model based Artificial Neural Network (ANN). Input parameters of the model are EDV, MDV and energy value. The model was optimized from structure designing, training algorithm and performance evaluating. The test study was carried out with independent test samples. It is shows experimentally that 94.3 percent of test samples estimation error is limited in 2 mm. In view of application, the ANN estimation model has higher accuracy and could meet the need production line. This dissertation developed a quality information system used in BWDCRSW of aluminum alloys. The system could complete functions such as processing parameter collected, data transfer and storage, related information extracted, welding parameter set and preview, data and information display, weld defect diagnosis, nugget size estimation, the quality information statistic analysis, the welding process stability assessment and so on. The system developed this paper realize not only spot weld quality information could be recordable and traceable, but revolution from empirical assessment to scientific diagnosis.更多还原