数字图像应用于疲劳监测的测量参数研究

张玉玲; 谢爱华; 杨云涛; 高占军; 张楠; 张贤卿; 董佳霖

doi:10.13206/j.gjgS22012901

数字图像应用于疲劳监测的测量参数研究

doi: 10.13206/j.gjgS22012901

张玉玲^1,2,3,4,
谢爱华⁵,
杨云涛^3,4,
高占军⁵,
张楠⁴,
张贤卿²,
董佳霖²

1. 中国铁道科学研究院集团有限公司, 北京 100081;
2. 浙江数智交院科技股份有限公司, 杭州 310030;
3. 浙江树人大学, 杭州 310015;
4. 北京交通大学, 北京 100044;
5. 中铁第五勘察设计院集团有限公司, 北京 102600

基金项目:

浙江省交通运输厅科技计划项目(2020001)。

详细信息

作者简介:
张玉玲,女,1957年出生,研究员。Email:zyl@rails.cn

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出版历程
- 收稿日期: 2022-01-29
- 网络出版日期: 2022-09-02

Test Research on Measurement Parameters of Digital Image Applied to Fatigue Monitoring

1. China Academy of Railway Sciences Co., Ltd., Beijing 100081, China;
2. Zhejiang Shuzhi Jiaoyuan Technology Co., Ltd., Hangzhou 310030, China;
3. Zhejiang Shuren University, Hangzhou 310015, China;
4. Beijing Jiaotong University, Beijing 100044, China;
5. China Railway Fifth Survey and Design Institute Group Co., Ltd., Beijing 102600, China

摘要

摘要:
钢构件的疲劳监测是钢结构健康监测系统的重要组成部分,而在近年图像采集和数据远程传输技术迅速发展的大环境下,将非接触式数字图像测量和识别技术应用于疲劳监测的研究和进展,受到各方专业人士的关注。为实现通过对数字图像中某种参数变化的识别,在出现可辨识的裂纹之前监测到疲劳异常的目标,设计并加工了Q345qD试件进行疲劳试验。试验过程中采用ARAMIS非接触式三维光学测量系统对观测区域进行动态连续拍照,获得疲劳全过程图像,并将图像在测量系统内部转换为数字作为检测量。对比分析疲劳全过程图像所能够获取的力学指标和获取方法,研究数字图像应变及位移参数的形态和应用可行性;对比静载试验中电测应变片与图像应变测量结果,确定非接触式数字图像测量是否满足应用精度要求;研究试件疲劳过程的应变和位移变化规律,对图像的各种数据进行疲劳过程敏感性分析,研究最优参数指标,确定特征点数据提取方案;验证数字图像技术应用于疲劳监测的可行性和实施方案,兼顾客观性和自动化。
研究表明:通过ARAMIS三维数字图像测量系统能够非接触动态采集测量表面的图像数据,所获取其中任意点的三维应变值和位移值满足精度要求;采用提取截面线均值方法能够有效获取钢构件截面名义应变;通过ARAMIS三维数字图像测量系统能够动态采集测量表面的应变图像数据,获取其中任意点的三维应变值和位移值,由位移指标得到的疲劳异常信息相对较晚,不适合作为疲劳监测的测量参数;确定采用数字图像的应变参数进行疲劳监测具有可行性,提出可在应变等值云图上截取最大应变特征值作为疲劳监测数值系列。所得到的测量数据客观有效、实施性强,是数字图像应用于疲劳监测的最优测量参数。
- 黑白散斑 /
- 应变 /
- 疲劳试验 /
- ARAMIS光学测量系统
Abstract:
Fatigue monitoring of steel structure is an important part of steel structure health monitoring system.In recent years,under the rapid development of image acquisition and data remote transmission technology,the application of non-contact digital image measurement technology in fatigue monitoring has attracted the attention.In order to achieve the goal of detecting the fatigue anomaly by means of the identification of certain parameter changes in the digital image before the appearance of identifiable cracks,Q345qD steel specimens were designed and processed for fatigue test.During the test,the ARAMIS optical measurement system was used to take pictures of the observation area dynamically and continuously to obtain the whole fatigue process image,and the image was converted into data inside the measurement system as the measured value.By comparing and analyzing the mechanical indexes and collection methods during the whole fatigue process,the shape and application feasibility of the strain and displacement parameters of the digital image were studied.Comparing the results of electrical strain gauge with image strain measurement in static load test to make sure that the accuracy of digital image measurement was satisfied or not.The strain and displacement changes of the specimen during fatigue process were studied.The sensitivity analysis of various parameter of the image with fatigue process was carried out.The optimal parameter index and the way to collect them were studied.Finally,the feasibility and implementation scheme of the application of digital image technology to fatigue monitoring are verified meanwhile both of objectivity and automation were in consideration.
It was shown that the ARAMIS optical measuring techniques can collect dynamically the image data of the measured surface without contact.The obtained 3D strain values meet the accuracy requirement.The nominal strain of cross-section can be obtained by average value method of cross section line.The fatigue abnormal information obtained from the displacement parameter is relatively late,which is unacceptable for fatigue monitoring.While it is acceptable to take the strain parameter as the monitoring object of digital image.It is proposed that the maximum strain eigenvalue on the equivalent cloud image can be intercepted as a numerical series for fatigue monitoring.The obtained data are objective,effective and practical,and are the optimal measurement parameters for the application of digital image to fatigue monitoring.
- black and white speckle /
- strain /
- fatigue test /
- ARAMIS optical measuring techniques

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参考文献(15)

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