基于信号响应分析模型的金属结构损伤导波检出概率

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摘要飞机结构损伤导波在线监测技术作为一种新颖的无损检测手段，为了真正实现该技术在结构运营维护过程中的视情维护，必须明确其结构损伤检出概率，以指导结构检查维修方案的制定。本文提出了一种基于信号响应分析模型的结构损伤导波检出概率计算方法，该方法通过构建在线导波监测信号的损伤指数与裂纹长度间的对应关系，得到结构损伤检出概率的统计计算模型，并分析了拟合参数的不确定性对计算模型的影响，构建了不同置信度下的导波检出概率计算模型。通过开展金属开孔和搭接结构疲劳裂纹导波监测试验，验证了该方法的有效性。试验结果表明，损伤指数类型、对应关系拟合函数和传感器监测方案均对结构损伤导波检出概率具有影响，且在95%置信度90%检出概率下金属开孔和搭接结构的可检裂纹长度分别约为2.6 mm和9.5 mm。

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	王莉1
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	杨宇2
	刘国强2
	王霞光2
	李嘉欣2
	任一鹏2

关键词 ：结构健康监测, 导波, 检出概率, 金属, 疲劳裂纹

Abstract：In order to realize the condition-based maintenance and formulate the inspection and maintenance scheme during the service, probability of detection (POD) for guided wave damage monitoring technology must be clarified, as a new nondestructive testing method. This paper presents a novel POD computation method for guided wave based on signal response analysis model. First, the statistical computation model of POD is obtained by establishing the mapping relationship between the damage features of online response guided waves and fatigue crack. Then, by analyzing the quantitative effect of uncertainties of fitting parameters on the statistical computation model, POD computation models under different confident levels are obtained. The proposed method is validated on fatigue cracks monitoring experiments on metal center-hole and lap specimens. The results show that damage features, fitting functions and transducers monitoring schemes all have effects on POD, and the detectable crack length under 95% confidence level and 90% detection probability for center-hole and lap metal structures are about 2.6 mm and 9.5 mm.

Key words： structural health monitoring guided waves probability of detection(POD) metal fatigue crack

收稿日期: 2023-02-03 出版日期: 2024-01-28

引用本文:

王莉1,2，杨宇2，刘国强2，王霞光2，李嘉欣2，任一鹏2. 基于信号响应分析模型的金属结构损伤导波检出概率[J]. 振动与冲击, 2024, 43(2): 32-41.
WANG Li1,2，YANG Yu2，LIU Guoqiang2，WANG Xiaguang2，LI Jiaxin2，REN Yipeng2. Probability of detection of cracks in metal structures using guided wave based on a signal response analysis model. JOURNAL OF VIBRATION AND SHOCK, 2024, 43(2): 32-41.

链接本文:

http://jvs.sjtu.edu.cn/CN/ 或 http://jvs.sjtu.edu.cn/CN/Y2024/V43/I2/32

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