摘要
针对大型钢管裂纹与孔洞的局部损伤缺陷,采用非晶态合金多传感器阵列获取钢管在空间与时间上的多源缺陷信息.通过实验提取了反映钢管缺陷的特征信号,建立缺陷状态数学模型,形成了多传感器信息融合所需的先验知识.基于多传感器信息融合原理,构建了适合于钢管损伤的多传感器信息融合模型,研究了模型在不同层次上的信息融合特点,提高了对钢管局部损伤状态定量识别与评估的准确性和可靠性.
For the local damage of cracks and holes in large steel pipes,multi-source defect information in space and time for cracks and holes damage was obtained by multi-sensor arrays.Through experiments,characteristic signals that reflected steel pipe defects were extracted and the mathematical models of the defect state were established,resulting in the formation of the prior knowledge required by multi-sensor information fusion.Based on the theory of multi-sensor information fusion,the multi-sensor information fusion model for pipe damage was constructed.The features of information fusion on different levels were studied,which improved the accuracy and reliability in the quantitative identification and evaluation of local damage state of steel pipe.
出处
《集美大学学报（自然科学版）》
CAS
2011年第2期123-127,共5页
Journal of Jimei University：Natural Science
基金
福建省自然科学基金资助项目(2008J04007)
福建省青年创新基金资助项目(2008F3078)
关键词
钢管
局部损伤
多传感器检测
特征信号
信息融合模型
steel pipe
local damage
multi-sensor detection
characteristic signal
information fusion model
