CAJ | 학술논문

针对传统涡流检测逆向算法难以满足结构健康监测技术对实时性、在线以及算法复杂性低的要求，介绍了一种花萼状涡流阵列传感器，分析了传感器感应线圈输出信号在裂纹扩展过程中的变化特点和规律，提出了基于裂纹特征在线提取的裂纹在线定量识别算法，并通过304不锈钢和TC-4钛合金的疲劳裂纹在线监测试验对算法的有效性进行了验证。研究表明：采用滑动窗口分析方式，对窗口内数据流进行最小二乘回归和递推最小二乘回归，依据回归参数和阈值可以对裂纹特征进行有效识别，进而实现裂纹的在线定量监测。
침대전통와류검측역향산법난이만족결구건강감측기술대실시성、재선이급산법복잡성저적요구，개소료일충화악상와류진열전감기，분석료전감기감응선권수출신호재렬문확전과정중적변화특점화규률，제출료기우렬문특정재선제취적렬문재선정량식별산법，병통과304불수강화TC-4태합금적피로렬문재선감측시험대산법적유효성진행료험증。연구표명：채용활동창구분석방식，대창구내수거류진행최소이승회귀화체추최소이승회귀，의거회귀삼수화역치가이대렬문특정진행유효식별，진이실현렬문적재선정량감측。
Considering that the inverse algorithm of traditional eddy current testing can not meet the requirements of real-time, on-line, and simplification in structure health monitoring, an rosette eddy current sensor array was present,the output characteristics of the sensor while crack propagating were analyzed,and a crack quantitative i-dentification algorithm based on extraction of crack-characteristics was proposed. Then crack monitoring experiments of 304 stainless steel and TC-4 titanium alloy specimen were carried out to validate the effective of the algorithm. It was shown that the sliding window analysis mode could be employed in signal processing. The data stream within sliding window was processed by least square regression algorithm and recursive least square regression algorithm. Then the crack characteristics in data stream could be detected through regression parameters and threshold,and the crack length could be identified on-line quantitatively.