Pang Caoyuan, Zhou Jianting, Zhao Ruiqiang, Ma Hu, Zhou Yi
College of Civil Engineering, Chongqing Jiaotong University, Chongqing 400074, China.
College of Materials Science and Engineering and Engineering Research Center of Bridge Structure and Material in the Mountainous Area of Ministry of Education, Chongqing Jiaotong University, Chongqing 400074, China.
Materials (Basel). 2019 Apr 10;12(7):1167. doi: 10.3390/ma12071167.
Based on the metal magnetic memory effect, this paper proposed a new non-destructive testing method for the internal tensile force detection of steel bars by analyzing the self-magnetic flux leakage (SMFL) signals. The variation of the SMFL signal of the steel bar with the tensile force indicates that the curve of the SMFL signal has a significant extreme point when the tensile force reaches about 65% of the yield tension, of which the first derivative curve has extreme points in the elastic and yielding stages, respectively. To study the variation of SMFL signal with the axial position of the steel bar under different tensile forces, a parameter reflecting the fluctuation of the SMFL signal along the steel bar is proposed. The linear relationship between this parameter and the tensile force can be used to quantitatively calculate the tensile force of steel bar. The method in this paper provides significant application prospects for the internal force detection of steel bar in the actual engineering.
基于金属磁记忆效应，通过分析自漏磁场（SMFL）信号，提出了一种用于检测钢筋内部拉力的新型无损检测方法。钢筋SMFL信号随拉力的变化表明，当拉力达到屈服拉力的65%左右时，SMFL信号曲线有一个明显的极值点，其一阶导数曲线在弹性阶段和屈服阶段分别有极值点。为研究不同拉力下SMFL信号随钢筋轴向位置的变化，提出了一个反映SMFL信号沿钢筋波动的参数。该参数与拉力之间的线性关系可用于定量计算钢筋的拉力。本文方法为实际工程中钢筋内力检测提供了重要的应用前景。
