基于漏磁检测的桥梁拉索断丝识别

为实现桥梁拉索漏磁(MFL)检测中低信噪比(SNR)时的断丝识别,提出了基于有效短时互相关(STCC)的损伤识别方法.对拉索进行重复测试并提取对应的信号片段进行互相关分析,通过重新归一化,在短时互相关序列中融入短时能量特征,再结合双阈值法进行断丝识别.制作了含有多种断丝损伤的足尺拉索模型进行漏磁检测试验,基于试验结果验证所提出的方法.结果表明:该方法的损伤判别精度比既有方法提高了15.7%～16.9%,在低信噪比下仍取得了较高的损伤识别精度.

Broken Wire Identification in Bridge Cables Based on Magnetic Flux Leakage Examination

A damage identification method based on effective short time cross correlation (STCC) was proposed to identify wire breakage, in the case of low signal-to-noise (SNR) ratio with the magnetic flux leakage (MFL) detection of bridge cables. The corresponding signal fragment from repeated tests of the cable was extracted for effective STCC analysis. The effective STCC was renormalized to combine with the characteristics of short-time energy. Then, the double threshold method was used to identify the broken wire damage. A full-scale cable model with various kinds of wire breakage was made for MFL examination, and the experimental results were used to verify the proposed method. The results show that the proposed method improves the damage recognition accuracy by about 15.7%~16.9% compared with the existing methods, and obtains high identification accuracy even with low SNR ratio.