首页|基于小波包分解的钢绞线拉伸损伤评价方法研究

基于小波包分解的钢绞线拉伸损伤评价方法研究

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钢绞线长期承受载荷时容易出现磨损、锈蚀及断丝等各种损伤,对其进行损伤监测尤为重要.声发射检测技术由于动态检测的特点,在钢绞线损伤监测中具有明显优势.本文首先对钢绞线进行拉伸加载测试,对钢绞线整个损伤过程进行声发射监测,采集拉伸裂纹萌生、扩展及断裂阶段的声发射信号.然后采用小波包分解对不同损伤阶段的声发射信号进行处理,计算这些阶段的频谱特征和能量分布.最后通过对比分析不同损伤阶段声发射信号的频谱特征和能量分布图,找出不同损伤阶段的信号特征信息,实现对钢绞线损伤过程的定量评价.该方法还可以应用于其他金属材料损伤过程的定量评价.
Study on Evaluation Method of Steel Strand Tensile Damage Based on Wavelet Packet Decomposition
When steel strands are subjected to long-term loads,they are prone to various damages such as wear,corrosion,and wire breakage,and monitoring their damage is particularly important.Acoustic emission detection technology has significant advantages in steel strand damage monitoring due to its dynamic detection characteristics.This article first conducts tensile loading tests on steel strands,monitors the entire damage process of steel strands through acoustic emission,and collects acoustic emission signals during the initiation,propagation,and fracture stages of tensile cracks.Then,wavelet packet decomposition is used to process the acoustic emission signals of different damage stages,and the spectral characteristics and energy distribution maps of these stages are calculated.Finally,by comparing and analyzing the spectral characteristics and energy distribution maps of acoustic emission signals at different damage stages,the signal characteristic information of different damage stages can be identified,which can achieve a quantitative evaluation of the damage process of steel strands.This method can also be applied to the quantitative evaluation of damage processes in other metal materials.

steel strandacoustic emissionwavelet packet decompositioninjury stagequantitative evaluation

刘伟成、陈杰、汪棋、胥凯晖、沈佳卉

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江西省检验检测认证总院特种设备检验检测研究院,南昌 330052

江西衡熙工程质量检测有限公司,南昌 331700

中国人民解放军 94829部队,南昌 330201

中国电建集团江西省电力设计院有限公司,南昌 330096

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钢绞线 声发射 小波包分解 损伤阶段 定量评价

国家市场监督管理总局科技项目

2023MK071

2024

南昌航空大学学报(自然科学版)
南昌航空大学

南昌航空大学学报(自然科学版)

影响因子:0.287
ISSN:1001-4926
年,卷(期):2024.38(1)
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