摘要
通过研究钢轨轨底角和轨距角缺陷的频率敏感性,探讨了低频声波应用于钢轨缺陷检测的可能性。Ansys-LSDYNA软件用于数值研究,建立了2m长的钢轨模型,缺陷通过删除相应位置的单元模拟,瞬态动力学分析用于求解钢轨动态响应。数值研究表明,对于竖向的激励信号,竖直方向响应在绝对值上高于横向响应,但横向动态响应对损伤的频率敏感性明显高于竖向动态响应;利用小波包分解技术比较了对损伤敏感的频率范围,基于特定频率下的小波包分解能量定义了敏感损伤指标,结果表明该损伤指标随损伤程度的增加单调递增,可作为识别钢轨缺陷的损伤指标使用。该方法采用在钢轨踏面激发和接收信号,具有方便操作的优点。
In this paper,the possibility of low frequency acoustic wave applying to the detection of rail defects was discussed by studying the frequency sensitivity of the rail bottom and gauge angle defects. Ansys-LSDYNA was used to simulate the propagation of acoustic wave in a 2 m long rail model. The defect was simulated by deleting the corresponding element. Both vertical and transverse response was recorded at the surface of rail head. The wavelet packet decomposition technique was used to find out the frequency range which is very sensitive to the damage. A damage index was defined according to the wavelet packet energy at the frequency range,and it was increased monotonically with the increase of the damage extent. The numerical results showed the feasibility and availability of the presented method.
作者
赵彦舜
张伟伟
张柱
ZHAO Yan-shun;ZHANG Wei-wei;ZHANG Zhu(School of Applied Science,Taiyuan University of Science and Technology,Taiyuan 030024,China)
出处
《太原科技大学学报》
2018年第4期325-329,共5页
Journal of Taiyuan University of Science and Technology
基金
山西省青年科学基金(2015021021)
关键词
钢轨
缺陷
小波包分解
损伤识别
rail
the defect
wavelet packet decomposition
damage identification
