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用于多边形钻杆检测的超声导波数值研究

Numerical Study on Ultrasonic Guided Waves for the Inspection of Polygonal Drill Pipes.

作者信息

Wan Xiang, Zhang Xuhui, Fan Hongwei, Tse Peter W, Dong Ming, Ma Hongwei

机构信息

School of Mechanical Engineering, Xi'an University of Science and Technology, Xi'an 710054, China.

Shaanxi Key Laboratory of Mine Mechanical and Electrical Equipment Intelligent Monitoring, School of Mechanical Engineering, Xi'an University of Science and Technology, Xi'an 710054, China.

出版信息

Sensors (Basel). 2019 May 8;19(9):2128. doi: 10.3390/s19092128.

Abstract

The polygonal drill pipe is one of the most critical yet weakest part in a high-torque drill machine. The inspection of a polygonal drill pipe to avoid its failure and thus to ensure safe operation of the drilling machine is of great importance. However, the current most frequently used ultrasonic inspection method is time-consuming and inefficient when dealing with a polygonal drill pipe, which is normally up to several meters. There is an urgent need to develop an efficient method to inspect polygonal drill pipes. In this paper, an ultrasonic guided wave technique is proposed to inspect polygonal drill pipes. Dispersion curves of polygonal drill pipes are firstly derived by using the semi-analytical finite element method. The ALID (absorbing layer using increasing damping) technique is applied to eliminate unwanted boundary reflections. The propagation characteristics of ultrasonic guided waves in normal, symmetrically damaged, and asymmetrically damaged polygonal drill pipes are studied. The results have shown that the ultrasonic guided wave technique is a promising and effective method for the inspection of polygonal drill pipes.

摘要

多边形钻杆是高扭矩钻机中最关键但也是最薄弱的部件之一。对多边形钻杆进行检测以避免其失效,从而确保钻机的安全运行至关重要。然而,当前最常用的超声检测方法在处理通常长达数米的多边形钻杆时既耗时又低效。迫切需要开发一种高效的方法来检测多边形钻杆。本文提出了一种超声导波技术来检测多边形钻杆。首先利用半解析有限元法推导了多边形钻杆的频散曲线。应用ALID(采用增加阻尼的吸收层)技术消除不需要的边界反射。研究了超声导波在正常、对称损伤和非对称损伤多边形钻杆中的传播特性。结果表明,超声导波技术是一种用于检测多边形钻杆的有前景且有效的方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/58ac/6539063/c30aff714b72/sensors-19-02128-g001.jpg

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