Quantitative Detection of Local Flaw Under the Lift-Off Effect for Steel Wire Ropes

IF 4.3 2区综合性期刊 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC

IEEE Sensors Journal Pub Date : 2024-07-10 DOI:10.1109/JSEN.2024.3421650

Leilei Yang;Zhiliang Liu;Liyuan Ren;Feilong Liao;Mingjian Zuo

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Abstract

The quantitative analysis of steel wire rope (SWR) is critical for judging its remaining strength and serves as the basis for determining its retirement criteria. However, in magnetic flux leakage (MFL) detection, the lift-off change generated during the movement causes the detection signal to fluctuate, thereby interfering with the quantitative analysis of local flaws (LFs). With the help of the intrinsic characteristic of SWR structure, a quantitative LF detection method with MFL rectification based on strand signals is proposed in this article. The analytical models of LF and strand signals under ideal conditions and the lift-off effect are built. Through calculating lift-off parameters, LF signals are rectified to perform quantitative analysis. Through the case study, the detection results of 2.47 and 4.54 broken wires are 2.55 and 4.67. Compared with the diagnostic results before MFL signal rectification and different quantitative methods, the proposed method can greatly improve the accuracy and robustness of quantitative LF analysis under different lift-off scenarios.

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钢丝绳提升效应下局部缺陷的定量检测

钢丝绳 (SWR) 的定量分析对于判断其剩余强度至关重要，也是确定其报废标准的基础。然而，在漏磁通量（MFL）检测中，运动过程中产生的升降变化会导致检测信号波动，从而干扰局部缺陷（LF）的定量分析。本文借助 SWR 结构的固有特性，提出了一种基于股信号的 MFL 整流定量 LF 检测方法。本文建立了理想条件下 LF 和钢绞线信号的分析模型以及升力效应模型。通过计算升离参数，对低频信号进行整流，从而进行定量分析。通过案例研究，2.47 和 4.54 断线的检测结果分别为 2.55 和 4.67。与 MFL 信号整流前的诊断结果和不同的定量方法相比，所提出的方法可大大提高不同升限情况下 LF 定量分析的准确性和鲁棒性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

IEEE Sensors Journal 工程技术-工程：电子与电气

CiteScore

7.70

自引率

14.00%

发文量

2058

审稿时长

5.2 months

期刊介绍： The fields of interest of the IEEE Sensors Journal are the theory, design , fabrication, manufacturing and applications of devices for sensing and transducing physical, chemical and biological phenomena, with emphasis on the electronics and physics aspect of sensors and integrated sensors-actuators. IEEE Sensors Journal deals with the following: -Sensor Phenomenology, Modelling, and Evaluation -Sensor Materials, Processing, and Fabrication -Chemical and Gas Sensors -Microfluidics and Biosensors -Optical Sensors -Physical Sensors: Temperature, Mechanical, Magnetic, and others -Acoustic and Ultrasonic Sensors -Sensor Packaging -Sensor Networks -Sensor Applications -Sensor Systems: Signals, Processing, and Interfaces -Actuators and Sensor Power Systems -Sensor Signal Processing for high precision and stability (amplification, filtering, linearization, modulation/demodulation) and under harsh conditions (EMC, radiation, humidity, temperature); energy consumption/harvesting -Sensor Data Processing (soft computing with sensor data, e.g., pattern recognition, machine learning, evolutionary computation; sensor data fusion, processing of wave e.g., electromagnetic and acoustic; and non-wave, e.g., chemical, gravity, particle, thermal, radiative and non-radiative sensor data, detection, estimation and classification based on sensor data) -Sensors in Industrial Practice

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