Eliminating Shaking Noise for Defect Detection of Steel Wire Ropes Based on Magnetic Flux Leakage Signals

Ren, Liyuan; Liu, Zhiliang; Wang, Haoran; Zhou, Jianguo; Tang, Haihan

doi:10.1109/iaeac47372.2019.8997698

Cited by 4 publications

(3 citation statements)

References 5 publications

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“…Therefore, many nondestructive testing methods [6,7] have appeared in wire rope defect inspection, for instance, the widely used magnetic flux leakage testing method [8], metal magnetic memory, [9] and ultrasonic guided wave detection method [10]. The defect is tinny in most cases, while the detection signals are very weak and mixed with strand signals as a result of the spiral wire rope structures and environmental noises [11,12], which makes the wire rope defect identification and signal processing full of difficulty and challenges.…”

Section: Introductionmentioning

confidence: 99%

Weak Signal Processing Methods Based on Improved HHT and Filtering Techniques for Steel Wire Rope

Liu

Sun

et al. 2022

Applied Sciences

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As one of the most important processes in steel wire rope inspection, defect signal processing is of great significance in guaranteeing safety and precision measurement. Aiming at the weak signal detection of steel wire rope with mixed strands and noise, a combined signal processing method based on magnetic flux leakage testing and multi-step filtering techniques are proposed in this paper. The experiments are first introduced and performed on three typical types of steel wire rope with diameters of 28 mm, 32 mm, 45 mm, and different wire broken defects detected under liftoff distances of 13 mm and 20 mm; the acquired signals are then analyzed both in time and frequency domain. According to the weak signal characterizations, the principle of the proposed methods and algorithm are given concretely. Afterwards, comparison of signal processing results between the traditional lowpass filtering, wavelet denoising, median filtering, and the proposed method are presented. Finally, the influence factors of smoothing types and moving average span of the proposed methods are investigated. The processing results of the proposed methods are shown through short-time Fourier transform and signal-to-noise ratio analysis, which not only demonstrates the validity and feasibility of the combined methods with the highest signal to noise ratio of 90.37 dB, but also exhibits a great potential of precision defect detection and practical application in steel wire rope inspection.

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Section: Introductionmentioning

confidence: 99%

Weak Signal Processing Methods Based on Improved HHT and Filtering Techniques for Steel Wire Rope

Liu

Sun

et al. 2022

Applied Sciences

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“…Therefore, Zhou [2] studied the spatial information of shaking noise and proposed an improved median filter to remove it. Ren [3] analysed the causes and features of shaking noise, and proposed the targeted algorithms to eliminate it.…”

Section: Introductionmentioning

confidence: 99%

“…A series of methods [2][3][4] above have emerged to try to eliminate the above problems, which perform a targeted treatment by analysing the impact of change in lift-off distance. However, they are all to some extent to alleviate or mitigate the problem, and a complete solution requires obtaining the instantaneous lift-off value of the detection process.…”

Section: Introductionmentioning

confidence: 99%

Instantaneous lift-off distance estimation in magnetic flux leakage testing of steel wire ropes

Zhou

Ren

Liu

2022

J. Phys.: Conf. Ser.

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Steel wire rope (SWR) defects plagued its application in many important fields, such as cranes, ports, etc. However, the accuracy of SWRs’ local flaws detection based on magnetic flux leakage (MFL) method is susceptible to the lift-off distance. This paper proposes an instantaneous lift-off distance estimation method to study the effect of lift-off distance on MFL detection for SWR. We firstly derive the relation between the lift-off distance and the MFL field strength based on the magnetic dipole model. After obtaining the time-frequency representation of the MFL signal by using multi-synchrosqueezing transform, we extract the instantaneous amplitude (IA) of the strand signal without other noise interference. Finally, the nonlinear least-squares method is used to fit the relation between the IAs of the strand signals and the lift-off distances to achieve the estimation of the instantaneous lift-off distance. A SWR with three local flaws is tested to validate the proposed method. This work provides instantaneous monitoring of lift-off distances, and it can be used in future noise suppressing methods development or quantitative analysis of local flaws.

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Comparison and analysis of multiple signal processing methods in steel wire rope defect detection by hall sensor

2021

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Eliminating Shaking Noise for Defect Detection of Steel Wire Ropes Based on Magnetic Flux Leakage Signals

Cited by 4 publications

References 5 publications

Weak Signal Processing Methods Based on Improved HHT and Filtering Techniques for Steel Wire Rope

Weak Signal Processing Methods Based on Improved HHT and Filtering Techniques for Steel Wire Rope

Instantaneous lift-off distance estimation in magnetic flux leakage testing of steel wire ropes

Comparison and analysis of multiple signal processing methods in steel wire rope defect detection by hall sensor

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