The study of a novel ultrasonic A-scan signal processing method based on fractal theory

Zhu, Ye; Wei, Shicheng; Dong, Yusen; Liang, Yi; Wang, Yujiang

doi:10.1142/s0217984917400279

Cited by 3 publications

(1 citation statement)

References 3 publications

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“…8. The technical requirements to be realized can be summarized as follows: (1) the bonding quality Algorithms regarding the fractal theory is mentioned in previous work [15].…”

Section: Ut and Signal Processingmentioning

confidence: 99%

Ultrasonic testing system design for defect visualization of inhomogeneous multi-layered pipes

Zhu¹,

Liang²,

Wei³

et al. 2019

SN Appl. Sci.

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One of the major concerns of pipe equipment used for oil, gas and nuclear power generation, is their failure due to corrosion and abrasion of their inner walls. However, current methods have some problems detecting the inner wall of long and deep pipes, which has become an urgent safety problem. In this paper, we have designed and tested a suitable scanning and imaging method that offers high quality imaging, high efficiency and low cost. We applied the technique on remanufactured ceramic-lined steel composite pipe parts using a 4-module visualization nondestructive testing device. Digital signal and imaging algorithms were employed to superimpose multi-interface images to reconstruct 3D models of tested pipes with defects. Our findings suggest that ultrasonic scanning technique is feasible to analyze inner wall damages. The newly-designed hardware and software system shows efficiency and effectivity in the testing experiments on specimens with artificial markers and defects.

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“…8. The technical requirements to be realized can be summarized as follows: (1) the bonding quality Algorithms regarding the fractal theory is mentioned in previous work [15].…”

Section: Ut and Signal Processingmentioning

confidence: 99%

Ultrasonic testing system design for defect visualization of inhomogeneous multi-layered pipes

Zhu¹,

Liang²,

Wei³

et al. 2019

SN Appl. Sci.

Self Cite

View full text Add to dashboard Cite

show abstract

Research on ultrasonic defect imaging based on a neural network with Gaussian weight function fusion model

Lu,

Yao,

et al. 2024

Construction and Building Materials

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A quantitative detection method for stress corrosion cracks in turbine discs using a BPSO-RBFNN model

Yang

Jia

Meng

2018

Meas. Sci. Technol.

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Stress corrosion cracks are a huge potential security problem for steam turbine discs, and the quantitative detection of the initial cracks is significant for estimating the safety factor and the service life of the turbine discs. In this paper, the initial corrosion cracks are detected using the ultrasonic phased array, and a binary particle swarm optimization-radial basis function neural network (BPSO-RBFNN) model is proposed for the quantitative evaluation of small cracks in the early corrosion stage. The echoes reflected from the small cracks with different depths and orientation are acquired using the ultrasonic phased array. From these echo signals, some related features in the time domain, frequency domain and about nonlinearity are extracted. A quantitative analysis model based on the BPSO algorithm and the RBFNN is investigated for the feature optimization and the quantitative evaluation of the crack depth and orientation. The results showed that this method was effective in this quantitative evaluation work.

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The study of a novel ultrasonic A-scan signal processing method based on fractal theory

Cited by 3 publications

References 3 publications

Ultrasonic testing system design for defect visualization of inhomogeneous multi-layered pipes

Ultrasonic testing system design for defect visualization of inhomogeneous multi-layered pipes

Research on ultrasonic defect imaging based on a neural network with Gaussian weight function fusion model

A quantitative detection method for stress corrosion cracks in turbine discs using a BPSO-RBFNN model

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