Transient thermal pattern separation and detection of conductive defects in composite insulators using eddy current pulsed thermography

Tu, Yanxin; Mei, Hongwei; Liu, Lishuai; Shen, Zekai; Guo, Chenjun; Wang, Liming

doi:10.1016/j.ndteint.2022.102653

Cited by 17 publications

(3 citation statements)

References 24 publications

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“…Internal defects in materials generally cause changes in sound, light, heat, magnetism and electricity, and the NDT technology evaluates material defects by capturing real-time changes in these properties. At presently, there are various types of NDT techniques that are used for defects detection, such as pulsed eddy current testing [16][17][18], ultrasonic inspection [19][20][21][22][23], magnetic particle inspection [24,25], dye penetrant testing [26,27], and X-ray radiography [28,29]. In recent years, the rapid development of infrared thermal imagers has led to the widespread application of the infrared thermal imaging technology, and the active infrared thermography (IRT) has achieved success in many engineering practices, such as corrosion monitoring of metals and detection of internal defects in composite materials.…”

Section: Introductionmentioning

confidence: 99%

Detection of flat-bottom holes in composite materials using multi-dimensional complementary ensemble empirical mode decomposition algorithm

Zhang,

Li,

Wang

et al. 2023

J. Inst.

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Due to high-temperature resistance, high strength, and excellent fatigue resistance, composite materials are widely used in automotive manufacturing, aerospace, infrastructure and other fields. Consequently, the demand for defect detection of composite materials is also increasing. As a non-destructive testing technique, the active infrared thermography, which can achieve full-field defect detection, is suitable for defect detection of composite materials. However, this method is susceptible to noises caused by the environment and heating sources. In order to solve the problem of the defect signal being submerged by these noises, a multi-dimensional complementary ensemble empirical mode decomposition (MCEEMD) algorithm is introduced in this paper. This method can decompose the signal into the low-frequency background noise, the high-frequency heating noise, and useful defect signals, and these noises can be easily removed to improve the contrast to noise ratio (CNR) of defect images. Based on this proposed method, a defect detection experiment on the carbon fiber reinforced plastic (CFRP) is performed in this paper, and experimental results show that the method can effectively remove environmental noise and heating noise, and it can detect 11 out of 12 defects on the CFRP sample with an average CNR of 9.107. Compared with the traditional differential absolute contrast method, this method can detect one additional small defect with the aspect ratio of 1.67 and one deep defect with a depth of 2 mm.

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Section: Introductionmentioning

confidence: 99%

Detection of flat-bottom holes in composite materials using multi-dimensional complementary ensemble empirical mode decomposition algorithm

Zhang,

Li,

Wang

et al. 2023

J. Inst.

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show abstract

“…Tu et al [18] proposed a method based on ECPT combined with feature extraction transform algorithms for transient thermal pattern separation and defect detection in composite insulators with internal conductive defects. Liu et al [19] used ECPT in the characterization of RCF cracks in the rail by taking advantage of electromagnetic thermal execution. Hernandez et al [20] performed pulsed phase thermography using electromagnetic coil excitation to capture thermal transient localized responses for defect characterization.…”

Section: Introductionmentioning

confidence: 99%

Theoretical and Numerical Study of Eddy Current Pulsed Thermography to Detect Damage of Deep-Sea Manned Pressure Hull

Zhang

Wang

et al. 2023

JMSE

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At present, research on pressure hull safety is mainly focused on the constitutive model of material properties and the evaluation model of structural parameters aiming at fatigue life prediction. The damage identification and quantitative evaluation methods of pressure hulls have not been studied. In this study, an eddy current thermal imaging method is introduced to detect micro-cracks in a deep-sea spherical pressure hull. In the detection method, temperature is used as a parameter to identify and quantify cracks. The temperature distribution around the cracks is studied using theoretical analysis and finite element simulation. A theoretical model is established using electromagnetic theory and heat transfer theory. Moreover, the temperature difference between the cracked area and the non-cracked area can be obtained by solving the heat conduction equation. A pulsed eddy current thermal imaging testing system is established, and a defective titanium alloy specimen is tested. At the same time, the temperature around the cracks in the specimens is simulated. The specimens have the same material and welding as a deep-sea spherical pressure hull. This paper discusses the possibility of its use in a pressure hull, which will provide a reference for micro-crack damage identification and quantitative evaluation of a deep-sea spherical pressure hull.

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“…Previous studies of AIT focused on surface defects in composites, and the detection accuracy of inner defects was poor. The detection effect of AIT can be improved by using the enhancement algorithm [27]. Therefore, the AIT method has great application potential for defect detection in the production process of composite insulating components and even in the operation process.…”

Section: Introductionmentioning

confidence: 99%

Nondestructive Evaluation of Composite Bonding Structure Used in Electrical Insulation Based on Active Infrared Thermography

et al. 2022

Self Cite

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Nondestructive testing and evaluation of composite insulating components of electrical equipment is extremely necessary for assuring the safety of a power system. However, most existing nondestructive testing methods are not applicable for fast and effective live detection due to their time-consuming operation, high cost, and contact or near-field measurement. In this work, the effectiveness of active infrared thermography was investigated for detecting defects in silicone rubber (SIR)–fiber-reinforced plastic (FRP) bonding structures, which have been commonly used in insulating components of power equipment. The effectiveness of differential thermal image for enhancing the contrast of defective and sound areas and eliminating additive noise was demonstrated. Particularly, frame difference thermal image obtained by subtracting two differential thermal images extracting from respectively before and after the contrast inversion was proposed to enhance defect identification. The results revealed that defects of various sizes and depths such as voids, cracks, and interface disbonding of the SIR–FRP bonding structure were accurately detected by thermographic data. With the advantages of a quick and simple process, safety, universal applicability, visual results, far-field measurement, and quantitative defect estimation capabilities, active infrared thermography would be quite promising for live detection of electrical equipment.

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Transient thermal pattern separation and detection of conductive defects in composite insulators using eddy current pulsed thermography

Cited by 17 publications

References 24 publications

Detection of flat-bottom holes in composite materials using multi-dimensional complementary ensemble empirical mode decomposition algorithm

Detection of flat-bottom holes in composite materials using multi-dimensional complementary ensemble empirical mode decomposition algorithm

Theoretical and Numerical Study of Eddy Current Pulsed Thermography to Detect Damage of Deep-Sea Manned Pressure Hull

Nondestructive Evaluation of Composite Bonding Structure Used in Electrical Insulation Based on Active Infrared Thermography

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