Improvement of Defect Feature Extraction in Eddy Current Pulsed Thermography

Zhu, Peipei; Tian, Lulu; Cheng, Yuhua

doi:10.1109/access.2019.2908457

Cited by 3 publications

(2 citation statements)

References 22 publications

(35 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The first aspect is the use of different excitation methods; the second is expansion of the scope of application; and the third is the optimization of thermal image processing. In the early research of thermal image data processing methods, the data processing method based on pulsed eddy current thermal imaging detection technology is generally to select the best thermal image to extract defect features and then complete the defect identification [47].…”

Section: Xsl • Fomentioning

confidence: 99%

Infrared Thermal Imaging of Patients With Acute Upper Respiratory Tract Infection: Mixed Methods Analysis

Zhang¹,

Cao²,

Deng³

et al. 2021

Interact J Med Res

View full text Add to dashboard Cite

Background: Upper respiratory tract infection is a common disease of the respiratory system. Its incidence is very high, and it can even cause pandemics. Infrared thermal imaging (IRTI) can provide an objective and quantifiable reference for the visual diagnosis of people with acute respiratory tract infection, and it can function as an effective indicator of clinical diagnosis. Objective:The aims of this study are to observe and analyze the infrared expression location and characteristics of patients with acute upper respiratory tract infection through IRTI technology and to clearly express the quantification of temperature, analyze the role of IRTI in acute upper respiratory tract diagnostic research, and understand the impact of IRTI in qualitative and quantitative research. Methods: From December 2018 to February 2019, 154 patients with acute upper respiratory tract infection were randomly selected from the emergency department of the First Affiliated Hospital of Guangzhou Medical University. Among these patients, 73 were men and 81 were women. The subjects were divided into two groups according to the presence of fever, namely, fever and nonfever groups. Qualitative and quantitative analyses of the infrared thermal images were performed to compare the results before and after application of the technology.Results: Using the method described in this paper, through the analysis of experimental data, we elucidated the role of IRTI in the diagnosis of acute upper respiratory tract infection, and we found that qualitative and quantitative IRTI analyses play important roles. Through the combination of theory and experimental data, the IRTI analysis showed good results in identifying acute upper respiratory tract infection.Conclusions: IRTI technology plays an important role in identifying the infrared expression location and characteristics of patients with acute upper respiratory tract infection as well as in the quantification of clear expression of body temperature, and it provides an objective and quantifiable reference basis for elucidating the pathogenesis of these patients.

show abstract

Section: Xsl • Fomentioning

confidence: 99%

Infrared Thermal Imaging of Patients With Acute Upper Respiratory Tract Infection: Mixed Methods Analysis

Zhang¹,

Cao²,

Deng³

et al. 2021

Interact J Med Res

View full text Add to dashboard Cite

show abstract

“…voids, defects, corrosion), modify this thermal response and produce hot or cold areas on the sample surface sites. To improve the identification of defects, it is then necessary to automate the image processing [12].…”

Section: Introductionmentioning

confidence: 99%

Active Thermography Data-Processing Algorithm for Nondestructive Testing of Materials

et al. 2020

View full text Add to dashboard Cite

This article presents the development of an active thermography algorithm capable of detecting defects in materials, based on the techniques of Thermographic Signal Reconstruction (TSR), Thermal Contrast (TC) and the physical principles of heat transfer. The results obtained from this algorithm are compared to the TSR technique and the raw thermogram obtained by stepped thermography inspection. Experimentally, a short thermal pulse is used and the surface temperature of the sample is monitored over time with an infrared camera. Due to the volume of data, the first step is data compression. Newton's law of cooling was used to store the normalized temperature data pixel-by-pixel over time and a compression ratio of 99% was obtained. The main contributions of the developed algorithm are: only four parameters for data compression and the concept of change in the direction of the heat flow to delimit the edges of the defects, where the borders are identified with a remarkable accuracy. Some well known image processing technique are also integrated to improve the thermal analysis: edge detection/interface between the sample and the image background; consolidation in a single image by aggregating the indicators referring to the concept of cooling/heating time constant, maximum thermal amplitude and contrast. INDEX TERMS active thermography, thermal analysis, infrared imaging, data compression, change detection algorithms, image processing.

show abstract