Progress in Active Infrared Imaging for Defect Detection in the Renewable and Electronic Industries

18Citations
Citations of this article
57Readers
Mendeley users who have this article in their library.

Abstract

In recent years, infrared thermographic (IRT) technology has experienced notable advancements and found widespread applications in various fields, such as renewable industry, electronic industry, construction, aviation, and healthcare. IRT technology is used for defect detection due to its non-contact, efficient, and high-resolution methods, which enhance product quality and reliability. This review offers an overview of active IRT principles. It comprehensively examines four categories based on the type of heat sources employed: pulsed thermography (PT), lock-in thermography (LT), ultrasonically stimulated vibration thermography (UVT), and eddy current thermography (ECT). Furthermore, the review explores the application of IRT imaging in the renewable energy sector, with a specific focus on the photovoltaic (PV) industry. The integration of IRT imaging and deep learning techniques presents an efficient and highly accurate solution for detecting defects in PV panels, playing a critical role in monitoring and maintaining PV energy systems. In addition, the application of infrared thermal imaging technology in electronic industry is reviewed. In the development and manufacturing of electronic products, IRT imaging is used to assess the performance and thermal characteristics of circuit boards. It aids in detecting potential material and manufacturing defects, ensuring product quality. Furthermore, the research discusses algorithmic detection for PV panels, the excitation sources used in electronic industry inspections, and infrared wavelengths. Finally, the review analyzes the advantages and challenges of IRT imaging concerning excitation sources, the PV industry, the electronics industry, and artificial intelligence (AI). It provides insights into critical issues requiring attention in future research endeavors.

Cited by Powered by Scopus

A Comprehensive Review of Deep Learning-Based PCB Defect Detection

28Citations
N/AReaders
Get full text

Quality Assurance in Resistance Spot Welding: State of Practice, State of the Art, and Prospects

17Citations
N/AReaders
Get full text

A Comprehensive Review of Methods for Hydrological Forecasting Based on Deep Learning

14Citations
N/AReaders
Get full text

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Cite

CITATION STYLE

APA

Zhao, X., Zhao, Y., Hu, S., Wang, H., Zhang, Y., & Ming, W. (2023, October 27). Progress in Active Infrared Imaging for Defect Detection in the Renewable and Electronic Industries. Sensors (Basel, Switzerland). https://doi.org/10.3390/s23218780

Readers' Seniority

Tooltip

PhD / Post grad / Masters / Doc 11

69%

Researcher 3

19%

Lecturer / Post doc 2

13%

Readers' Discipline

Tooltip

Engineering 12

67%

Computer Science 3

17%

Business, Management and Accounting 2

11%

Earth and Planetary Sciences 1

6%

Article Metrics

Tooltip
Mentions
News Mentions: 1

Save time finding and organizing research with Mendeley

Sign up for free