Applications of infrared thermography in electronics research

This paper presents a way to measure the true temperature of the electronic devices without disturbing their normal operating conditions, which involved with estimating target emissivity, background temperature correctly and choosing infrared transparent material and its transmission estimation. The temperature distributions of the main board in personal computer were measured by the method presented here with infrared thermography in several different running conditions. The measurement errors and their possible remedies are also discussed.

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“…Here c is the emissivity of the target, so the transmission of window can be calculated with e and eey by (2).…”

Section: Transmission and Its Error Estimation For Infrared Transparementioning

confidence: 99%

Infrared thermography for true temperature measurement of the main board in personal computer

2002

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“…Thermography is widely used in automatic controls and in the evaluation of the structural performance of components in the automotive sector [15,16]. Additionally, thermal imaging is used in the electronics and electrical engineering industry to assess critical components of boards [17] or switch boards [18] and the strength of the constituent materials [19,20]. Additionally, thermography is useful in different biomedical applications such as monitoring the temperature of patients [4] and the performance of devices that come in contact with them [21,22].…”

Section: Introductionmentioning

confidence: 99%

Prognostic Health Management Using IR Thermography: The Case of a Digital Twin of a NiTi Endodontic File

Ruffa

Lugarà

Fulco

et al. 2023

Sensors

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Prognostic and health management technologies are increasingly important in many fields where reducing maintenance costs is critical. Non-destructive testing techniques and the Internet of Things (IoT) can help create accurate, two-sided digital models of specific monitored objects, enabling predictive analysis and avoiding risky situations. This study focuses on a particular application: monitoring an endodontic file during operation to develop a strategy to prevent breakage. To this end, the authors propose an innovative, non-invasive technique for early fault detection based on digital twins and infrared thermography measurements. They developed a digital twin of a NiTi alloy endodontic file that receives measurement data from the real world and generates the expected thermal map of the object under working conditions. By comparing this virtual image with the real one acquired by an IR camera, the authors were able to identify an anomalous trend and avoid breakage. The technique was calibrated and validated using both a professional IR camera and an innovative low-cost IR scanner previously developed by the authors. By using both devices, they could identify a critical condition at least 11 s before the file broke.

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“…In recent years, IRT has been widely used and adopted by the NDT & E community due to its contactless and noninvasive features suitable for assessing machine health with higher reliability and accuracy. 2,3 IRT has found significant importance in the field of electronic research for detecting chip temperature and its behaviour, 4 knowing the condition of machine, 5 HVAC of the structures in the field of civil engineering, 6 understanding the behaviour of the material like plastic deformation 7 and many other industries like food and agriculture. 8 Unlike IRT, other techniques require various sensors that can sense the noise or vibration coming out of the machine but in that process, it can capture the noise and often disturb the system configuration.…”

Section: Introductionmentioning

confidence: 99%

Intelligent Fault Diagnosis of Bearings based on Convolutional Neural Network using Infrared Thermography

Sharma

Goyal

Kanda

2022

Proceedings of the Institution of Mechanical Engineers, Part J:

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Bearings, as a key part of rotating machinery, are prone to failure due to fatigue and aging resulting from their long-term and high-load operation. To ensure stability of the mechanical equipment, monitoring bearing health is helpful to guarantee smooth operation of machinery and increasing machinery availability. This article puts forward an intelligent non-invasive thermal images-based fault diagnostic approach to periodically monitor condition of the rolling contact bearings in respect of their deterioration due to defects on the inner race, outer race and balls/rollers. Thermal images of four bearing conditions, including one healthy and three faulty states, have been considered followed by a performance classification based comparative analysis using Support Vector Machines (SVM) and Convolutional Neural Network (CNN). The CNN consists of many tools under its cap but for this work, the AlexNet architecture is used which has proved to be more effective than SVM. The experimental findings reveal that non-contact infrared thermography has enormous potential for automatically identifying problems and detecting early warning, regardless of speed, resulting in negligible shutdowns of the system due to bearing failure.

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Applications of infrared thermography in electronics research

Cited by 8 publications

References 4 publications

Infrared thermography for true temperature measurement of the main board in personal computer

Infrared thermography for true temperature measurement of the main board in personal computer

Prognostic Health Management Using IR Thermography: The Case of a Digital Twin of a NiTi Endodontic File

Intelligent Fault Diagnosis of Bearings based on Convolutional Neural Network using Infrared Thermography

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