The intensity of the infrared radiation emitted by objects is mainly a function of their temperature. In infrared thermography, this feature is used for multiple purposes: as a health indicator in ...medical applications, as a sign of malfunction in mechanical and electrical maintenance or as an indicator of heat loss in buildings. This paper presents a review of infrared thermography especially focused on two applications: temperature measurement and non-destructive testing, two of the main fields where infrared thermography-based sensors are used. A general introduction to infrared thermography and the common procedures for temperature measurement and non-destructive testing are presented. Furthermore, developments in these fields and recent advances are reviewed.
A new active thermography scheme is here introduced, referred as ”‘Multi-Frequency Thermography”’, which uses an optimized multi-tone signal for simultaneously implementing lock-in analysis on a ...discrete and arbitrary set of linearly spaced frequencies. Such a signal, which modulates the intensity of the heating source here being a LED system in the visible range, results from the non-trivial summation of a desired number of odd and even harmonics of a fundamental tone, each of them having a specific initial phase value but equal amplitude, so as to deliver the same energy amount for all the chosen frequencies. In this way, a discrete set of thermal waves having different diffusion lengths are simultaneously excited within the inspected sample to probe different depths into it. With respect to standard lock-in thermography, it is demonstrated that the proposed approach can extract amplitude and phase features for all the excited frequencies from a single measurement, which lasts as long as a lock-in implemented at the fundamental tone. Both quantitative and qualitative comparisons with standard lock-in thermography are here reported, showing an excellent agreement. Hence, this new active thermography scheme can provide several advantages in practical implementations of thermography nondestructive evaluation.
•A completely novel thermography scheme is introduced, i.e. “Multi-Frequency Thermography”.•It makes use of a multi-frequency (MF) signal for modulating the heat emission.•The duration of the MF signal is equal to that of the fundamental tone.•It is suitable to be used with low-power sources, e.g. LEDs, lasers.•A thorough comparison with standard lock-in tests is reported.
•Review of state-of-the-art literature and research regarding the passive and active infrared thermography.•Fundamentals of IRT and the thermographic process for building diagnostics is ...presented.•Previous studies employing passive, active pulsed, and active lock-in thermographies for building diagnostics presented.•While IRT is a useful tool, there is still a great prospect for the development of more advanced and accurate approaches.
Infrared thermography (IRT) has met an extensive popularity among the non-destructive technologies for building diagnostics, especially with the increasing concerns of energy minimisation and low energy consumption of the building sector. Its popularity for a broad range of applications can be attributed to its non-contact safe nature, its usefulness and effectiveness, as well as the energy and cost savings it can achieve. This paper reviews the state-of-the-art literature and research regarding the passive and active infrared thermography. The fundamentals of IRT are thoroughly explained and the thermographic process for building diagnostics is presented. This work also presents the fields of applicability of IRT with a focus on the building sector, as well as the advantages, limitations and potential sources of errors of IRT employment. Additionally previous non-destructive testing (NDT) studies that employed passive, active pulsed, and active lock-in thermographies for building diagnostics are presented. A review of the thermal image analysis methods and the future trends of thermal imaging are also included in this work. It can be concluded that while IRT is a useful tool for the characterisation of defects in the building sector, there is great prospect for the development of more advanced, effective and accurate approaches that will employ a combination of thermography approaches.
•The transverse thermal resistance of chip was 1.25 times of the longitudinal thermal resistance.•The max temperature is 72.45 ℃, 43.15 ℃, 37.02 ℃ and 36.58 ℃ while the defect is missing bump and ...pad, missing bump, normal bump and bridge bump, respectively.•The normal bump and bridge bump are inspected by the max amplitude which the normal is 22.5 and the bridge is 26.5.•The state changed from solid to mushy and mushy to liquid when the time was 3.5 s and 8.45 s, respectively.
Flip chip technology has been used extensively in microelectronic packaging due to the high density, fine spacing, smaller size. However, the size and spacing of the solder bumps are decreasing gradually, defect detection is getting more and more difficult. Thus, the growing demand for high reliability has generated considerable attention on the importance of defect inspection. This paper proposes an in-situ infrared thermography monitoring method with in situ monitoring system bases on modified thermal resistance network model that added the phase transition for the non-destructive analysis of packaging process. The different defects, such as missing bump and pad, missing bump, and bridge are inspected with an accuracy of up to 90 % based on in situ monitoring system. The maximum error between the model and the experiment is 27.6 %, while the minimum error is 13.6 %. The experiment results show that the max temperature of missing bump and pad, missing bump is 35.43 °C and 6.13 °C higher than normal, and the bridge is 0.44 °C lower than normal, respectively. The maximum amplitude by the Fourier transform is used to inspect due to the max temperature of normal and bridge are indiscernible, the results show that the bridge is 4 lower than normal. The model and experimental results show that the in-situ infrared thermography monitoring method is effective for detecting defects in high density electronic devices. The proposed method of in situ monitoring is expected to provide a new strategy for next generation of three-dimensional heterogeneous integrated chips defect inspection.
•Non-invasive fast active thermography-based method for gunshot residue detection.•Comparison of halogen long-pulse and flash-pulse thermography for GSR detection around bullet holes in a ...fabric.•Comparison of six IRNDI evaluation/post-processing methods for the highest contrast GSR visualization.•Higher-order statistics kurtosis determination for thermographic response signal compression of the flash-pulse IRNDI of GSR.
Detection of gunshot residues (GSR) in a bullet hole area is one of the forensic investigations aiding in the reconstruction of crime scenes. Traditionally, chromogenic methods based on chemical exposure or microscopic/spectroscopic methods are used for this purpose. In this study, we explore the applicability of active excitation infrared thermography methods for GSR detection in the bullet hole area on fabric samples. A standard 9 mm full metal jacket ammunition with a nickel-plated shell and natural cotton fabric samples were used for experiments in this study. The applicability of active thermography methods based on two different light/heat excitation sources to detect the GSR was investigated. Flash-pulse and long-pulse thermography were compared through an experimental investigation. We evaluated the effectiveness of various thermographic data processing methods, including background subtraction, temperature derivative analysis, Fourier transform phase analysis, principal component analysis, and higher-order statistics for GSR evaluation. Our findings demonstrate that flash-pulse thermography and kurtosis analysis yield the highest contrast-to-noise ratio (CNR) and produce sharp, clear images of GSR, making it the optimal method for thermographic GSR detection. Our study indicates that even though the GSR particles are tiny, they can produce sufficient contrast to be detected by the thermographic methods if appropriate experimental and post-processing procedures are used. Thus, these methods could complement GSR detection as they are non-destructive and offer rapid inspection.
The aim of this work is the estimation of the specimen thickness from pulsed thermography data using the virtual wave concept. A virtual wave signal is calculated by applying a local transformation ...to the measured temperature data. This virtual wave is a solution of the wave equation, whereby for the parameter estimation also ultrasonic evaluation methods can be used, e.g. pulse-echo method for time-of-flight measurements. The time-of-flight is directly related to the distance traveled by the wave and can be used to reconstruct the position of the interface. This method yields a very good estimation of the thickness of a steel step wedge, with the advantage that the same evaluation method can be used for reflection as well as transmission measurements.
The pavement distress measurement is a crucial aspect in guaranteeing the safety of transportation infrastructure. In this regard, we introduce a novel and cost-effective multi-sensor approach for ...pavement segmentation during low-light night conditions. By utilizing the low-cost Azure Kinect multi-sensor system, we generated a multi-sensor dataset that encompasses aligned IR, RGB, and depth images. Then we carried out the data annotation process on the RGB images. A total of 11,343 manual annotations were meticulously made on 791 images, which were randomly selected from a collection of 96,891 frames. Subsequently, four different deep learning-based image segmentation models were analyzed both quantitatively and qualitatively. The results indicated that the segmentation performance on the IR dataset outperformed that of the RGB dataset. The model with the highest mIoU (mean Intersection over Union) of 0.7169 was ConvNext when trained on the IR dataset. Furthermore, we proposed the use of relative height for evaluating the severity of pavement distress. On the aligned depth map, the relative height was calculated using the depth data from the corresponding pavement distress area. Additionally, a quantitative comparison between manual annotations and the results obtained through deep learning revealed that the latter was more effective in identifying more severe forms of pavement distress. Through this study, we established the feasibility of collecting pavement distress data during nighttime using a low-cost multi-sensor system.
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•A lightweight, portable solution for pavement segmentation is proposed.•A multi-sensor dataset for pavement distress is created and annotated.•Deep learning models are applied to IR and low-light RGB data.•Pavement distress severity is determined from the aligned depth maps.
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