Pub Date : 2022-08-04DOI: 10.1080/17686733.2022.2105019
R. Krankenhagen
On May 25 of this year, Christiane Maierhofer, our long-time colleague and previous editor-in-chief of the QIRT Journal, passed away after a serious illness. Although we were aware of her condition, the news hit us completely by surprise and with great force. She leaves a big gap both at the Federal Institute for Materials Research and Testing (BAM) and in the QIRT community, and we have yet to learn how we will deal with it in the future. Christiane Maierhofer was a native of Berlin and firmly rooted in the region. She studied physics at the TU Berlin from 1983 to 1989 and wrote her diploma thesis on quantum well structures in AlGaAs. She received her PhD in 1992, also in Berlin, at the Fritz Haber Institute of the Max Planck Society on a similar topic in solid state physics. She then moved to BAM in 1993, turning her attention to non-destructive testing in civil engineering. In doing so, she mainly used radar techniques. Since about 2000 she was engaged in thermography and created with her early scientific publications essential basics for the application of active thermography in civil engineering. Under her leadership, the originally small thermography working group developed into one of the largest research groups to deal exclusively with thermography. In spring 2015 she was appointed head of the new department “Thermographic Methods” at BAM. Within this framework, the fields of application expanded towards the characterization of fiber-reinforced plastics and metals and, more recently, additively manufactured materials. Based on her growing international reputation, she participated in various committees and standardization bodies, including CEN, DIN and DGZfP. In July 2016, Christiane Maierhofer took over the position of Editor-in-Chief of the QIRT Journal (from Daniel Balageas). One of her professional highlights was undoubtedly the chairing of the 2018 QIRT conference in Berlin, which will certainly be remembered fondly by all participants. Her treacherous illness ended this career in an unexpected way. She will be remembered by all of us as a determined and hardworking colleague who was always open to new ideas. At the same time, she always remained friendly, fair, and modest, a combination that cannot be taken for granted in a research landscape usually characterized by competition and rivalry. Indeed, we will miss Christiane and we thank her so much for all she did for the QIRT community! QUANTITATIVE INFRARED THERMOGRAPHY JOURNAL 2022, VOL. 19, NO. 4, 221–222 https://doi.org/10.1080/17686733.2022.2105019
{"title":"Obituary of Christiane Maierhofer","authors":"R. Krankenhagen","doi":"10.1080/17686733.2022.2105019","DOIUrl":"https://doi.org/10.1080/17686733.2022.2105019","url":null,"abstract":"On May 25 of this year, Christiane Maierhofer, our long-time colleague and previous editor-in-chief of the QIRT Journal, passed away after a serious illness. Although we were aware of her condition, the news hit us completely by surprise and with great force. She leaves a big gap both at the Federal Institute for Materials Research and Testing (BAM) and in the QIRT community, and we have yet to learn how we will deal with it in the future. Christiane Maierhofer was a native of Berlin and firmly rooted in the region. She studied physics at the TU Berlin from 1983 to 1989 and wrote her diploma thesis on quantum well structures in AlGaAs. She received her PhD in 1992, also in Berlin, at the Fritz Haber Institute of the Max Planck Society on a similar topic in solid state physics. She then moved to BAM in 1993, turning her attention to non-destructive testing in civil engineering. In doing so, she mainly used radar techniques. Since about 2000 she was engaged in thermography and created with her early scientific publications essential basics for the application of active thermography in civil engineering. Under her leadership, the originally small thermography working group developed into one of the largest research groups to deal exclusively with thermography. In spring 2015 she was appointed head of the new department “Thermographic Methods” at BAM. Within this framework, the fields of application expanded towards the characterization of fiber-reinforced plastics and metals and, more recently, additively manufactured materials. Based on her growing international reputation, she participated in various committees and standardization bodies, including CEN, DIN and DGZfP. In July 2016, Christiane Maierhofer took over the position of Editor-in-Chief of the QIRT Journal (from Daniel Balageas). One of her professional highlights was undoubtedly the chairing of the 2018 QIRT conference in Berlin, which will certainly be remembered fondly by all participants. Her treacherous illness ended this career in an unexpected way. She will be remembered by all of us as a determined and hardworking colleague who was always open to new ideas. At the same time, she always remained friendly, fair, and modest, a combination that cannot be taken for granted in a research landscape usually characterized by competition and rivalry. Indeed, we will miss Christiane and we thank her so much for all she did for the QIRT community! QUANTITATIVE INFRARED THERMOGRAPHY JOURNAL 2022, VOL. 19, NO. 4, 221–222 https://doi.org/10.1080/17686733.2022.2105019","PeriodicalId":54525,"journal":{"name":"Quantitative Infrared Thermography Journal","volume":"19 1","pages":"221 - 222"},"PeriodicalIF":2.5,"publicationDate":"2022-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44158162","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-03DOI: 10.1080/17686733.2022.2105478
R. C. Martínez Montejano, David Emmanuel García Martínez, Jose J. Jaime Rodriguez, Eleazar Samuel Kolosovas Machuca, Luis Javier Ontañón García Pimentel
ABSTRACT Quality control processes guarantee the proper product performance prior to its distribution in the market. In particular, the analysis of this process in plastic containers is developed by sensors that measure the internal pressure. In this study, an experimental framework for detecting structural damages is proposed. The main contribution lies in the use of passive thermography and digital image processing, where the raw thermographic images are analysed in LabVIEW. The digital interface presents in a user-friendly manner the results of the full process along with the location and characteristics of the structural damage. The results obtained denote an improvement in the quality process by increasing the resolution for the error detection in structural damages around 0.4 mm, which falls out of the scope of classic pressure sensors. The thermographic scans serve as a contrast medium for highlighting the damage in the containers and do not depend on the environmental temperature.
{"title":"Improvement of the manufacturing quality test of plastic containers by using thermography scans","authors":"R. C. Martínez Montejano, David Emmanuel García Martínez, Jose J. Jaime Rodriguez, Eleazar Samuel Kolosovas Machuca, Luis Javier Ontañón García Pimentel","doi":"10.1080/17686733.2022.2105478","DOIUrl":"https://doi.org/10.1080/17686733.2022.2105478","url":null,"abstract":"ABSTRACT Quality control processes guarantee the proper product performance prior to its distribution in the market. In particular, the analysis of this process in plastic containers is developed by sensors that measure the internal pressure. In this study, an experimental framework for detecting structural damages is proposed. The main contribution lies in the use of passive thermography and digital image processing, where the raw thermographic images are analysed in LabVIEW. The digital interface presents in a user-friendly manner the results of the full process along with the location and characteristics of the structural damage. The results obtained denote an improvement in the quality process by increasing the resolution for the error detection in structural damages around 0.4 mm, which falls out of the scope of classic pressure sensors. The thermographic scans serve as a contrast medium for highlighting the damage in the containers and do not depend on the environmental temperature.","PeriodicalId":54525,"journal":{"name":"Quantitative Infrared Thermography Journal","volume":"1 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2022-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42075539","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-11DOI: 10.1080/17686733.2022.2097614
Usha Rani Gogoi, M. Bhowmik, Gautam Majumdar
ABSTRACT The presence of suspicious hyperthermic regions (SHRs) in breast thermograms is a prominent indicator of breast pathology, for which delineation and analysis of SHRs have a crucial role in early detection of breast abnormalities. A novel approach for breast abnormality grading, namely the morphology model of suspicious hyperthermic regions (MMSHRs), is proposed here. The proposed model first segments SHRs from breast-thermograms and then analyzes their morphology to grade the thermograms according to their degree of severity. To segment SHRs, a simple but effective method that computes the similarity score of each pixel with the highest intensity value is designed. . The performance of the proposed segmentation method is tested on both public and in-house-captured datasets. With the optimal values of seven evaluation metrics, the proposed segmentation method outperforms other state-of-the-art segmentation methods. The values of evaluation metrics further justify that the proposed SHRs segmentation method addresses all the limitations regarding infrared breast thermogram segmentation, and reduces the under-segmentation and over-segmentation of SHRs. Following segmentation of SHRs, the MMSHRs extract the corresponding morphological features, allowing the classification of thermograms into mild and severely abnormal with the classification accuracy of 91% and area under the receiver operating characteristic curve of .9998.
{"title":"MMSHRs: a morphology model of suspicious hyperthermic regions for degree of severity prediction from breast thermograms","authors":"Usha Rani Gogoi, M. Bhowmik, Gautam Majumdar","doi":"10.1080/17686733.2022.2097614","DOIUrl":"https://doi.org/10.1080/17686733.2022.2097614","url":null,"abstract":"ABSTRACT The presence of suspicious hyperthermic regions (SHRs) in breast thermograms is a prominent indicator of breast pathology, for which delineation and analysis of SHRs have a crucial role in early detection of breast abnormalities. A novel approach for breast abnormality grading, namely the morphology model of suspicious hyperthermic regions (MMSHRs), is proposed here. The proposed model first segments SHRs from breast-thermograms and then analyzes their morphology to grade the thermograms according to their degree of severity. To segment SHRs, a simple but effective method that computes the similarity score of each pixel with the highest intensity value is designed. . The performance of the proposed segmentation method is tested on both public and in-house-captured datasets. With the optimal values of seven evaluation metrics, the proposed segmentation method outperforms other state-of-the-art segmentation methods. The values of evaluation metrics further justify that the proposed SHRs segmentation method addresses all the limitations regarding infrared breast thermogram segmentation, and reduces the under-segmentation and over-segmentation of SHRs. Following segmentation of SHRs, the MMSHRs extract the corresponding morphological features, allowing the classification of thermograms into mild and severely abnormal with the classification accuracy of 91% and area under the receiver operating characteristic curve of .9998.","PeriodicalId":54525,"journal":{"name":"Quantitative Infrared Thermography Journal","volume":"20 1","pages":"157 - 181"},"PeriodicalIF":2.5,"publicationDate":"2022-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44986292","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-03DOI: 10.1080/17686733.2022.2056987
Shakeb Deane, N. Avdelidis, C. Ibarra-Castanedo, Alex A. Williamson, Stephen Withers, A. Zolotas, X. Maldague, M. Ahmadi, Shashank Pant, M. Genest, Hobivola A. Rabearivelo, A. Tsourdos
ABSTRACT This work aims to address the effectiveness and challenges of using active infrared thermography (IRT) onboard an unmanned aerial vehicle (UAV) platform. The work seeks to assess the performance of small low-powered forms of excitation which are suitable for active thermography and the ability to locate subsurface defects on composites. An excitation source in multiple 250 W lamps is mounted onto a UAV and is solely battery powered with a remote trigger to power cycle them. Multiple experiments address the interference from the UAV whilst performing an active IRT inspection. The optimal distances and time required for a UAV inspection using IRT are calculated. Multiple signal processing techniques are used to analyse the composites which help locate the sub-surface defects. It was observed that a UAV can successfully carry the required sensors and equipment for an Active thermographic NDT inspection which can provide access to difficult areas. Most active thermographic inspection equipment is large, heavy, and expensive. Furthermore, using such equipment for the inspection of complex structures is time-consuming. For example, a cherry picker would be required to inspect the tail of an aircraft. This solution looks to assist engineers in inspecting complex composite structures and could potentially significantly reduce the time and cost of a routine inspection.
{"title":"Development of a thermal excitation source used in an active thermographic UAV platform","authors":"Shakeb Deane, N. Avdelidis, C. Ibarra-Castanedo, Alex A. Williamson, Stephen Withers, A. Zolotas, X. Maldague, M. Ahmadi, Shashank Pant, M. Genest, Hobivola A. Rabearivelo, A. Tsourdos","doi":"10.1080/17686733.2022.2056987","DOIUrl":"https://doi.org/10.1080/17686733.2022.2056987","url":null,"abstract":"ABSTRACT This work aims to address the effectiveness and challenges of using active infrared thermography (IRT) onboard an unmanned aerial vehicle (UAV) platform. The work seeks to assess the performance of small low-powered forms of excitation which are suitable for active thermography and the ability to locate subsurface defects on composites. An excitation source in multiple 250 W lamps is mounted onto a UAV and is solely battery powered with a remote trigger to power cycle them. Multiple experiments address the interference from the UAV whilst performing an active IRT inspection. The optimal distances and time required for a UAV inspection using IRT are calculated. Multiple signal processing techniques are used to analyse the composites which help locate the sub-surface defects. It was observed that a UAV can successfully carry the required sensors and equipment for an Active thermographic NDT inspection which can provide access to difficult areas. Most active thermographic inspection equipment is large, heavy, and expensive. Furthermore, using such equipment for the inspection of complex structures is time-consuming. For example, a cherry picker would be required to inspect the tail of an aircraft. This solution looks to assist engineers in inspecting complex composite structures and could potentially significantly reduce the time and cost of a routine inspection.","PeriodicalId":54525,"journal":{"name":"Quantitative Infrared Thermography Journal","volume":"20 1","pages":"198 - 229"},"PeriodicalIF":2.5,"publicationDate":"2022-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48881108","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-05-17DOI: 10.1080/17686733.2022.2047301
J. Fleuret, S. Ebrahimi, C. Ibarra-Castanedo, X. Maldague
ABSTRACT This paper explores the implementation of Latent Low-Rank Representation (LatLRR) on pulsed thermographic data. LatLRR decomposes an image in the form of a linear association of three types of information: observed, unobserved and noise. This information is then used in order to separate the salient and principal features. This study has found that when used as a post-processing method prior to the application of state-of-the-art signal processing techniques, such as principal component thermography (PCT) and pulsed phase thermography (PPT), LatLRR significantly improves defect detection: 18% for PCT and 92% for PPT. Nevertheless, no noticeable improvement was measured when LatLRR was used to reconstruct a noiseless version of each image of a dataset, before processing it with a state-of-the-art algorithm. The investigations conducted on each type of feature returned by the LatLRR have also failed to provide results regarding the detection of defects.
{"title":"Latent Low Rank Representation Applied to Pulsed Thermography Data For Carbon Fibre Reinforced Polymer Inspection","authors":"J. Fleuret, S. Ebrahimi, C. Ibarra-Castanedo, X. Maldague","doi":"10.1080/17686733.2022.2047301","DOIUrl":"https://doi.org/10.1080/17686733.2022.2047301","url":null,"abstract":"ABSTRACT This paper explores the implementation of Latent Low-Rank Representation (LatLRR) on pulsed thermographic data. LatLRR decomposes an image in the form of a linear association of three types of information: observed, unobserved and noise. This information is then used in order to separate the salient and principal features. This study has found that when used as a post-processing method prior to the application of state-of-the-art signal processing techniques, such as principal component thermography (PCT) and pulsed phase thermography (PPT), LatLRR significantly improves defect detection: 18% for PCT and 92% for PPT. Nevertheless, no noticeable improvement was measured when LatLRR was used to reconstruct a noiseless version of each image of a dataset, before processing it with a state-of-the-art algorithm. The investigations conducted on each type of feature returned by the LatLRR have also failed to provide results regarding the detection of defects.","PeriodicalId":54525,"journal":{"name":"Quantitative Infrared Thermography Journal","volume":"20 1","pages":"143 - 156"},"PeriodicalIF":2.5,"publicationDate":"2022-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49176435","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-05-12DOI: 10.1080/17686733.2022.2049050
J. Fleuret, S. Ebrahimi, C. Ibarra-Castanedo, X. Maldague
This paper explores the application of Blind Image Quality Assessment (BIQA) metrics to pulsed thermography. Two BIQA were used to subsample a sequence of images acquired using Pulse Thermography (...
本文探讨了盲图像质量评估(BIQA)指标在脉冲热成像中的应用。使用两个BIQA对脉冲热成像(…
{"title":"Application of blind image quality assessment metrics to pulsed thermography","authors":"J. Fleuret, S. Ebrahimi, C. Ibarra-Castanedo, X. Maldague","doi":"10.1080/17686733.2022.2049050","DOIUrl":"https://doi.org/10.1080/17686733.2022.2049050","url":null,"abstract":"This paper explores the application of Blind Image Quality Assessment (BIQA) metrics to pulsed thermography. Two BIQA were used to subsample a sequence of images acquired using Pulse Thermography (...","PeriodicalId":54525,"journal":{"name":"Quantitative Infrared Thermography Journal","volume":"46 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2022-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138507204","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-04-18DOI: 10.1080/17686733.2022.2060545
I. Garrido, S. Lagüela, Q. Fang, P. Arias
ABSTRACT Infrastructure inspection is fundamental to keep its service performance at the highest level. For that, special attention should be paid to the most severe defects in order to be able to subsequently mitigate or even eliminate them. Therefore, this paper introduces the combination of an automatic thermogram pre-processing algorithm and a Deep Learning (DL) model, Mask R-CNN, applied to thermal images acquired from different infrastructures (buildings, heritage sites and civil infrastructures) with water-related problems and thermal bridges. The pre-processing algorithm developed is based on thermal fundamentals. As an output, the thermal contrast between defect and defect-free areas is increased in each image. Then, Mask R-CNN is trained using the pre-processing algorithm outputs as input dataset to automatically detect, segment and classify each defect area. The training process of Mask R-CNN is improved by the prior application of the proposed pre-processing algorithm in terms of time. This shows the capacity of thermal fundamentals to improve the performance of the DL models for their application to the InfraRed Thermography (IRT) field. In addition, DL models are introduced for the first time in the thermographic inspection of water-related problems and thermal bridges when inspecting an infrastructure.
{"title":"Introduction of the combination of thermal fundamentals and Deep Learning for the automatic thermographic inspection of thermal bridges and water-related problems in infrastructures","authors":"I. Garrido, S. Lagüela, Q. Fang, P. Arias","doi":"10.1080/17686733.2022.2060545","DOIUrl":"https://doi.org/10.1080/17686733.2022.2060545","url":null,"abstract":"ABSTRACT Infrastructure inspection is fundamental to keep its service performance at the highest level. For that, special attention should be paid to the most severe defects in order to be able to subsequently mitigate or even eliminate them. Therefore, this paper introduces the combination of an automatic thermogram pre-processing algorithm and a Deep Learning (DL) model, Mask R-CNN, applied to thermal images acquired from different infrastructures (buildings, heritage sites and civil infrastructures) with water-related problems and thermal bridges. The pre-processing algorithm developed is based on thermal fundamentals. As an output, the thermal contrast between defect and defect-free areas is increased in each image. Then, Mask R-CNN is trained using the pre-processing algorithm outputs as input dataset to automatically detect, segment and classify each defect area. The training process of Mask R-CNN is improved by the prior application of the proposed pre-processing algorithm in terms of time. This shows the capacity of thermal fundamentals to improve the performance of the DL models for their application to the InfraRed Thermography (IRT) field. In addition, DL models are introduced for the first time in the thermographic inspection of water-related problems and thermal bridges when inspecting an infrastructure.","PeriodicalId":54525,"journal":{"name":"Quantitative Infrared Thermography Journal","volume":" ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2022-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49385107","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-03-28DOI: 10.1080/17686733.2022.2056986
Wesley Bond, V. Panicker, J. McMillan, R. Simpson, M. Hayes, G. Machin, G. Casarosa, J. Etchells
ABSTRACT The ground testing of satellites requires the validation of the satellite’s thermal model whilst operational in vacuum. Thermocouples are widely used for this testing, but they are only able to provide a point temperature measurement. In contrast a vacuum capable, metrological thermal imager could be used to measure the temperature across a large surface area with high spatial resolution. Such a system will also have increased utility compared to a thermal imager operated within a canister if it is a low size, weight and power (SWaP) device that can be easily mounted. The ESA General Support and Technology Programme has enabled the National Physical Laboratory to develop a vacuum capable, low SWaP thermal imager that can provide traceable, calibrated temperature measurement in thermal vacuum from −40°C to 60°C. The calculated instrument calibration uncertainty is less than ± 0.85°C (k = 2).
{"title":"A metrology enabled thermal imager for thermal vacuum testing","authors":"Wesley Bond, V. Panicker, J. McMillan, R. Simpson, M. Hayes, G. Machin, G. Casarosa, J. Etchells","doi":"10.1080/17686733.2022.2056986","DOIUrl":"https://doi.org/10.1080/17686733.2022.2056986","url":null,"abstract":"ABSTRACT The ground testing of satellites requires the validation of the satellite’s thermal model whilst operational in vacuum. Thermocouples are widely used for this testing, but they are only able to provide a point temperature measurement. In contrast a vacuum capable, metrological thermal imager could be used to measure the temperature across a large surface area with high spatial resolution. Such a system will also have increased utility compared to a thermal imager operated within a canister if it is a low size, weight and power (SWaP) device that can be easily mounted. The ESA General Support and Technology Programme has enabled the National Physical Laboratory to develop a vacuum capable, low SWaP thermal imager that can provide traceable, calibrated temperature measurement in thermal vacuum from −40°C to 60°C. The calculated instrument calibration uncertainty is less than ± 0.85°C (k = 2).","PeriodicalId":54525,"journal":{"name":"Quantitative Infrared Thermography Journal","volume":"20 1","pages":"182 - 197"},"PeriodicalIF":2.5,"publicationDate":"2022-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45147367","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-02-07DOI: 10.1080/17686733.2021.2025015
J. Fleuret, S. Ebrahimi, C. Castanedo, X. Maldague
ABSTRACT This study introduces and evaluates a new approach to reconstruct image sequences acquired during non-destructive testing by pulsed thermography. The proposed method consists of applying two linear support vector regressions to model the evolution of the data from both a spatial and temporal point of view. Each regression vectors will map the data with the number of pixels and the number of frames using convex optimisation. Then the regression vectors are used to predict a more robust representation of the data, thus reconstructing the sequence. The proposed method has been applied to data related to a reference sample of carbon reinforced fibre with known defects. This approach was evaluated on a sequence with severe non-uniform heating and was compared with state-of-the-art methods. Despite being sensitive to non-uniform heating, the proposed method provided a higher CNR score on smaller defects, compared with state-of-the-art methods. For the shallowest defects it shows better performance in term of contrast reconstruction compared to partial least-squares thermography (PLST). It also outperforms principal component thermography (PCT), and thermographic signal reconstruction-PCT (TSR-PCT) for defects located at a depth of 0.6 mm and 0.8 mm below the surface.
{"title":"On the use of pulsed thermography signal reconstruction based on linear support vector regression for carbon fiber reinforced polymer inspection","authors":"J. Fleuret, S. Ebrahimi, C. Castanedo, X. Maldague","doi":"10.1080/17686733.2021.2025015","DOIUrl":"https://doi.org/10.1080/17686733.2021.2025015","url":null,"abstract":"ABSTRACT This study introduces and evaluates a new approach to reconstruct image sequences acquired during non-destructive testing by pulsed thermography. The proposed method consists of applying two linear support vector regressions to model the evolution of the data from both a spatial and temporal point of view. Each regression vectors will map the data with the number of pixels and the number of frames using convex optimisation. Then the regression vectors are used to predict a more robust representation of the data, thus reconstructing the sequence. The proposed method has been applied to data related to a reference sample of carbon reinforced fibre with known defects. This approach was evaluated on a sequence with severe non-uniform heating and was compared with state-of-the-art methods. Despite being sensitive to non-uniform heating, the proposed method provided a higher CNR score on smaller defects, compared with state-of-the-art methods. For the shallowest defects it shows better performance in term of contrast reconstruction compared to partial least-squares thermography (PLST). It also outperforms principal component thermography (PCT), and thermographic signal reconstruction-PCT (TSR-PCT) for defects located at a depth of 0.6 mm and 0.8 mm below the surface.","PeriodicalId":54525,"journal":{"name":"Quantitative Infrared Thermography Journal","volume":"20 1","pages":"39 - 61"},"PeriodicalIF":2.5,"publicationDate":"2022-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42341239","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-02-07DOI: 10.1080/17686733.2022.2033529
Nils J. Ziegeler, P. Nolte, S. Schweizer
ABSTRACT In this work, an evaluation method for transient thermal measurements is presented. It allows for a high temporal sensitivity by analysing the spectral composition of a thermal transient, the so-called time constant spectrum. The spectral components provide a detailed insight into the heat flow dynamics and thermal parameters describing a multi-layer system. The method is based on a one-dimensional heat path analysis technique common for the thermal characterisation of electronic components, called ‘network identification by deconvolution’. Here, a generalisation, called ‘thermographic network identification’, is presented to obtain spatially resolved thermal equivalence networks as complete thermal model of the device under study. As a proof of concept, two samples are investigated. The method is discussed on the basis of the obtained results.
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