Pub Date : 2023-01-27DOI: 10.1080/17686733.2023.2170647
V. Vavilov, P. Bison, D. Burleigh
{"title":"Ermanno Grinzato’s contribution to infrared diagnostics and nondestructive testing: in memory of an outstanding researcher","authors":"V. Vavilov, P. Bison, D. Burleigh","doi":"10.1080/17686733.2023.2170647","DOIUrl":"https://doi.org/10.1080/17686733.2023.2170647","url":null,"abstract":"","PeriodicalId":54525,"journal":{"name":"Quantitative Infrared Thermography Journal","volume":" ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2023-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46785630","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 : 2023-01-11DOI: 10.1080/17686733.2023.2164945
E. Koroteeva
{"title":"Assessing the effective penetration depth of mid-wave infrared radiation in water for fluid dynamic measurements","authors":"E. Koroteeva","doi":"10.1080/17686733.2023.2164945","DOIUrl":"https://doi.org/10.1080/17686733.2023.2164945","url":null,"abstract":"","PeriodicalId":54525,"journal":{"name":"Quantitative Infrared Thermography Journal","volume":" ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2023-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43946212","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 : 2023-01-10DOI: 10.1080/17686733.2022.2158678
Ahmet Özdil, B. Yılmaz
{"title":"Medical infrared thermal image based fatty liver classification using machine and deep learning","authors":"Ahmet Özdil, B. Yılmaz","doi":"10.1080/17686733.2022.2158678","DOIUrl":"https://doi.org/10.1080/17686733.2022.2158678","url":null,"abstract":"","PeriodicalId":54525,"journal":{"name":"Quantitative Infrared Thermography Journal","volume":" ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2023-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44881262","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 : 2022-12-23DOI: 10.1080/17686733.2022.2152259
B. Oswald-Tranta, A. Hackl, P. Lopez de Uralde Olavera, E. Gorostegui-Colinas, A. Rosell
{"title":"Calculating probability of detection of short surface cracks using inductive thermography","authors":"B. Oswald-Tranta, A. Hackl, P. Lopez de Uralde Olavera, E. Gorostegui-Colinas, A. Rosell","doi":"10.1080/17686733.2022.2152259","DOIUrl":"https://doi.org/10.1080/17686733.2022.2152259","url":null,"abstract":"","PeriodicalId":54525,"journal":{"name":"Quantitative Infrared Thermography Journal","volume":" ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2022-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43097837","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 : 2022-11-17DOI: 10.1080/17686733.2022.2143227
Á. Machado, M. Cañada-Soriano, I. Jimenez-Perez, M. Gil-Calvo, F. Carpes, P. Pérez-Soriano, J. Priego-Quesada
{"title":"Distance and camera features measurements affect the detection of temperature asymmetries using infrared thermography","authors":"Á. Machado, M. Cañada-Soriano, I. Jimenez-Perez, M. Gil-Calvo, F. Carpes, P. Pérez-Soriano, J. Priego-Quesada","doi":"10.1080/17686733.2022.2143227","DOIUrl":"https://doi.org/10.1080/17686733.2022.2143227","url":null,"abstract":"","PeriodicalId":54525,"journal":{"name":"Quantitative Infrared Thermography Journal","volume":" ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2022-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44449610","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 : 2022-11-15DOI: 10.1080/17686733.2022.2146419
M. Kałuża, A. Hatzopoulos
{"title":"Application of extension rings in thermography for electronic circuits imaging","authors":"M. Kałuża, A. Hatzopoulos","doi":"10.1080/17686733.2022.2146419","DOIUrl":"https://doi.org/10.1080/17686733.2022.2146419","url":null,"abstract":"","PeriodicalId":54525,"journal":{"name":"Quantitative Infrared Thermography Journal","volume":" ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2022-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46710454","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 : 2022-11-02DOI: 10.1080/17686733.2022.2126630
A. Masaki, K. Nagumo, K. Oiwa, A. Nozawa
ABSTRACT Technology to detect signs of drowsiness in drivers is essential even in the age of automated driving to prevent traffic accidents. In this study, facial skin temperature, which can be measured remotely using infrared thermography, as a measure for determining drowsiness was in focus. Facial skin temperature is an autonomic nervous system index that depends on skin blood flow. It is known that facial skin temperature changes depending on the physiological and psychological state, and that it is affected by drowsiness. We focused on an anomaly detection algorithm called the variational autoencoder (VAE). In this study, a model to detect drowsiness was constructed using VAE with only the facial skin temperature during arousal from sleep and search was made for facial areas where skin temperature fluctuates with drowsiness using the model. As a result, it was found that the side of the nasal dorsum may fluctuate with drowsiness and that facial skin temperature may fluctuate asymmetrically with drowsiness. Skin temperature around the orbit was shown to be an area of possible physiological and psychological significance related to autonomic nervous system activity. Based on the above, the degree of anomaly was confirmed to vary depending on the degree of drowsiness, indicating the usefulness of using VAE for drowsiness detection based on facial skin temperature.
{"title":"Feature analysis for drowsiness detection based on facial skin temperature using variational autoencoder : a preliminary study","authors":"A. Masaki, K. Nagumo, K. Oiwa, A. Nozawa","doi":"10.1080/17686733.2022.2126630","DOIUrl":"https://doi.org/10.1080/17686733.2022.2126630","url":null,"abstract":"ABSTRACT Technology to detect signs of drowsiness in drivers is essential even in the age of automated driving to prevent traffic accidents. In this study, facial skin temperature, which can be measured remotely using infrared thermography, as a measure for determining drowsiness was in focus. Facial skin temperature is an autonomic nervous system index that depends on skin blood flow. It is known that facial skin temperature changes depending on the physiological and psychological state, and that it is affected by drowsiness. We focused on an anomaly detection algorithm called the variational autoencoder (VAE). In this study, a model to detect drowsiness was constructed using VAE with only the facial skin temperature during arousal from sleep and search was made for facial areas where skin temperature fluctuates with drowsiness using the model. As a result, it was found that the side of the nasal dorsum may fluctuate with drowsiness and that facial skin temperature may fluctuate asymmetrically with drowsiness. Skin temperature around the orbit was shown to be an area of possible physiological and psychological significance related to autonomic nervous system activity. Based on the above, the degree of anomaly was confirmed to vary depending on the degree of drowsiness, indicating the usefulness of using VAE for drowsiness detection based on facial skin temperature.","PeriodicalId":54525,"journal":{"name":"Quantitative Infrared Thermography Journal","volume":" ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2022-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47954001","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 : 2022-09-28DOI: 10.1080/17686733.2022.2129135
Ella Mahoro, M. Akhloufi
{"title":"Breast cancer classification on thermograms using deep CNN and transformers","authors":"Ella Mahoro, M. Akhloufi","doi":"10.1080/17686733.2022.2129135","DOIUrl":"https://doi.org/10.1080/17686733.2022.2129135","url":null,"abstract":"","PeriodicalId":54525,"journal":{"name":"Quantitative Infrared Thermography Journal","volume":" ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2022-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42412030","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 : 2022-09-08DOI: 10.1080/17686733.2022.2121102
Choosak Ngaongam, M. Ekpanyapong, R. Ujjin
ABSTRACT This paper aims to optimise the vibration frequency that produces the highest temperature difference between crack location and non-defect location. The optimisation was based on thermoelastic damping analysis, and the analytical frequencies were varied between 10 Hz and 100 kHz. The result of optimisation was frequency 20 kHz for this study. In experiments, the effects of vibration frequency and vibration amplitude were studied. The experimental frequencies were 4.7, 20, 24 and 28 kHz. The piezoelectric disc was used as a sensor to measure the vibration amplitude on crack location. Then, the measured amplitudes were read in terms of the output voltage from the piezoelectric disc as 2, 4, 6 and 10 Vrms. The maximum difference in temperature between crack and non-defect locations was 0.33°C, which was obtained from vibration frequency of 20 kHz. Using high vibration amplitude did not significantly increase the temperature difference between crack and non-defect locations.
{"title":"Surface crack detection by using vibrothermography technique","authors":"Choosak Ngaongam, M. Ekpanyapong, R. Ujjin","doi":"10.1080/17686733.2022.2121102","DOIUrl":"https://doi.org/10.1080/17686733.2022.2121102","url":null,"abstract":"ABSTRACT This paper aims to optimise the vibration frequency that produces the highest temperature difference between crack location and non-defect location. The optimisation was based on thermoelastic damping analysis, and the analytical frequencies were varied between 10 Hz and 100 kHz. The result of optimisation was frequency 20 kHz for this study. In experiments, the effects of vibration frequency and vibration amplitude were studied. The experimental frequencies were 4.7, 20, 24 and 28 kHz. The piezoelectric disc was used as a sensor to measure the vibration amplitude on crack location. Then, the measured amplitudes were read in terms of the output voltage from the piezoelectric disc as 2, 4, 6 and 10 Vrms. The maximum difference in temperature between crack and non-defect locations was 0.33°C, which was obtained from vibration frequency of 20 kHz. Using high vibration amplitude did not significantly increase the temperature difference between crack and non-defect locations.","PeriodicalId":54525,"journal":{"name":"Quantitative Infrared Thermography Journal","volume":" ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2022-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46763308","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}
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