Sub-Surface Defect Depth Approximation in Cold Infrared Thermography
Detection and characterisation of hidden corrosion are considered challenging yet crucial activities in many sensitive industrial plants where preventing the loss of containment or structural reliability are paramount. In the last two decades, infrared (IR) thermography has proved to be a reliable m...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-09-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/22/18/7098 |
| _version_ | 1827656688204775424 |
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| author | Siavash Doshvarpassand Xiangyu Wang |
| author_facet | Siavash Doshvarpassand Xiangyu Wang |
| author_sort | Siavash Doshvarpassand |
| collection | DOAJ |
| description | Detection and characterisation of hidden corrosion are considered challenging yet crucial activities in many sensitive industrial plants where preventing the loss of containment or structural reliability are paramount. In the last two decades, infrared (IR) thermography has proved to be a reliable means for inspection of corrosion or other sub-surface anomalies in low to mid thickness metallic mediums. The foundation of using IR thermography for defect detection and characterisation is based on active thermography. In this method of inspection, an external excitation source is deployed for the purpose of stimulating thermal evolutions inside objects. The presence of sub-surface defects disrupts the evolution of electromagnetic pulse inside an object. The reflection of altered pulse at the surface can be recorded through thermal camera in the form of temperature anomalies. Through authors’ previous works, cold thermography has shown that it can be a viable defect detection alternative to the most commonly used means of active thermography, known as heating. In the current work, the characterisation of defect dimensions, i.e., depth and diameter, has been explored. A simple analytical model for thermal contrast over defect is used in order to approximate the defect depth and diameter. This is achieved by comparing the similarities of the model and the experimental contrast time-series. A method of time-series similarity measurement known as dynamic time wrapping (DTW) is used to score the similarity between a pair of model and experiment time-series. The final outcome of the proposed experimental setup has revealed that there is a good potential to predict the metal loss of up to 50% in mid-thickness substrate even by deploying a less accurate nonradiometric thermal device and no advanced image processing. |
| first_indexed | 2024-03-09T22:32:51Z |
| format | Article |
| id | doaj.art-638ae582c3a64a2892c16c6e0e2b1ce2 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-09T22:32:51Z |
| publishDate | 2022-09-01 |
| publisher | MDPI AG |
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| series | Sensors |
| spelling | doaj.art-638ae582c3a64a2892c16c6e0e2b1ce22023-11-23T18:54:24ZengMDPI AGSensors1424-82202022-09-012218709810.3390/s22187098Sub-Surface Defect Depth Approximation in Cold Infrared ThermographySiavash Doshvarpassand0Xiangyu Wang1Australasian Joint Research Centre for Building Information Modelling, Curtin University, Bentley, WA 6102, AustraliaAustralasian Joint Research Centre for Building Information Modelling, Curtin University, Bentley, WA 6102, AustraliaDetection and characterisation of hidden corrosion are considered challenging yet crucial activities in many sensitive industrial plants where preventing the loss of containment or structural reliability are paramount. In the last two decades, infrared (IR) thermography has proved to be a reliable means for inspection of corrosion or other sub-surface anomalies in low to mid thickness metallic mediums. The foundation of using IR thermography for defect detection and characterisation is based on active thermography. In this method of inspection, an external excitation source is deployed for the purpose of stimulating thermal evolutions inside objects. The presence of sub-surface defects disrupts the evolution of electromagnetic pulse inside an object. The reflection of altered pulse at the surface can be recorded through thermal camera in the form of temperature anomalies. Through authors’ previous works, cold thermography has shown that it can be a viable defect detection alternative to the most commonly used means of active thermography, known as heating. In the current work, the characterisation of defect dimensions, i.e., depth and diameter, has been explored. A simple analytical model for thermal contrast over defect is used in order to approximate the defect depth and diameter. This is achieved by comparing the similarities of the model and the experimental contrast time-series. A method of time-series similarity measurement known as dynamic time wrapping (DTW) is used to score the similarity between a pair of model and experiment time-series. The final outcome of the proposed experimental setup has revealed that there is a good potential to predict the metal loss of up to 50% in mid-thickness substrate even by deploying a less accurate nonradiometric thermal device and no advanced image processing.https://www.mdpi.com/1424-8220/22/18/7098cold infrared thermographynon-destructive testingmetal loss defect characterisationdefect depth predictionstructural health monitoringvision-based sensors |
| spellingShingle | Siavash Doshvarpassand Xiangyu Wang Sub-Surface Defect Depth Approximation in Cold Infrared Thermography Sensors cold infrared thermography non-destructive testing metal loss defect characterisation defect depth prediction structural health monitoring vision-based sensors |
| title | Sub-Surface Defect Depth Approximation in Cold Infrared Thermography |
| title_full | Sub-Surface Defect Depth Approximation in Cold Infrared Thermography |
| title_fullStr | Sub-Surface Defect Depth Approximation in Cold Infrared Thermography |
| title_full_unstemmed | Sub-Surface Defect Depth Approximation in Cold Infrared Thermography |
| title_short | Sub-Surface Defect Depth Approximation in Cold Infrared Thermography |
| title_sort | sub surface defect depth approximation in cold infrared thermography |
| topic | cold infrared thermography non-destructive testing metal loss defect characterisation defect depth prediction structural health monitoring vision-based sensors |
| url | https://www.mdpi.com/1424-8220/22/18/7098 |
| work_keys_str_mv | AT siavashdoshvarpassand subsurfacedefectdepthapproximationincoldinfraredthermography AT xiangyuwang subsurfacedefectdepthapproximationincoldinfraredthermography |