{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,8]],"date-time":"2025-11-08T17:50:30Z","timestamp":1762624230159,"version":"build-2065373602"},"reference-count":37,"publisher":"MDPI AG","issue":"19","license":[{"start":{"date-parts":[[2019,10,4]],"date-time":"2019-10-04T00:00:00Z","timestamp":1570147200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004663","name":"Ministry of Science and Technology, Taiwan","doi-asserted-by":"publisher","award":["[MOST 107-2625-M-027-003 and MOST 108-2625-027-001]"],"award-info":[{"award-number":["[MOST 107-2625-M-027-003 and MOST 108-2625-027-001]"]}],"id":[{"id":"10.13039\/501100004663","id-type":"DOI","asserted-by":"publisher"}]},{"name":"National Center for Research on Earthquake Engineering, Taiwan","award":["2016"],"award-info":[{"award-number":["2016"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Image analysis techniques have been applied to measure the displacements, strain field, and crack distribution of structures in the laboratory environment, and present strong potential for use in structural health monitoring applications. Compared with accelerometers, image analysis is good at monitoring area-based responses, such as crack patterns at critical regions of reinforced concrete (RC) structures. While the quantitative relationship between cracks and structural damage depends on many factors, cracks need to be detected and quantified in an automatic manner for further investigation into structural health monitoring. This work proposes a damage-indexing method by integrating an image-based crack measurement method and a crack quantification method. The image-based crack measurement method identifies cracks locations, opening widths, and orientations. Fractal dimension analysis gives the flexural cracks and shear cracks an overall damage index ranging between 0 and 1. According to the orientations of the cracks analyzed by image analysis, the cracks can be classified as either shear or flexural, and the overall damage index can be separated into shear and flexural damage indices. These damage indices not only quantify the damage of an RC structure, but also the contents of shear and flexural failures. While the engineering significance of the damage indices is structure dependent, when the damage indexing method is used for structural health monitoring, the damage indices safety thresholds can further be defined based on the structure type under consideration. Finally, this paper demonstrates this method by using the results of two experiments on RC tubular containment vessel structures.<\/jats:p>","DOI":"10.3390\/s19194304","type":"journal-article","created":{"date-parts":[[2019,10,4]],"date-time":"2019-10-04T10:54:58Z","timestamp":1570186498000},"page":"4304","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Damage Indexing Method for Shear Critical Tubular Reinforced Concrete Structures Based on Crack Image Analysis"],"prefix":"10.3390","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1547-317X","authenticated-orcid":false,"given":"Yuan-Sen","family":"Yang","sequence":"first","affiliation":[{"name":"Department of Civil Engineering, National Taipei University of Technology, Taipei 106, Taiwan"}]},{"given":"Chia-Hao","family":"Chang","sequence":"additional","affiliation":[{"name":"Department of Civil Engineering, National Taipei University of Technology, Taipei 106, Taiwan"}]},{"given":"Chiun-lin","family":"Wu","sequence":"additional","affiliation":[{"name":"National Center for Research on Earthquake Engineering, Taipei 106, Taiwan"}]}],"member":"1968","published-online":{"date-parts":[[2019,10,4]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1695","DOI":"10.1016\/j.measurement.2012.04.018","article-title":"Optical fiber sensors for static and dynamic health monitoring of civil engineering infrastructures: Abode wall case study","volume":"45","author":"Antunes","year":"2012","journal-title":"Measurement"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"227","DOI":"10.1016\/j.conbuildmat.2015.12.019","article-title":"Experimental damage evaluation of reinforced concrete steel bars using piezoelectric sensors","volume":"105","author":"Karayannis","year":"2016","journal-title":"Constr. Build. Mater."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"740","DOI":"10.1061\/(ASCE)0733-9445(1985)111:4(740)","article-title":"Seismic Damage Analysis of Reinforced Concrete Buildings","volume":"111","author":"Park","year":"1985","journal-title":"J. Struct. Eng."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"429","DOI":"10.1061\/(ASCE)0733-9445(1987)113:3(429)","article-title":"Analytical Modeling of Hysteretic Behavior of R\/C Frames","volume":"113","author":"Roufaiel","year":"1987","journal-title":"J. Struct. Eng."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"719","DOI":"10.1002\/eqe.4290160507","article-title":"Seismic Damage Prediction Deterministic Methods\u2014Concepts and Procedures","volume":"16","author":"Powell","year":"1998","journal-title":"Earthq. Eng. Struct. Dyn."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"6","DOI":"10.1016\/j.softx.2017.10.009","article-title":"OpenSeesPy: Python library for the OpenSees finite element framework","volume":"7","author":"Zhu","year":"2018","journal-title":"SoftwareX"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"397","DOI":"10.1111\/mice.12259","article-title":"Direct-Iterative Hybrid Solution in Nonlinear Dynamic Structural Analysis","volume":"32","author":"Yang","year":"2017","journal-title":"Comput. Civ. Infrastruct. Eng."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"42","DOI":"10.1016\/j.simpat.2012.06.002","article-title":"An Online Optimization Method for Bridge Dynamic Hybrid Simulations","volume":"28","author":"Yang","year":"2018","journal-title":"Simul. Model. Pract. Theory"},{"key":"ref_9","first-page":"319","article-title":"Experimental Study of the Behavior of Beam-Column Connections with Expanded Beam Flanges","volume":"31","author":"Ma","year":"2019","journal-title":"Steel Compos. Struct."},{"key":"ref_10","unstructured":"Japan Building Disaster Prevention Association (2001). Standard for Seismic Evaluation of Existing Reinforced Concrete Buildings, Japan Building Disaster Prevention Association. Japanese edition of 2001, English Version 1st."},{"key":"ref_11","unstructured":"International Atomic Energy Agency (2002). Guidebook on Non-Destructive Testing of Concrete Structures, International Atomic Energy Agency."},{"key":"ref_12","unstructured":"Federal Highway Administration (2012). Bridge Inspector\u2019s Reference Manual."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Szel\u0105g, M. (2018). The Influence of Metakaolinite on the Development of Thermal Cracks in a Cement Matrix. Materials, 11.","DOI":"10.3390\/ma11040520"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1016\/j.compstruct.2019.01.024","article-title":"Digital Image Correlation (DIC) for Measurement of Strains and Displacements in Coarse, Low Volume-Fraction FRP Composites Used in Civil Infrastructure","volume":"212","author":"Castillo","year":"2019","journal-title":"Compos. Struct."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"205","DOI":"10.1016\/j.acme.2018.10.003","article-title":"Digital image correlation (DIC) on fresh cement mortar to quantify settlement and shrinkage","volume":"19","author":"Dzaye","year":"2019","journal-title":"Arch. Civ. Mech. Eng."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Yang, Y.-S. (2019). Measurement of Dynamic Responses from Large Structural Tests by Analyzing Non-Synchronized Videos. Sensors, 19.","DOI":"10.3390\/s19163520"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"16551","DOI":"10.3390\/s131216551","article-title":"Monitoring of Structures and Mechanical Systems Using Virtual Visual Sensors for Video Analysis: Fundamental Concept and Proof of Feasibility","volume":"13","author":"Schumacher","year":"2013","journal-title":"Sensors"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Salhaoui, M., Guerrero-Gonz\u00e1lez, A., Arioua, M., Ortiz, F.J., El Oualkadi, A., and Torregrosa, C.L. (2019). Smart Industrial IoT Monitoring and Control System Based on UAV and Cloud Computing Applied to a Concrete Plant. Sensors, 19.","DOI":"10.3390\/s19153316"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"199","DOI":"10.1016\/j.ymssp.2016.11.021","article-title":"Experimental validation of cost-effective vision-based structural health monitoring","volume":"88","author":"Feng","year":"2017","journal-title":"Mech. Syst. Signal Process."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"142","DOI":"10.1016\/j.measurement.2014.10.039","article-title":"A preliminary study on the response of steel structures using surveillance camera image with vision-based method during the Great East Japan Earthquake","volume":"62","author":"Cheng","year":"2015","journal-title":"Meas."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1155\/2016\/3954573","article-title":"A Review of Machine Vision-Based Structural Health Monitoring: Methodologies and Applications","volume":"2016","author":"Ye","year":"2016","journal-title":"J. Sensors"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Wu, C.L., Hsu, T.T.C., Chang, C.Y., Yang, H.C., Chang, C.C., Wang, K.J., Yang, Y.S., Mo, Y.L., Lu, H.J., and Chen, Y.C. (2018). Reversed Cyclic Tests of 1\/13 Scale Cylindrical Concrete Containment Structures, National Center for Research on Earthquake Engineering. Technical Report 18-001.","DOI":"10.1007\/978-981-13-3278-4_9"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1607","DOI":"10.1007\/s11340-013-9769-7","article-title":"Damage Assessment of Reinforced Concrete Structures Using Fractal Analysis of Residual Crack Patterns","volume":"53","author":"Farhidzadeh","year":"2013","journal-title":"Exp. Mech."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"120","DOI":"10.1016\/j.autcon.2018.03.012","article-title":"Image analysis method for crack distribution and width estimation for reinforced concrete structures","volume":"91","author":"Yang","year":"2018","journal-title":"Autom. Constr."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Cho, H.-W., Yoon, H.-J., and Yoon, J.-C. (2016). Analysis of Crack Image Recognition Characteristics in Concrete Structures Depending on the Illumination and Image Acquisition Distance through Outdoor Experiments. Sensors, 16.","DOI":"10.3390\/s16101646"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Yu, L., Tian, Y., and Wu, W. (2019). A Dark Target Detection Method Based on the Adjacency Effect: A Case Study on Crack Detection. Sensors, 19.","DOI":"10.3390\/s19122829"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Dorafshan, S., Thomas, R.J., and Maguire, M. (2019). Benchmarking Image Processing Algorithms for Unmanned Aerial System-Assisted Crack Detection in Concrete Structures. Infrastructures, 4.","DOI":"10.3390\/infrastructures4020019"},{"key":"ref_28","first-page":"1","article-title":"Metaheuristic Optimized Edge Detection for Recognition of Concrete Wall Cracks: A Comparative Study on the Performances of Roberts, Prewitt, Canny, and Sobel Algorithms","volume":"2018","author":"Hoang","year":"2018","journal-title":"Adv. Civ. Eng."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"731","DOI":"10.1111\/mice.12334","article-title":"Autonomous Structural Visual Inspection using Region-Based Deep Learning for Detecting Multiple Damage Types","volume":"33","author":"Cha","year":"2018","journal-title":"Comput. Aided Civ. Infrastruct. Eng."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"598","DOI":"10.1016\/j.engstruct.2017.10.070","article-title":"A novel unsupervised deep learning model for global and local health condition assessment of structures","volume":"156","author":"Rafiei","year":"2018","journal-title":"Eng. Struct."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"1031","DOI":"10.1016\/j.conbuildmat.2018.08.011","article-title":"Comparison of deep convolutional neural networks and edge detectors for image-based crack detection in concrete","volume":"186","author":"Dorafshan","year":"2018","journal-title":"Constr. Build. Mater."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"244","DOI":"10.1016\/j.conbuildmat.2019.01.150","article-title":"A fast adaptive crack detection algorithm based on a double-edge extraction operator of FSM","volume":"204","author":"Luo","year":"2019","journal-title":"Constr. Build. Mater."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"787","DOI":"10.1016\/j.aej.2017.01.020","article-title":"Crack detection using image processing: A critical review and analysis","volume":"57","author":"Mohan","year":"2018","journal-title":"Alex. Eng. J."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"99","DOI":"10.1016\/j.advengsoft.2015.02.005","article-title":"Thin crack observation in a reinforced concrete bridge pier test using image processing and analysis","volume":"83","author":"Yang","year":"2015","journal-title":"Adv. Eng. Softw."},{"key":"ref_35","unstructured":"Yang, Y.S. (2019, August 01). ImPro Stereo. National Taipei University of Technology. Available online: https:\/\/sites.google.com\/site\/improstereoen\/."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1002\/eqe.1111","article-title":"A Simple Image-Based Strain Measurement Method for Measuring the Strain Fields in an RC-Wall Experiment","volume":"41","author":"Yang","year":"2012","journal-title":"Earthq. Eng. Struct. Dyn."},{"key":"ref_37","unstructured":"Kaehler, A., and Bradski, G. (2016). Learning OpenCV3: Computer Vision in C++ with the OpenCV Library, O\u2019Reilly Media."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/19\/19\/4304\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T13:27:33Z","timestamp":1760189253000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/19\/19\/4304"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,10,4]]},"references-count":37,"journal-issue":{"issue":"19","published-online":{"date-parts":[[2019,10]]}},"alternative-id":["s19194304"],"URL":"https:\/\/doi.org\/10.3390\/s19194304","relation":{},"ISSN":["1424-8220"],"issn-type":[{"type":"electronic","value":"1424-8220"}],"subject":[],"published":{"date-parts":[[2019,10,4]]}}}