Defining A Conceptual Framework for Vibration-Based Damage Detection Platforms Using Blockchain

Document Type : Original Article

Authors

1 Department of Civil Engineering, University of Malaya, 50603 Kuala Lumpur, Malaysia.

2 Department of Quantity Surveying, University of Malaya, 50603 Kuala Lumpur, Malaysia.

3 Department of Mechanical Engineering, University of Malaya, 50603 Kuala Lumpur, Malaysia.

4 Department of Artificial Intelligence, University of Malaya, 50603 Kuala Lumpur, Malaysia.

Abstract

Current vibration-based damage detection consists of two main components, including modal parameter estimation methods and detection techniques. The second component employs the first part to detect and locate damage. Therefore, both are influenced by each other. They are typically predicted upon centralized data collection techniques, which significantly affect the ability to extract information on the structural health condition. Besides, the modal domain methods play an important role in structural damage identification and their popularity is much more than time domain or frequency domain approach. In the same line, an advanced decentralized database technology is required for the aforesaid techniques to overcome high maintenance cost of centralized approaches. Therefore, this study aims to improve the reliability and efficiency of current damage detection platforms through the integration of vibration-based methods and blockchain. To this end, a conceptual framework is proposed to make a connection between hardware and software components of structural damage detection.

Keywords

Main Subjects


[1] Gordan M, Razak HA, Ismail Z, Ghaedi K. Data mining based damage identification using imperialist competitive algorithm and artificial neural network. Latin American Journal of Solids and Structures. 2018;15(8). [View at Google Scholar] ; [View at Publisher]
[2] Bazazan Lotfi S, Rahimi M. A Study on Vulnerability of Urban Neighborhoods to Earthquake (Case Study: Farahzad Neighborhood, Tehran). Journal of civil Engineering and Materials Application. 2017 Jun 1;1(1):1-7. [View at Google Scholar] ; [View at Publisher]
[3] Gordan M, Razak HA, Ismail Z, Ghaedi K. Recent developments in damage identification of structures using data mining. Latin American Journal of Solids and Structures. 2017;14(13):2373-401. [View at Google Scholar] ; [View at Publisher]
[4] Gordan M, Ismail Z, Razak HA, Ghaedi K, Ibrahim Z, Tan ZX, Ghayeb HH. Data mining-based damage identification of a slab-on-girder bridge using inverse analysis. Measurement. 2020 Feb 1;151:107175. [View at Google Scholar] ; [View at Publisher]
[5] Gordan M, Ismail Z, Razak HA, Ibrahim Z. Vibration-Based Structural Damage Identification Using Data Mining. In: 24th International Congress on Sound and Vibration (ICSV24) London. 2017a. [View at Publisher]
[6] Türker T. Ambient vibration test of building base slab for different ground conditions. Measurement. 2014 Jun 1;52:77-84. [View at Google Scholar] ; [View at Publisher]
[7] Jo BW, Khan RM, Lee YS. Hybrid blockchain and internet-of-things network for underground structure health monitoring. Sensors. 2018 Dec;18(12):4268. [View at Google Scholar] ; [View at Publisher]
[8] Talebkhah M, Sali A, Marjani M, Gordan M, Hashim SJ, Rokhani FZ. Edge computing: Architecture, Applications and Future Perspectives. In: IICAIET2020 (IEEE International Conference on Artificial intelligence in Engineering and Technology). Sabah, Malaysia; 2020. [View at Publisher]
[9] Casino F, Dasaklis TK, Patsakis C. A systematic literature review of blockchain-based applications: current status, classification and open issues. Telematics and informatics. 2019 Mar 1;36:55-81. [View at Google Scholar] ; [View at Publisher]
[10] Hooman M. Model updating and damage detection of frame structures using output-only measurements/Hooman Monajemi (Doctoral dissertation, University of Malaya). [View at Google Scholar] ; [View at Publisher]
[11] Tan ZX, Thambiratnam DP, Chan TH, Gordan M, Abdul Razak H. Damage detection in steel-concrete composite bridge using vibration characteristics and artificial neural network. Structure and Infrastructure Engineering. 2020 Sep 1;16(9):1247-61. [View at Google Scholar] ; [View at Publisher]
[12] Lee LS, Karbhari VM, Sikorsky CH. Investigation of integrity and effectiveness of RC bridge deck rehabilitation with CFRP composites. SSRP. 2004;8. [View at Google Scholar] ; [View at Publisher]
[13] Qu CX, Yi TH, Li HN. Mode identification by eigensystem realization algorithm through virtual frequency response function. Structural Control and Health Monitoring. 2019 Oct;26(10):e2429. [View at Google Scholar] ; [View at Publisher]
[14] Rahman AG, Ong ZC, Ismail Z. Enhancement of coherence functions using time signals in Modal Analysis. Measurement. 2011 Dec 1;44(10):2112-23. [View at Google Scholar] ; [View at Publisher]
[15] Brincker R, Ventura C. Introduction to operational modal analysis. John Wiley & Sons; 2015 Sep 8. [View at Google Scholar] ; [View at Publisher]
[16] Hou J, Jankowski Ł, Ou J. Frequency-domain substructure isolation for local damage identification. Advances in Structural Engineering. 2015 Jan;18(1):137-53. [View at Google Scholar] ; [View at Publisher]
[17] Gordan M, Razak HA, Ismail Z, Ghaedi K, Tan ZX, Ghayeb HH. A hybrid ANN-based imperial competitive algorithm methodology for structural damage identification of slab-on-girder bridge using data mining. Applied Soft Computing. 2020 Mar 1;88:106013. [View at Google Scholar] ; [View at Publisher]
[18] Abdo M. Structural health monitoring, history, applications and future. A review book. Open Science. 2014. [View at Google Scholar] ; [View at Publisher]
[19] Rytter T. Vibrational Based Inspection of Civil Engineering Structures. PhD Thesis, Department of Building Technology and Structural Engineering, Aalborg University, Denmark; 1993. [View at Google Scholar] ; [View at Publisher]
[20] Rehman SK, Ibrahim Z, Memon SA, Jameel M. Nondestructive test methods for concrete bridges: A review. Construction and building materials. 2016 Mar 15;107:58-86. [View at Google Scholar] ; [View at Publisher]
[21] Luo D, Ma J, Ibrahim Z, Ismail Z. Etched FBG coated with polyimide for simultaneous detection the salinity and temperature. Optics Communications. 2017 Jun 1;392:218-22. [View at Google Scholar] ; [View at Publisher]
[22] Li Z, Guo J, Liang W, Xie X, Zhang G, Wang S. Structural health monitoring based on realadaboost algorithm in wireless sensor networks. InInternational Conference on Wireless Algorithms, Systems, and Applications 2014 Jun 23 (pp. 236-245). Springer, Cham. [View at Google Scholar] ; [View at Publisher]
[23] Chin S, Yoon S, Choi C, Cho C. RFID+ 4 D CAD for progress management of structural steel works in high-rise buildings. Journal of Computing in Civil Engineering. 2008 Mar;22(2):74-89. [View at Google Scholar] ; [View at Publisher]
[24] Gordan M, Ismail Z, Ghaedi K, Ibrahim Z, Hashim H, Ghayeb HH, Talebkhah M. A Brief Overview and Future Perspective of Unmanned Aerial Systems for In-Service Structural Health Monitoring. [View at Google Scholar] ; [View at Publisher]
[25] Belghith A, Koubaa A, Shakshuki E. Challenges and trends in wireless ubiquitous computing systems. Pers Ubiquitous Comput. 2011;15(8):781–2. [View at Google Scholar] ; [View at Publisher]
[26] Gürkaynak G, Yılmaz İ, Yeşilaltay B, Bengi B. Intellectual property law and practice in the blockchain realm. Computer law & security review. 2018 Aug 1;34(4):847-62. [View at Google Scholar] ; [View at Publisher]
[27] Gordan M, Ismail Z, Ibrahim Z, Hashim H. Data Mining Technology for Structural Control Systems: Concept, Development, and Comparison. InRecent Trends in Artificial Neural Networks-from Training to Prediction 2019 Oct 25. IntechOpen. [View at Google Scholar] ; [View at Publisher]
[28] Sikorski JJ, Haughton J, Kraft M. Blockchain technology in the chemical industry: Machine-to-machine electricity market. Applied energy. 2017 Jun 1;195:234-46. [View at Google Scholar] ; [View at Publisher]
[29] Dorri A, Kanhere SS, Jurdak R. MOF-BC: A memory optimized and flexible blockchain for large scale networks. Future Generation Computer Systems. 2019 Mar 1;92:357-73. [View at Google Scholar] ; [View at Publisher]
[30] Severeijns L. What is blockchain? How is it going to affect Business? Vrije Univ Amsterdam. 2017. [View at Publisher]
[31] Makhdoom I, Abolhasan M, Abbas H, Ni W. Blockchain's adoption in IoT: The challenges, and a way forward. Journal of Network and Computer Applications. 2019 Jan 1;125:251-79. [View at Google Scholar] ; [View at Publisher]