NEW MAGNETIC LINEAR SENSOR FOR CRACK MONITORING IN STRUCTURES

Main Article Content

Sergej Evtushenko
Maksim Zheleznov
Mikhail Kuchumov
Liubov Adamtsevich

Abstract

Due to the recent deployment of new sensing technologies and monitoring devices aiming to control technical condition of structures and its safety, the problem of optimization of data acquisition process and economic expediency during Structural Health Monitoring has arisen. This article presents the design and implementation of a new linear displacement sensor prototype with advanced functionality capable to measure three significant parameters affecting the condition of concrete and brick structures: cracks width, environmental temperature and humidity. The measuring method is based on the efficient principle of converting input values using Hall effect, which is rarely found in structural monitoring. The sensor prototype also includes a hardware set for immediate processing and transmitting data, which ensures efficient remote monitoring. As a result of the work, research and analysis of methods and principles for measuring linear displacements were carried out, selection and justification of the choice of hardware components of the sensor were performed, electronic circuit and functional diagrams were developed. Furthermore, work was done on modeling the structural elements of the sensor and their final production was executed. According to the results of tests of the sensor prototype, numerical characteristics were obtained, its performance was confirmed and, eventually, the ways of further improvement are proposed.  

Downloads

Download data is not yet available.

Article Details

How to Cite
Evtushenko, S., Zheleznov, M., Kuchumov, M., & Adamtsevich, L. (2025). NEW MAGNETIC LINEAR SENSOR FOR CRACK MONITORING IN STRUCTURES. International Journal for Computational Civil and Structural Engineering, 21(1), 105-120. https://doi.org/10.22337/2587-9618-2025-21-1-105-120
Section
Articles

References

Evtushenko S.I., Kuchumov M.A. Linear displacement sensor for use in monitoring systems for engineering structures of civil infrastructure facilities. Actual problems of computer modeling of structures and constructions: Abstracts of reports of the VIIIth international symposium / FSBEI HE "Tambov State Technical University". - Tambov, 2023.–379-381

Bao, X., Li, Z., Wang, Z. (2019). Challenges in Crack Detection for Bridge Structures: A Review, Journal of Bridge Engineering, 24(3), 112-125.

Gao, Y., Liu, F., & Yang, H. (2018). Advanced Non-Destructive Testing Methods for Crack Detection in Bridges, Structural Health Monitoring, 15(5), 421-438.

Johnson, M., Kim, J., Singh, A. (2020). Data Management and Interpretation in Bridge Health Monitoring Systems, Computers and Structures, 89(2), 102-114.

Kim, S., Park, D., & Lee, H. (2018). Impact of Environmental Factors on Crack Monitoring in Bridges, Journal of Civil Engineering and Management, 14(6), 353-366.

Cabboi A, Gentile C, Saisi A. (2017) From continuous vibration monitoring to FEM-based damage assessment: Application on a stone-masonry tower, Construction Buildings Materials, 156, 2017 - pp. 252-265

Orban Z. (2004) Assessment, reliability and maintenance of masonry arch railway bridges in Europe, ARCH´04 P. Roca and E. Oñate (Eds) CIMNE, Barcelona, p. 5-8

Huang, Z., Fang, X., Guo, S. (2019). Wireless Sensor Networks in Bridge Monitoring: A Review, Sensors, 19(15), 3342.

Vega R.C., Cubas G., Sandoval-Chileño M.A., Castañeda Briones L.A. (2022) Position Measurements Using Magnetic Sensors for a Shape Memory Alloy Linear Actuator, Sensors,22(19), 7460; https://doi.org/10.3390/s22197460

Yan L., Zhang H., Ye P. (2017) Mover Position Detection for PMTLM Based on Linear Hall Sensors through EKF Processing, Sensors,17(4), 782; https://doi.org/10.3390/s17040782

Zhang J., Shi Y., Huang Y. (2022) A Displacement Sensing Method Based on Permanent Magnet and Magnetic Flux Measurement, Sensors, 22(12), 4326; https://doi.org/10.3390/s22124326

Gkantou, M., Muradov, M., Kamaris, G.S., Hashim H., Atherton, W., Kot P. (2023) Novel electromagnetic sensors embedded in reinforced concrete beams for crack detection, Sensors (Switzerland) 19(23), 5175.

Ubertini, F., Comanducci, G., Cavalagli, N., Laura Pisello, A., Luigi Materazzi, A., Cotana, F. (2017) Environmental effects on natural frequencies of the San Pietro bell tower in Perugia, Italy, and their removal for structural performance assessment, Mechanical Systems and Signal Processing, vol. 82, pp. 307-322, 2017, doi: 10.1016/j.ymssp.2016.05.025

Su, Z., Zhou, C., Hong, M., Cheng, L., Wang, Q., Qing, X. (2014) Acousto-ultrasonics-based fatigue damage characterization: Linear versus nonlinear signal features, Mechanical Systems and Signal Processing, vol. 45, pp. 225-239, doi: 10.1016/j.ymssp.2013.10.017

Shen, Y., Giurgiutiu, V. (2014) Predictive modeling of nonlinear wave propagation for structural health monitoring with piezoelectric wafer active sensors, Journal of Intelligent Material Systems and Structures, vol. 25, pp. 506-520, 2014, doi: 10.1177/1045389X13500572

Hong, M., Su, Z., Lu, Y., Sohn, H., Qing, X. (2015) Locating fatigue damage using temporal signal features of nonlinear Lamb waves, Mechanical Systems and Signal Processing, vol. 60, pp. 182-197, doi: 10.1016/j.ymssp.2015.01.020

Muñoz, C.Q.G., Márquez, F.P.G. (2016) A new fault location approach for acoustic emission techniques in wind turbines, Energies, vol. 9, doi: 10.3390/en9010040

Rodríguez, G., Casas, J.R., Villaba, S. (2015) Cracking assessment in concrete structures by distributed optical fiber, Smart Materials and Structures, vol. 24, doi: 10.1088/0964-1726/24/3/035005

Romhány, G., Czigány, T., Karger-Kocsis, J. (2017) Failure Assessment and Evaluation of Damage Development and Crack Growth in Polymer Composites Via Localization of Acoustic Emission Events: A Review, Polymer Reviews, vol. 57, pp. 397-439, doi: 10.1080/15583724.2017.1309663

Gkantou, M., Muradov, M., Kamaris, G.S., Hashim, K., Atherton, W., Kot, P. (2019) Novel electromagnetic sensors embedded in reinforced concrete beams for crack detection, Sensors (Switzerland), vol. 19, doi: 10.3390/s19235175

Xu, K., Ren, C., Deng, Q., Jin, Q., Chen, X. (2018) Real-time monitoring of bond slip between GFRP bar and concrete structure using piezoceramic transducer-enabled active sensing, Sensors (Switzerland), vol. 18, doi: 10.3390/s18082653

Wang, R., Wu, Q., Yu, F., Okabe, Y., Xiong, K. (2019) Nonlinear ultrasonic detection for evaluating fatigue crack in metal plate, Structural Health Monitoring, vol. 18, pp. 869-881, doi: 10.1177/1475921718784451

Tung, S.-T., Yao, Y., Glisic, B. (2014) Sensing sheet: The sensitivity of thin-film full-bridge strain sensors for crack detection and characterization, Measurement Science and Technology, vol. 25, doi: 10.1088/0957-0233/25/7/075602

Bao, Y., Tang, F., Chen, Y., Meng, W., Huang, Y., Chen, G. (2016) Concrete pavement monitoring with PPP-BOTDA distributed strain and crack sensors, Smart Structures and Systems, vol. 18, pp. 405-423 doi: 10.12989/sss.2016.18.3.405

Hou, Y., Wang, L., Sun, R., Zhang, Y., Gu, M., Zhu, Y., Tong, Y., Liu, X., Wang, Z., Xia, J., Hu, Y., Wei, L., Yang, C., Chen, M. (2022) Crack-Across-Pore Enabled High-Performance Flexible Pressure Sensors for Deep Neural Network Enhanced Sensing and Human Action Recognition, ACS Nano, vol. 16, pp. 8358-8369, doi: 10.1021/acsnano.2c02609

Tarpø, M., Nabuco, B., Georgakis, C., Brincker, R. (2020) Expansion of experimental mode shape from operational modal analysis and virtual sensing for fatigue analysis using the modal expansion method, International Journal of Fatigue, vol. 130, doi: 10.1016/j.ijfatigue.2019.105280

Shen, Y., Wang, J., Xu, W. (2018) Nonlinear features of guided wave scattering from rivet hole nucleated fatigue cracks considering the rough contact surface condition, Smart Materials and Structures, vol. 27, doi: 10.1088/1361-665X/aadd2d

Papoutsidakis M., Drosos C., Chatzopoulos A. (2018) Position Sensors – A Brief Guide of Use of the Most Common Types / International Journal of Computer Applications, p. 11.

Rainieri, C.; Fabbrocino, G.; Cosenza, E. (2008) Integrated systems for structural health monitoring: Worldwide applications and perspectives. In Proceedings of the 4th European Workshop on Structural Health Monitoring; Uhl, T., Ostachowicz, W., Holnicki-Szulc, J., Eds.; DEStech Publications, Inc.: Lancaster, PA, USA; p. 4

Li Z., Jin Z. Shao S., Zhao T., Wang P. (2019) Influence of Moisture Content on Electromagnetic Response of Concrete Studied Using a Homemade Apparatus, Sensors, 19(21), 4637; https://doi.org/10.3390/s19214637

Leyang Yan, Hui Zhang, Peiqing Ye.(2017) Mover Position Detection for PMTLM Based on Linear Hall Sensors through EKF Processing // Sensors 17(4), 782; https://doi.org/10.3390/s17040782 - p. 2.

Nong S.-X., Yang D.-H., Yi T.-H. (2021) Pareto-Based Bi-Objective Optimization Method of Sensor Placement in Structural Health Monitoring // Buildings 11(11), 549; https://doi.org/10.3390/buildings11110549

Kuchumov M., Evtushenko S.(2022) New Soil Stress Measurement Sensor Based on the Effect of Elastic Charging of Electrodes / Buildings 12(3), 327; https://doi.org/10.3390/buildings12030327

Similar Articles

You may also start an advanced similarity search for this article.