| Type of Material: | Thesis |
| Title: | Piezo based structural health monitoring of concrete systems using machine learning |
| Researcher: | Bansal, Tushar |
| Guide: | Talakokula, Visalakshi | Sathujoda, Prabhakar |
| Department: | Department of Civil Engineering |
| Publisher: | Bennett University |
| Place: | Greater Noida |
| Year: | 2022 |
| Language: | English |
| Subject: | Engineering | Engineering and Technology | Engineering Marine | Civil Engineering | Engineering and Technology |
| Dissertation/Thesis Note: | PhD; Department of Civil Engineering, Bennett University, Greater Noida; 2022 |
| Fulltext: | Shodhganga |
| 003 | IN-AhILN | |
| 005 | 2026-10-12 18:02:02 | |
| 008 | __ | 261012t2022||||ii#||||g|m||||||||||eng|| |
| 035 | __ | |a(IN-AhILN)th_464123 |
| 040 | __ | |dIN-AhILN|aBENN_201310 |
| 041 | __ | |aeng |
| 100 | __ | |eResearcher|aBansal, Tushar |
| 110 | __ | |aDepartment of Civil Engineering|0U-0890|dGreater Noida|bBennett University|ein |
| 245 | __ | |aPiezo based structural health monitoring of concrete systems using machine learning |
| 260 | __ | |aGreater Noida|c2022|bBennett University |
| 502 | __ | |bPhD|d2022|cDepartment of Civil Engineering, Bennett University, Greater Noida |
| 518 | __ | |oDate of Award|d2022 |
| 518 | __ | |d2017|oDate of Registration |
| 518 | __ | |d2022|oDate of Completion |
| 520 | __ | |aMonitoring the health of infrastructure has become imperative now a days due to vast infrastructure development in the last few decades which has now aged. Proper monitoring of the structures during the construction as well as design life stage can avoid catastrophic failures. Strength and durability are the two main aspects of reinforced concrete structures and providing a real time monitoring of these are the big challenges which almost all the concrete researchers are working around the world. The field of structural health monitoring (SHM) using piezo sensors via electro-mechanical impedance (EMI) has grown tremendously in recent years can provide a solution to these issues. The application of machine learning (ML) techniques is experiencing exponential growth in SHM domain using sensors because of the immense capability of handling voluminous datasets and making past and future predictions based on input data used for training. The aim of the present research is to utilize smart sensors, namely PZT sen |
| 650 | __ | |aCivil Engineering|2UGC |
| 650 | __ | |aEngineering and Technology|2AIU |
| 653 | __ | |aEngineering |
| 653 | __ | |aEngineering and Technology |
| 653 | __ | |aEngineering Marine |
| 700 | __ | |aTalakokula, Visalakshi|eGuide |
| 700 | __ | |aSathujoda, Prabhakar|eGuide |
| 856 | __ | |uhttp://shodhganga.inflibnet.ac.in/handle/10603/446789|yShodhganga |
| 905 | __ | |afromsg |
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