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Investigation of Thermal Effects in Structural Health Monitoring using Piezoelectric Sensors for Aerospace Applications

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dc.contributor.author Hussain, Bilal
dc.date.accessioned 2024-08-20T09:45:25Z
dc.date.available 2024-08-20T09:45:25Z
dc.date.issued 2024
dc.identifier.other 328719
dc.identifier.uri http://10.250.8.41:8080/xmlui/handle/123456789/45601
dc.description Supervisor: Dr. Anas bin Aqeel en_US
dc.description.abstract A Structural Health Monitoring (SHM) system can continuously report on the structure’s status, perform data analysis, and deliver assessment results automatically. SHM systems can play a very important role, especially in aerospace structures in which a variety of low-weight materials i.e. when composites are in use, where it is very necessary to know the health and degradation level of such structures. To measure the health of such structures using SHM systems various sensors/transducers are required. Piezoelectric sensors have been is used in SHM systems for the past few decades because of their many advantages such as robustness, fast response time, compact size, and versatility. A few active and passive technologies have been developed to make use of piezoelectric sensors for example Guided waves (GW), Acoustic emission and Electromechanical Impedance (EMI). The piezoelectric sensors have a vast variety of advantages but they are also prone to some disadvantages during their usage. These disadvantages mostly occur due to certain environmental effects like temperature, radiation, and vibration etc. Environmental effects and damages to the structure play a significant role on the data acquisition by the sensors. In this paper, we are trying to measure the effect of structural damage and temperature on the sensors used to collect the data for an EMI-based SHM system and develop a technique using various Machine Learning Algorithms to compensate for these effects. en_US
dc.language.iso en en_US
dc.publisher College of Electrical & Mechanical Engineering (CEME), NUST en_US
dc.subject Structural Health Monitoring (SHM), Electromechanical Impedance (EMI), Carbon Fiber, Machine Learning, en_US
dc.title Investigation of Thermal Effects in Structural Health Monitoring using Piezoelectric Sensors for Aerospace Applications en_US
dc.type Thesis en_US


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