Characterization of the temperature, load and damage effects using piezoelectric transducer patches based on fuzzy clustering

• Autor(a) principal: Lopes, V. [UNESP]
• Data de Publicação: 2011
• Outros Autores: Gonsalez, C. G. [UNESP], Da Silva, S., Roy, S., Kode, K., Sunor, F.
• Tipo de documento: Artigo de conferência
• Idioma: eng
• Título da fonte: Repositório Institucional da UNESP
• Texto Completo: http://hdl.handle.net/11449/73036
• topic: Critical challenges; Damage effects; Data sets; Environmental conditions; Induced damage; Practical implementation; PZT; Sensor data; Sensor measurements; Aluminum; Fuzzy clustering; Intelligent structures; Maintenance; Piezoelectric transducers; Sensors

Structural Health Monitoring (SHM) denotes a system with the ability to detect and interpret adverse changes in a structure. One of the critical challenges for practical implementation of SHM system is the ability to detect damage under changing environmental conditions. This paper aims to characterize the temperature, load and damage effects in the sensor measurements obtained with piezoelectric transducer (PZT) patches. Data sets are collected on thin aluminum specimens under different environmental conditions and artificially induced damage states. The fuzzy clustering algorithm is used to organize the sensor measurements into a set of clusters, which can attribute the variation in sensor data due to temperature, load or any induced damage.