Bueno, Douglas Domingues [UNESP]Marqui, Clayton Rodrigo [UNESP]Santos, Rodrigo Borges [UNESP]Da Silva, SamuelJunior, Vicente Lopes [UNESP]2014-05-272014-05-272008-12-01Conference Proceedings of the Society for Experimental Mechanics Series.2191-56442191-5652http://hdl.handle.net/11449/70841Structural Health Monitoring (SHM) denotes a system with the ability to detect and interpret adverse changes in structures in order to improve reliability and reduce life-cycle costs. The greatest challenge for designing a SHM system is knowing what changes to look for and how to classify them. Different approaches for SHM have been proposed for damage identification, each one with advantages and drawbacks. This paper presents a methodology for improvement in vibration signal analysis using statistics information involving the probability density. Generally, the presence of noises in input and output signals results in false alarms, then, it is important that the methodology can minimize this problem. In this paper, the proposed approach is experimentally tested in a flexible plate using a piezoelectric (PZT) actuator to provide the disturbance.engDamage detectionFalse alarmsProbability densityPZT actuatorTime seriesDamage IdentificationDetection approachFlexible platesInput and outputsLifecycle costsProbability densitiesPZTVibration signal analysisActuatorsAlarm systemsErrorsExhibitionsStructural dynamicsTrabalho apresentado em eventoAcesso aberto2-s2.0-848615565111457178419328525