Anais do Congresso Brasileiro de Automática 2020, 2020
A comparative analysis of machine learning techniques for rotating machine faults diagnosis based... more A comparative analysis of machine learning techniques for rotating machine faults diagnosis based on vibration spectra images is presented. The feature extraction of dierent types of faults, such as unbalance, misalignment, shaft crack, rotor-stator rub, and hydrodynamic instability, is performed by processing the spectral image of vibration orbits acquired during the rotating machine run-up. The classiers are trained with simulation data and tested with both simulation and experimental data. The experimental data are obtained from measurements performed on an rotor-disk system test rig supported on hydrodynamic bearings. To generate the simulated data, a numerical model of the rotating system is developed using the Finite Element Method (FEM). Deep learning, ensemble and traditional classication methods are evaluated. The ability of the methods to generalize the image classication is evaluated based on their performance in classifying experimental test patterns that were not used d...
Smart Materials, Adaptive Structures and Intelligent Systems, Volume 2, 2008
The aim of this paper is to evaluate the use of the Structural Health Monitoring (SHM) technique ... more The aim of this paper is to evaluate the use of the Structural Health Monitoring (SHM) technique based on the concept of electromechanical impedance for the assessment of low-energy impact damage in laminated carbon-fiber composite plates. The experiments were carried-out by using an especially designed pendulum, and were planned in such a way to accommodate a range of test conditions, such as impact energy and dimension of the impacting piece. Also, it was investigated the influence of the frequency band in which the impedance functions are measured. Additionally, statistical metamodels were built aiming at establishing functional relations between the values of the damage metric and impact energy for single and multiple impacts. The obtained results demonstrate the capability of the monitoring method to identify various damage levels corresponding to different impact conditions.
Structural Health Monitoring (SHM) is the process of damage identification in mechanical structur... more Structural Health Monitoring (SHM) is the process of damage identification in mechanical structures that encompasses four main phases: damage detection, damage localization, damage extent evaluation and prognosis of residual life. Among various existing SHM techniques, the one based on electromechanical impedance measurements has been considered as one of the most effective, especially in the identification of incipient damage. This method measures the variation of the electromechanical impedance of the structure as caused by the presence of damage by using piezoelectric transducers bonded on the surface of the structure (or embedded into it). The most commonly used smart material in the context of the present contribution is the lead zirconate titanate (PZT). Through these piezoceramic sensor-actuators, the electromechanical impedance, which is directly related to the mechanical impedance of the structure, is obtained as a frequency domain dynamic response. Based on the variation o...
Anais do Congresso Brasileiro de Automática 2020, 2020
A comparative analysis of machine learning techniques for rotating machine faults diagnosis based... more A comparative analysis of machine learning techniques for rotating machine faults diagnosis based on vibration spectra images is presented. The feature extraction of dierent types of faults, such as unbalance, misalignment, shaft crack, rotor-stator rub, and hydrodynamic instability, is performed by processing the spectral image of vibration orbits acquired during the rotating machine run-up. The classiers are trained with simulation data and tested with both simulation and experimental data. The experimental data are obtained from measurements performed on an rotor-disk system test rig supported on hydrodynamic bearings. To generate the simulated data, a numerical model of the rotating system is developed using the Finite Element Method (FEM). Deep learning, ensemble and traditional classication methods are evaluated. The ability of the methods to generalize the image classication is evaluated based on their performance in classifying experimental test patterns that were not used d...
Smart Materials, Adaptive Structures and Intelligent Systems, Volume 2, 2008
The aim of this paper is to evaluate the use of the Structural Health Monitoring (SHM) technique ... more The aim of this paper is to evaluate the use of the Structural Health Monitoring (SHM) technique based on the concept of electromechanical impedance for the assessment of low-energy impact damage in laminated carbon-fiber composite plates. The experiments were carried-out by using an especially designed pendulum, and were planned in such a way to accommodate a range of test conditions, such as impact energy and dimension of the impacting piece. Also, it was investigated the influence of the frequency band in which the impedance functions are measured. Additionally, statistical metamodels were built aiming at establishing functional relations between the values of the damage metric and impact energy for single and multiple impacts. The obtained results demonstrate the capability of the monitoring method to identify various damage levels corresponding to different impact conditions.
Structural Health Monitoring (SHM) is the process of damage identification in mechanical structur... more Structural Health Monitoring (SHM) is the process of damage identification in mechanical structures that encompasses four main phases: damage detection, damage localization, damage extent evaluation and prognosis of residual life. Among various existing SHM techniques, the one based on electromechanical impedance measurements has been considered as one of the most effective, especially in the identification of incipient damage. This method measures the variation of the electromechanical impedance of the structure as caused by the presence of damage by using piezoelectric transducers bonded on the surface of the structure (or embedded into it). The most commonly used smart material in the context of the present contribution is the lead zirconate titanate (PZT). Through these piezoceramic sensor-actuators, the electromechanical impedance, which is directly related to the mechanical impedance of the structure, is obtained as a frequency domain dynamic response. Based on the variation o...
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