A study is presented in this paper able to identify and to quantify the effects of sensor characteristics and of data processing aspects on the uncertainty of the features used for Condition Monitoring (CM) applications, based on a hybrid approach. The precision of the sensors and the modalities to perform the FFT and obtain the related features are evaluated, to improve the coherence of information deriving from the data obtained by means of a physics-based model and that gained from the experiments. Validation of the features related to both classes is expected to improve the fusion process of data and the accuracy of prognostic algorithms.
Validation of signal processing techniques for vibration measurements / D’Emilia, Giulio; Di Gasbarro, David; Gaspari, Antonella; Natale, Emanuela. - (2017). (Intervento presentato al convegno 4th Conference on Vibration Measurement, Together with 23rd TC3 Conference on the Measurement of Force, Mass and Torque and 13th TC5 Conference on the Measurement of Hardness tenutosi a Helsinki, Finland nel 30th May to 1st of June, 2017).
Validation of signal processing techniques for vibration measurements
Antonella Gaspari;
2017-01-01
Abstract
A study is presented in this paper able to identify and to quantify the effects of sensor characteristics and of data processing aspects on the uncertainty of the features used for Condition Monitoring (CM) applications, based on a hybrid approach. The precision of the sensors and the modalities to perform the FFT and obtain the related features are evaluated, to improve the coherence of information deriving from the data obtained by means of a physics-based model and that gained from the experiments. Validation of the features related to both classes is expected to improve the fusion process of data and the accuracy of prognostic algorithms.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
