Nell’ambito del corso della laurea magistrale in ingegneria dell’automazione “Dynamical Systems Theory”, “Dynamical Systems Theory”, in collaborazione con il Decision and Control Laboratory, l’Ing Medolla del Centro Studi Componenti per Veicoli (Bosch CVIT) terrà un seminario gratuito dal titolo “Data-based predictive diagnostics for common rail high pressure pums”, aperto a studenti e dottorandi del Politecnico di Bari.
Titolo: Data-based predictive diagnostics for common rail high pressure pums
Relatore: Ciro Medolla, Centro Studi Componenti per Veicoli (Bosch CVIT)
Luogo e data: Martedì 20 dicembre ore 13 in aula Q, Politecnico di Bari.
Abstract: Predictive maintenance improves product lifetime over repairing costs for the end user. Data-based models allow to estimate the state of health of equipment and predict when it will fail. When failure evolution over time is not clear, the data-driven approach can be also helpful to identify relevant features for the estimation of state of health. We have used this methods to get knowledge about drive-train failure in Common Rail High Pressure Pump, identifying the main indicators of damage evolution with the aim of predicting when it will fail. The method and results of the analysis will be presented with an overview on machine learning models.
