Nowadays, machines-diagnostics via vibration monitoring is rising an always growing interest thanks to the huge and accurate amount of health information which could be extracted by the raw data coming from accelerometers. Damage severity, type and location of a fault are the kind of information which are buried in the time records. The scope of this paper is double: first, to present the huge amount of data which have been acquired on the rolling bearing test rig of the Dynamic and Identification Research Group (DIRG), in the Department of Mechanical and Aerospace Engineering at Politecnico di Torino and to share them with the scientific community; secondly, to present a statistical approach analysis and its performances as example of a simple technique to be fruitfully adopted for comparison. To this goal, a detailed presentation of the test rig is given, which comprehends different working conditions up to 30,000 rpm, damage types and levels, var- ious sensors positions and directions as well as an endurance test. The related time records can be downloaded from ftp://ftp.polito.it/people/DIRG_BearingData/. Afterword, tried-and-tested statistical tools are exploited to learn the information about bearing damages from this massive amounts of data. This ‘‘data mining” will be performed using inferential statistical techniques as analysis of variance (ANOVA), applied on usual statistical features, which characterize of the signal. A linear discriminant analysis (LDA) in the configuration proposed by Fisher will be also used to see if the data were classifiable in a multidimensional space with this basic algorithm. Finally, an Outlier Analysis based on Mahalanobis distance will be formulated, so as to distinguish a damage condition from the healthy state (training data), compensating when possible for environmental (temperature) and operational (speed and load) variations.

The Politecnico di Torino rolling bearing test rig: Description and analysis of open access data / Daga, Alessandro Paolo; Fasana, Alessandro; Marchesiello, Stefano; Garibaldi, Luigi. - In: MECHANICAL SYSTEMS AND SIGNAL PROCESSING. - ISSN 0888-3270. - STAMPA. - 120:(2019), pp. 252-273. [10.1016/j.ymssp.2018.10.010]

The Politecnico di Torino rolling bearing test rig: Description and analysis of open access data

Daga, Alessandro Paolo;Fasana, Alessandro;Marchesiello, Stefano;Garibaldi, Luigi
2019

Abstract

Nowadays, machines-diagnostics via vibration monitoring is rising an always growing interest thanks to the huge and accurate amount of health information which could be extracted by the raw data coming from accelerometers. Damage severity, type and location of a fault are the kind of information which are buried in the time records. The scope of this paper is double: first, to present the huge amount of data which have been acquired on the rolling bearing test rig of the Dynamic and Identification Research Group (DIRG), in the Department of Mechanical and Aerospace Engineering at Politecnico di Torino and to share them with the scientific community; secondly, to present a statistical approach analysis and its performances as example of a simple technique to be fruitfully adopted for comparison. To this goal, a detailed presentation of the test rig is given, which comprehends different working conditions up to 30,000 rpm, damage types and levels, var- ious sensors positions and directions as well as an endurance test. The related time records can be downloaded from ftp://ftp.polito.it/people/DIRG_BearingData/. Afterword, tried-and-tested statistical tools are exploited to learn the information about bearing damages from this massive amounts of data. This ‘‘data mining” will be performed using inferential statistical techniques as analysis of variance (ANOVA), applied on usual statistical features, which characterize of the signal. A linear discriminant analysis (LDA) in the configuration proposed by Fisher will be also used to see if the data were classifiable in a multidimensional space with this basic algorithm. Finally, an Outlier Analysis based on Mahalanobis distance will be formulated, so as to distinguish a damage condition from the healthy state (training data), compensating when possible for environmental (temperature) and operational (speed and load) variations.
File in questo prodotto:
File Dimensione Formato  
The Politecnico di Torino rolling bearing test rig_Description and analysis of open access data.pdf

accesso riservato

Descrizione: Articolo definitivo, veste editoriale
Tipologia: 2a Post-print versione editoriale / Version of Record
Licenza: Non Pubblico - Accesso privato/ristretto
Dimensione 4.17 MB
Formato Adobe PDF
4.17 MB Adobe PDF   Visualizza/Apri   Richiedi una copia
Description and analysis of open access data.pdf

Open Access dal 11/10/2020

Descrizione: Articolo definitivo, veste NON editoriale
Tipologia: 2. Post-print / Author's Accepted Manuscript
Licenza: Creative commons
Dimensione 6.41 MB
Formato Adobe PDF
6.41 MB Adobe PDF Visualizza/Apri
FTP_AREA.pdf

accesso aperto

Descrizione: Link all'area FTP da cui scaricare i dati
Tipologia: Altro materiale allegato
Licenza: Pubblico dominio
Dimensione 9.17 kB
Formato Adobe PDF
9.17 kB Adobe PDF Visualizza/Apri
Pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2716028
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo