In recent years new diagnostics methodologies have emerged, with particular interest into machinery operating in non-stationary conditions. In fact continuous speed changes and variable loads make non-trivial the spectrum analysis. A variable speed means a variable characteristic fault frequency related to the damage that is no more recognizable in the spectrum. To overcome this problem the scientific community proposed different approaches listed in two main categories: model-based approaches and expert systems. In this context the paper aims to present a simple expert system derived from the mechanisms of the immune system called Euclidean Distance Minimization, and its application in a real case of bearing faults recognition. The proposed method is a simplification of the original process, adapted by the class of Artificial Immune Systems, which proved to be useful and promising in different application fields. Comparative results are provided, with a complete explanation of the algorithm and its functioning aspects

Artificial Immune System via Euclidean Distance Minimization for Anomaly Detection in Bearings / Montechiesi, Luca; Cocconcelli, Marco; Rubini, Riccardo. - In: MECHANICAL SYSTEMS AND SIGNAL PROCESSING. - ISSN 0888-3270. - STAMPA. - 76-77:(2016), pp. 380-393. [10.1016/j.ymssp.2015.04.017]

Artificial Immune System via Euclidean Distance Minimization for Anomaly Detection in Bearings

COCCONCELLI, Marco;RUBINI, Riccardo
2016-01-01

Abstract

In recent years new diagnostics methodologies have emerged, with particular interest into machinery operating in non-stationary conditions. In fact continuous speed changes and variable loads make non-trivial the spectrum analysis. A variable speed means a variable characteristic fault frequency related to the damage that is no more recognizable in the spectrum. To overcome this problem the scientific community proposed different approaches listed in two main categories: model-based approaches and expert systems. In this context the paper aims to present a simple expert system derived from the mechanisms of the immune system called Euclidean Distance Minimization, and its application in a real case of bearing faults recognition. The proposed method is a simplification of the original process, adapted by the class of Artificial Immune Systems, which proved to be useful and promising in different application fields. Comparative results are provided, with a complete explanation of the algorithm and its functioning aspects
5-mag-2015
76-77
380
393
Artificial Immune System via Euclidean Distance Minimization for Anomaly Detection in Bearings / Montechiesi, Luca; Cocconcelli, Marco; Rubini, Riccardo. - In: MECHANICAL SYSTEMS AND SIGNAL PROCESSING. - ISSN 0888-3270. - STAMPA. - 76-77:(2016), pp. 380-393. [10.1016/j.ymssp.2015.04.017]
Montechiesi, Luca; Cocconcelli, Marco; Rubini, Riccardo
File in questo prodotto:
File Dimensione Formato  
MSSP 76-77 (2016) Montechiesi Cocconcelli Rubini.pdf

non disponibili

Tipologia: Versione pubblicata dall'editore
Dimensione 699.09 kB
Formato Adobe PDF
699.09 kB Adobe PDF   Visualizza/Apri   Richiedi una copia
MSSP_R1_completo.pdf

Open access

Tipologia: Versione dell'autore revisionata e accettata per la pubblicazione
Dimensione 901.32 kB
Formato Adobe PDF
901.32 kB Adobe PDF Visualizza/Apri
Pubblicazioni consigliate

Licenza Creative Commons
I metadati presenti in IRIS UNIMORE sono rilasciati con licenza Creative Commons CC0 1.0 Universal, mentre i file delle pubblicazioni sono rilasciati con licenza Attribuzione 4.0 Internazionale (CC BY 4.0), salvo diversa indicazione.
In caso di violazione di copyright, contattare Supporto Iris

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/1073651
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 27
  • ???jsp.display-item.citation.isi??? 20
social impact