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Mechanical rotor unbalance monitoring based on system identification and signal processing approaches.

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Title: Mechanical rotor unbalance monitoring based on system identification and signal processing approaches.
Authors: Puerto-Santana, Cristian1,2 (AUTHOR) cpuerto@ainguraiiot.com, Ocampo-Martinez, Carlos2 (AUTHOR) carlos.ocampo@upc.edu, Diaz-Rozo, Javier1 (AUTHOR) jdiaz@ainguraiiot.com
Source: Journal of Sound & Vibration. Dec2022, Vol. 541, pN.PAG-N.PAG. 1p.
Subjects: System identification, Signal processing, Finite element method, Monitoring of machinery, Magnetic bearings, Mass production, Rotors
Abstract: Mechanical unbalance is an important source of vibrations that can cause malfunctions in rotodynamic machinery. In industrial applications, unbalance is a critical issue for mass production machines. Previous studies for detecting and monitoring unbalance are based on balancing machines, trial weights, and intrusive actuators, while other studies rely on signal processing techniques, finite element analysis and physical modeling. These methodologies have some critical drawbacks, especially when non-intrusive monitoring is required, such as having to trial weights or determine constructive parameters such as mass and stiffness. The proposed approach is based on detecting and monitoring the unbalance condition in rotatory machines using data extracted from vibration sensors and a rotation sensor fitted to the system supports. The methodology comprises two main steps: identifying the appropriate speed range for unbalance monitoring and the modal parameters of the rotor, and determining and continuously monitoring the unbalance condition. Signal processing and system identification techniques are used to estimate unbalance in the rotatory machine. Experimental results for two rotodynamic systems demonstrate satisfactory performance in identifying and monitoring different unbalance conditions. • A novel methodology for non intrusive mechanical unbalance monitoring is proposed. • The method selects the proper rotation speed for unbalance monitoring. • Unbalance is detected without using finite element analysis or trial weights. • Campbell diagrams modal parameters are estimated to compute unbalance. • The method is experimentally validated on two different rotodynamic systems. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Sound & Vibration is the property of Academic Press Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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  Availability: 0
Header DbId: egs
DbLabel: Engineering Source
An: 159821896
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
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  Data: Mechanical rotor unbalance monitoring based on system identification and signal processing approaches.
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  Data: <searchLink fieldCode="AR" term="%22Puerto-Santana%2C+Cristian%22">Puerto-Santana, Cristian</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<i> cpuerto@ainguraiiot.com</i><br /><searchLink fieldCode="AR" term="%22Ocampo-Martinez%2C+Carlos%22">Ocampo-Martinez, Carlos</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> carlos.ocampo@upc.edu</i><br /><searchLink fieldCode="AR" term="%22Diaz-Rozo%2C+Javier%22">Diaz-Rozo, Javier</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> jdiaz@ainguraiiot.com</i>
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Sound+%26+Vibration%22">Journal of Sound & Vibration</searchLink>. Dec2022, Vol. 541, pN.PAG-N.PAG. 1p.
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  Data: <searchLink fieldCode="DE" term="%22System+identification%22">System identification</searchLink><br /><searchLink fieldCode="DE" term="%22Signal+processing%22">Signal processing</searchLink><br /><searchLink fieldCode="DE" term="%22Finite+element+method%22">Finite element method</searchLink><br /><searchLink fieldCode="DE" term="%22Monitoring+of+machinery%22">Monitoring of machinery</searchLink><br /><searchLink fieldCode="DE" term="%22Magnetic+bearings%22">Magnetic bearings</searchLink><br /><searchLink fieldCode="DE" term="%22Mass+production%22">Mass production</searchLink><br /><searchLink fieldCode="DE" term="%22Rotors%22">Rotors</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Mechanical unbalance is an important source of vibrations that can cause malfunctions in rotodynamic machinery. In industrial applications, unbalance is a critical issue for mass production machines. Previous studies for detecting and monitoring unbalance are based on balancing machines, trial weights, and intrusive actuators, while other studies rely on signal processing techniques, finite element analysis and physical modeling. These methodologies have some critical drawbacks, especially when non-intrusive monitoring is required, such as having to trial weights or determine constructive parameters such as mass and stiffness. The proposed approach is based on detecting and monitoring the unbalance condition in rotatory machines using data extracted from vibration sensors and a rotation sensor fitted to the system supports. The methodology comprises two main steps: identifying the appropriate speed range for unbalance monitoring and the modal parameters of the rotor, and determining and continuously monitoring the unbalance condition. Signal processing and system identification techniques are used to estimate unbalance in the rotatory machine. Experimental results for two rotodynamic systems demonstrate satisfactory performance in identifying and monitoring different unbalance conditions. • A novel methodology for non intrusive mechanical unbalance monitoring is proposed. • The method selects the proper rotation speed for unbalance monitoring. • Unbalance is detected without using finite element analysis or trial weights. • Campbell diagrams modal parameters are estimated to compute unbalance. • The method is experimentally validated on two different rotodynamic systems. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Journal of Sound & Vibration is the property of Academic Press Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
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    Identifiers:
      – Type: doi
        Value: 10.1016/j.jsv.2022.117313
    Languages:
      – Code: eng
        Text: English
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        PageCount: 1
        StartPage: N.PAG
    Subjects:
      – SubjectFull: System identification
        Type: general
      – SubjectFull: Signal processing
        Type: general
      – SubjectFull: Finite element method
        Type: general
      – SubjectFull: Monitoring of machinery
        Type: general
      – SubjectFull: Magnetic bearings
        Type: general
      – SubjectFull: Mass production
        Type: general
      – SubjectFull: Rotors
        Type: general
    Titles:
      – TitleFull: Mechanical rotor unbalance monitoring based on system identification and signal processing approaches.
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      – PersonEntity:
          Name:
            NameFull: Puerto-Santana, Cristian
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          Name:
            NameFull: Ocampo-Martinez, Carlos
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          Name:
            NameFull: Diaz-Rozo, Javier
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            – D: 22
              M: 12
              Text: Dec2022
              Type: published
              Y: 2022
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              Value: 541
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