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Fault diagnosis of single-phase induction motor based on acoustic signals.

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Title: Fault diagnosis of single-phase induction motor based on acoustic signals.
Authors: Glowacz, Adam1 adglow@agh.edu.pl
Source: Mechanical Systems & Signal Processing. Feb2019, Vol. 117, p65-80. 16p.
Subjects: Fault tolerance (Engineering), Induction motors, Acoustic signal processing, Stators, Rotating machinery
Abstract: Highlights • Methods of fault diagnosis of the single-phase induction motor were proposed. • Original method of feature extraction of acoustic signal called SMOFS-22-MULTIEXPANDED was developed. • Five states of the single-phase induction motor were analysed. • Efficiency of acoustic signal recognition was analysed. Abstract The paper presents description of bearing, stator and rotor fault diagnostic methods of a single-phase induction motor. The presented methods use acoustic signals. Five states of the single-phase induction motor were analysed: healthy motor, motor with shorted coils of auxiliary winding and main winding, motor with shorted coils of auxiliary winding, motor with broken rotor bar and faulty ring of squirrel-cage, motor with faulty bearing. A method of feature extraction of acoustic signals – SMOFS-22-MULTIEXPANDED (Shortened Method of Frequencies Selection Multiexpanded) was developed and implemented. The SMOFS-22-MULTIEXPANDED was implemented as feature extraction method of acoustic signals. Classification step was performed using the NN (the Nearest Neighbour) classifier. The proposed methods had good results for diagnosis of bearing, stator and rotor faults of the single-phase induction motor. The developed approach can find applications for fault diagnosis of other types of rotating machines. [ABSTRACT FROM AUTHOR]
Copyright of Mechanical Systems & Signal Processing 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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Header DbId: egs
DbLabel: Engineering Source
An: 131664648
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
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  Data: Fault diagnosis of single-phase induction motor based on acoustic signals.
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  Data: <searchLink fieldCode="AR" term="%22Glowacz%2C+Adam%22">Glowacz, Adam</searchLink><relatesTo>1</relatesTo><i> adglow@agh.edu.pl</i>
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  Data: <searchLink fieldCode="JN" term="%22Mechanical+Systems+%26+Signal+Processing%22">Mechanical Systems & Signal Processing</searchLink>. Feb2019, Vol. 117, p65-80. 16p.
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  Data: <searchLink fieldCode="DE" term="%22Fault+tolerance+%28Engineering%29%22">Fault tolerance (Engineering)</searchLink><br /><searchLink fieldCode="DE" term="%22Induction+motors%22">Induction motors</searchLink><br /><searchLink fieldCode="DE" term="%22Acoustic+signal+processing%22">Acoustic signal processing</searchLink><br /><searchLink fieldCode="DE" term="%22Stators%22">Stators</searchLink><br /><searchLink fieldCode="DE" term="%22Rotating+machinery%22">Rotating machinery</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Highlights • Methods of fault diagnosis of the single-phase induction motor were proposed. • Original method of feature extraction of acoustic signal called SMOFS-22-MULTIEXPANDED was developed. • Five states of the single-phase induction motor were analysed. • Efficiency of acoustic signal recognition was analysed. Abstract The paper presents description of bearing, stator and rotor fault diagnostic methods of a single-phase induction motor. The presented methods use acoustic signals. Five states of the single-phase induction motor were analysed: healthy motor, motor with shorted coils of auxiliary winding and main winding, motor with shorted coils of auxiliary winding, motor with broken rotor bar and faulty ring of squirrel-cage, motor with faulty bearing. A method of feature extraction of acoustic signals – SMOFS-22-MULTIEXPANDED (Shortened Method of Frequencies Selection Multiexpanded) was developed and implemented. The SMOFS-22-MULTIEXPANDED was implemented as feature extraction method of acoustic signals. Classification step was performed using the NN (the Nearest Neighbour) classifier. The proposed methods had good results for diagnosis of bearing, stator and rotor faults of the single-phase induction motor. The developed approach can find applications for fault diagnosis of other types of rotating machines. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Mechanical Systems & Signal Processing 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:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1016/j.ymssp.2018.07.044
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      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 16
        StartPage: 65
    Subjects:
      – SubjectFull: Fault tolerance (Engineering)
        Type: general
      – SubjectFull: Induction motors
        Type: general
      – SubjectFull: Acoustic signal processing
        Type: general
      – SubjectFull: Stators
        Type: general
      – SubjectFull: Rotating machinery
        Type: general
    Titles:
      – TitleFull: Fault diagnosis of single-phase induction motor based on acoustic signals.
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              M: 02
              Text: Feb2019
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              Y: 2019
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              Value: 117
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            – TitleFull: Mechanical Systems & Signal Processing
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