Current- and Vibration-Based Detection of Misalignment Faults in Synchronous Reluctance Motors
Misalignment faults in drive systems occur when the motor and load are not properly aligned, leading to deviations in the centerlines of the coupled shafts. These faults can cause significant damage to bearings, shafts, and couplings, making early detection essential. Traditional diagnostic techniqu...
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MDPI AG
2025-04-01
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| author | Angela Navarro-Navarro Vicente Biot-Monterde Jose E. Ruiz-Sarrio Jose A. Antonino-Daviu |
| author_facet | Angela Navarro-Navarro Vicente Biot-Monterde Jose E. Ruiz-Sarrio Jose A. Antonino-Daviu |
| author_sort | Angela Navarro-Navarro |
| collection | DOAJ |
| description | Misalignment faults in drive systems occur when the motor and load are not properly aligned, leading to deviations in the centerlines of the coupled shafts. These faults can cause significant damage to bearings, shafts, and couplings, making early detection essential. Traditional diagnostic techniques rely on vibration monitoring, which provides insights into both mechanical and electromagnetic fault signatures. However, its main drawback is the need for external sensors, which may not be feasible in certain applications. Alternatively, motor current signature analysis (MCSA) has proven effective in detecting faults without requiring additional sensors. This study investigates misalignment faults in synchronous reluctance motors (SynRMs) by analyzing both vibration and current signals under different load conditions and operating speeds. Fast Fourier transform (FFT) is applied to extract characteristic frequency components linked to misalignment. Experimental results reveal that the amplitudes of rotational frequency harmonics (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>1</mn><mi>x</mi><msub><mi>f</mi><mi>r</mi></msub></mrow></semantics></math></inline-formula>, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>2</mn><mi>x</mi><msub><mi>f</mi><mi>r</mi></msub></mrow></semantics></math></inline-formula>, and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>3</mn><mi>x</mi><msub><mi>f</mi><mi>r</mi></msub></mrow></semantics></math></inline-formula>) increase in the presence of misalignment, with <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>1</mn><mi>x</mi><msub><mi>f</mi><mi>r</mi></msub></mrow></semantics></math></inline-formula> exhibiting the most stable progression. Additionally, acceleration-based vibration analysis proves to be a more reliable diagnostic tool compared to velocity measurements. These findings highlight the potential of combining current and vibration analysis to enhance misalignment detection in SynRMs, improving predictive maintenance strategies in industrial applications. |
| format | Article |
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| language | English |
| publishDate | 2025-04-01 |
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| spelling | doaj-art-52d9e470478c48b8bc7fb8ffba6848d12025-08-20T02:18:09ZengMDPI AGMachines2075-17022025-04-0113431910.3390/machines13040319Current- and Vibration-Based Detection of Misalignment Faults in Synchronous Reluctance MotorsAngela Navarro-Navarro0Vicente Biot-Monterde1Jose E. Ruiz-Sarrio2Jose A. Antonino-Daviu3Instituto Tecnológico de la Energía (ITE), Universitat Politècnica de València (UPV), Camino de Vera S/N, 46022 Valencia, SpainInstituto Tecnológico de la Energía (ITE), Universitat Politècnica de València (UPV), Camino de Vera S/N, 46022 Valencia, SpainInstituto Tecnológico de la Energía (ITE), Universitat Politècnica de València (UPV), Camino de Vera S/N, 46022 Valencia, SpainInstituto Tecnológico de la Energía (ITE), Universitat Politècnica de València (UPV), Camino de Vera S/N, 46022 Valencia, SpainMisalignment faults in drive systems occur when the motor and load are not properly aligned, leading to deviations in the centerlines of the coupled shafts. These faults can cause significant damage to bearings, shafts, and couplings, making early detection essential. Traditional diagnostic techniques rely on vibration monitoring, which provides insights into both mechanical and electromagnetic fault signatures. However, its main drawback is the need for external sensors, which may not be feasible in certain applications. Alternatively, motor current signature analysis (MCSA) has proven effective in detecting faults without requiring additional sensors. This study investigates misalignment faults in synchronous reluctance motors (SynRMs) by analyzing both vibration and current signals under different load conditions and operating speeds. Fast Fourier transform (FFT) is applied to extract characteristic frequency components linked to misalignment. Experimental results reveal that the amplitudes of rotational frequency harmonics (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>1</mn><mi>x</mi><msub><mi>f</mi><mi>r</mi></msub></mrow></semantics></math></inline-formula>, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>2</mn><mi>x</mi><msub><mi>f</mi><mi>r</mi></msub></mrow></semantics></math></inline-formula>, and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>3</mn><mi>x</mi><msub><mi>f</mi><mi>r</mi></msub></mrow></semantics></math></inline-formula>) increase in the presence of misalignment, with <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>1</mn><mi>x</mi><msub><mi>f</mi><mi>r</mi></msub></mrow></semantics></math></inline-formula> exhibiting the most stable progression. Additionally, acceleration-based vibration analysis proves to be a more reliable diagnostic tool compared to velocity measurements. These findings highlight the potential of combining current and vibration analysis to enhance misalignment detection in SynRMs, improving predictive maintenance strategies in industrial applications.https://www.mdpi.com/2075-1702/13/4/319accelerationcurrent analysisdiagnosisfast Fourier transformmisalignmentsynchronous reluctance motor |
| spellingShingle | Angela Navarro-Navarro Vicente Biot-Monterde Jose E. Ruiz-Sarrio Jose A. Antonino-Daviu Current- and Vibration-Based Detection of Misalignment Faults in Synchronous Reluctance Motors Machines acceleration current analysis diagnosis fast Fourier transform misalignment synchronous reluctance motor |
| title | Current- and Vibration-Based Detection of Misalignment Faults in Synchronous Reluctance Motors |
| title_full | Current- and Vibration-Based Detection of Misalignment Faults in Synchronous Reluctance Motors |
| title_fullStr | Current- and Vibration-Based Detection of Misalignment Faults in Synchronous Reluctance Motors |
| title_full_unstemmed | Current- and Vibration-Based Detection of Misalignment Faults in Synchronous Reluctance Motors |
| title_short | Current- and Vibration-Based Detection of Misalignment Faults in Synchronous Reluctance Motors |
| title_sort | current and vibration based detection of misalignment faults in synchronous reluctance motors |
| topic | acceleration current analysis diagnosis fast Fourier transform misalignment synchronous reluctance motor |
| url | https://www.mdpi.com/2075-1702/13/4/319 |
| work_keys_str_mv | AT angelanavarronavarro currentandvibrationbaseddetectionofmisalignmentfaultsinsynchronousreluctancemotors AT vicentebiotmonterde currentandvibrationbaseddetectionofmisalignmentfaultsinsynchronousreluctancemotors AT joseeruizsarrio currentandvibrationbaseddetectionofmisalignmentfaultsinsynchronousreluctancemotors AT joseaantoninodaviu currentandvibrationbaseddetectionofmisalignmentfaultsinsynchronousreluctancemotors |