Araştırma Makalesi
BibTex RIS Kaynak Göster

Eccentricity Fault in Induction Motors Using Statistical Process Control Method

Yıl 2024, Cilt: 8 Sayı: 2, 192 - 201, 30.12.2024
https://doi.org/10.47897/bilmes.1583712

Öz

Induction motors are the most commonly used electric motors in the industry. The main reasons for choosing induction motors are their robust structure and low maintenance requirements. However, the harsh working conditions of the industry cause motor faults. Predicting motor faults in advance or determining the cause of fault is very important for businesses. In this study, an attempt was made to detect the eccentricity fault of the induction motor with a cheap and easy method. The eccentricity fault, which is a mechanical fault and is frequently encountered, was tried to be determined by monitoring the motor current signals. The motor current signals were analyzed with the statistical process control method from statistical methods. For the first time, with this study, the eccentricity fault occurring in an induction motor operating under different speed conditions was successfully detected with the statistical process control method.

Kaynakça

  • [1] M. M. Tezcan and A. S. Akyurt, “Transforming of Conventional Type Squirrel Cage Induction Motor to Permanent Magnet Synchronous Motor for Improving Efficiency on Industrial Applications,” Int. Sci. Vocat. Stud. J., vol. 6, no. 1, pp. 32–40, Jun. 2022, doi: 10.47897/BILMES.1129634.
  • [2] M. Akar, A. Fenercioğlu, M. Soyaslan, (2011). "Asenkron Motorlarda Rotor Çubuğu Kırık Arızasının Elektromanyetik Tork ile Tespiti". In 6th International Advanced Technologies Symposium (IATS’11) (pp. 142-146).
  • [3] A. Ünsal and S.Güçlü,. "Asenkron Motorlarda Rotor Çubuğu Kırıklarının Mann-Whıtney U-Testi İle İncelenmesi." Journal of Science and Technology of Dumlupınar University, (2015),pp.(035), 79-92.
  • [4] K. V. Kumar, S. S. Kumar, B. Praveena, J. P. John, and J. E. Paul, “Soft computing based fault diagnosis,” 2010 2nd Int. Conf. Comput. Commun. Netw. Technol. ICCCNT 2010, 2010, doi: 10.1109/ICCCNT.2010.5591631.
  • [5] P. Vas, “Parameter Estimation, Condition Monitoring, and Diagnosis of Electrical Machines,” Param. Estim. Cond. Monit. Diagnosis Electr. Mach., Feb. 1992, doi: 10.1093/OSO/9780198593751.001.0001.
  • [6] E. Eser, Z. Doğan, “Asenkron Motorlarda Rotor Çubuk Kırığı Arızasının İstatisteksel Proses Kontrol Metodu İle Tespiti.,” 2. Uluslararası Mühendislikmimarlık Ve Tasarım Kongresi, 2017.
  • [7] M. Eftekhari, M. Moallem, S. Sadri, and A. Shojaei, “Review of induction motor testing and monitoring methods for inter-turn stator winding faults,” 2013 21st Iran. Conf. Electr. Eng. ICEE 2013, 2013, doi: 10.1109/IRANIANCEE.2013.6599713.
  • [8] W. F. Godoy, I. N. Da Silva, A. Goedtel, and R. H. Cunha Palácios, “Evaluation of stator winding faults severity in inverter-fed induction motors,” Appl. Soft Comput., vol. 32, pp. 420–431, Jul. 2015, doi: 10.1016/J.ASOC.2015.03.053.
  • [9] S. Günal, D. Gökhan Ece, and Ö. Nezih Gerek, “Induction machine condition monitoring using notch-filtered motor current,” Mech. Syst. Signal Process., vol. 23, no. 8, pp. 2658–2670, Nov. 2009, doi: 10.1016/J.YMSSP.2009.05.011.
  • [10] E. Cabal-Yepez, R. A. Osornio-Rios, R. J. Romero-Troncoso, J. R. Razo-Hernandez, and R. Lopez-Garcia, “FPGA-based online induction motor multiple-fault detection with fused FFT and wavelet analysis,” ReConFig’09 - 2009 Int. Conf. ReConFigurable Comput. FPGAs, pp. 101–106, 2009, doi: 10.1109/RECONFIG.2009.9.
  • [11] T. Stapenhurst, “Mastering statistical process control,” Mastering Stat. Process Control, pp. 1–455, May 2013, doi: 10.4324/9780080479545.
  • [12] B.Birgören, İstatistiksel kalite kontrolü. Nobel Akademik Yayıncılık. Ankara, (2015).
  • [13] M. E. H. Benbouzid, “A review of induction motors signature analysis as a medium for faults detection,” IEEE Trans. Ind. Electron., vol. 47, no. 5, pp. 984–993, 2000, doi: 10.1109/41.873206.
  • [14] K. S.Gaeid and H. A.Mohamed,. "Diagnosis and fault tolerant control of the induction motors techniques a review." Australian Journal of Basic and Applied Sciences, 4(2), 227-246,(2008), doi:10.1016/j.jsv.2009.01.058
  • [15] B.Kara, "Şebeke kalkışlı daimi mıknatıslı senkron motorda eksenden kaçıklık arızası teşhisi" , Master Thesis, Tokat Gaziosmanpaşa Univercity, 2017.
  • [16] M. Hajiaghajani, Application of Pattern Recognition to Fault Diagnosis. Taylor and Francis Group, 2017.
  • [17] D. G. Dorrell, W. T. Thomson, and S. Roach, “Analysis of airgap flux, current, and vibration signals as a function of the combination of static and dynamic airgap eccentricity in 3-phase induction motors,” IEEE Trans. Ind. Appl., vol. 33, no. 1, pp. 24–34, 1997, doi: 10.1109/28.567073.
  • [18] Polat, A. "Asenkron Motorda Eksen Kaçıklığının Analizi, " Master Thesis, Istanbul Technical Univercity, 2013.
  • [19] M. Eker and M. Akar, “Eccentricity fault diagnosis in a permanent magnet synchronous motor under nonstationary speed conditions,” Turkish J. Electr. Eng. Comput. Sci., vol. 25, no. 3, pp. 1881–1893, Jan. 2017, doi: 10.3906/elk-1601-157.
  • [20] S. Ben Salem, M. Salah, K. Bacha, and A. Chaari, “Experimental investigation of the eccentricity impact on the line current spectrum for induction motors fault diagnosis purposes,” 2016 17th Int. Conf. Sci. Tech. Autom. Control Comput. Eng. STA 2016 - Proc., pp. 205–210, Jun. 2017, doi: 10.1109/STA.2016.7952070.
  • [21] S. Nandi, H. A. Toliyat, and X. Li, “Condition monitoring and fault diagnosis of electrical motors - A review,” IEEE Trans. Energy Convers., vol. 20, no. 4, pp. 719–729, Dec. 2005, doi: 10.1109/TEC.2005.847955.
  • [22] B. Wang, C. Lin, H. Inoue, and M. Kanemaru, “Induction Motor Eccentricity Fault Detection and Quantification Using Topological Data Analysis,” IEEE Access, vol. 12, pp. 37891–37902, 2024, doi: 10.1109/ACCESS.2024.3376249.
  • [23] Y. B. Koca and A. Ünsal, “Asenkron Motor Arızalarının Değerlendirilmesi,” J. Tech. Sci., vol. 7, no. 2, pp. 37–46, Jul. 2017
  • [24] C.Kurien, and A. K. Srivastava, "Condition monitoring of systems in thermal power plant for vibration, motor signature, noise and wear debris analysis." World Scientific News, 31-43,2018.
  • [25] B.Mulgrew, , P.Grant, , J.Thompson,. Digital signal processing: concepts and applications., 2002. [E-book] Available: Google e-book..
  • [26] G. Niu, X. Dong, and Y. Chen, “Motor Fault Diagnostics Based on Current Signatures: A Review,” IEEE Trans. Instrum. Meas., vol. 72, 2023, doi: 10.1109/TIM.2023.3285999.
  • [27] A.Bellini, , F.Filippetti, , C.Tassoni, , G. A.Capolino, "Advances in diagnostic techniques for induction machines." IEEE Transactions on industrial electronics, 55(12), 4109-4126, 2008, doi: 10.1109/TIE.2008.2007527
  • [28] Yıldırım, H., and Karaca, E., "Üretim Sürecinde İstatistiksel Proses Kontrol (İpk) Uygulamaları Ve Elektronik Sektöründe Bir İnceleme" Öneri Dergisi, 10(39), 77-87, 2013, doi.org/10.14783/od.v10i39.1012000309.
  • [29] S. Patır, “İstatistiksel Proses Kontrol Teknikleri Ve Kontrol Grafiklerinin Malatyadaki Bir Tekstil (İplik Dokuma) İşletmesinde Bobin Sarim Kontrolüne Uygulanmasi,” Sosyal Ekonomik Araştırmalar Dergisi, 9(18), 231-250.
  • [30] J. Niezgoda, “The use of statistical process control tools for analysing financial statements,” Folia Oeconomica Stetin., vol. 17, no. 1, pp. 129–137, 2017, doi.org/10.1515/foli-2017-0010.
  • [31] S. Maraş and H. Arslan, “Düz Dişli Çark Sistemindeki Aşınma Hatasının İstatistiksel Proses Kontrol Metodu İle Belirlenmesi,” Pamukkale Üniversitesi Mühendislik Bilim. Derg., vol. 20, no. 1, pp. 9–14, Jan. 2014, doi: 10.5505/PAJES.2014.28247.

Eccentricity Fault in Induction Motors Using Statistical Process Control Method

Yıl 2024, Cilt: 8 Sayı: 2, 192 - 201, 30.12.2024
https://doi.org/10.47897/bilmes.1583712

Öz

Induction motors are the most commonly used electric motors in the industry. The main reasons for choosing induction motors are their robust structure and low maintenance requirements. However, the harsh working conditions of the industry cause motor faults. Predicting motor faults in advance or determining the cause of fault is very important for businesses. In this study, an attempt was made to detect the eccentricity fault of the induction motor with a cheap and easy method. The eccentricity fault, which is a mechanical fault and is frequently encountered, was tried to be determined by monitoring the motor current signals. The motor current signals were analyzed with the statistical process control method from statistical methods. For the first time, with this study, the eccentricity fault occurring in an induction motor operating under different speed conditions was successfully detected with the statistical process control method.

Kaynakça

  • [1] M. M. Tezcan and A. S. Akyurt, “Transforming of Conventional Type Squirrel Cage Induction Motor to Permanent Magnet Synchronous Motor for Improving Efficiency on Industrial Applications,” Int. Sci. Vocat. Stud. J., vol. 6, no. 1, pp. 32–40, Jun. 2022, doi: 10.47897/BILMES.1129634.
  • [2] M. Akar, A. Fenercioğlu, M. Soyaslan, (2011). "Asenkron Motorlarda Rotor Çubuğu Kırık Arızasının Elektromanyetik Tork ile Tespiti". In 6th International Advanced Technologies Symposium (IATS’11) (pp. 142-146).
  • [3] A. Ünsal and S.Güçlü,. "Asenkron Motorlarda Rotor Çubuğu Kırıklarının Mann-Whıtney U-Testi İle İncelenmesi." Journal of Science and Technology of Dumlupınar University, (2015),pp.(035), 79-92.
  • [4] K. V. Kumar, S. S. Kumar, B. Praveena, J. P. John, and J. E. Paul, “Soft computing based fault diagnosis,” 2010 2nd Int. Conf. Comput. Commun. Netw. Technol. ICCCNT 2010, 2010, doi: 10.1109/ICCCNT.2010.5591631.
  • [5] P. Vas, “Parameter Estimation, Condition Monitoring, and Diagnosis of Electrical Machines,” Param. Estim. Cond. Monit. Diagnosis Electr. Mach., Feb. 1992, doi: 10.1093/OSO/9780198593751.001.0001.
  • [6] E. Eser, Z. Doğan, “Asenkron Motorlarda Rotor Çubuk Kırığı Arızasının İstatisteksel Proses Kontrol Metodu İle Tespiti.,” 2. Uluslararası Mühendislikmimarlık Ve Tasarım Kongresi, 2017.
  • [7] M. Eftekhari, M. Moallem, S. Sadri, and A. Shojaei, “Review of induction motor testing and monitoring methods for inter-turn stator winding faults,” 2013 21st Iran. Conf. Electr. Eng. ICEE 2013, 2013, doi: 10.1109/IRANIANCEE.2013.6599713.
  • [8] W. F. Godoy, I. N. Da Silva, A. Goedtel, and R. H. Cunha Palácios, “Evaluation of stator winding faults severity in inverter-fed induction motors,” Appl. Soft Comput., vol. 32, pp. 420–431, Jul. 2015, doi: 10.1016/J.ASOC.2015.03.053.
  • [9] S. Günal, D. Gökhan Ece, and Ö. Nezih Gerek, “Induction machine condition monitoring using notch-filtered motor current,” Mech. Syst. Signal Process., vol. 23, no. 8, pp. 2658–2670, Nov. 2009, doi: 10.1016/J.YMSSP.2009.05.011.
  • [10] E. Cabal-Yepez, R. A. Osornio-Rios, R. J. Romero-Troncoso, J. R. Razo-Hernandez, and R. Lopez-Garcia, “FPGA-based online induction motor multiple-fault detection with fused FFT and wavelet analysis,” ReConFig’09 - 2009 Int. Conf. ReConFigurable Comput. FPGAs, pp. 101–106, 2009, doi: 10.1109/RECONFIG.2009.9.
  • [11] T. Stapenhurst, “Mastering statistical process control,” Mastering Stat. Process Control, pp. 1–455, May 2013, doi: 10.4324/9780080479545.
  • [12] B.Birgören, İstatistiksel kalite kontrolü. Nobel Akademik Yayıncılık. Ankara, (2015).
  • [13] M. E. H. Benbouzid, “A review of induction motors signature analysis as a medium for faults detection,” IEEE Trans. Ind. Electron., vol. 47, no. 5, pp. 984–993, 2000, doi: 10.1109/41.873206.
  • [14] K. S.Gaeid and H. A.Mohamed,. "Diagnosis and fault tolerant control of the induction motors techniques a review." Australian Journal of Basic and Applied Sciences, 4(2), 227-246,(2008), doi:10.1016/j.jsv.2009.01.058
  • [15] B.Kara, "Şebeke kalkışlı daimi mıknatıslı senkron motorda eksenden kaçıklık arızası teşhisi" , Master Thesis, Tokat Gaziosmanpaşa Univercity, 2017.
  • [16] M. Hajiaghajani, Application of Pattern Recognition to Fault Diagnosis. Taylor and Francis Group, 2017.
  • [17] D. G. Dorrell, W. T. Thomson, and S. Roach, “Analysis of airgap flux, current, and vibration signals as a function of the combination of static and dynamic airgap eccentricity in 3-phase induction motors,” IEEE Trans. Ind. Appl., vol. 33, no. 1, pp. 24–34, 1997, doi: 10.1109/28.567073.
  • [18] Polat, A. "Asenkron Motorda Eksen Kaçıklığının Analizi, " Master Thesis, Istanbul Technical Univercity, 2013.
  • [19] M. Eker and M. Akar, “Eccentricity fault diagnosis in a permanent magnet synchronous motor under nonstationary speed conditions,” Turkish J. Electr. Eng. Comput. Sci., vol. 25, no. 3, pp. 1881–1893, Jan. 2017, doi: 10.3906/elk-1601-157.
  • [20] S. Ben Salem, M. Salah, K. Bacha, and A. Chaari, “Experimental investigation of the eccentricity impact on the line current spectrum for induction motors fault diagnosis purposes,” 2016 17th Int. Conf. Sci. Tech. Autom. Control Comput. Eng. STA 2016 - Proc., pp. 205–210, Jun. 2017, doi: 10.1109/STA.2016.7952070.
  • [21] S. Nandi, H. A. Toliyat, and X. Li, “Condition monitoring and fault diagnosis of electrical motors - A review,” IEEE Trans. Energy Convers., vol. 20, no. 4, pp. 719–729, Dec. 2005, doi: 10.1109/TEC.2005.847955.
  • [22] B. Wang, C. Lin, H. Inoue, and M. Kanemaru, “Induction Motor Eccentricity Fault Detection and Quantification Using Topological Data Analysis,” IEEE Access, vol. 12, pp. 37891–37902, 2024, doi: 10.1109/ACCESS.2024.3376249.
  • [23] Y. B. Koca and A. Ünsal, “Asenkron Motor Arızalarının Değerlendirilmesi,” J. Tech. Sci., vol. 7, no. 2, pp. 37–46, Jul. 2017
  • [24] C.Kurien, and A. K. Srivastava, "Condition monitoring of systems in thermal power plant for vibration, motor signature, noise and wear debris analysis." World Scientific News, 31-43,2018.
  • [25] B.Mulgrew, , P.Grant, , J.Thompson,. Digital signal processing: concepts and applications., 2002. [E-book] Available: Google e-book..
  • [26] G. Niu, X. Dong, and Y. Chen, “Motor Fault Diagnostics Based on Current Signatures: A Review,” IEEE Trans. Instrum. Meas., vol. 72, 2023, doi: 10.1109/TIM.2023.3285999.
  • [27] A.Bellini, , F.Filippetti, , C.Tassoni, , G. A.Capolino, "Advances in diagnostic techniques for induction machines." IEEE Transactions on industrial electronics, 55(12), 4109-4126, 2008, doi: 10.1109/TIE.2008.2007527
  • [28] Yıldırım, H., and Karaca, E., "Üretim Sürecinde İstatistiksel Proses Kontrol (İpk) Uygulamaları Ve Elektronik Sektöründe Bir İnceleme" Öneri Dergisi, 10(39), 77-87, 2013, doi.org/10.14783/od.v10i39.1012000309.
  • [29] S. Patır, “İstatistiksel Proses Kontrol Teknikleri Ve Kontrol Grafiklerinin Malatyadaki Bir Tekstil (İplik Dokuma) İşletmesinde Bobin Sarim Kontrolüne Uygulanmasi,” Sosyal Ekonomik Araştırmalar Dergisi, 9(18), 231-250.
  • [30] J. Niezgoda, “The use of statistical process control tools for analysing financial statements,” Folia Oeconomica Stetin., vol. 17, no. 1, pp. 129–137, 2017, doi.org/10.1515/foli-2017-0010.
  • [31] S. Maraş and H. Arslan, “Düz Dişli Çark Sistemindeki Aşınma Hatasının İstatistiksel Proses Kontrol Metodu İle Belirlenmesi,” Pamukkale Üniversitesi Mühendislik Bilim. Derg., vol. 20, no. 1, pp. 9–14, Jan. 2014, doi: 10.5505/PAJES.2014.28247.
Toplam 31 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Elektrik Makineleri ve Sürücüler
Bölüm Makaleler
Yazarlar

Emrah Eser 0000-0002-9325-0767

Zafer Doğan 0000-0002-7953-0578

Erken Görünüm Tarihi 30 Aralık 2024
Yayımlanma Tarihi 30 Aralık 2024
Gönderilme Tarihi 12 Kasım 2024
Kabul Tarihi 26 Kasım 2024
Yayımlandığı Sayı Yıl 2024 Cilt: 8 Sayı: 2

Kaynak Göster

APA Eser, E., & Doğan, Z. (2024). Eccentricity Fault in Induction Motors Using Statistical Process Control Method. International Scientific and Vocational Studies Journal, 8(2), 192-201. https://doi.org/10.47897/bilmes.1583712
AMA Eser E, Doğan Z. Eccentricity Fault in Induction Motors Using Statistical Process Control Method. ISVOS. Aralık 2024;8(2):192-201. doi:10.47897/bilmes.1583712
Chicago Eser, Emrah, ve Zafer Doğan. “Eccentricity Fault in Induction Motors Using Statistical Process Control Method”. International Scientific and Vocational Studies Journal 8, sy. 2 (Aralık 2024): 192-201. https://doi.org/10.47897/bilmes.1583712.
EndNote Eser E, Doğan Z (01 Aralık 2024) Eccentricity Fault in Induction Motors Using Statistical Process Control Method. International Scientific and Vocational Studies Journal 8 2 192–201.
IEEE E. Eser ve Z. Doğan, “Eccentricity Fault in Induction Motors Using Statistical Process Control Method”, ISVOS, c. 8, sy. 2, ss. 192–201, 2024, doi: 10.47897/bilmes.1583712.
ISNAD Eser, Emrah - Doğan, Zafer. “Eccentricity Fault in Induction Motors Using Statistical Process Control Method”. International Scientific and Vocational Studies Journal 8/2 (Aralık 2024), 192-201. https://doi.org/10.47897/bilmes.1583712.
JAMA Eser E, Doğan Z. Eccentricity Fault in Induction Motors Using Statistical Process Control Method. ISVOS. 2024;8:192–201.
MLA Eser, Emrah ve Zafer Doğan. “Eccentricity Fault in Induction Motors Using Statistical Process Control Method”. International Scientific and Vocational Studies Journal, c. 8, sy. 2, 2024, ss. 192-01, doi:10.47897/bilmes.1583712.
Vancouver Eser E, Doğan Z. Eccentricity Fault in Induction Motors Using Statistical Process Control Method. ISVOS. 2024;8(2):192-201.


Creative Commons License
Creative Commons Atıf 4.0 It is licensed under an International License