Diagnosa Kerusakan Rolling Bearing Motor Induksi Menggunakan Sinyal Suara
DOI:
https://doi.org/10.30649/je.v4i2.112Keywords:
motor induksi, bearing, sinyal suara, fast fourier transform, spectrum, real-timeAbstract
Monitoring kondisi motor induksi perlu dilakukan secara kontinue. Biaya perawatan akan berkurang secara signifikan jika kesehatan motor terus terpantau. Tujuan monitoring kondisi yaitu untuk deteksi kerusakan secara dini sehingga menghidari kerusakan parah, meningkatkan keandalan, dan menghidari terhentinya operasional motor. Kerusakan elemen motor yang sering terjadi adalah kerusakan bearing. Penelitian ini mengembangkan sistem monitoring kondisi bearing berdasarkan analisis sinyal suara dimana proses monitoring dilakukan secara realtime. Dengan pengembangan sistem secara realtime maka memberikan solusi yang efekti dan tidak menyita waktu. Sensor yang murah dan mudah didapat ditawarkan pada pengembangan penelitian ini. Sinyal suara yang ditangkap oleh microphone secara langsung diolah dengan sistem pengolahan sinyal dan analisis spectrum. Monitoring kondisi dilakukan pada elemen bearing yaitu inner race, outer race, dan ball bearing. Hasil penelitian mendapatkan sistem monitoring yang handal dan dan menghasilkan diagnosis yang akurat dengan presentase sebesar 98.3 -100%.
References
X. Liang, M.Z. Ali and H. Zhang, "Induction Motors Fault Diagnosis Using Finite Element Method: A Review," in IEEE Transactions on Industry Applications, vol. 56, no. 2, pp. 1205-1217, March-April 2020.
D.F. de Souza, F.A.M. Salotti, I.L. Sauer, H. Tatizawa, A.T.de Almeida, & A.G. Kanashiro. ”A Performance Evalu-ation of Three‐Phase Induction Electric Motors between 1945 and 2020. Energies, 15(6), 1–31. 2022. doi: 10.3390/en15062002.
I.D.P. Karyatanti, R.S. Zulkifli, A. Noersena, F.R. Purnomo, B.Y. Dewantara & A.Wijayanto . “Identifica-tion Of Ball Bearing Damage On Induction Motors Through Sound Signal Analysis”. Journal of Electrical and Electronics Engineering, 15(1), 33–38. 2022.
Diah, I., Karyatanti, P., Noersena, A., Purnomo, F. R., Zulkifli, R. S., & Wijayanto, A. “Analysis of Outer Race Bearing Damage by Calculation of Sound Signal Frequency Based on the FFT Method”. 28–39. 2023.
I.P.K. Diah, B.Y. Dewantara, D. Rahmatullah, I. Winarno, & C. Hidayanto. “Decomposition Wavelet Transform As Identification Of Outer Race Bearing Damage Through Stator Flow Analysis In Induction Motor”. International Conference on Informa-tion and Communications Technology, ICOIACT 2019, July, 733–737. 2019. doi:10.1109/ICOIACT46704.2019.8938512.
T.A. Dhomad, A.A. Jaber. ”Bearing Fault Diagnosis Using Motor Current Signature Analysis And The Artificial Neural Network”. International Journal On Advanced Science, Engineering And Information Technology, 10 (1), 70–79. 2020. doi: 10.18517/ijaseit.10.1.10629
V. Barai, S.M. Ramteke, V. Dhanal-kotwar, Y. Nagmote, S. Shende, & D. Deshmukh. ”Bearing Fault Diagnosis Using Signal Processing And Machine Learning Techniques”: A review. IOP Conference Series: Materials Science and Engineering, 1259 (1), 012034. 2022. doi: 10.1088/1757899x/12-59/1/012034.
H. Nakamura, K. Asano, S. Usuda, & Y. Mizuno. ”A Diagnosis Method Of Bearing And Stator Fault in Motor Using Rotating Sound Based on Deep Learning”. Energies, 14(5), 1319. 2021. doi: 10.3390/en14051319
C.Y. Lee, & Y.H. Cheng. “Motor Fault Detection Using Wavelet Transform And Improved Pso-Bp Neural Network”. Processes, 8(10), 1–16. 2020. doi: 10.3390/pr8101322
M. Jalayer, A. Kaboli, C. Orsenigo, & C. Vercellis. “Fault Detection and Diagnosis with Imbalanced and Noisy Data: A Hybrid Framework for Rotating Machinery”. Machines, 10(4), 1–22. 2022. doi: 10.3390/machi-nes10040237
G. Wu, T. Yan, G. Yang, H. Chai, & C. Cao. “A Review on Rolling Bearing Fault Signal Detection Methods Based on Different Sensors”. Sensors, 22 (21). 2022. doi: 10.3390/-s22218330
P. Ewert, C.T. Kowalski and T. Orlowska-Kowalska.”Low Cost Moni-toring And Diagnosis System For Rolling Bearing Faults Of The Induction Motor Based On Neural Network Approach”. Electronics, 9(9), p.1334, 2020. doi: 10.3390/electronics9091334
S. Jawad, A. Jaber. “Bearings Health Monitoring Based on Frequency-Domain Vibration Signals Analysis”. Engineering and Technology Journal, 41(1),86–95. 2022. doi: 10.30684/etj.-2022.131581.1043
T.G. Calva, D.M Sotelo, V.F Cavero, R. R Troncoso. “Early Detection of Faults in Induction Motors A Review”. Energies, 15 (21), 7855. 2022. doi : 10.3390/en15217855
S. Muthukumaran, A. Rammohan, S. Sekar, M. Maiti, & K. Bingi. ”Bearing Fault Detection In Induction Motors Using Line Currents”. ECTI Transac-tions on Electrical Engineering, Elec-tronics, and Communications, 19 (2), 209–219. 2021. doi: 10.3-7936/ECTI-EEC.2021192.244163
N.W. Nirwan, H.B. Ramani. “Condition Monitoring And Fault Detection In Roller Bearing Used In Rolling Mill By Acoustic Emission And Vibration Analysis”. Materials Today: Proceedings, 51(xxxx), 344–354. 2021. doi: 10.1016/j.matpr.2021.05.447
D. Goyal, C. Mongia, S. Sehgal. “Applications Of Digital Signal Processing In Monitoring Machining Processes And Rotary Components: A Review”. IEEE Sensors Journal, 21(7), pp.8780-8804. 2021. doi: 10.1109/-JSEN.2021.3050718
