Permatasari, Virliana Septi (2022) Perancangan Sistem Deteksi Kesalahan Paralel Dan Angular Misalignment Pada Motor Induksi Menggunakan Logika Fuzzy. Other thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Salah satu kerusakan yang terjadi pada motor induksi adalah misalignment. Misalignment adalah kondisi kesalahan penyimpangan sumbu yang terjadi pada mesin berputar yang dapat menyebabkan penurunan efisiensi motor induksi. Dalam penelitian ini dilakukan perancangan sistem deteksi kesalahan menggunakan logika fuzzy untuk mendeteksi dan memperkirakan besarnya jarak paralel misalignment dan derajat angular misalignment yang terjadi pada motor induksi. Perancangan sistem deteksi melalui tiga tahapan yaitu dimulai dari ekstraksi sinyal menggunakan Fast Fourier Transform (FFT) untuk mengubah output sinyal pada motor induksi dari domain waktu menjadi domain frekuensi. Selanjutnya digunakan findpeaks function untuk mengetahui nilai amplitudo dari peak pertama dan ketiga dari variabel arus Q1 (PiQ1f) yang akan digunakan sebagai input dari sistem deteksi. Arus Q1 (PiQ1f) digunakan sebagai input sistem deteksi karena memiliki nilai peak yang sebanding dengan besarnya kesalahan paralel dan angular misalignment. Terakhir logika fuzzy dengan model sugeno digunakan untuk menentukan besarnya jarak paralel misalignment dan derajat angular misalignment. Dari perancangan sistem tersebut didapatkan hasil bahwa sistem deteksi mampu mendeteksi dan mengidentifikasi kondisi paralel misalignment dan angular misalignment dengan benar.
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One of the damages that occurs in induction motors is misalignment. Misalignment is a condition of axis deviation error that occurs in a rotating machine that can cause a decrease in the efficiency of the induction motor. In this study, the design of a fault detection system using fuzzy logic was carried out to detect and estimate the magnitude of the parallel misalignment distance and the degree of angular misalignment that occurs in induction motors. The design of the detection system goes through three stages, starting from signal extraction using Fast Fourier Transform (FFT) to convert the signal output on the induction motor from the time domain to the frequency domain. Furthermore, the findpeaks function is used to find out the amplitude values of the first and third peaks of the Q1 current variable (PiQ1f) which will be used as input from the detection system. The Q1 current (PiQ1f) is used as the input of the detection system because it has a peak value proportional to the magnitude of the parallel and angular misalignment. Finally, fuzzy logic with the sugeno model is used to determine the magnitude of the distance of parallel misalignment and the degree of angular misalignment. From the design of the system, it was found that the detection system was able to detect and identify parallel misalignment and angular misalignment conditions correctly.
| Item Type: | Thesis (Other) |
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| Additional Information: | RSF 629.89 Per p-1 2022 |
| Uncontrolled Keywords: | Angular Misalignment, Logika Fuzzy, Motor Induksi, Paralel Misalignment, Sistem Deteksi Kesalahan. Angular Misalignment, Fault Detection System, Fuzzy Logic, Induction Motor, Parallel Misalignment. |
| Divisions: | Faculty of Industrial Technology and Systems Engineering (INDSYS) > Physics Engineering > 30201-(S1) Undergraduate Thesis |
| Depositing User: | Mr. Marsudiyana - |
| Date Deposited: | 11 May 2026 03:47 |
| Last Modified: | 11 May 2026 03:47 |
| URI: | http://repository.its.ac.id/id/eprint/133112 |
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