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All Journal Semesta Teknika Turbo : Jurnal Program Studi Teknik Mesin Kontribusia : Research Dissemination for Community Development
Berli P. Kamiel
Universitas Muhammadiyah Yogyakarta
Humanities Engineering Environmental Science Languange, Linguistic, Communication & Media Mechanical Engineering Public Health Social Sciences

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Deteksi Kavitasi Pada Pompa Sentrifugal Menggunakan Spektrum Getaran dan Spektrum Envelope Berli P. Kamiel; Deby Arikh Nafsaka; Bambang Riyanta; Azhim Asyratul
Semesta Teknika Vol 22, No 1 (2019): MEI 2019
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/st.221231

Abstract

AbstrakKavitasi adalah salah satu indikator penting kondisi operasi sebuah pompa sentrifugal. Fenomena kavitasi ditunjukkan dengan terbentuknya formasi gelembung udara yang kemudian pecah secara tiba-tiba akibat perubahan tekanan pada sisi hisap pompa. Kavitasi dapat menyebabkan kerusakan yang parah komponen pompa terutama bagian sudu atau impeller. Kavitasi biasanya dapat diidentifikasi melalui suara bising dan timbulnya getaran yang berlebihan. Sebuah metode deteksi kavitasi dibutuhkan agar potensi kerusakan lebih lanjut pada pompa sentrifugal dapat diantisipasi secepatnya. Penelitian ini bertujuan menghasilkan sebuah metode deteksi kavitasi menggunakan spektrum getaran dan spektrum envelope pada bentang frekwensi rendah 0-4 kHz dan bentang frekwensi tinggi 4-8,5 kHz. Sinyal getaran pompa direkam menggunakan sebuah akselerometer yang diletakkan pada rumah volute pompa arah aksial. Sinyal getaran kemudian ditransformasikan kedalam spektrum dan spektrum envelope menggunakan  Fast Fourier Transform. Spektrum dan spektrum envelope untuk masing-masing bentang frekwensi dibandingkan antara pompa kondisi normal dan kondisi tiga level kavitasi kavitasi. Hasil penelitian menunjukkan bahwa spektrum frekwensi rendah dapat digunakan untuk mendeteksi kavitasi level 3 yang ditunjukkan dengan peningkatan amplitudo frekwensi poros sebesar 47,6 Hz dan ½ BPF sebesar 149,6 Hz. Sedangkan kavitasi level 1 dapat dideteksi oleh spektrum envelope pada bentang frekwensi tinggi. Dapat disimpulkan pula bahwa penurunan ampitudo teramati secara umum pada domain waktu seiring dengan meningkatnya level kavitasi. AbstractCavitation is an important indication of operation condition for a centrifugal pump. An indication of the appearance of cavitation is the formation of bubbles which collapse suddenly when the pressure changed on the suction side of the pump. The formation of cavitation bubbles can cause fault to the inner pump components. The fault that often results from cavitation phenomenon is affected in the impeller. This fault is usully identified through noise and vibration generated. Therefore, a method is needed to detect early cavitation phenomenon at the centrifugal pump. This study aims to develop cavitation detection methods using the vibration spectrum and envelope spectrum of low frequency band of 0-4 kHz and high frequency band of 4 kHz-8,5 kHz. In this study, cavitation detection in conducted by recording vibration signals that occur at centrifugal pump using an accelerometer. The data obtained is then transformed into the frequency domain and envelope spectrum using Fast Fourier Transform. The results were compared between normal condition and level 1, 2, and 3 cavitation. Comparisons were made on each vibration spectrum and envelope spectrum at the low frequency and high frequency bands. The result of this study showed that the vibration spectrum with low frequency band can detect the formation of level 3 cavitation with an increase in shaft frequency amplitude (47,26 Hz) and ½ BPF (149,6 Hz). Whereas early cavitation or level 1 cavitation was identified through the envelope spectrum at high frequency band. It also showed that a decrease in amplitude occured gradually in the time domain along with increasing level of cavitation.
Identifikasi cacat lintasan luar bantalan bola menggunakan Support Vector Machine (SVM) pada fan industri Berli P. Kamiel; Wildan T.B Anggoro; Bambang Riyanta
TURBO [Tulisan Riset Berbasis Online] Vol 8, No 2 (2019): Jurnal Turbo Desember 2019
Publisher : Universitas Muhammadiyah Metro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (710.596 KB) | DOI: 10.24127/trb.v8i2.1024

Abstract

Air regulation creates a comfortable and healthy environment for activities in the industry. A fan is a rotary machine that functions to regulate and circulate air in a room or work area. The bearing is an important component of a fan that is potentially damaged during operation. Damage to the bearing will interfere with perform the fan and can even disrupt a whole production process. A bearing condition monitoring method is needed that is effective and easy to use. Conventional methods such as spectrum analysis and sound analysis are not easy to use by operators in the field due to spectrum analysis requires spectrum reading experience while sound analysis is highly dependent on personal experience. This study proposes a vibration-based pattern recognition method that is Support Vector Machine (SVM) to detect damage to a bearing. This method effectively classifies bearing conditions and is easy to use. The study aims to obtain a method of detecting defects in single-row bearing outer paths on industrial fans using SVM. The study uses an industrial fan test rig with two bearing conditions, that is normal conditions (no defects) and external track defects with a depth of 1.4 mm defect and 0.4 mm width. Recording vibration signals using a data acquisition module with a sampling speed of 17066 Hz and a motor rotational speed of 2850 rpm. The SVM classifier is trained using 9 selected statistical parameters which are extracted from 700 sets of vibration signal recordings. The results showed the statistical parameters that were effectively used were Root Mean Square (RMS), Standard Deviation, Kurtosis, Variance, Entropy, Standard Error, Median, Signal-to-Noise and Distortion Ratio (SINAD), and Signal to Noise Ratio (SNR).  The most optimal SVM model is obtained by applying combine Median-SINAD statistical parameters, with the same testing accuracy for the RBF, Polynomial and Linear kernels at 100%. Keywords:  Bearings, external path defects, kernel, statistical parameters, SVM.
Development of Computer-Based Learning Tools and Media at Sekolah Menengah Pertama (SMP) Muhammadiyah Tanjung Tri Wahyono; Berli P. Kamiel; Fitroh Anugerah K Yudha; M. Budi Nur Rahman; Krisdiyanto Krisdiyanto
Kontribusia : Research Dissemination for Community Development Vol 6 No 2 (2023): Kontribusia, August
Publisher : OJS Universitas Muhammadiyah Gresik

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30587/kontribusia.v6i2.5512

Abstract

Knowledge and skills about computer and information technology should be taught to students from an early age. These skills are needed when continuing education to the next level. Junior high school students really need these skills to equip them to face technological developments and advances towards more sophisticated developments. To be able to achieve this goal, adequate infrastructure is needed so that the learning process of computer and information technology can run smoothly and effectively. Until now, learning about computer and information technology at SMP Muhammadiyah Tanjung has not been implemented due to the unavailability of computer equipment that can be used by students. Through this PPM Muhammadiyah scheme community service program, a computer room and laboratory will be gradually developed at SMP Muhammadiyah Tanjung according to the available budget so that it can be used as a learning room and practice of computer and information technology for students. The method used is in collaboration with Mechanical Engineering Study Program and SMP Muhammadiyah Tanjung, Kec. Muntilan, Kab. Magelang for the design and supply of sufficient tools. With this Muhammadiyah PPM scheme service program, it is hoped that students will be able to skillfully operate computer units and can develop skills and use information technology in a better direction.
Co-Authors Azhim Asyratul Bambang Riyanta Deby Arikh Nafsaka Fitroh Anugerah K Yudha Krisdiyanto, Krisdiyanto M. Budi Nur Rahman Tri Wahyono Wildan T.B Anggoro