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All Journal ComEngApp : Computer Engineering and Applications Journal VALENSI JURNAL KIMIA SAINS DAN APLIKASI Jurnal Natur Indonesia Teknika Jurnal Riset Kimia SEMIRATA 2015 Jurnal Pengabdian UntukMu NegeRI Jurnal Surya Medika Jurnal CoreIT Indonesian Journal of Chemistry JSFK (Jurnal Sains Farmasi & Klinis) JURNAL PHOTON JURNAL PENDIDIKAN TAMBUSAI J-Dinamika: Jurnal Pengabdian Kepada Masyarakat Building of Informatics, Technology and Science Jurnal Yustitia Zonasi: Jurnal Sistem Informasi JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Journal of Computer System and Informatics (JoSYC) Community Development Journal: Jurnal Pengabdian Masyarakat Jurnal Pengabdian kepada Masyarakat Nusantara Information System Journal (INFOS) KLIK: Kajian Ilmiah Informatika dan Komputer JUSTIN (Jurnal Sistem dan Teknologi Informasi) Dinamika Lingkungan Indonesia Makara Journal of Science MASALIQ: Jurnal Pendidikan dan Sains Aurelia: Jurnal Penelitian dan Pengabdian Masyarakat Indonesia Counseling and Humanities Review Jurnal Aplikasi IPTEK Indonesia AHKAM : Jurnal Hukum Islam dan Humaniora Mestaka: Jurnal Pengabdian Kepada Masyarakat Journal Of Artificial Intelligence And Software Engineering Journal of Hypermedia & Technology-Enhanced Learning Jurnal Pengabdian Nusantara JKM: Jurnal Kemitraan Masyarakat Jurnal Kesehatan Masyarakat
Jasril Jasril
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Journal : ComEngApp : Computer Engineering and Applications Journal

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The Turbofan Engine Remaining Useful Life Prediction Using 1-Dimentional Convolutional Neural Network Fauzan, Ahmad; Handayani, Lestari; Insani, Fitri; Jasril, Jasril; Sanjaya, Suwanto
Computer Engineering and Applications Journal Vol 13 No 03 (2024)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18495/comengapp.v13i03.484

Abstract

Turbofan engines have been the dominant type of engine in aircraft for the last forty years. Ensuring the quality of these engines is crucial for flight safety, particularly for long-distance flights. However, their performance degrades over time, impacting flight safety. To address this issue, it is essential to predict potential engine failures by estimating the Remaining Useful Life (RUL) of the engines Deep learning, especially Convolutional Neural Networks (CNNs), has demonstrated exceptional proficiency in handling intricate, non-linear data, leading to improved RUL predictionsdue to their ability to process complex and non-linear data. In this project, a 1-D CNN is used to predict RUL using the NASA C-MAPSS FD001 dataset, which consists of 3 settings and 21 sensors, though sensors with stagnant readings are excluded. The dataset is normalized using min-max and z-score methods, and then segmented into sequences for input into the 1-D CNN model. Various training scenarios were evaluated, with the best RMSE of 3.26 achieved using 10 epochs, a learning rate of 0.0001, and z-score normalization. The results indicate that feature selection can produce a lower RMSE compared to scenarios without feature selection.
Co-Authors - Aisyah - Nurlaili -, Sulismayati A, Muhammad Rizki Abdul Aziz Adel Zamri Adel Zamri Afrita, Indra agistia, nesa Ahmad Fauzan Ainil Mardiyah Aisyah Aisyah Aisyah, - Akbar, Unggul Al Fiqri, M. Faiz Alfarabi.B, Alif Ananda, Muthia Ananda, Sherly Anggita, Anggi Fisi Anori, Sartika Aprilia, Tasya Asmawati Asmawati Bintal Amin Christine Jose Christine Jose Dampang, Hasria Darian Alfatos Delsi K Delsi K Delsina Faiza Denai Wahyuni Denai Wahyuni Desviana, Laila Dewi, Erna Puspita Elin Haerani Elka Yuslinda Elvia Budianita Elviyenti, Elviyenti Fadhilah Syafria Fadhli, Irfan Faladhin, Johan Fauzi, Faradiba Kamilia Fawrin, Heralda Febi Yanto Fernando, Rivan Fiffah, Chainul Firmathoina, Aisyah Fitra Perdana Fitri Insani Fitria Novitasari Frischa Meivilona Yendi Guspriadi, Yan Haiyul Fadhli Hamersat, Danu Haresman, Haresman Hariansyah, Jul Hasmalina Nasution Hendra, Rudi Hilwan Yuda Teruna Hurria, Hurria Ihsan Ikhtiarudin Iis Afrianty Ika Parma Dewi Ikhtiaruddin, Ihsan Illahi, Ridho Indah Wulandari Işık, Kenan Isnaniar Iswantir M Jufrizal Syahri Kurnia Gusti, Siska Laila Desviana Lazulva Lazulva, Lazulva Lestari Handayani Lisa Utami Mar'arif, Muhammad Mulky Masykur Hz Masykur HZ Muhammad Affandes Muhammad Irsyad Muhdarina Muhdarina Muhdarina Muliani, Sarifah Muslim Syaifullah, Mhd Nazir, Alwis Nazruddin Safaat H Negara, Benny Sukma Neni Frimayanti Nofirda, Fitri Ayu Novianty, Riryn Nuraini Ramadhani Nurhayati Nurlaili Nurlaili Nurlaili, - Nurwijayanti Oktavia, Lola Perdana , Fitra Pranata, Joni Prasetya Prasetya, Prasetya Putra, Ade Herdian Putra, Rido Putri, Atika Putri, Rahmayani Indah Rahayu, Anggi Putri Rahma Dona Rahmadini Syafri Rahmiwati Hilma Ramadhani, Eka Ramadhani, Siti Ramadhanti, Aulia Rizki Retno Hidayati Rudi Hendra Sardi, Hajra Sari, Meidita Kemala Sari, Nila Puspita Silvera Devy Siregar, Alfi Salimah Siregar, Sri Hilma Siregar, srihilma Soeci Izzati Adlya Sofyan Husein Siregar Sulismayati - Surya Agustian Suwanto Sanjaya Sya'ban, Andrian Nur Thamrin Tri Windarti Tri Windarti Tria Harlianti Triana, Yeni Umar Hamdan, Umar Veithzal Rivai Zainal Wan, Xue Wenni, Osriza Wulan Sari, Wulan Yasthophi, Arif Yeni, Wila Mutiara Yuana Nurulita Yuca, Verlanda Yuharmen - Yum Eryanti Yuni Fatisa Zadrian Ardi Zahra, Fadhila Az Zahri, Firman Zikra, Nadila `Nasution, Hasmalina