Nurrohman, Virbyansah Achmadan (2018) Perangkat Pemantau dan Identifikasi Kondisi Rel Kereta Api sebagai Pemandu Petugas Perawatan Rel dan Masinis Kereta Api. Undergraduate thesis, Institut Teknologi Sepuluh Nopember.
Preview |
Text
07211440000020_Undergraduate_Theses.pdf - Accepted Version Download (1MB) | Preview |
Abstract
Pemeriksaan rutin kondisi rel kereta api sudah dilaksanakan oleh PT Kereta Api Indonesia (PT KAI) menggunakan kereta ukur. Akibat tidak seimbangnya jumlah kereta ukur dengan panjang jalur rel kereta api yang harus diperiksa, pemeriksaan rel kereta api hanya bisa dilaksanakan sebanyak dua kali dalam satu tahun. Hal tersebut dirasa masih belum cukup untuk memperbarui data kondisi rel. Pada tugas akhir ini dibuatlah suatu sistem pemantau kondisi rel kereta api secara real time dengan menggunakan sensor vibrasi untuk mengidentifikasi kondisi rel kereta api berdasarkan lokasi. Data dapat diperbarui lebih cepat karena sistem dapat diterapkan pada semua jenis kereta api. Setelah dilakukan pengujian, didapatkan tingkat validasi data berdasarkan rata-rata selisih nilai geteran sebesar 0,06 g sumbu horizontal, 0,1 g sumbu lateral, 0,19 g sumbu vertikal dengan selisih jarak sebesar 34,3 meter, nilai galat rata-rata sensor adalah galat lokasi sebesar 12,2 meter, dengan delay gps 2,8 detik, galat kecepatan sebesar 17,36%, dan galat akselerometer sebesar 0,059 g dan interval waktu transmisi data sebesar 1,04 detik. Dengan dikembangkannya alat ini, petugas perwatan rel kereta api akan mendapat laporan kondisi rel kereta api beradasarkan warna marker sesuai dengan parameter nilai indeks dan dengan aplikasi peringatan dini, masinis kereta api mendapat notifikasi batas kecepatan maksimal pada lokasi rel tertentu.
=============================================================================== Inspection routine of railroad conditions has been carried out by PT Kereta Api Indonesia (PT KAI) using a measurement train. Due to the unbalanced number of trains with the length of the railway tracks to be checked, the rail inspection can only be run two times a year. It is still not enough to update the rail condition data. In this final project a real time railway monitoring system by using vibration sensor to identify rail condition based on location is developed. Data can be updated faster because the system can be applied to all types of trains. After testing, data validation rate was obtained based on average difference of 0.06 g horizontal axis, 0.1 g lateral axis, 0.19 g vertical axis with distance difference of 34.3 meters, average error value the sensor is a location error of 12.2 meters, with a gps delay of 2.8 seconds, a speed error of 17.36 %, and an accelerometer error of 0.059 g and a data transmission time interval of 1.04 seconds. With the development of this tool, railway trainers will get reports on railway conditions based on marker colors according to index value parameters and with early warning applications, train drivers receive maximum speed limit notification at certain rail locations.
Item Type: | Thesis (Undergraduate) |
---|---|
Additional Information: | RSKom 005.133 Nur p |
Uncontrolled Keywords: | Kereta Api, Peta Digital, Indeks Rel, Batas Kecepatan, Peringatan dini |
Subjects: | T Technology > T Technology (General) > T174 Technological forecasting T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK5103.2 Wireless communication systems. Two way wireless communication T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7871.674 Detectors. Sensors T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK9956 Radio. Wireless telephone T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK5101 Telecommunication |
Divisions: | Faculty of Electrical Technology > Computer Engineering > 90243-(S1) Undergraduate Thesis |
Depositing User: | Virbyansah Achmadan Nurrohman |
Date Deposited: | 26 Nov 2020 06:09 |
Last Modified: | 26 Nov 2020 06:09 |
URI: | http://repository.its.ac.id/id/eprint/58496 |
Actions (login required)
View Item |