Perancangan reduksi noise sensor bahan bakar menggunakan filter kalman
Info Katalog
File Repositori
Subyek : Fuel consumption;Kalman filtering;Machine tools - Design
Penerbit : FTI - Usakti
Kota Terbit : Jakarta
Tahun Terbit : 2021
Pembimbing 1 : Suhartati Agoes
Kata Kunci : fuel sensor, kalman filter, noise, covariance q, covariance r
Status Posting : Published
Status : Lengkap
File Repositori
| No. | Nama File | Hal. | Link |
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| 1. | 2021_TS_MTE_162160001_Halaman-Judul.pdf | 10 | |
| 2. | 2021_TS_MTE_162160001_Lembar-Pengesahan.pdf | ||
| 3. | 2021_TS_MTE_162160001_Bab-1_Pendahuluan.pdf | ||
| 4. | 2021_TS_MTE_162160001_Bab-2_Tinjauan-Pustaka.pdf |
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| 5. | 2021_TS_MTE_162160001_Bab-3_Metodologi-Penelitian.pdf |
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| 6. | 2021_TS_MTE_162160001_Bab-4_Analisis-dan-Pembahasan.pdf |
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| 7. | 2021_TS_MTE_162160001_Bab-5_Kesimpulan.pdf |
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| 8. | 2021_TS_MTE_162160001_Daftar-Pustaka.pdf | ||
| 9. | 2021_TS_MTE_162160001_Lampiran.pdf |
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P Perancangan Reduksi Noise Sensor Bahan Bakar MenggunakanFilter KalmanPada bidang transportasi, telematika digunakan untuk mendapatkan informasikendaraan yang memanfaatkan teknologi Global Positioning System (GPS) yangterintegrasi sensor sehingga informasi kendaraan dapat dipantau. Salah satunyapemantauan bahan bakar. Sensor bahan bakar memiliki akurasi yang baik padakondisi kendaraan diam namun kestabilan data terganggu saat kendaraan berjalandi jalan yang tidak rata dan mengakibatkan tangki terguncang. Penelitian inimembahas sistem reduksi noise sensor bahan bakar menggunakan filter Kalmanuntuk mengatasi permasalahan ketidakstabilan data akibat guncangan. Tujuanpenelitian adalah mereduksi noise sehingga diperoleh data hasil filter yangmendekati aktual. Filterisasi dilakukan dengan mengubah kovarian error proses (Q)dan error pengukuran (R) pada filter Kalman. Noise sensor bahan bakardisimulasikan menggunakan model tangki yang digerakkan aktuator yang dapatbergerak miring terhadap sumbu x dan sumbu y menyerupai perilaku kendaraan.Data tingkat bahan bahan bakar hasil pembacaan sensor dikirim GPS melaluijaringan seluler ke server yang kemudian difilter menggunakan aplikasi web. Darihasil pengujian diperoleh filter terbaik dengan (Q) sebesar 0,13dan (R) sebesar 0,13.Kesalahan rata-rata hasil filter terbaik yaitu 4,73%, dimana nilai ini lebih kecil1,92% dari kesalahan rata-rata data sensor sebelum difilter yaitu sebesar 6,65%yang membuktikan sistem mampu mereduksi noise yang terjadi pada sensor bahanbakar dengan filter Kalman.
D Design of Fuel Sensor Noise Reduction Using Kalman FiltersIn the field of transportation, telematics is used to obtain vehicle information usingGlobal Positioning System (GPS) technology which is integrated with sensors sothat vehicle information can be monitored. One of them is fuel monitoring. The fuelsensor has good accuracy in stationary conditions, but the stability of the data isdisturbed when the vehicle is running on an uneven road and causes the tank toshake. This study discusses a fuel sensor noise reduction system using a Kalmanfilter to overcome the problem of data instability due to shocks. The aim of thisresearch is to reduce noise so that the filter results are closer to the actual result.Filtering is done by changing the process error covariance (Q) and measurementerror (R) in the Kalman filter. The fuel sensor noise is simulated using a model tankdriven by an actuator that can tilt towards the x-axis and the y-axis to resemble thebehavior of a vehicle. The fuel level data from the sensor readings is sent by GPSvia the cellular network to a server which is then filtered using a web application.From the test results obtained the best filter with (Q) 0.13and (R) 0.13. The averageerror of the best filter results is 4.73%, where this value is 1.92% smaller than theaverage error of sensor data before filtering, which is 6.65% which proves thesystem is able to reduce noise that occurs on the fuel sensor by Kalman filters
