Perancangan dan Implementasi Sistem Monitoring Beban dan Kecepatan Kendaraan Menggunakan Teknologi Weigh in Motion

Septiana, Trisya; Zaini, Zaini

doi:10.25077/jnte.v7n1.512.2018

Cited by 3 publications

(2 citation statements)

References 6 publications

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“…Pada sensor load cell terdapat elemen pegas yang mampu memberikan sinyal tegangan jika ada tarikan atau tekanan yang diberkan pada sensor load cell. Sensor ini mampu menghasilkan sinyal keluaran yang berubah secara kontinu dengan nilai output berbanding lurus dengan beban yang diterapkan [9]. Prinsip kerja dari load cell adalah menggunakan perlawanan listrik ke tegangan logam foil yang saling berhubungan, dititik maksimum tegangan elemen tersebut diukur kemudian dikonversi mejadi tegangan listrik proporsional [10].…”

Section: 5unclassified

Rancang Bangun Alat Prediksi Kondisi Tubuh Ideal Menggunakan Metode Fuzzy Logic Sugeno

Fikri¹,

Erwanto

Yuliana

2018

JIS

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Parameters used to determine one's body condition is weight and height. Manually to determine the Body Mass Index (BMI) requires two steps, namely measuring body weight and height then calculate body mass index, so less effective. Using fuzzy logic sugeno method, can be designed a device to predict the condition of the human body based on body mass index by measuring weight and height with just one step using this device. From the results of the research that has been done, the load cell is able to measure the weight well, with an average error of 3.95%, and for ultrasonic sensors are able to detect distances very well, with an average error of 1.5%. As for the overall devices testing there is an average error of IMT results of 4.61%. However, although there are differences in IMT results from of measurement by manual devices and measurement with digital devices, the results of both are still in the same category of body condition. AbstrakParameter yang digunakan untuk menentukan kondisi tubuh sesorang adalah berat badan serta tinggi badan. Secara manual untuk menentukan Indeks Massa tubuh (IMT) membutuhkan dua langkah, yaitu mengukur berat badan serta tinggi badan kemudian dihitung IMT-nya, sehingga kurang efektif. Dengan Menggunakan metode logika fuzzy sugeno, dapat dirancang alat untuk memprediksi kondisi tubuh manusia berdasarkan Indeks Massa Tubuh dengan cara mengukur berat badan serta tinggi badan hanya dengan satu langkah memggunakan alat tersebut. Dari hasil penelitian yang telah dilakukan, load cell mampu mengukur berat dengan baik, dengan error rata-rata sebesar 3,95 %, dan untuk sensor ultrasonik mampu mendeteksi jarak dengan sangat baik, dengan error rata-rata sebesar 1,5%. Sedangkan untuk pengujian alat secara keseluruhan terdapat error rata-rata hasil IMT sebesar 4,61%. Akan tetapi meskipun terdapat perbedaan hasil IMT dari pengukuran dengan alat manual dan pengukuran dengan alat digital, hasil keduanya masih dalam kategori kondisi tubuh yang sama.

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Section: 5unclassified

Rancang Bangun Alat Prediksi Kondisi Tubuh Ideal Menggunakan Metode Fuzzy Logic Sugeno

Fikri¹,

Erwanto

Yuliana

2018

JIS

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“…In connection with this problem, optical fiber-based sensor technology seems to be an alternative solution. Weigh in Motion (WIM) is a method used for measuring vehicle loads that can be done when the vehicle is in motion which is used in vehicle traffic counting [7]. Some of the advantages of WIM technology include being more efficient and saving time, especially during busy traffic.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Characterization of Macrobending Loss Optical Fiber-Based Load Sensor

Widiyatmoko¹,

Rofianingrum²

2021

JoTP

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The weight of vehicles passing through the road greatly affects road damage, so it is necessary to have a non-stop weighing system or Weight in Motion (WIM). In this study, the dynamic characterization of the WIM sensor was carried out based on the principle of optical fiber macrobending. In this study, a single-mode step-index optical fiber was used as the sensor material and a laser diode with a power of 5 mW and a wavelength of 1,550 nm as a light source. Characterization was carried out by running over the sensor using a motor with three variations of speed, namely 10 km/hour, 15 km/hour, and 20 km/hour. Two different conditions were also carried out, namely, the sensor was directly crushed and the sensor was reinforced in the form of a half-cylinder wooden beam. The test was carried out with three different types of sensors. From the observations, data shows that the addition of a beam can increase the accuracy of the reading as seen from the smaller the difference in the output voltage reading for the same type of sensor and vehicle speed. Besides that, there is a strengthening of the sensor resistance up to 10 times which is known from the sensor output voltage where the voltage at the addition of the beam is 1/10 of the reading without the beam. This is due to an increase in the sensor area exposed to the load.

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