Smoothing Techniques for Real-Time Turbine Speed Sensors

2014 ◽  
Author(s):  
Louis Alberto Gutierrez ◽  
Paolo Pezzini ◽  
David Tucker ◽  
Larry Banta
Keyword(s):  
Fuel Cell ◽  
Noise Reduction ◽  
Real Time ◽  
Exponential Smoothing ◽  
Department Of Energy ◽  
Optical Encoder ◽  
Data Noise ◽  
Double Exponential ◽  
Double Exponential Smoothing ◽  
Turbine Speed

A data noise reduction model for a direct-fired fuel cell turbine hybrid power system was evaluated using a hardware-based simulation of an integrated gasifier/fuel cell/turbine hybrid cycle (IGFC), implemented through the Hybrid Performance (HyPer) project at the National Energy Technology Laboratory, U.S. Department of Energy (NETL). The Hyper facility is designed to explore dynamic operation of hybrid systems and quantitatively characterize such transient behavior. The system is controlled by an embedded real-time control platform provided by Woodward Industrial Control. Every sensor is monitored by the platform, and an overall strategy drives the system from start-up to shut-down. Fuel is regulated by a valve which reacts based on the speed of the turbine. There are three optical encoder sensors which are used to monitor turbine speed, and the average of these three sensors is used as feedback for a PID controller, which works to regulate fuel consumption to the combustor. The turbine speed has demonstrated fluctuation in certain conditions, which may be a result of data noise combined with a systemic instability in the flow to the turbine. This research introduces the method of Double Exponential Smoothing as it is applied to data noise reduction in an embedded control platform. An experimental test was conducted to evaluate the performance of the fuel valve speed control when filtered by a real-time Double Exponential Smoothing Algorithm. The results demonstrate, that when compared with traditional filtering techniques, Double Exponential Smoothing offers a significant improvement in both signal volatility and data latency.

scholarly journals Efficient Prediction of Network Traffic for Real-Time Applications

2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Muhammad Faisal Iqbal ◽  
Muhammad Zahid ◽  
Durdana Habib ◽  
Lizy Kurian John
Keyword(s):  
Power Consumption ◽  
Real Time ◽  
Power Management ◽  
Dynamic Resource Allocation ◽  
Computation Complexity ◽  
Real Time Traffic ◽  
Double Exponential ◽  
Efficient Prediction ◽  
Dynamic Resource ◽  
Double Exponential Smoothing

Accurate real-time traffic prediction is required in many networking applications like dynamic resource allocation and power management. This paper explores a number of predictors and searches for a predictor which has high accuracy and low computation complexity and power consumption. Many predictors from three different classes, including classic time series, artificial neural networks, and wavelet transform-based predictors, are compared. These predictors are evaluated using real network traces. Comparison of accuracy and cost, both in terms of computation complexity and power consumption, is presented. It is observed that a double exponential smoothing predictor provides a reasonable tradeoff between performance and cost overhead.

scholarly journals Pengendalian Persediaan Bahan Baku Nalco Water Treatment Dengan Menggunakan Metode Lot Sizing

2019 ◽  
Vol 2 (2) ◽  
pp. 80
Author(s):  
Masad Hariyadi ◽  
Boy Isma Putra
Keyword(s):  
Water Treatment ◽  
Raw Materials ◽  
Unit Cost ◽  
Exponential Smoothing ◽  
Raw Material ◽  
Economic Order Quantity ◽  
Economic Order ◽  
Order Quantity ◽  
Double Exponential ◽  
Double Exponential Smoothing

The limited supply of Nalco raw materials from producers has become a problem for PT ABC, this has led to the control of raw material inventory at PT ABC not including good management, because in the management of raw materials the company still records inventory with manual systems and in ordering raw materials only based on estimates. From the results of the study, the forecasting method used is the Double Exponential Smoothing Holt's, Brown, and Holt Winters Additive Algorithm methods, from the three methods that are most suitable is the Double Exponential Smoothing Brown method with the smallest Mean Square Error of 256.2. Calculation of Sizing Lot by using Economic Order Quantity method, Least Unit Cost method, and Silver Meal method, of the three methods the most optimal is the Economic Order Quantity method because it has the lowest cost of Rp. 12,651,145. The calculation of Safety Stock gets 17 Pail results. and for Reorder Points for Nalco Water Treatment raw material, which is 29 Pail.

scholarly journals Peramalan Kurs IDR Terhadap USD Menggunakan Double Moving Averages Dan Double Exponential Smoothing

2019 ◽  
Vol 2 (2) ◽  
pp. 48-55
Author(s):  
Padrul Jana ◽  
Rokhimi Rokhimi ◽  
Ismi Ratri Prihatiningsih
Keyword(s):  
Exponential Smoothing ◽  
Moving Averages ◽  
Double Exponential ◽  
Double Exponential Smoothing

Kurs IDR terhadap USD yang fluktuatif sangat mempengaruhi ekonomi Indonesia saat ini, dibutuhkan suatu metode untuk meramalkan Kurs IDR terhadap USD agar bisa diprediksi. Diharapkan  para pemangku kepentingan segera mengambil kebijakan strategis demi stabilitas ekonomi nasional. Metode peramalan dalam tulisan ini menggunakan Double Moving Averages dan Double Exponential Smoothing dengan . Hasil peramalan menggunakan metode Double Moving Averages diperoleh IDR/USD, IDR/USD, IDR/USD dan Double Exponential Smoothing diperoleh IDR/USD, IDR/USD, IDR/USD. 14"> Kata Kunci: IDR, USD, Double Moving Averages, Double Exponential Smoothing.

scholarly journals Sistem Informasi Produksi Pakan Ternak Menggunakan Metode Triple Exponential Smoothing (TES) Pada PT. Charoen Pokhpand Medan

2021 ◽  
Vol 4 (2) ◽  
pp. 169
Author(s):  
Umi Pratiwi ◽  
Fhery Agustin
Keyword(s):  
Exponential Smoothing ◽  
Double Exponential ◽  
Double Exponential Smoothing

<p><em>PT. Charoen Pokhpand Medan merupakan perusahaan yang bergerak di bidang produksi dan penjualan produk pakan ternak. Namun ada beberapa kendala yang dihadapi oleh perusahaan yaitu sistem yang berjalan masih menggunakan microsoft excell dalam proses pencatatan dan pembuatan laporan produksi pakan ternak. Dan PT. Charoen Pokhpand Medan harus mendata satu persatu hasil produksi pakan ternak yang terjadi. Bagian produksi mengalami kendala dalam pembuatan laporan peramalan produksi pakan ternak dan untuk prediksi produksi pakan ternak pada periode berikutnya. Dan proses perhitungan peramalan produksi pakan ternak masih menggunakan perhitungan sederhana sehingga dalam penyampaian laporan produksi pakan ternak kepada pimpinan membutuhkan waktu yang lama tidak efektif dan efisien. Dalam proses perhitungan peramalan produksi pakan ternak sering terjadi kesalahan dan tidak sinkron dengan data penjualan sesungguhnya, dibutuhkan metode dalam perhitungan produksi pakan ternak ke periode berikutnya. Dengan menerapkan perbandingan metode triple exponential smoothing dan double exponential smoothing dapat membantu perusahaan dalam mengatasi masalah yang dihadapi oleh perusahaan. Karena triple exponential smoothing </em><em>digunakan ketika terdapat unsur trend dan perilaku musiman yang ditunjukkan pada data. Metode Exponential Smoothing yang dapat digunakan untuk hampir segala jenis data stasioner atau non –stasioner sepanjang data tersebut tidak mengandung faktor musiman.</em></p>

scholarly journals USULAN PERMINTAAN PRODUK SN 5 ML DI PT. XYZ DENGAN METODE TIME SERIES

2021 ◽  
Vol 8 (2) ◽  
pp. 117-122
Author(s):  
Sambas Sundana ◽  
Destri Zahra Al Gufronny
Keyword(s):  
Time Series ◽  
Moving Average ◽  
Exponential Smoothing ◽  
Double Exponential ◽  
Double Exponential Smoothing ◽  
Single Exponential ◽  
Weighted Moving Average

Permasalahan yang dihadapi PT. XYZ yaitu kesulitan dalam menentukan jumlah permintaan produk yang harus tersedia untuk periode berikutnya agar tetap dapat memenuhi kebutuhan pelanggan dan tidak menyebabkan penumpukan barang dalam jangka waktu yang lama terutama produk SN 5 ML yang memiliki permintaan jumlah paling besar dari produk lainnya. Tujuan dari penelitian ini yaitu menentukan metode peramalan yang tepat untuk meramalkan jumlah permintaan produk SN 5 ml periode Januari sampai dengan Desember 2021 Metode yang digunakan dalam penelitian ini yaitu metode peramalan Moving Average (MA), Weighted Moving Average (WMA), Single Exponential Smoothing (SES), dan Double Exponential Smoothing (DES). Adapun langkah langkah peramalan yang dilakukan yaitu menentukan tujuan peramalan,memilih unsur apa yang akan diramal, menentukan horizon waktu peramalan (pendek, menengah, atau panjang), memilih tipe model peramalan, mengumpulkan data yang di perlukan untuk melakukan peramalan, memvalidasi dan menerapkan hasil peramalan Berdasarkan perhitungan didapat metode peramalan dengan persentase tingkat kesalahan terkecil dibandingkan dengan metode lainnya yaitu  metode Moving Average (MA) dengan hasil yang diperoleh permintaan produk SN 5 ML pada bulan Januari sampai dengan Desember 2021 yaitu sebanyak 22.844.583 unit

scholarly journals Forecasting Stock Market Price of Gold, Silver, Crude Oil and Platinum by Using Double Exponential Smoothing, Holt’s Linear Trend and Random Walk

2021 ◽  
Vol 1874 (1) ◽  
pp. 012087
Author(s):  
Shuhaidah Abdul Shukor ◽  
Suliadi Firdaus Sufahani ◽  
Kamil Khalid ◽  
Mohd Helmy Abd Wahab ◽  
Syed Zulkarnain Syed Idrus ◽  
...  
Keyword(s):  
Random Walk ◽  
Stock Market ◽  
Crude Oil ◽  
Linear Trend ◽  
Market Price ◽  
Exponential Smoothing ◽  
Double Exponential ◽  
Gold Silver ◽  
Double Exponential Smoothing
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