Evaluasi Performa 1st Order LPF dan EMA: Denoising Data Sensor di bawah Pengaruh Transien Pulsa Gaussian

Muhammad Fikri; Fahrur Riza P.; Awansah; M. Nur Khawarizmi; Rizkima Akbar S.

doi:10.23960/jitet.v13i3.7669

Authors

Muhammad Fikri Universitas Lampung
Fahrur Riza P.
Awansah
M. Nur Khawarizmi
Rizkima Akbar S.

DOI:

https://doi.org/10.23960/jitet.v13i3.7669

Abstract Views: 27 File Views: 26

Keywords:

denoising, signal conditioner, LPF, EMA, transient event, data sensor

Abstract

Penelitian ini bertujuan untuk mengevaluasi performa 1^st Order Low-Pass Filter (LPF) dan Exponential Moving Average (EMA) sebagai signal conditioner untuk denoising data sensor, dengan fokus pada respons denoiser terhadap event transien. Metode synthetic benchmarking digunakan dengan data sensor sintetis yang terkontaminasi derau Gaussian dan injeksi pulsa Gaussian sebagai event transien pada interval waktu tertentu. Analisis dilakukan di domain waktu dan frekuensi menggunakan metrik Signal-to-Noise Ratio (SNR), Root Mean Squared Error (RMSE) keseluruhan dan transien, Peak Amplitude Preservation (PAP), serta Delay. Hasil simulasi menunjukkan bahwa kedua denoiser relatif efektif dalam mereduksi derau dan meningkatkan SNR. EMA terbukti superior dalam mempreservasi event transien, dengan PAP 65,89%, delay 2 ms, dan RMSE_transient 0,7845 dibandingkan LPF dengan PAP 57,98%, delay 3 ms, dan RMSE_transient 0,8886. Penelitian ini menggarisbawahi adanya kompromi inheren antara efektivitas denoising dan integritas event transien. Kondisi tersebut menunjukkan bahwa pemilihan denoiser harus mempertimbangkan prioritas spesifik masing-masing aplikasi.

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References

Z. Zhang, X. Kong, Y. Zheng, L. Zhou, and X. Lai, "Real-time diagnosis of micro-short circuit for Li-ion batteries utilizing low-pass filters," Energy, vol. 166, pp. 1013–1024, 2019, doi: 10.1016/j.energy.2018.10.160.

B. Gao, G. Hu, Y. Zhong, and X. Zhu, "Cubature Kalman filter with both adaptability and robustness for tightly-coupled GNSS/INS integration," IEEE Sensors Journal, vol. 21, no. 13, pp. 14997–15011, Jul. 1, 2021, doi: 10.1109/JSEN.2021.3073963.

G. Welch and G. Bishop, An Introduction to the Kalman Filter, Tech. Rep. TR 95-041, Dept. of Computer Science, Univ. of North Carolina at Chapel Hill, 2006.

Y. Li and X. Wang, "Comparative Study of Simple Moving Average and Exponential Moving Average in Short-Term Forecasting," Journal of Forecasting and Analytics, vol. 12, no. 3, pp. 215–225, 2020.

J. Barbancho, C. León, F. J. Molina, and A. M. Barbancho, “Real-time implementation of digital filters on low-cost microcontrollers for audio applications,” IEEE Transactions on Consumer Electronics, vol. 56, no. 3, pp. 1362–1369, Aug. 2010, doi: 10.1109/TCE.2010.5606273.

Z. Wang, Y. Chen, and L. Zhang, “Comparison of various single filtering techniques for sensor data denoising,” IEEE Sensors Journal, vol. 22, no. 4, pp. 3567–3576, Feb. 2022, doi: 10.1109/JSEN.2022.3141234.

J. Fraden, Handbook of Modern Sensors: Physics, Designs, and Applications, 4th ed. New York, NY, USA: Springer, 2010.

J. G. Proakis and D. G. Manolakis, Digital Signal Processing: Principles, Algorithms and Applications, 4th ed. Upper Saddle River, NJ, USA: Prentice Hall, 2007, ch. 10, pp. 783-840.

W. Kester, Data Conversion Handbook. Burlington, MA, USA: Newnes/Analog Devices Inc., 2005.

S. W. Smith, The Scientist and Engineer’s Guide to Digital Signal Processing. San Diego, CA, USA: California Technical Publishing, 1997.

C. Ifeachor and B. W. Jervis, Digital Signal Processing: A Practical Approach, 2nd ed. Harlow, England: Pearson Education, 2002.

A. V. Oppenheim and R. W. Schafer, Discrete-Time Signal Processing, 3rd ed. Upper Saddle River, NJ, USA: Prentice Hall, 2010.

M. Fikri, S. Herdjunanto, and A. Cahyadi, "On the performance similarity between exponential moving average and discrete linear Kalman filter," in Proc. 2019 Asia Pacific Conf. on Research in Industrial and Systems Engineering (APCoRISE), Depok, Indonesia, 2019, pp. 1–5, doi: 10.1109/APCoRISE46197.2019.9318810.

H. Kim, "Signal processing using moving averages," Journal of Signal Processing, vol. 45, no. 3, pp. 256–267, 2020.

Financial time series and exponential moving averages," Journal of Financial Data Analysis, vol. 32, no. 2, pp. 115–123, 2018.

P. E. McSharry, G. D. Clifford, L. Tarassenko, and L. A. Smith, "A dynamical model for the simulation of ECG data," IEEE Trans. Biomed. Eng., vol. 50, no. 3, pp. 289-296, Mar. 2003.

M. H. Alkarim, I. I. Prasojo, S. A. Nugroho, and E. E. Nugroho, "Penerapan algoritma filter untuk meningkatkan akurasi pembacaan sensor suhu MLX90614 pada objek dengan eliminasi pengaruh suhu lingkungan," JITET, vol. 13, no. 3, Jul. 2025.