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Related Experiment Video

Updated: Feb 26, 2026

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator

Published on: October 28, 2022

Online Denoising Based on the Second-Order Adaptive Statistics Model.

Sheng-Lun Yi^1,2, Xue-Bo Jin^3,4, Ting-Li Su^5,6

¹School of Computer Information and Engineering, Beijing Technology and Business University, Beijing 100048, China. yishenglun@st.btbu.edu.cn.

Sensors (Basel, Switzerland)

|July 21, 2017

Summary

This summary is machine-generated.

This study introduces a new online denoising method for industrial processes with colored noise. The technique effectively processes real-time data, balancing efficiency and accuracy for practical applications.

Keywords:

Kalman filter Yule–Walker algorithm online denoising real-time data processing the second-order adaptive statistics model

Related Experiment Videos

Last Updated: Feb 26, 2026

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator

Published on: October 28, 2022

Area of Science:

Signal Processing
Adaptive Systems
Industrial Automation

Background:

Real-time industrial processes require immediate data usability.
Colored noise in practical measurements presents a significant denoising challenge.
Existing methods struggle with the complexities of colored noise in dynamic systems.

Purpose of the Study:

To propose a novel online denoising method for practical measurement data with colored noise.
To incorporate colored noise characteristics into a dynamic model using an adaptive parameter.
To achieve a balance between processing efficiency and denoising accuracy.

Main Methods:

A closed-loop system comprising state estimation and adaptive parameter updating.
State estimation using a second-order adaptive statistics model implemented with a Kalman filter.
Adaptive parameter updating via the Yule-Walker algorithm.

Main Results:

The proposed method effectively denoises signals contaminated with colored noise.
Online processing capability was achieved through a recursive Kalman filter implementation.
Experimental validation on reinforced concrete structure data confirmed method effectiveness.

Conclusions:

The developed online denoising method successfully addresses colored noise in industrial settings.
The approach offers a practical solution for real-time data processing.
The method demonstrates a favorable trade-off between computational efficiency and denoising performance.