20102010 3rd International Congress on Image and Signal ProcessingRequires access

A fault diagnosis method for rolling bearing based on empirical mode decomposition and homomorphic filtering demodulation

Junfa Leng, Shuangxi Jing, Hua Wei

Open publisher page 3 citations

Abstract

A new fault diagnosis method based on empirical mode decomposition (EMD) and homomorphic filtering demodulation is proposed for rolling bearing. The vibration signal of fault rolling bearing is decomposed into a series of intrinsic mode functions (IMFs) by EMD, then extract the envelopes from the outstanding IMFs with various fault characteristic information by homomorphic filtering demodulation and Hilbert envelope demodulation, and do the comparison analysis. The research results show that homomorphic filtering demodulation is superior to Hilbert envelope demodulation, and the combination of EMD and homomorphic filtering demodulation is an effective approach for rolling bearing fault diagnosis.

About this research paper

What this paper is about

A new fault diagnosis method based on empirical mode decomposition (EMD) and homomorphic filtering demodulation is proposed for rolling bearing. The vibration signal of fault rolling bearing is decomposed into a series of intrinsic mode functions (IMFs) by EMD, then extract the envelopes from the outstanding IMFs with various fault characteristic information by homomorphic filtering demodulation and Hilbert envelope demodulation, and do the comparison analysis. The research results show that homomorphic filtering demodulation is superior to Hilbert envelope demodulation, and the combination of EMD and homomorphic filtering demodulation is an effective approach for rolling bearing fault diagnosis.

Why it matters

OpenAlex reports 3 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

A new fault diagnosis method based on empirical mode decomposition (EMD) and homomorphic filtering demodulation is proposed for rolling bearing. The vibration signal of fault rolling bearing is decomposed into a series of intrinsic mode functions (IMFs) by EMD, then extract the envelopes from the outstanding IMFs with various fault characteristic information by homomorphic filtering demodulation and Hilbert envelope demodulation, and do the comparison analysis. The research results show that homomorphic filtering demodulation is superior to Hilbert envelope demodulation, and the combination of EMD and homomorphic filtering demodulation is an effective approach for rolling bearing fault diagnosis.

Key concepts: Demodulation, Hilbert–Huang transform, Homomorphic filtering, Fault (geology), Hilbert transform, Computer science, Bearing (navigation), SIGNAL (programming language)

Related papers

Back to paper searchBrowse research topicsOriginal source
A fault diagnosis method for rolling bearing based on empirical mode decomposition and homomorphic filtering demodulation — Research Paper | ScholarLens