A Hybrid Signal Processing Approach to Sensor Data Analysis

Ruqiang Yan; Robert X. Gao

doi:10.1115/IMECE2003-42586

A Hybrid Signal Processing Approach to Sensor Data Analysis

Ruqiang Yan
, Robert X. Gao

University of Massachusetts

Research output: Contribution to conference › Paper › peer-review

8 Scopus citations

Abstract

This paper presents a hybrid signal processing approach combining the wavelet transform and spectral analysis. A new approach to selecting a mother wavelet for decomposition of vibration signals was demonstrated. Subsequently, the best-suited decomposition scale was selected based on the energy content of the wavelet coefficients. Subsequently, the envelope spectrum of the wavelet coefficients at the best-suited decomposition scale was used to identify the defect and its location. Experimental analysis of signals from a defect-seeded bearing has shown that the developed approach is more efficient than the conventional spectral analysis techniques.

Original language	English
Pages	1159-1166
Number of pages	8
DOIs	https://doi.org/10.1115/IMECE2003-42586
State	Published - 2003
Externally published	Yes
Event	2003 ASME International Mechanical Engineering Congress - Washington, DC., United States Duration: 15 Nov 2003 → 21 Nov 2003

Conference

Conference	2003 ASME International Mechanical Engineering Congress
Country/Territory	United States
City	Washington, DC.
Period	15/11/03 → 21/11/03

Keywords

Continuous wavelet transform
Defect diagnosis
Signal enveloping
Spectral analysis

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10.1115/IMECE2003-42586

Cite this

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title = "A Hybrid Signal Processing Approach to Sensor Data Analysis",

abstract = "This paper presents a hybrid signal processing approach combining the wavelet transform and spectral analysis. A new approach to selecting a mother wavelet for decomposition of vibration signals was demonstrated. Subsequently, the best-suited decomposition scale was selected based on the energy content of the wavelet coefficients. Subsequently, the envelope spectrum of the wavelet coefficients at the best-suited decomposition scale was used to identify the defect and its location. Experimental analysis of signals from a defect-seeded bearing has shown that the developed approach is more efficient than the conventional spectral analysis techniques.",

keywords = "Continuous wavelet transform, Defect diagnosis, Signal enveloping, Spectral analysis",

author = "Ruqiang Yan and Gao, \{Robert X.\}",

year = "2003",

doi = "10.1115/IMECE2003-42586",

language = "英语",

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note = "2003 ASME International Mechanical Engineering Congress ; Conference date: 15-11-2003 Through 21-11-2003",

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AU - Gao, Robert X.

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N2 - This paper presents a hybrid signal processing approach combining the wavelet transform and spectral analysis. A new approach to selecting a mother wavelet for decomposition of vibration signals was demonstrated. Subsequently, the best-suited decomposition scale was selected based on the energy content of the wavelet coefficients. Subsequently, the envelope spectrum of the wavelet coefficients at the best-suited decomposition scale was used to identify the defect and its location. Experimental analysis of signals from a defect-seeded bearing has shown that the developed approach is more efficient than the conventional spectral analysis techniques.

AB - This paper presents a hybrid signal processing approach combining the wavelet transform and spectral analysis. A new approach to selecting a mother wavelet for decomposition of vibration signals was demonstrated. Subsequently, the best-suited decomposition scale was selected based on the energy content of the wavelet coefficients. Subsequently, the envelope spectrum of the wavelet coefficients at the best-suited decomposition scale was used to identify the defect and its location. Experimental analysis of signals from a defect-seeded bearing has shown that the developed approach is more efficient than the conventional spectral analysis techniques.

KW - Continuous wavelet transform

KW - Defect diagnosis

KW - Signal enveloping

KW - Spectral analysis

UR - https://www.scopus.com/pages/publications/1842614346

U2 - 10.1115/IMECE2003-42586

DO - 10.1115/IMECE2003-42586

M3 - 论文

AN - SCOPUS:1842614346

SP - 1159

EP - 1166

T2 - 2003 ASME International Mechanical Engineering Congress

Y2 - 15 November 2003 through 21 November 2003

ER -

A Hybrid Signal Processing Approach to Sensor Data Analysis

Abstract

Conference

Keywords

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