Time-Domain Fault Diagnosis Method of Mechanical and Electrical Equipment Based Improved Dynamic Time Wraping

Zhi Wu Shang; Zhen Wu Liu; Ya Feng Li; Wang Tai Yong

doi:10.4028/www.scientific.net/KEM.693.1539

Paper Titles

An Experimental Research on the Vibration Reduction of Ball Bearings by Superfinishing Process
p.1509

A Processing Method of Identifying Spectrum of Shock Load for the Combustion Gas Stream
p.1517

A Transient Faults Diagnosis Method Based on EEMD, Spectral Kurtosis Theory and Energy Operator Demodulating
p.1524

Research of Noise Mechanism and Performance Improve of DVC Drum
p.1532

Time-Domain Fault Diagnosis Method of Mechanical and Electrical Equipment Based Improved Dynamic Time Wraping
p.1539

Vibration Analysis of Civil Aero-Engine Based on Stochastic Resonance Preprocessing
p.1545

2-D Defect Profile Reconstruction from Ultrasonic Guided Wave Signals Based on Radial Wavelet Basis Function Neural Network with ELM
p.1551

Design for New Gear Measuring Centers
p.1562

Development of Portable Fault Diagnosis System Based on SR
p.1567

HomeKey Engineering MaterialsKey Engineering Materials Vol. 693Time-Domain Fault Diagnosis Method of Mechanical...

Time-Domain Fault Diagnosis Method of Mechanical and Electrical Equipment Based Improved Dynamic Time Wraping

Abstract:

Dynamic time warping used in speech recognition widely was migrated to fault feature extraction and diagnosis in time domain. Integration of phase compensation, slope weighted, derivative, sliding window connection, fast dynamic time planning method is applied to dynamic time warping method. And a new method of time-domain signal feature extraction and fault diagnostic based on improved dynamic time warping method of mechanical and electrical equipment was proposed. Identification and localization of fault signal characteristics may be done by improving dynamic time warping method to obtain a residual signal sequences with fault characterized sidebands and selecting the statistical characteristic parameters such as peak, RMS, kurtosis spectrum to complete identification and localization of fault signal characteristics. New time-domain fault trend prediction method of mechanical and electrical equipment was established based on new statistical parameter Thikat. A new idea and target was provided for fault diagnosis of mechanical and electrical equipment.

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Periodical:

Key Engineering Materials (Volume 693)

Pages:

1539-1544

DOI:

https://doi.org/10.4028/www.scientific.net/KEM.693.1539

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Online since:

May 2016

Authors:

Zhi Wu Shang*, Zhen Wu Liu, Ya Feng Li, Wang Tai Yong

Keywords:

Dynamic Time Warping, Thikat, Time-Domain Fault Diagnosis, Trend Forecast

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