Paper Title:
Extraction Feature of Motor Unbalance and Interference of Alternating Current Based on the Wavelet Transform
  Abstract

A new method for extracting spectrum feature of motor unbalance and interference of alternating current (AC) is proposed. The flatness error of workpiece surface includes much errors information, and the information contains high frequency signal and low frequency signal, for these errors information, a new identification method of turning errors of workpiece based on the wavelet transform and power spectral density analysis is proposed. According to the focal variation character of wavelet and the energy value of power spectral density analysis, the feature of motor unbalance and AC from the measured flatness error of workpiece is extracted and identified.

  Info
Periodical
Edited by
Qi Luo
Pages
1028-1033
DOI
10.4028/www.scientific.net/AMM.55-57.1028
Citation
D. J. Chen, J. W. Fan, F. H. Zhang, "Extraction Feature of Motor Unbalance and Interference of Alternating Current Based on the Wavelet Transform", Applied Mechanics and Materials, Vols. 55-57, pp. 1028-1033, 2011
Online since
May 2011
Export
Price
$32.00
Share

In order to see related information, you need to Login.

In order to see related information, you need to Login.

Authors: Jian Zhou, Li Qing Li
Abstract:Silk fabrics density are usually very high because the silk yarns are finer than spinning yarns, so it difficult to calculate the density...
371
Authors: Gui Juan Zhao
Abstract:A test section was selected in Luo-San expressway.Four detection methods of compaction degree which are sand cone method, cutting ring,...
252
Authors: Jun Jing Yang, Hong Yan Chu, Li Gang Cai, Lei Su
Chapter 18: Quality Monitoring and Control of the Manufacturing Process
Abstract:Abstract : Aiming at the controlled object with large lag, model uncertainty and time variation due to the effects of working environment in...
3071
Authors: Qi Sheng He, Na Li
Chapter 16: Cultivation and Conservation of Forest
Abstract:In this paper, the effects of different LiDAR point density on individual tree parameters including tree height and crown diameter were...
5320