The Experts below are selected from a list of 297 Experts worldwide ranked by ideXlab platform

Lei Wang - One of the best experts on this subject based on the ideXlab platform.

  • The Research of Order Prediction Model for Textile Machinery Manufacturing Enterprise Based on Customer Demand
    Proceedings of the 2015 International Conference on Automation Mechanical Control and Computational Engineering, 2015
    Co-Authors: Shunsheng Guo, Lei Wang
    Abstract:

    With the development of information technology, Textile Machinery manufacturing enterprises (TMME) are facing the new situation of "Two Integration", in order to better responding to market customer demand (CD), the order prediction is becoming more and more important. The background of product model of TMME is different from other manufacturing enterprise, the CD information about TMME is full of diversity, fuzziness and concealment. In this paper, an order prediction model for TMME is constructed by combining the CD with improved time series, also it has been applied and verified in an actual enterprise.

  • The Performance Study of Hybrid-driving Differential Gear Trains
    Mathematical Models and Methods in Applied Sciences, 2009
    Co-Authors: Lei Wang, Jiancheng Yang
    Abstract:

    This article in view of the differential gear trains theory characteristic, carried on the analysis to the mechanism performance, and obtained the best design scheme of the Hybrid-driving two degree of freedom differential gear trains. Adopted programmable logic controller (short for PLC) component and frequency converter to control the constant speed motor and the variable speed motor, developed a laboratory bench of Hybrid-driving two degree of freedom differential gear trains and utilized a encoder to gather the experimental data under this condition. This laboratory bench will be used as a research platform for basic theory of Textile Machinery and providing the rationale to optimize its variable speed mechanism.

Wei Zhang - One of the best experts on this subject based on the ideXlab platform.

  • Research on Signal Processing Method in Complex Textile Machinery System Based on Principal Component Analysis and Wavelet Analysis
    2010 International Conference on Intelligent Computation Technology and Automation, 2010
    Co-Authors: Zhengying Lin, Weiyuan Shi, Wei Zhang
    Abstract:

    This paper proposed a signal processing method based on principal component analysis (PCA) and wavelet analysis, aiming to reduce the dimension of the data and obtain both frequency and time localization information which could help to find abnormal phenomenon quickly and orient the position and the time of faults exactly in the complex Textile Machinery system. At first, the original signals were simplified by principal component transform, which was conducted by calculating the eigen value and eigenvector of correlation coefficient matrix, and by defining the first few PCs containing most of the variables according to contribute rate and cumulative contribute rate. Secondly, the restructured signals were decomposed into approximative and detailed ones for obtaining meaningful captures of instantaneous frequency by wavelet analysis. In this stage, Hilbert Envelope Analysis was also carried out to the first layer detail signal and to find its power spectrum. From practical application, this signal processing method was approved validated.

Zhang Wei - One of the best experts on this subject based on the ideXlab platform.

  • Research on signal processing method for complex Textile Machinery system based on principal component analysis and wavelet analysis
    Journal of Hefei University of Technology, 2010
    Co-Authors: Zhang Wei
    Abstract:

    This paper proposes a signal processing method for the complex Textile Machinery system based on principal component analysis(PCA) and wavelet analysis.At first,the original signals are simplified by principal component transform,which is conducted by calculating the eigenvalue and eigenvector of correlation coefficient matrix,and the first few principal components(PCs) containing most of the variables are defined according to contribution rate and cumulative contribution rate.Secondly,the restructured signals are decomposed into approximative and detailed ones for obtaining meaningful captures of instantaneous frequency by wavelet analysis.And then,Hilbert Envelope Analysis of the first layer detail signal is also carried out to find its power spectrum.This signal processing method is validated by practical application.

Zhou Lei - One of the best experts on this subject based on the ideXlab platform.

Sun Yan - One of the best experts on this subject based on the ideXlab platform.