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Input Variable Selection for Neural Networks of Yarn Properties of Rotor Spinning

Author: YangXiaoXia
Tutor: ChenTing
School: Donghua University
Course: Textile Engineering
Keywords: rotor spinning neural network yarn properties input variable selection
CLC: TS104
Type: Master's thesis
Year: 2009
Downloads: 26
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Abstract


The rotor spinning process is a complex manufacturing system.There are so many factors which all can influence the properties of the yarns produced.There will be too many input variables if all factors are considered when use the artificial neural networks to predict the yarn properties of rotor spinning. Too many input variables will increase the training load of the ANNs,and it is harmful for the accuracy of the prediction.In fact,the number of the samples in the spinning mill is limited, so less input variables is better.Therefor,it`s necessary to establish ANNs model to accurately predict the quality of rotor spun yarns with less input variables.At present,empirical approach and certain mathematical method have been using in selecting input variables.The former is subjective then cannot show the importance of how the input variables influence the output variables;the later may lose its justness because different mathematical methods focus on different aspects.This paper introduces four methods to rank input variables: the first one is grey incidence analysis;the second one uses a data sensitivity criterion based on a distance method that analyzes the measured data of raw material,machine,process and rotor spun yarns;the third one takes the human knowledge on the rotor spun yarn into account;the last method is a new fuzzy selection criterion which thinks much of the sensitive of the measured data.First of all,the research chooses 17 input variables from raw material properties,spinning machine and spinning process. Then there are experiments on raw material properties,spinning and rotor spun yarns properties.Due to the experiments,all input/output data is gained.After that,the four methods are use to rank the input variables for certain property of the yarns and four different rankings come out.At last,the fuzzy selecting criterion plays an important part again in combination the rankings.The ANN model is established for every specific property of the yarns,at first,the model is taken to test and verify the efficiency of the selecting methods;then,from the first to the seventh variables in the ranking line are taken as the most relevant input variables of the ANN for predicting the quality of the rotor spun yarns.The result is that,the prediction of the ANNs is close to the real data.It’s proved the selecting methods are efficient and right,as well as the ANNs can be used to predict the quality of rotor spun yarn.

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CLC: > Industrial Technology > Light industry,handicrafts > Textile industry,dyeing and finishing industry > General issues > Spinning theories and spinning process
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