| Handle has been closely related to people’s lives since ancient times.From the selection of traditional clothing fabrics in ancient times to the pursuit of diversified textile properties in the modern.With the improvement of living standards and the development of science and technology,handle has gradually become the emphasis to the people as the perception of touching the fabrics by hands,and it has also become a key factor in textile sales.The research topic of fabric handle has been studied by domestic and foreign scholars,mainly concentrating on the development of testing methods and characterization instruments,but there are shortcomings such as complex testing procedures,high cost,insufficient evaluation system,and lack of basic and theoretical mechanics research and quantitative and intelligent characterization system.As a major country in textile manufacturing and textile trade,the development of our country’s textile industry is in an important period of strategic opportunities.It is necessary to ensure the quality of textiles to occupy international competitive advantages.The in-depth integration of information intelligence technology and the textile field is conducive to promoting the efficient development of the textile industry.Therefore,the study of fabric handle has practical value and scientific significance.Based on the existing research foundation,this topic has developed a Quick-Intelligent Handle Evaluation System（QIHES）with original property rights around the characterization of the fabric handle.The measuring mechanism is inspired by the gesture of gripping the fabric by five fingers,and the latest sensor technology and microcomputer control technology to manufacture hardware and software modules,thus realizing various system features such as structure integration,operation automation,comprehensive functions and display visualization of QIHES.Also,based on the principle of single-test,multi-stage and multi-index output,automatic integrated testing of thickness,compression,bending,friction and stretching by QIHES is achieved.On the basis of this new handle characterization instrument,we have carried out in-depth research from many aspects:（1）according to the QIHES curve,stage analysis of QIHES is proposed,single test process can be divided into four characteristic test stages:compression,bending,friction and stretching,and can be extracted the characteristic indexes from the curve of each stage as the property indexes of objective test.（2）in-depth analysis of fabric handle is conducted to clarify its content and internal laws,and specifically the total handle value（THV）can be divided into four primary handle characteristics（FPHC）,namely compression fullness handle（CFH）,bending stiffness handle（BSH）,friction roughness handle（FRH）,and stretching tightness handle（STH）,in addition,touch gestures for the THV and FPHC and subjective evaluation method have been designed and established.（3）through the comparative analysis between the objective testing and subjective evaluation,the influence mechanism of characteristic indexes on the corresponding handle attributes is clarified and the quantitative analysis between the indexes and grades of FPHC and THV is realized.（4）a mathematical-mechanical modeling method is proposed for fabric bending and stretching,and the mechanical model of non-contact and contact sections is established based on the segmented and separated analysis method,which is verified by actual testing results,in addition,the influence of friction coefficient,tensile modulus,bending rigidity and other mechanical factors also has been verified.（5）the finite element modeling method for fabric compression and friction has been proposed.Based on the actual feature structure of the instrument and actual yarn size,a multi-scale instrument-fabric finite element model was established to analyze the influence of fabric parameters on compression and friction properties,and the internal relationship between deformation characteristics and mechanical properties has been deeply clarified combined with the actual test.（6）the algorithm evaluation model of fabric handle is proposed,based on different algorithms such as multiple linear stepwise regression,multi-level fuzzy comprehensive evaluation（MFCE）,particle swarm optimization based K-means（PSO-K）,etc.,the evaluation models of FPHC and THC are established respectively,which solves the subjective and objective evaluation system,and the connection between each FPHC and THV,the influence of fabric performance in different directions on handle attributes,and the calculation and classification of THV based on objective indexes.The specific conclusions of this research are as follow:（1）Press roller,humanoid fingers plate and press plate of QIHES jointly construct the complex deformation of the fabric,which restores the action of human hand touching the fabric.The force-displacement curve can be directly displayed after the test and can be divided into compression,bending,friction and stretching stage according to the characteristics of the curve.The characteristic indexes of each stage are effectively extracted,including compression slope,compression work,bending slope,bending work,bending peak force,friction force,friction slope,stretching slope and stretching displacement.（2）The standardized subjective evaluation methods of FPHC and THV are verified by the Kendall concordance coefficient W and （?）~2test results（W are all greater than 0.87,and the statistic values of （?）~2 are all greater than 76.15）,which prove the consistency of the evaluators’subjective ratings and the effectiveness of subjective evaluation methods.The proportion of each fabric handle attributes of FPHC in the THV is determined based on the subjective rating results.Among them,the proportion of BSH is the highest,reaching 0.554,that is,the bending rigidity has the greatest impact on the fabric handle.（3）QIHES objective characteristic indexes of each stage can evaluate the handle difference of each handle attribute.The smaller the compression slope and the compression work,the smaller the compressible space of the fabric,the easier it is to obtain a higher subjective grade of compression fullness,that is,the easier it is to obtain thin and light handle.The higher the bending slope,bending work and peak force,the larger the force and energy consumption required for the bending deformation,indicating the fabric is more difficult to bend,that is,its bending stiffness is more rigid.The higher the friction force and slope,the rougher the fabric friction roughness handle.The smaller the stretching slope and the larger stretching displacement,which means the fabric can obtain greater extension under a smaller tensile load with better elasticity,thus the subjective grade of stretching tightness is higher.（4）Based on the structural characteristics of each stage of QIHES and the deformation characteristics of fabric,the bending and stretching mechanical models are constructed.The bending situation 1 model is the closest to the actual testing results considering the friction effect,and the maximum bending force increases with the increase of friction coefficient μ and bending rigidity B.The stretching model considering the bending rigidity,modified friction law（n=0.67）,Poisson effect,etc.can express the stretching properties and is closer to the testing results according to the mechanical analysis.The Poisson effect has the least impact on the tensile properties.With the increase of friction coefficient and tensile modulus,the modified friction law replaces the classic friction law（n=1）,and the thickness-radius ratio of the roller-fabric decreases,the stretching slope and work increase.（5）Based on the actual measurement conditions of compression and friction of QIHES,the fabric finite element models of compression and friction are constructed.The comparison between the simulation results and the actual testing results demonstrate the effectiveness of the finite element models of compression and friction.The simulation analysis of the complex deformation of fabric compression and friction has been realized,and the deformation features of the fabric in the compression and friction stages and the influence mechanism of the mechanical factors in each stage are clarified.According to the analysis of factors affecting compression mechanics,it is shown that compression characteristic indexes including compression slope and work increase with the increase of elastic modulus and friction coefficient,and compression slope decrease with the increase of yarn spacing and warp crimp height,indicating that fabrics with lower friction coefficient and elastic modulus,larger yarn spacing and smaller crimp height are easier to be compressed.According to the analysis of the influencing factors of friction mechanics,the friction force increases with the increase of friction coefficient and elastic modulus,and all the friction characteristic indexes decrease with the yarn spacing and warp crimp height increase.（6）The multiple linear stepwise regression evaluation model of FPHC and THV constructed based on the characteristic indexes has high consistency with the subjective evaluation results（the correlation coefficient r is greater than 0.9 and the goodness of fit R~2 is greater than 0.84）,and the fabric handle grade can be predicted directly through objective characteristic indexes.Through the establishment of MFCE,the effect of different directions（warp,weft,45°）on the compression,bending,friction and stretching properties of the fabric and the proportion of FPHC in THV are clarified.For compression and stretching,the properties in the warp direction have the greatest impact on the handle,while the properties in three directions have similar effects on it for bending and friction.In addition,the weights of CFH,BSH and FRH in THV reach 0.30,0.32 and 0.33respectively,and the minimum weight of STH is 0.05.The slope coefficient of the linear correlation function between the multiple linear stepwise regression model and the subjective rating of THV is only 0.590,while the slope coefficient of MFCE is 0.994.It shows that the MFCE can more accurately convert the objective characteristic indexes into the grades of THV compared with the multiple linear stepwise regression model.based on the self-adaptive PSO-K（SAPSO-K）,the average relative error between the clustering results and the subjective rating is 4.455.SAPSO-K has the smallest error value compared to the K-means and agglomerative hierarchical clustering,and has experienced fewer iterations to achieve the best fitness compared with PSO-K,indicating that SAPSO-K can efficiently and accurately classify THV of fabrics. |
PDF Full Text Request