Investigating the challenges of measuring combination mechanics in textile fabrics

Measurements of the mechanical behavior of fabrics started during the Zeppelin era in the 1900s, where tensile, shear and biaxial behavior of the airship’s envelope fabric were measured. More measurement methods were developed later when there was a need to measure fabric handle and behavior. Although measurements of tensile, shear, buckling and bending have been established and are being used, their combinations, which represent a more realistic approach, are still being developed. However, these multi-axial measurements pose challenges not only in apparatus design but also in determining the measurement parameters. Here these challenges are being put forward and further research requirements are identified and discussed. </jats:p

Investigating the Synthesis and Characterization of a Novel “Green” H₂O₂-Assisted, Water-Soluble Chitosan/Polyvinyl Alcohol Nanofiber for Environmental End Uses

The present work highlights the formation of a novel green nanofiber based on H2O2-assisted water-soluble chitosan/polyvinyl alcohol (WSCHT/PVA) by using water as an ecofriendly solvent and genipin used as a nontoxic cross-linker. The 20/80 blend ratio was found to have the most optimum uniform fiber morphology. WSCHT retained the same structure as WISCHT. The prepared nanofibers were characterized by Scanning electron microscopy (SEM), Fourier transform spectroscopy (FTIR), Thermo gravimetric analysis (TGA), Differential scanning calorimeter (DSC), X-ray diffraction (XRD), Water Contact Angle (WCA) and Ultraviolet-visible spectroscopy (UV-vis). During electrospinning, the crystalline microstructure of the WSCHT/PVA underwent better solidification and after cross-linking there was an increase in the melting temperature of the fiber. Swelling ratio studies revealed noticeable increase in hydrophilicity with increase of WSCHT, which was further demonstrated by the decrease of contact angle from 64.74&deg; to 14.68&deg;. WSCHT/PVA nanofiber mats exhibit excellent UV blocking protection with less than 5% transmittance value and also showed improved in vitro drug release properties with stable release for longer duration (cross-linked fibers) and burst release for shorter duration (uncross linked) fibers. Finally our experimental data demonstrates excellent adsorption ability of Colour Index (C.I.) reactive black 5 (RB5) due to protonated amino groups

The use of a Multi-label Classification Framework for the Detection of Broken Bars and Mixed Eccentricity Faults based on the Start-up Transient

[EN] In this article a data driven approach for the classification of simultaneously occurring faults in an induction motor is presented. The problem is treated as a multi-label classification problem with each label corresponding to one specific fault. The faulty conditions examined, include the existence of a broken bar fault and the presence of mixed eccentricity with various degrees of static and dynamic eccentricity, while three "problem transformation" methods are tested and compared. For the feature extraction stage, the startup current is exploited using two well-known time-frequency (scale) transformations. This is the first time that a multi-label framework is used for the diagnosis of co-occurring fault conditions using information coming from the start-up current of induction motors. The efficiency of the proposed approach is validated using simulation data with promising results irrespective of the selected time-frequency transformation.This work was supported in part by the Spanish MINECO and FEDER program in the framework of the "Proyectos I + D del Subprograma de Generacion de Conocimiento, Programa Estatal de Fomento de la Investigacion Cientifica y Tecnica de Excelencia" under Grant DPI2014-52842-P and in part by the Horizon 2020 Framework program DISIRE under the Grant Agreement 636834.Georgoulas, G.; Climente Alarcón, V.; Antonino-Daviu, J.; Tsoumas, IP.; Stylios, CD.; Arkkio, A.; Nikolakopoulos, G. (2016). The use of a Multi-label Classification Framework for the Detection of Broken Bars and Mixed Eccentricity Faults based on the Start-up Transient. IEEE Transactions on Industrial Informatics. 13(2):625-634. https://doi.org/10.1109/TII.2016.2637169S62563413