Wrinkling and folding are crucial morphological and structural motifs in polymeric sheet materials. In this study, a simultaneous-mechanical test method was proposed to evaluate the wrinkling behaviour by simply constructing the folding deformations of fibrous sheet materials. The internal relationship between fabric folding and wrinkling was studied, and the similar power law relation of the wrinkling force and the number of folded layers between wrinkling and folding of fabrics was experimentally proved. This leads to a view of wrinkling from a hierarchical folding process, laying down the way to describe the disordered wrinkling by a facile folding test. The proposed test method and instrument can simulate the complex deformation and mechanical action during the wrinkling process by curve parameters extracted from the measured force-displacement curve. The correlation analysis between the curve parameters and wrinkling grades of subjective evaluation was conducted. Moreover, the prediction model of wrinkling grades was constructed and validated to give a direct overall evaluation of wrinkling grades for industrial application. The evaluation results of the prediction model based on the proposed mechanical test method showed good agreement with the traditional subjective evaluation results, which indicated that the designed method and instrument provided a feasible and effective measurement using a facile folding process for the surface wrinkling properties of fibrous sheet materials, enhancing our design and tuning capability for the morphology instability and wrinkling of fibrous sheet materials.
The use of green intelligent sensing systems which are based on triboelectric nanogenerators have sparked a surge of research in recent years. The development has made significant contributions to the field of promoting human health. However, the integration of an intelligent sensing system with multi-directional triboelectric nanogenerators (TENGs) remains challenges in the field of motion monitoring. To solve this research issue, this study designed a self-powered multifunctional fitness blanket (SF-MFB) which incorporates four TENGs, features multi-sensors and wireless motion monitoring capabilities. It presents a self-powered integrated sensing system which utilizes four TENG sensing units to monitor human motion. Each TENG sensing unit collects the mechanical energy generated during motion. The system is composed of SF-MFB, Bluetooth transmission terminal, and upper computer analysis terminal. Its main purpose is to wirelessly monitor and diagnose human sports skills and enables real-time human-computer interaction. The TENG integrated self-powered sensing system demonstrates practicality in sports skills monitoring, diagnosis, human-computer interaction and entertainment. This research introduces a novel approach for the application of TENG self-powered intelligent integrated sensing system in health promotion.
The main aim of this paper is to investigate the feasibility of using the Wool HandleMeter as an economical and effective method to predict the handle characteristics of wool-rich woven fabrics suitable for winter suiting. The correlation analysis and step-wise regression method were used to determine applicable curve parameters extracted from the Wool HandleMeter in order to explain the handle characteristics of the woven fabrics by a series of multiple regression models. Moreover, an independent set of woven samples was selected to validate the regression models on the basis of the Kawabata Evaluation System for Fabrics, subjective handle evaluation and the formability index FFAST. The results showed that the Wool HandleMeter together with the developed regression models is an excellent starting point for the simple evaluation of handle characteristics of wool-rich woven fabrics and can be the basis for further development of the Wool HandleMeter for woven fabrics.
As the Internet of Things becomes more and more mainstream, sensors are widely used in the field of motion monitoring. In this paper, we propose a lightweight and sensitive triboelectric nanogenerator (LS-TENG) consisting of transparent polytetrafluoroethylene (PTFE) and polyamide (PA) films as triboelectric layers, polydimethylsiloxane (PDMS) as support layer, and copper foil as electrode. LS-TENG can be attached to the joints of the human body, and the mechanical energy generated by human motion is converted into electric energy based on the triboelectric effect, thus realizing self-power supply. LS-TENG can monitor the angle changes in elbow and wrist joints when athletes pull the loop and actively generate the output voltage as a sensing signal, which is convenient for coaches to monitor the quality of athletes’ hitting in real time. In addition, LS-TENG can also be used as a power supply for other wireless electronic devices, which facilitates the construction and transmission of large motion data and opens up a new development direction for the field of motion monitoring.
Abstract Twisted yarn artificial muscles have attracted great interests for diverse applications, such as soft robotics, miniaturization controllers and smart textiles. A challenging issue in fabricating the twisted yarn artificial muscles is to retain the inserted twist. Different from the exiting strategies of forming double-helical structures or harnessing complex chemical technologies, we herein propose a simple combination of plasma and UV-light treatments to train natural wools into twist-stable single-helical yarn artificial muscles without external torsional tethering, which realizes easy fabrication of twisted actuators, and achieves better moisture-actuating performance (nearly five times higher in maximum rotation) compared to equivalent double-helical actuators. The stable morphology of woolen yarn muscles affected by the opening and closing of disulfide bonds is explained from microstructure characterization and theoretical analysis. The charming properties of single-helical yarn muscles will provide new inspiration for the development of fiber-based actuators in industrial routines, which is expected to promote the practical application of yarn muscles in smart textiles and wider fields.
Abstract Background It is now well understood that, as an uncomfortable sensation evoked by special fabric, prickle derives from the mechanical stimulation of protruding hairiness from fabric surface against the human skin, in which some nociceptors are easy to be triggered by stiff fiber ends. However, up to now, the neural mechanism of the brain for perceiving fabric‐evoked prickle is still unclear. Materials and Methods In this work, A type of single‐fiber stimulus made from nylon filament was used to repetitively prick the skin of volar forearm at a specific frequency, and the technology of functional magnetic resonance imaging (fMRI) was adopted to detect the brain response synchronously. Results The results show that repetitive prickling stimulation from the single fiber applied to the volar forearm aroused distributed activation in several brain regions, such as primary somatosensory cortex, secondary somatosensory cortex, motor cortex, bilateral occipital lobe, insular cortex, and ipsilateral limbic lobe. Although the brain activation distribution is similar to pain, the single fiber–evoked prickle sensation possesses unique activation characteristics in several brain regions. Conclusion It is suggested that the sensation evoked by cutaneous prickling stimulation from single fiber belongs to a kind of multidimensional experience involving somatosensory, motor, emotional, cognitive, etc Our study constitutes an important step toward identifying the brain mechanism of fabric‐evoked prickle.
A self-powered triboelectric nanogenerator (SPTENG) based on triboelectric effect and an intelligent interactive system are fabricated for monitoring shooting training and virtual training. The SPTENG is composed of latex and PTFE and an intelligent system. Based on triboelectric effect, the SPTENG can be used to monitor the progress of trigger pressing without a power supply (this is supplied by trigger movements). Because of the flexible properties, it can be attached to a trigger conveniently to monitor the progress of trigger pressing, such as trigger time, trigger stability, etc. Meanwhile, as part of an intelligent shooting system, police can formulate a standard scheme according to signals to improve their skills. Furthermore, they can use it to train between reality and virtuality. Therefore, it has a wide development space in human-computer interaction and real-time information processing.
It is still a challenging task to objectively evaluate the fabric smoothness appearance due to the complexity and variety of fabrics. Innovative methods that can accurately quantify the surface smoothness in a practical and repeatable way are desideratum. To address this challenge, we put forward a new mechanical testing method, that is, mechanical test system for fabric shape retention (MTS-FSR). The design details and testing principle of the MTS-FSR were presented. The measured force-displacement curves were fitted and eight characteristic indices related to fabric wrinkling were determined and interpreted by their physical meanings. The repeatability and accuracy of the system were studied to verify the reliability of the method. Moreover, a prediction model for fabric smoothness appearance was established based on decision tree algorithm that was proved superior to other common used learning algorithms (e.g. support vector machine (SVM), random forest (RF) and Back-Propagation neural network (BPNN)) based on comparison analysis. The experimental results show that the designed instrument provides a feasible and effective measurement method for the objective evaluation of fabric smoothness appearance with good accuracy and resolution.
The main content dealt with in this paper was to make a theoretical analysis of the vibration transmission property of spacer fabric as cushion materials. A forced vibration test with sinusoidal excitation was conducted, and the corresponding model of the vibration transmission coefficient was established based on a single-degree-of-freedom system. Experimental and theoretical vibration indexes, including natural frequency and the vibration transmission coefficient, were obtained from experimental and theoretical vibration transmission coefficient–frequency curves, respectively. After comparing theoretical parameters with experimental parameters, we were pleased to find out that their maximum vibration transmission coefficient and natural frequency showed good accordance with each other. Moreover, the effect of different parameters of spacer fabric on vibration transmission properties, including thickness, filament diameter, area density and inclination angle and arrangement of spacer filaments, were investigated, which is helpful to better design spacer fabrics with good vibration transmission.
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