Helder Carvalho

The industrial manufacturing of sewn products has always been one of the critical processes of the textile chain concerning quality assurance. Assuring the appropriate set-up and operation of all the machines, and thus the final seam quality, is a very complex task. Traditionally, this task is accomplished by empirical methods, with machine setting and quality control relying on the skills of operators and technicians. In this work, an approach to a more knowledge-based and integrated process planning and control is presented. A system was developed to measure and analyze the most important mechanical effects occurring during high-speed sewing. A general overview over this development is given in this paper.

This work describes the development and test of a wireless sensor network used by a biomedical signal monitoring system. Data communication is based on a body area network (BAN) materialized as a wireless network in two versions, one based on the 802.15.4 specification and another on a higher-level Zigbee protocol. The system was developed using the Jennic JN5148 microcontroller, Jennics ZBPro stack and the JenOs RT kernell.

This paper presents the development of a moisture sensor matrix based on textile materials provided with conductive yarns. The measurement principle is based on the measurement of electrical resistance of the textile. The main purpose of this work is to support research on the prevention of pressure ulcers in people committed to bed rest or using wheelchairs. In the first stage of development, the project is studying the relation between physical parameters, exposure time and the levels of discomfort and pain experienced by the patients. In a later stage, the underlying measurement and evaluation principles will be used to develop single sensors or sensor matrixes to be connected to active patient monitoring systems able to warn in situations of excess of moisture and/or pressure (produced by sweat, open wounds, incontinence, etc.).

This paper presents the development of signal acquisition and analysis equipment for the measurement of sewing parameters on a high-speed overlock sewing machine. The objective of the work was to provide investigators of the textile area with hardware and software to ease the investigation on the dynamical behaviour of the following sewing parameters: force on needle bar; and presser-foot and thread tensions. It should also have enough flexibility to incorporate further signal entries, and provide the user with tools to ease the gathering and analysis of tests on different materials, sewing speeds and machine configurations and settings. Outputs for actuators to implement closed-loop control strategies are also available. The paper presents an overview of the system, which is a development of earlier hardware and software and focuses on the results concerning the measurement of the force on the needle-bar; this parameter is important to investigate needle penetration force in fabrics during sewing. Several signal-processing algorithms, that aim to automate the detection of some characteristics, are described. The purpose of this system, that implements some novel strategies, is to develop an add-on kit to apply to different sewing machines, but presently it has been implemented on a PC as a quality assessment system which will be used by textile technicians to build a quality database

This study describes some possibilities of setting up an adaptive control method for an electromagnetically actuated presser-foot in an industrial high-speed sewing machine. The control of fabrics feeding in sewing machines is difficult not only because of the complexity of relations between the intervening variables (material properties, sewing speed), but also because in many operations a varying number of material plies are crossed. This implies that the reference for the controller has to be adapted dynamically. Several methods, using PID and/or fuzzy logic control, have been tried and are described in this paper. A preliminary sewing test is able to provide data to tune the controller variables. With these adaptation techniques, the machine would be able to automatically adapt its feeding system according to the material being sewn.

This work reports a electrocardiograph and skin conductivity hardware architecture, based on E-textile electrodes, attached to a wheelchair for affective and physiological computing. Appropriate conditioning circuits and a microcontroller platform that performs acquisition, primary processing, and communication using Bluetooth were designed and implemented. To increase the accuracy and repeatability of the skin conductivity measuring channel, force measurement sensors were attached to the system certifying measuring contact force on the electrode level. Advanced processing including R-wave peak detector, adaptive filtering and autonomic nervous system analysis based on wavelets transform was designed and implemented on a server. A central design of affective recognition and biofeedback system is described.

Garment construction is a complex process due to the properties of the textile materials. Furthermore it still relies on human operators in most of the material handling and process monitoring. On the other hand, the set-up of the machines is still based on trial-and-error and empirical knowledge. Current market trends with higher demand on quality, shorter production runs and increasing variety of materials boost the economical significance of machine set-up and better process planning, monitoring and control. This paper presents the development of monitoring and control techniques aiming at the introduction of new tools to accomplish this. A sensor-based data acquisition and analysis system has been developed that enables a quick offline evaluation of the performance of the machine in several of its subsystems. Knowledge that has been gained from these measurements is the basis to develop CAE/CAM tools and real-time control devices.