International Journal of Sensors Wireless Communications and Control - Volume 2, Issue 3, 2012

This paper describes a custom developed yarn parameterization system to characterize yarn diameter, mass and hairiness. The system has been named YSQ (Yarn System Quality) and is based on capacitive and optical sensors generally used to infer information about yarn quality. The designed sensor system is fully described. All data acquisition and processing is performed using a DAQ board from National Instruments (USB-6251) and custom software developed in LabVIEW®. Moreover it presents a solution based on image processing techniques to determine yarn mass parameters as well as yarn production characteristics. A low cost solution based on a web-pc camera plus the optics of a low cost analog microscope and a software tool based on IMAQ Vision from LabVIEW® were employed. Several tests were performed and compared to other methodologies of yarn parameterization validating the proposed solution. The results support the claim that this system can be an alternative solution to the traditional yarn testers, with several advantages (including: low cost, low weight, low volume, easy maintenance and reduced hardware).

In this paper, the inexpensive optical sensor of a common computer mouse is proposed as a tool to measure the yarn diameter. In the textile industry this measurement tool has many applications in quality control and assurance. This optical sensor operates in combination with a plastic lens and an external LED to complete an inexpensive and compact vision system. The optical sensor includes a fast optical monochrome imaging device of 30x30 pixels and an internal processing unit originally programmed to measure displacement in the images acquired. The imaging device can operate at very high frame rates and the image acquired can be accessed externally to develop new low-cost and real-time monitoring applications such as the measurement of yarn diameters.

Machine vision based systems are increasingly being used in textile quality characterization due to their ability to provide valuable information. The purpose of this study is to review some methodologies of evaluating fiber and yarn using optical devices. Optical and electron microscopes, along with image processing techniques were used to investigate the morphology and cross-sectional shape of electrospun nanofibers. Fibrous web inspection for neps and trash was considered by means of an optical device as well. The use of a CCD camera and image analysis in evaluating yarn quality and characterizing the wicking and wetting behaviors of yarns suggests that the future of the yarn sensors will be in the field of the optical systems. Optical systems provide all information that the conventional systems can give, but they can also provide extra dimensional and geometrical information. In comparison to most other methods, optical methods are quick, inexpensive and precise.

Fabric surface appearance is one of the most important visible properties of fabrics determining their price and consumer satisfaction. This characteristic is routinely evaluated with reference to a set of visual standards in the textile industry. The visual evaluation is unreliable, time-consuming, inefficient, and, depends on many human factors. Machine vision techniques can overcome these difficulties and evaluate the fabric surface with high precision and high speed. Application of machine vision to evaluate woven fabric appearance such as seersucker effect, repetition, uniformity, disorder, wrinkling, and quality of printed patterns needs a lighting system, an image capturing device, a computer, and appropriate software for data processing. This paper introduces some new quantitative analysis methods for fabric appearance inspection and addresses the development of optical devices in evaluating textural features. The gray-level co-occurrence matrix, spectral density function, angular power spectrum function, distance matching function, and, normalized cross-correlation are the most important algorithms used in this new method. The method developed in this work makes the rapid and exact inspection of fabric surface possible. Objective results from these new methods were compared with subjective ones from human experts. The correlation between texture analysis and subjective evaluation was acceptable at 95% confidence interval for all cases.

Horizontal movement in flocking is a common phenomenon in nature. In this paper, a quantitative model was developed to describe the collective horizontal flight of bird flocking. A decentralized feedback control strategy for a group of multi-agents has been proposed. With this control strategy or control law, all multi-agents can move within a certain height range, ensuring that freedom from collisions between neighboring agents should not occur. The control strategy is expected to be used in civilian aircraft modeling and control of intelligent service system.

This paper presents a survey on the current state-of-art in various Reprogramming Architectures for Wireless Sensor Network (WSN). Recent research in wireless sensor network has highlighted the importance of supporting the capability for remote reprogramming of sensor nodes via wireless network. Wireless sensor networks are expected to be deployed for long periods of time, and the nodes are likely to need software update during their lifetime, both for bug fixes and in order to support new requirements. Network reprogramming allows for over-the-air software updates in sensor networks. Dynamic reprogramming of sensor applications and sensor operating systems are emerging as a critical function required in wireless sensor networks. This ability to remotely patch or upgrade software in deployed sensor nodes via the wireless network is complicated by the increasing trend towards heterogeneity in WSN hardware platforms, sensor operating systems and role-based differentiation, e.g. between aggregators and leaf sensor nodes. Most of the current network reprogramming protocols focus on propagating the same code image to a network of homogeneous sensor nodes. Naive approaches to adapt such protocols for heterogeneity are largely inefficient. Ease of programming has long been recognized as a major hurdle to the adoption of WSN technology. In response to this need, several platform dependent programming solutions have been hitherto developed. A well-established characterization of the available approaches is, however, largely missing. As a result, researchers are unable to orient themselves in this diverse field, and developers struggle in identifying the solutions most appropriate to their application requirements. The purpose of this survey is to describe features of different reprogramming architectures in wireless sensor networks & highlight major concerns pertaining to investigation of efficiency and performance of these architectures for Wireless Sensor Network. The modern techniques in various reprogramming architectures for WSNs have been examined in terms of Reprogramming Architecture, Code dissemination/Code acquisition, Encoding /Decoding, Single-hop/Multihop reprogramming, MAC protocol, Hierarchy, Pipelining, Scope Selection Support and Idle listening to adaptive sleeping etc. These features are surveyed for various Code dissemination protocols both Entire Program Image based & Difference-based Methods for reprogramming WSN.

This paper starts with the introduction of the architecture model of the data acquisition system, In this module, a number of factors are involved in influencing the data acquisition system. The theoretical analysis and deduction result of the various confounding factors, such as the additive noise n0 (t) of signal source, the ripple noise of supply power and the jitter of clock, etc have later been described in this paper. The above three factors influence the signal-to-noise ratio (SNR) formula of data acquisition system, which has been derived from the above analysis, and then it gets a constraint condition for the optimize design. At last, it introduces a multiple parameters simulation module that is established in the software ADS2008, and with the help of this simulation module tries to get the simulation results to verify the correctness of the above theoretical deduction. So the technical problem of optimizing design for data acquisition systems under the influence of multiple factors has been solved in the paper, showing its great significance in the real applications.