This paper presents a novel application of neural network modeling in the optimization of sensor locations for the measurement of flue gas flow in industrial ducts and stacks. The proposed neural network model has been validated with an experiment based upon a case-study power plant. The results have shown that the optimized sensor location can be easily determined with this model. The industry can directly benefit from the improvement of measurement accuracy of the flue gas flow in the optimized sensor location and the reduction of manual measurement operation with Pitot tube
Stylus profilometry has been used for many years to measure surface finish. A stylus is drawn across a surface creating an x
-y
data set. A range of 2D surface parameters can be calculated. Measurements are now possible using 3D technology by raster scanning a stylus across a surface. This creates an x
-y
-z
data set. Although various 3D parameters can be calculated, there is currently no 3D standard for parameters whereas there are 2D standards. Many studies of 2D parameters, their usefulness and reliability have been published but as yet there has been little work done on 3D parameters. This project seeks to redress the balance by presenting the results of a study into 3D parameters and their reliability. Raster-scan measurements have been made on a variety of different surfaces and at a variety of points within the surfaces. The paper reports on the stability and variability of the measurements.
A new measure for survivability of military communication networks based upon topological structures is presented. The proposed measure can be used to evaluate and enhance the survivability of military communication networks, which is illustrated through case studies. The computer simulation results have shown that the new measure can well reflect the survivability of networks. It can be used as a reliable criterion for estimating the survivability of networks and designing networks with high survivability
Burrs' presence in autobody panels is perceived as highly damaging since they aflectpnal quality especially in terms of corrosion resistance and assembly pegormances. Burr formation can be controlled during the trimming [2] therefore a hand held device that measure such a phenomenon is required by the automotive industry. Several sensing techniques were explored [3J choosing, for this application, a cantilever probe Jitted with strain gauges. The signal was amplified acquired and displayed employing an 8-bit microcontroller. The developed device shows high repeatability and it will be applied to set up an X-R Statistical Process Control Chart within an automotive manufacturer.
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