Real-time Measurement of Surface Deformation of Rotating Blades

This paper presents the results for the real-time measurement of surface deformation of rotating elements. A digital image correlation technique is used to estimate the surface displacements and strains. Speckle patterns are spray painted on the surface of interest and digital images taken before and during deformation caused by rotary motion. The digital image of the deformed blade is taken by freezing the speckled pattern with the help of a stroboscope. The technique provides several advantages over traditional methods in terms of obtaining whole-field deformation profiles, a non-invasive measurement scheme, and a simple and economical set-up. Results are presented for 1D uniform strain as well as 2D strain in a region next to a hole in a rubber specimen that is rotated at different speeds. The scheme presented in this paper can also be extended to measuring out-of-plane deformation by the use of an additional camera. The proposed technique can be used for measuring deformations in turbine blades, helicopter blades, or any other rotating elements

Genetic algorithm for design of reflective filters: Application to AlxGa1-xN based Bragg reflectors

A genetic algorithm (GA) with adaptive mutations has been employed for the design of Bragg reflectors. The algorithm enables three different design types a) composition and thickness of two layers are chosen and the pair is repeated b) two compositions are chosen for the two alternating materials, and thickness of each layer is optimized c) composition and thickness of each layer are optimized. In all cases, the wavelength and composition dependence of the index of refraction is taken into account. Also, it is possible to impose constraints on the composition difference of the neighbouring layers, either with a penalty function or with narrowing the boundaries for possible compositions. This feature is important because the large lattice mismatch between GaN and AlN can cause poor surface morphology, so measured reflectivity would be lower than the calculated one due to the surface roughness. The algorithm enables finding the optimal design for two chosen incident and final media, and it is capable of taking into account the existence of a finite, optically thick substrate. We have investigated two systems: air/sapphire/AlxGa1-xN reflector/GaN and GaN/AlxGa1-xN/air.published_or_final_versio

Improved usability of the minimal model of insulin sensitivity based on an automated approach and genetic algorithms for parameter estimation. Clin Sci (Lond

A B S T R A C T Minimal model analysis of glucose and insulin data from an IVGTT (intravenous glucose tolerance test) is widely used to estimate insulin sensitivity; however, the use of the model often requires intervention by a trained operator and some problems can occur in the estimation of model parameters. In the present study, a new method for minimal model analysis, termed GAMMOD, was developed based on genetic algorithms for the estimation of model parameters. Such an algorithm does not require the fixing of initial values for the parameters (that may lead to unreliable estimates). Our method also implements an automated weighting scheme not requiring manual intervention of the operator, thus improving the usability of the model. We studied a group of 170 women with a history of previous gestational diabetes. Results obtained by GAMMOD were compared with those obtained by MINMOD (a traditional gradient-based algorithm for minimal model analysis). Insulin sensitivity by GAMMOD was (3.86 + − 0.19) compared with (4.33 + − 0.20) × 10 −4 µ-units · ml −1 · min −1 by MINMOD; glucose effectiveness was 0.0236 + − 0.0005 compared with 0.0229 + − 0.0005 min −1 respectively. The difference in the estimation by the two methods was within the precision expected for such metabolic parameters and is probably of no clinical relevance. Moreover, both the coefficient of variation of the estimated parameters and the error of fit were generally lower in GAMMOD, despite the fact that it does not require manual intervention. In conclusion, the GAMMOD approach for parameter estimation in the minimal model provides a reliable estimation of the model parameters and improves the usability of the model, thus facilitating its further use and application in a clinical context

Automatic correlation and calibration of noisy sensor readings using elite genetic algorithms

AbstractThis paper explores an image processing application of optimization techniques which entails interpreting noisy sensor data. The application is a generalization of image correlation; we attempt to find the optimal gruence which matches two overlapping gray scale images corrupted with noise. Both tabu search and genetic algorithms are used to find the parameters which match the two images. A genetic algorithm approach using an elitist reproduction scheme is found to provide significantly superior results

Robust Sensor Fusion Algorithms: Calibration and Cost Minimization.

A system reacting to its environment requires sensor input to model the environment. Unfortunately, sensors are electromechanical devices subject to physical limitations. It is challenging for a system to robustly evaluate sensor data which is of questionable accuracy and dependability. Sensor fusion addresses this problem by taking inputs from several sensors and merging the individual sensor readings into a single logical reading. The use of heterogeneous physical sensors allows a logical sensor to be less sensitive to the limitations of any single sensor technology, and the use of multiple identical sensors allows the system to tolerate failures of some of its component physical sensors. These are examples of fault masking, or N-modular redundancy. This research resolves two problems of fault masking systems: the automatic calibration of systems which return partially redundant image data is problematic, and the cost incurred by installing redundant system components can be prohibitive. Both are presented in mathematical terms as optimization problems. To combine inputs from multiple independent sensors, readings must be registered to a common coordinate system. This problem is complex when functions equating the readings are not known a priori. It is even more difficult in the case of sensor readings, where data contains noise and may have a sizable periodic component. A practical method must find a near optimal answer in the presence of large amounts of noise. The first part of this research derives a computational scheme capable of registering partially overlapping noisy sensor readings. Another problem with redundant systems is the cost incurred by redundancy. The trade-off between reliability and system cost is most evident in fault-tolerant systems. Given several component types with known dependability statistics, it is possible to determine the combinations of components which fulfill dependability constraints by modeling the system using Markov chains. When unit costs are known, it is desirable to use low cost combinations of components to fulfill the reliability constraints. The second part of this dissertation develops a methodology for designing sensor systems, with redundant components, which satisfy dependability constraints at near minimal cost. Open problems are also listed