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Carlos Hall Barbosa, Elisabeth Costa Monteiro, Flávia Pompéia
LOCALIZATION OF MAGNETIC FOREIGN BODIES IN HUMANS USING MAGNETIC FIELD SENSORS

A technique had been previously developed, based on magnetic field measurements using a SQUID sensor, to localise in three dimensions steel needles lost in the human body. In all six cases that were treated until now, the technique allowed easy surgical localisation of the needles with high accuracy, decreasing by a large factor the surgery time and also reducing the generally high odds of failure. The method is accurate, non-invasive and innocuous, with clear clinical importance. In this paper we present preliminary measurements performed with a fluxgate magnetometer instead of a SQUID.

F. Tatar, J.R. Mollinger, P. Turmezei, A. Bossche
CROSS-CORRELATION METHOD APPLIED TO AN ULTRASOUND SYSTEM FOR MEASURING POSITION AND ORIENTATION OF LAPAROSCOPIC SURGERY TOOLS

A new ultrasound wireless positioning system is developed that gives the surgeon the exact location and orientation of the instruments in the patient. The measuring system employ ultrasound markers placed on the instruments, outside of the human body. Knowing the dimensions of the usually rigid instruments it is possible to calculate their position and orientation inside the patient from the markers’ positions. Using the cross-correlation method we obtained a resolution of 0.7 mm in determining the marker positions.
To eliminate wiring to the tools a wireless radio wave (RF) system is used to trigger the ultrasound sensors.

Zdenek Malec, Petr Beneš
AN AUTOMATIC SYSTEM FOR MEASURING OF PROPERTIES OF PRECISION GEARBOXES

This paper deals in its first part especial requirements which must be fulfilled by gearboxes being used in applications demanding very high accuracy: uniformity of motion, exactly described hysteresis loop, limited vibrations and good efficiency. In the second part the basic conception of a realised experimental stand is described. The stand allows to perform all measurements, data acquisition and evaluation mentioned later. The control of all components of the measuring stand and the necessary data processing and final presentation of results is performed by a PC.

R Gozdur, M. Jerzy Korczynski
GLASS QUALITY TESTER

The techniques for digital image acquisition and digital image processing used to identify defects in transparent elements are described in the paper. The block diagram of the test set-up, algorithm of the software developed for identifying geometrical parameters of defects are presented here. The set-up, presented in the paper is proposed for glass quality production control at final and intermediate production line of double glassed windows. The other applications are foreseen. One of the very important feature is calibration of the image with the use of reference glasses, light correction and adjusting parameters of the set-up according to requirements. Calibration is achieved with the of use patterns prepared ahead of time and also with a use of the same set-up. Glass can be categorised depending on number of defects and percentage of defected area or can be disqualified at production line if any permanent defect is found in observed element.

Zbigniew Czaja, Romuald Zielonko
ON FAULT DIAGNOSIS OF ANALOGUE ELECTRONIC CIRCUITS WITH ACCESSIBILITY TO INTERNAL NODES BASED ON TRANSFORMATIONS IN MULTIDIMENSIONAL SPACES

In the paper new methods of fault localisation and identification in linear electronic circuits (two-port or multiport type) based on bilinear transformations in multidimensional spaces are presented. The novelty of these methods lies in transferring family of identification loci from a plane to multidimensional spaces. It implies greater distances between the loci and, in consequence, better fault resolution as well as robustness against non-faulty component tolerances and measurement errors. The methods can be used for diagnosis of electronic circuits in conventional testing systems and neural networks. They may be also useful in one or two-parameter identification measurements of other multi-parameter objects modelled by electrical circuits.

Leon Swedrowski
ROTOR DIAGNOSTICS OF INDUCTION MOTORS BY MEANS OF NEURAL NETWORKS

The investigation results presented in the paper are related to diagnostics of induction rotor’s cages. The virtual tool shown in the paper was created for investigations as an instrument to measure, to present and to register the stator’s current spectrum characteristics. The neuron classifier was constructed to create an instrument enabling to assign the induction motor under test to one of two groups – faultless or defective, and to prove the effectiveness of applying the neuron network in conjunction with the stator’s current spectrum analysis to find out damage in the rotor’s cage. Two options are described: Kohonen self-organizing feature maps and unidirectional multi-layer perceptrons (MLP). Both the networks have successfully solved the stator’s current spectra classification problem assigned to it, and also the technical diagnostics of the rotor’s cage condition.

Ludwik Spiralski, Lech Hasse, Krzysztof Rogala, Janusz Turczynski
PRODUCTION TESTING OF HIGH RELIABILITY INTERFERENCE SUPPRESSOR CAPACITORS

The system for production testing of high reliability interference suppressor capacitors have been presented. The noise level and non-linear distortions in capacitors can be established as a new criteria for reliability selection of interference suppressor capacitors. New tasks (measurement of third harmonic and noise) and their realization in the system have been proposed. It can improve the process of quality estimation of high reliability capacitors.

Jerzy Hoja, Grzegorz Lentka
NEW METHOD USING BILINEAR TRANSFORMATION FOR PARAMETER IDENTIFICATION OF ANTICORROSION COATINGS

The paper presents a new method of anticorrosion coatings diagnostics using bilinear transformation. It is possible to identify the parameters of the equivalent circuit of the coating on the basis of object impedance measurement at a few, optimally selected measurement frequencies. The rules of optimal frequency selection are given. The number of frequencies is equal to the number of the equivalent circuit components. The developed identification algorithm enables continuous monitoring of the coating performance. The main advantage of the method is a few (more than 10) times shorter identification process compared to traditional identification technique based on impedance spectroscopy followed by impedance spectrum fitting using computer programs (e.g. LEVM or EQUIVCRT), which are utilising complex non-linear least squares (CNLS) method.

Krzysztof J. Lewenstein, Krzysztof Urbaniak
COMPUTER ANALYSIS OF THE MAMMOGRAMS ORIENTED ON BREAST CANCER DETECTION

The aim of our study is to create a computer diagnostic system (CDS) for breast cancer (BC) recognizing.
As a software diagnostic tool we have used Fahlman’s cascade correlation neural network (FNN). The FNN was trained by the vector of features – parameters extracted from mammographic images of healthy tissue (H), tissue with benign (BT) and malignant tumour (M).
To prepare digital data for the NN new, original methods of transformation the mammograms were proposed: Algorithm of Summing up the Rows (ASR) operating on the binarized picture, and analysis of extracted features from Region Of Interest (ROI).
There were lots of parameters optimized in previous research; in this work we present discussion of the level of image binarization in ASR method, and discussion of shape, size and number of analyzed features in ROI method.
As the input data for neural network decision making system we have used six parameters calculated from a region of interest (ROI method), and four parameters calculated by the “summing up the rows algorithm” (ASR). We have used all mentioned parameters to create the best combination of features and find the best representative vector, and get the highest correctness of recognition.
The final diagnostic system could us obtain correctness of the mammogram interpretation about 92% for healthy tissue, 89% for benign and 91% for malignant tumors.

Pawel Lubkowski, Krzysztof Lewenstein, Krzysztof Urbaniak, Maciej Chojnacki
COMPUTER AIDED DIAGNOSTIC OF THE EYE BOTTOM IMAGES

In the paper we present results of our research concerning the fusion, digital conversion, and digital analysis of eye bottom images. We have started investigation about three years ago, and our goal is computer aided diagnosis of diabetes retinopathy. In diabetes retinopathy very important is analysis of the image of cardiovascular network of eye bottom. Many parameters of main vessels as diameters, positions, turns junctions and many others have changed in time. So in the first step of the research we decided to make a software tools for image analysis , useful for ophthalmologist for early detection of pathological changes.

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