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Emanuele Zappa, Rui Liu
Fourier-based image shift for periodic effect compensation in displacement monitoring using vision systems

In a wide range of monitoring applications, vision systems are nowadays applied. The main advantages of vision-based monitoring include the possibility to: i) measure a wide region of the target, obtaining a dense measurement, ii) obtain a 3D estimation of shape, displacements and strain field, iii) measure with a completely contactless technique, therefore avoiding loading effect and wear of measuring components and target. Digital Image Correlation (DIC) is an image processing technique that allows measuring the displacement and strain fields of target, as well as the 3D shape of the measurand in the case of stereo DIC. Displacement measurement obtained by DIC are affected by a systematic effect in displacement data. In this paper, we propose and qualify an image pre-processing technique, to be applied to the images before running the DIC analysis, capable to strongly reduce the systematic effect affecting the displacement results.

Liangliang Cheng, Giorgio Busca, Alfredo Cigada
Experimental strain modal analysis for beam-like structure by using distributed fiber optics

Modal analysis is commonly considered as an effective tool to obtain the inherent characteristics of structures including natural frequency, modal damping and mode shapes, which are significant indicators for monitoring the health status of engineering structures. In this paper, distributed fiber optics, as dense measurement transducer has been applied into acquiring huge amount of strain data along the beam surface. Thanks to the dense spatial resolution, CMIF (Complex Mode Indicator Function) is used to identify strain modal parameters like natural frequency and modal damping. Strain mode shapes can be obtained by using SVD technique.

Vladimir Chmelko, Martin Garan
Long-term monitoring of strains in a real operation of structures

In most of cases the structural condition monitoring allows to receive significant states or values in a real operation of that structure, such as:
- change in value of safety coefficient by reason of arising overload or non-standard operation mode during service
- vibrations increasing by reason of change in toughness of the structure
- increasing of fatigue damage accumulation in a critical point or section by reason of change in variable stress amplitudes
In this paper, there is presented the extended concept of compensation for elimination of unwanted offset change that can appear during long-term monitoring of the strain signal. The method of this compensation is shown and realized for performing the monitoring process on a real structure of pipeline system where as sensors were used the strain gauges.

Alberto Lavatelli, Emanuele Zappa
On the effects of motion blur in vision based 3D vibration monitoring

This paper addresses the problem of motion blur when 3D vibration monitoring is performed by means of vision based measurement methods. Starting from an original analytic model developed previously by the authors, the paper discusses the effects of acquisition parameters on the final measurement accuracy. Consequently the paper proposes an experimental method in order to asses the presented theoretical framework as well as the accuracy of a generic vision based vibration monitoring system.

Marc Seimert, Clemens Guehmann
Vibration based diagnostic of cracks in hybrid ball bearings

The paper presents a vibration based diagnostic system to detect cracks in balls of hybrid ball bearings. The diagnostic system based on a Bayesian Classifier. It is shown that it is able to separate healthy bearings from damaged balls and races. The system is tested with measurement data from a bearing test bench in different operating points of the bearing.

Dorel Aiordachioaie, Theodor D. Popescu
VIBROMOD - An experimental model for Change Detection and Diagnosis Problems

The objective of the paper is to introduce an experimental model (VIBROMOD) designed for solving change detection and diagnosis problems in various fields of applications, mainly vibration engineering. The hardware structure contains two basic levels: one for fast computations and alarms, which processes data in a matter of hours, and, an upper level, for large-scale monitoring and statistical computation of moments, over a time span of days and months. The algorithms running on VIBROMOD are coming from a specialized toolbox, which contains classical methods, based on statistical signal processing techniques, but also some advanced methods, based on time-frequency and information transforms. The monitored interaction between VIBROTOOL and VIBROMOD is the goal of a large project called VIBROCHANGE, and allows for rapid implementations, checking and testing of various algorithms and the development of benchmarks as well, for change detection and diagnosis problems.

Diego Scaccabarozzi, Bortolino Saggin, Luca Cornolti, Marco Tarabini, Hermes Giberti
Contactless measurement of PET bottles thickness

The tuning of Injection Stretch Blow Molding (ISBM) process for PET bottles is crucial to lower the production costs, reduce the environmental impact and assure a sufficient quality of the final product. Among the parameters defining PET bottles quality, the thickness is of primary importance for the appearance and mechanical resistance of the final product. Up to date, tuning of the process is demanded to the operator skills through a trial and error process, iterated until the wanted configuration is achieved. Moreover, the process is not controllable because the PET bottles characteristics are not currently measured. This work describes a method for PET bottles thickness measurement; the method could be implemented as part of an active control of the ISBM process. A noncontact method based on infrared transmittance measurement has been developed to evaluate the wall thickness of PET bottles. The method uncertainty is 6% when the nominal thickness ranges between 0.2 and 0.5 mm. A prototype of the measurement system has been developed and validated testing PET specimens with different geometry, pigmentation and composition.

Konstantin Trambitckii, Katharina Anding, Galina Polte, Daniel Garten, Victor Musalimov, Petr Kuritcyn
Metal surface quality assessment using 2D texture features

Quality assessment is an important step in production processes of metal parts. This step is required in order to check whether surface quality meets the requirements. Progress in the field of computing technologies and computer vision gives the possibility of surface quality assessment using industrial cameras and image processing methods. Authors of different papers proposed various texture feature algorithms which are suitable for different fields of images processing. In this research 27 texture features were calculated for surface images taken in the different lighting conditions. Correlation coefficients between these 2D texture features and 11 roughness 3D parameters were calculated. A strong correlation between 2D features and 3D parameters occurred for images captured under ring light conditions.

Zsolt János Viharos, Jenö Csanaki, János Nacsa, Márton Edelényi, Csaba Péntek, Krisztián Balázs Kis, Ádám Fodor, János Csempesz
Production trend identification and forecast for shop-floor business intelligence

The paper introduces a methodology to define production trend classes and also the results to serve with trend prognosis in a given manufacturing situation. The prognosis is valid for one, selected production measure (e.g. a quality dimension of one product, like diameters, angles, surface roughness, pressure, basis position, etc.) but the applied model takes into account the past values of many other, related production data collected typically on the shop-floor, too. Consequently, it is useful in batch or (customized) mass production environments. The proposed solution is applicable to realize production control inside the tolerance limits to proactively avoid the production process going outside from the given upper and lower tolerance limits.
The solution was developed and validated on real data collected on the shop-floor; the paper also summarizes the validated application results of the proposed methodology.

Piotr Bilski
Ambiguity groups detection in analog systems diagnostics using Self-Organizing Maps

The paper presents the application of Self- Organizing Maps (SOM) to the ambiguity groups detection in the analog system. This type of neural network is able to find dependencies in data, indicating groups of similar examples in the data set used for training the classifier or the regression machine. Various configurations of the network were implemented and compared. The ability to detect ambiguity groups was verified on the model of the induction machine. Results show the efficiency of the approach, able to identify examples difficult to distinguish by the fault detection and location scheme.

Page 328 of 977 Results 3271 - 3280 of 9762