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In this work the possibility to characterize mechanical components combining thermoelastic measurement technique (TSA) and digital image correlation (DIC) is studied. The combination of these two different methodologies allows to analyze thermo-mechanical characteristics of materials such as plastic and rubber, which are difficult to study with the only thermoelastic methodology. The digital image correlation allows to determinate the first invariant of deformation ε1, using a differential thermocamera. Lack of adiabatic conditions, essential for methodology use, makes analysis not simple. Digital image correlation allows to obtain the same information by correlating digital images acquired during static or dynamic deformationof an object, but with limitations linked to acquisition system. An accurate analysis is dedicated to the study of first invariant of deformation related to Young’s module variation, performed by load cycles with variable amplitude and displacement. Comparative analysis between the two measurement methodologies has been performed on rubber samples loaded by dynamic compression.
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The development of a diagnostic system is a complex engineering problem aimed at preventing damage caused by deteriorating properties of the materials and structures. This article presents the method of nondestructive testing of change control of concrete structures. The analysis of literature data shows that the overwhelming majority of studies are devoted to the change in electrical resistance of concrete in the collection of its strength, and practically no analogous studies regarding its aging are presented. Theoretical substantiation of the change in electrical concrete characteristics (conductivity, resistance) is given with a change in its strength. A work over-bridge in operation more than 30 years has been surveyed. The experimental part consisted in measuring the electrical potentials on the bridge structures, as well as in determining the strength of the material at the same points. Correlation dependence between the measured electric potential value and the strength of the samples taken from the bridge structures were obtained.
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Evaluation of the measured data, which are obtained from testing of the HCCI engine prototype, is a complex process taking into consideration questions of the vibration diagnostics. The complexity of this procedure is caused due to a necessity to evaluate a large amount of the various data. One of the solution possibilities is application of a multidimensional statistical model within the evaluation process in order to obtain more accurate information about the actual operational condition concerning the analysed engine.
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The method for the fault diagnosing of the air intake system of a gasoline engine, not detected by the on-board diagnostics system in a car, is described in this article. The aim is to detect and identify such faults like changes in sensor characteristic, faults of mass airflow measurement in the intake manifold or manifold leakages. These faults directly affect the air intake system performance that results in engine roughness and a power decrease. The method is based on the generation of residuals on the grounds of differences in indications of the manifold absolute pressure (MAP) and mass air flow (MAF) sensors installed in the car and the virtual, model-based sensors. The empirical model for the fault-free state was constructed at stationary operations of the engine. The residuals were then evaluated to classify the system health. Investigations were conducted for a conventional gasoline engine with port-fuel injection (PFI) and for a gasoline direct injection engine (GDI).
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Clutch-Brake system is one of the most important element of mechanical press line. The main purpose of it is to transmit the torque from the electric motor and flywheel to gear and main shaft. It ensures slide motion, but also press safety. One of the parameter that needs to be measured periodically is overrun. This value directly shows what is the condition of clutch-brake unit. The longer overrun, the worse brake operation. Unfortunately this one does not show what is the root cause of that situation. From that reason it is necessary to perform deeper diagnosis of complete system. One may find out from this article how to check clutch-brake unit in details- how to correlate slide position and slide speed with hydraulic pressure and position of safety valve (PSV).
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In this paper, authors described methods of material granularity evaluation and a novel method for grain size determination with inline electromagnetic mill device diagnostics. The milling process quality evaluation can be carried out with vibration measurements, analysis of the milling material images or well-known screening machines. The method proposed in this paper is developed to the online examination of the milled product during the milling process using real-time digital images. In this paper, authors concentrated their work on copper ore milling process. Determination of the total number of the grain, the size of each grain, also the classification of the grains are the main goal of the developed method. In the proposed method the vision camera with lightning mounted at two assumed angles has been used. The detection of the grains has been based on an adaptive segmentation algorithm, improved with distance transform to enhance grains detection. The information about particles shape and context is used to optimize the grain classification process in the next step. The final classification is based on the rule-based method with defined particle shape and size parameters.
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Modern systems and methods of Structural Health Monitoring (SHM) and Non Destructive Testing (NDT) require new types of transducers. In this paper, a new type of Lamb Wave transducer, the Tunable Interdigital Transducer (T-IDT), developed at AGH University of Science and Technology, is presented and its sensing capabilities are discussed based on experimental tests. The properties of the proposed transducer are similar to those of a traditional Interdigital Transducer (IDT), except for its ability to change the wavelength to which the transducer is tuned without introducing any physical changes in the electrode layout. In the paper, three sets of experiments are presented. The first two determine the ability of the transducer to measure the distance of damage from the transducer. The last set of experiments investigates the angular sensitivity of the proposed transducer for modelled damage. The presented results are compared to ones obtained with a traditional IDT.
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The objective of the present work is to develop analytical modelling of an unsteady fluid flow through an elastic tube. The fluid is considered to be Newtonian and incompressible. The cylindrical tube wall boundaries are isotropic. The study provides a review of recent modelling aimed at understanding the effects of fluid parameters over the elastic tube wall behaviour. First of all, the fluid flow is analysed following an asymptotic approach according to a large Reynolds number and a small aspect radio. Second of all, the wall has been assumed to be a thin shell, which generates a small axisymmetric vibration. The mathematical model is developed according the thin shell theory. The dynamic behaviour of the tube wall is represented and discussed.
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This paper presents a cointegration-based method for condition monitoring of wind turbines. Analysis of cointegration residuals – obtained from cointegration process of wind turbine data – is used for operational condition monitoring and fault detection. The method has been employed for on-line condition monitoring of a wind turbine drivetrain with a nominal power of 2 MW under varying environmental and operational conditions using only the temperature data of gearbox bearing and generator winding, which were collected by the Supervisory Control And Data Acquisition (SCADA) system. The results show that the proposed method can effectively monitor the wind turbine and reliably detect the gearbox fault.
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Most cold rolling mills are prone to chatter problem. Chatter marks are often observed on the strip surface in cold rolling mill leading to downgrade and rejection of rolled material. Chatter impact product quality as well as productivity of mill. In absence of online chatter detection no corrective action can be taken immediately and whole campaign gets affected. Most conventional approach for online chatter detection is by using vibration measurement of mill stands in time & frequency domain. Present work proposes two approaches to detect chatter in cold rolling mill using a statistical technique called Principal Component Analysis (PCA). In this paper two methods are used for chatter detection. First method applies PCA on Fast Fourier Transform (FFT) to differentiate between chatter and non-chatter condition. Second method applies PCA on statistical parameters calculated from raw vibration data to detect chatter.