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Yi Huang, Clemens Gühmann
Wireless Sensor Network for Temperature Estimations in an Asynchronous Machine Using a Kalman Filter

A 4th-order Kalman filter (KF) algorithm is implemented in a wireless sensor network (WSN) to estimate the temperatures of the stator windings, the rotor cage and the stator core of an asynchronous machine. The rotor speed, coolant air temperature, and the effective current and voltage are acquired by wireless transducer interface modules (WTIM) separately and are transmitted to a network capable application processor (NCAP) where the KF algorithm is implemented. The losses are calculated from the measurement and are processed together with the coolant air temperature by KF algorithm. As the resistance varies with the temperature, the rising resistance is compensated by the estimated stator windings temperature. Simulations and experiments were performed quite well on the test bench before the KF algorithm was implemented on a wireless sensor network. The real-time WSN temperature estimation system is independent from the control algorithm and can work under any load condition with very high accuracy.

Piotr Bilski
Unsupervised learning-based hierarchical diagnosis of analog circuits

The paper presents the automated diagnostic method of analog circuits combining supervised and unsupervised learning. The purpose of this sophisticated approach is to effectively distinguish easily identified states of the analyzed system from the more difficult ones. The latter are often related with existence of ambiguity groups, which create problems for the distinction of specific states. The proposed approach uses subsequently two algorithms. The first one extracts and learns to classify such “simple” training examples. The second one aims at the classification of more difficult ones. For both stages, Self-Organizing Maps and Random Forest were used, respectively. The scheme was tested on the model of the 3rd order Bessel highpass filter, confirming effectiveness of the approach.

Tommaso Addabbo, Ada Fort, Rossella Marino, Carlo Michelassi, Marco Mugnaini, Valerio Vignoli
Modelling of Non-Monotonic Hazard Function for the Early Production Life of Oil and Gas Plants

Common reliability models rely usually on simple assumptions as to manage constant failure rates especially when electronic components are treated in the reliability block diagram. Nevertheless, more realistic modeling imply to deal with Weibull based hazard functions or even with more complex models. For oil and gas plants, and repairable systems in general, actually, it may happen to deal with nonlinear behavior of the failure intensity function. Multiple slope changes may occur due to long observation time and to restoration activities affecting the overall system performance and failure rate shape over time. Commissioning phase is of particular interest for electro-mechanical complex systems because, depending on the plant extension and design, it can influence the hazard function shape and therefore its model. In this paper the authors will try to show how experimental failure rate information can be modeled by means of different hazard functions.

Giulio D’Emilia, David di Gasbarro, Antonella Gaspari, Emanuela Natale
About the role of uncertainty assessment in environmental testing

A short review is carried out about the uncertainty issues and requirements in environmental testing. Aspects concerning standards and operating procedures are considered and discussed, including considerations about test benches specifications and data analysis. Particular attention is paid on vibration tests and effects of different parameters. Some considerations are also presented considering the effect of data accuracy on reliability predictions.

Balázs Scherer
HIL test based non-intrusive diagnostics of cyber-physical systems

Cyber-physical systems have extensive contact with the physical world. Usually during the development of these systems, the testing phase cannot be done efficiently or safely in the complete real environment, and therefore HIL (Hardware In the Loop) simulators are used. During HIL testing, diagnostic protocols are used very often to gather detailed information about the DUT’s (Device Under Test) internal state. Diagnostic protocols are very useful during testing, but they cause a significant load to the DUT. This paper introduces a novel approach to replace traditional diagnostic protocols with a nonintrusive solution. The presented method is based on the debug capabilities of modern ARM Cortex M core microcontroller, and uses a CMSIS-DAP (Cortex Microcontroller Software Interface Standard Debug - Access Port) based interface.

Bence Csomos, Gabor Kohlrusz, Denes Fodor
State parameter estimation of lead-acid battery pack using impulse excitation method

This paper describes an analysis of impulse excitation method to determine initial parameters of lead-acid battery model. The initial model parameters are essential inputs of state predictors and significantly influence the precision of SoC and SoH tracking.
Two types of Randles-model have been introduced where the model parameters were exploited from the impulse excited voltage response of a battery. Current impulse excitation approach is resourcesaving and convenient way to generate excitation signal by for example, switching relays especially in automotive systems. Switching a relay through a load causes a squarewave-like change in the battery current. Either is a load current or charging current, the battery’s voltage response depends on the actual battery’s SoC and SoH. Using the discharge stages of voltage response characteristic of an Exide 15Ah AGM type battery, resistive and capacitive components of the battery model has been determined. The proposed model and method show promising results to set the initial parameters for state estimators.

Mònica Egusquiza, Carme Valero, Alex Presas, David Valentin, Matias Bossio, Eduard Egusquiza
Advanced condition monitoring of Pelton turbines

The ability of hydropower to adapt the electricity generation to the demand is necessary to integrate wind and solar energy to the grid. Nowadays hydropower turbines are required to work under harsher operating conditions and an advanced condition monitoring to detect damage is crucial. In this paper an improved method for condition monitoring procedure of Pelton turbines is introduced.
A numerical model for the dynamic behavior of the machine has been built-up so that vibrations, deformations and stresses can be calculated for every operating condition.
To improve the model, the data obtained during several years of monitoring was used. The analysis of the machines before and after overhauls was studied to determine the symptoms of damage and to upgrade the model.
The operating conditions can be applied to the digital turbine model to calculate vibrations, deformations and stresses. Eventually, the remaining useful life of the turbine can be estimated.

Gábor Kohlrusz, Krisztián Enisz, Dénes Fodor, Bence Csomós
Integrated model environment for digital controlled power converter analysis and diagnostics

In this paper an integrated model environment is demonstrated which makes it capable to develop control, fault detection or state estimation algorithms for digitally controlled electric drives. Due to the mixed-signal platform it is possible to test and validate the developed methods. In this work a capacitor degradation phenomenon has been investigated which simulates a failure in a PI regulated Buck DC-DC converter.

Vladimir V. Sinitsin
Roller bearing fault detection by applying wireless sensor of instantaneous accelerations of mechanisms moving elements

High-sensitivity tools and methods of receiving diagnostic information are needed to detect low-energy defects. In this paper, the author proposes experimental results of the application of instantaneous angular acceleration for roller bearing fault detection (outer race fault, inner race fault and one ball fault). The experimental results show that defects are clearly visible in frequency spectrum of the angular acceleration. Also, the results can be used to build the defect patterns. In addition, the results show that frequency spectrum components of angular acceleration are significantly amplified around natural frequencies of the mechanism. Moreover, the study showed that instantaneous angular acceleration can be applied for detection of incipient defects.

József Szabó, Péter Bakucz
Embedded integer NARX identification of knocking combustion of large gas engine

Embedded integer NARX (nonlinear autoregressive neural network with exogenous inputs) identification of the vibration experiments on knocking combustion of a Deutz MWM 8 cylinder large gas engine was carried. A measure of the degree of dependence of vibration and knocking reference values defined by the NARX recurrent neural network. A new identification is proposed based on the cross-correlation between the vibration signal and neural network error.

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