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1

A study of dynamic hysteresis model for a magnetorheological damper

Chen Kun-Yung, Kung Ming-Lung

Journal of Theoretical and Applied Mechanics

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2023

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Vol. 61 nr 2

259--274

EN

The paper proposes a new dynamic model based on the LuGre model and an electrical equation to describe the hysteresis phenomenon for a magnetorheological (MR) damper. In addition, a sliding mode observer (SMO) is proposed to estimate unmeasurable states of the MR damper. The parameters of the MR damper are successfully identified by using the self-learning particle swarm optimization (SLPSO) algorithm. The contributions of this paper are: i) a new dynamic model based on the LuGre model and an electrical equation for an MR damper is successfully formulated to fit for the hysteresis behavior, ii) the exerted damping force can be practically adjusted by using input voltage for the dynamic model, iii) the SMO is proposed to estimate the internal states and current, and iv) the unknown parameters of the MR damper are successfully identified by using the SLPSO algorithm with a numerical experiment.

2

Application of machine learning ensemble models for rainfall prediction

Ahmadi Hasan, Aminnejad Babak, Sabatsany Hojat

Acta Geophysica

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2023

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Vol. 71, no. 4

1775--1786

EN

Practical information can be drawn from rainfall for making long-term water resources management plans, taking flood mitigation measures, and even establishing proper irrigation systems. Given that a large amount of data with high resolution is required for physical modeling, this study proposes a new standalone sequential minimal optimization (SMO) regression model and develops its ensembles using Dagging (DA), random committee (RC), and additive regression (AR) models (i.e., DA-SMO, RC-SMO, and AR-SMO) for rainfall prediction. First, 30-year monthly data derived from the year 1988 to 2018 including evaporation, maximum and minimum temperatures, maximum and minimum relative humidity rates, sunshine hours, and wind speed as input and rainfall as the output were acquired from a synoptic station in Kermanshah, Iran. Next, based on the Pearson correlation coefficient (r-value) between input and output variables, different input scenarios were formed. Then, the dataset was separated into three subsets: development (1988–2008), calibration (2009–2010), and validation (2011–2018). Finally, the performance of the developed algorithms was validated using different visual (scatterplot and boxplot) and quantitative (percentage of BIAS, root mean square error, Nash–Sutcliffe efficiency, and mean absolute error) metrics. The results revealed that minimum relative humidity had the greatest effect on rainfall prediction. The most effective input scenario featured all the input variables except for wind speed. Our findings indicated that the DA-SMO ensemble algorithm outperformed other algorithms.

3

Spider monkey optimization (SMO) - lattice Levenberg-Marquardt recursive least squares based grid synchronization control scheme for a three-phase PV system

Dash Dipak Kumar, Sadhu Pradip Kumar, Subudhi Bidyadhar

Archives of Control Sciences

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2021

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Vol. 31, No. 3

707--730

EN

This paper presents a new grid integration control scheme that employs spider monkey optimization technique for maximum power point tracking and Lattice Levenberg Marquardt Recursive estimation with a hysteresis current controller for controlling voltage source inverter. This control scheme is applied to a PV system integrated to a three phase grid to achieve effective grid synchronization. To verify the efficacy of the proposed control scheme, simulations were performed. From the simulation results it is observed that the proposed controller provides excellent control performance such as reducing THD of the grid current to 1.75%.

4

Support vector machine for MUAP scalograms classification

Dobrowolski A., Wierzbowski M., Tomczykiewicz K.

Przegląd Elektrotechniczny

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2008

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R. 84, nr 12

335-338

EN

The paper presents a new approach to the computer aided diagnostic systems for the needs of quantitative electromyography. The approach is based on the analysis of wavelet scalograms of the motor unit action potentials calculated on the basis of 4th order Symlet wavelet. The scalograms provide the vector consisting of six features describing the state of a muscle. The vectors serve to carry out a classification of pathology by using support vector machines method.

PL

W referacie przedstawiono nową metodę diagnostyczną opartą na analizie skalogramów wyznaczonych za pomocą falek Symlet 4. Z otrzymanych skalogramów wyekstrahowano 6 cech, które posłużyły do klasyfikacji rodzaju patologii przeprowadzonej z wykorzystaniem metody maszyn wektorów nośnych. Implementacja programowa metody stworzy narzędzie diagnostyczne wspomagające badanie EMG o wysokim prawdopodobieństwie prawidłowej oceny stanu mięśnia.

5

Skalowanie obserwacji w wielowymiarowej diagnostyce maszyn niestacjonarnych

Cempel C., Tabaszewski M.

Diagnostyka

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2005

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Vol. 34

23--30

PL

Wiele obiektów krytycznych pracuje niestacjonarnie, a większość symptomów stanu technicznego zależy co najmniej od chwilowego obciążenia i warunków pracy. Zatem diagnostyka takich obiektów powinna mieć możliwość reskalowania odczytów symptomów do obciążenia znamionowego. Praca pokazuje taką możliwość dla przypadku wielowymiarowej symptomowej macierzy obserwacji, uzupełniając w ten sposób możliwości diagnozowania wielowymiarowego na przypadek niestacjonarnej pracy obiektów krytycznych.

EN

Many critical mechanical systems operate in a nonstationary regime (load), and many observed symptoms of its condition depend in a some way on a system load and/or environmental conditions. Hence the condition monitoring of a such systems ought to have some possibility of rescaling of observed symptoms to a standard load condition. This paper shows such a possibility of a symptoms rescaling in application to multidimensional vibration condition monitoring. It is shown on some real example of vibration condition monitoring, that rescaling of symptoms can make more reliable the assessment of current system condition, as well as its prognosis.