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A technique for estimation of non-linear stiffness parameters of rolling element bearings in rotor systems, based on the analysis of the random response signals picked up from the bearing caps, is developed.
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A technique for parameter estimation is carried out through online optimization where the estimates are taken from minimization of the sum of squared errors of the optimization problem by matching the experimental and calculated results within some given range of constraints [37, 38].
Ahmad et al. [18] proposed a technique for phasor estimation using IEC 61850-9-2 procesample sample values.
Fluid dynamic gauging (FDG) has previously been demonstrated as a technique for the estimation of fouling layer thickness during membrane filtration.
Reference [14] proposed a multi-state Markov model for a coal-fired power generating unit, and a technique for the estimation of transition intensities between the various generating capacity levels of the unit based on the actual measurements.
In the first study, a technique for SNR estimation of the PS signal is proposed using simple approximations, while in [26] the authors introduce a weighted energy detector scheme that is able to efficiently scan Bluetooth channels.
Sufficient conditions for global asymptotic stability are derived in terms of linear matrix inequalities (LMIs) and a technique for the estimation of the uncertainty bound is proposed by solving a generalized eigenvalue minimization problem.
The present paper is devoted to an experimental technique for estimation of the instantaneous impedance.
PF is an approximation technique for estimation problems where the variables involved do not hold Gaussianity uncertainty models and linear dynamics.
At the core of the method lies a technique for least-square estimation of the gains of the plant model at the frequency of excitation, which is adopted for the construction of a hybrid external model of an equivalent disturbance acting at the plant input.
To improve radar QPE, we have developed a technique for radar rainfall estimation, the Kyungpook National University Hybrid Surface Rainfall (KHSR), based on a two-dimensional hybrid surface consisting of the lowest radar bins that are immune to ground clutter, beam blockage, and non-meteorological echoes.
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