Abstract: An analysis method for turbine-generator torsional vibrations affected by power transmission system, which is processed by a computer system with a simulation software, is proposed. This analysis method comprises: building structures of a first system model and a second system model to respectively simulate a first system and a second system; building detailed models of the first and second system model; and analyzing the detailed models of the first and second system model in frequency- and time-domain.

Abstract: A turbine generator system is operable to provide electric power to an electric network connected thereto, and includes a turbine generator apparatus and an output module. The turbine generator apparatus includes a turbine rotor provided with a plurality of blades and rotatable to output a mechanical torque, and a generator coupled to the turbine rotor and to be driven by the mechanical torque to generate driving electric power having a system frequency. The output module is electrically connected to the turbine generator apparatus for converting the driving electric power into output electric power to be provided to the electric network. The generator includes a mechanical filter that is operable, when the turbine generator system has a fault, to resonate in a specified frequency that is based on the system frequency to make the blades of the turbine rotor less sensitive to electromagnetic torque disturbance attributed to the fault.

Abstract: An evaluation device is adapted for providing a transceiver system with performance information thereof. The transceiver system includes a transmitter and at least one receiver, and models a channel between the transmitter and the receiver using Nakagami distribution with a fading parameter. The evaluation device includes a signal-to-noise ratio (SNR) setting module, an error rate computing module, and an output module. The SNR setting module is operable to set an average SNR for the channel between the transmitter and the receiver of the transceiver system. The error rate computing module is operable, based upon the fading parameter, the average SNR and a number of the receiver, to compute a bit error rate over the channel between the transmitter and the receiver. The output module is operable to provide the transceiver system with the average SNR and the bit error rate as the performance information of the transceiver system.

Abstract: An electroencephalogram signal processing method includes a recording step, a retrieving step, a removing step and a synthesizing step. The recording step retrieves EEG signal components of a testee via a plurality of electrodes, wherein the EEG signal components serve as an input signal. The retrieving step filters the input signal to obtain a predetermined frequency band signal, and subtracts the predetermined frequency band signal from the input signal to obtain a difference signal. The removing step performs an independent component analysis operation between the difference signal and a separating matrix to obtain an analysis signal, generates a separating pseudo inverse and an independent analysis signal, and performs a matrix operation between the separating pseudo inverse and the independent analysis signal to obtain a corrected signal. The synthesizing step adds the corrected signal and the predetermined frequency band signal together to obtain an output signal.

Abstract: An evaluation device is adapted for providing a transceiver system with performance information thereof. The transceiver system includes a transmitter and at least one receiver, and models a channel between the transmitter and the receiver using Nakagami distribution with a fading parameter. The evaluation device includes a signal-to-noise ratio (SNR) setting module, an error rate computing module, and an output module. The SNR setting module is operable to set an average SNR for the channel between the transmitter and the receiver of the transceiver system. The error rate computing module is operable, based upon the fading parameter, the average SNR and a number of the receiver, to compute a bit error rate over the channel between the transmitter and the receiver. The output module is operable to provide the transceiver system with the average SNR and the bit error rate as the performance information of the transceiver system.

Abstract: An evaluation device is adapted for providing a transceiver system with performance information thereof. The transceiver system models a channel between a transmitter and a receiver thereof using Nakagami distribution with a fading parameter. The evaluation device includes a signal-to-noise ratio (SNR) computing module, a capacity computing module, and an output module. The SNR computing module is operable to set an average SNR for the channel between the transmitter and the receiver, and to compute an expected value and variance of an effective SNR of the transceiver system according to the fading parameter and the average SNR. The capacity computing module is operable to compute an outage capacity of the transceiver system based upon the expected value and the variance of the effective SNR and a transmission outage parameter. The output module is operable to provide the transceiver system with the average SNR and the outage capacity.

Abstract: An evaluation device is adapted for providing a transceiver system with performance information thereof. The transceiver system models a channel between a transmitter and a receiver thereof using Nakagami distribution with a fading parameter. The evaluation device includes a threshold value computing module, a signal-to-noise ratio (SNR) setting module, a probability computing module, and an output module. The threshold value computing module is operable to compute a threshold value based upon a given capacity. The SNR setting module is operable to set an average SNR for the channel between the transmitter and the receiver of the transceiver system. The probability computing module is operable, based upon the fading parameter, the average SNR and the threshold value, to compute an outage probability of the transceiver system corresponding to the given capacity. The output module is operable to provide the transceiver system with the average SNR and the outage probability.

Abstract: A system for computing machine parameters of an induction machine includes a relation providing module and a circuit parameter computing module. The relation providing module is operable to provide a relationship between slip rates and primary side resistances of the induction machine and a relationship between the slip rates and primary side reactances of the induction machine. The circuit parameter computing module is operable to perform a parameter computing process according to the relationships obtained from the relation providing module. The parameter computing process includes the steps of: a) generating a set of initial values of equivalent circuit parameters of the induction machine; b) updating the initial values; c) calculating a cumulative resistance error and a cumulative reactance error; and d) repeating steps b) and c) until the cumulative resistance error and the cumulative reactance error are smaller than first and second error thresholds, respectively.

Abstract: A signal analyzer includes a sampling unit, a filter unit coupled to the sampling unit, a computing unit coupled to the filter unit, and an output unit coupled to the computing unit. The sampling unit is operable to sample a time domain signal from a target system according to a predetermined sampling frequency to obtain a sampling signal. The filter unit is configured to perform filter processing upon the sampling signal so as to filter out harmonic frequency components from the sampling signal, thereby obtaining a fundamental frequency signal having a plurality of sample points. The computing unit is operable to compute a signal parameter set for each of temporally adjacent pairs of the sample points of the fundamental frequency signal. The output unit is configured to output information about dynamic behavior of the target system based upon the signal parameter sets computed by the computing unit.

Abstract: A beamformer includes a number (T) of consecutive combining stages. A Tth combining stage includes a converging unit. Each of first to (T?1)th combining stages includes a plurality of converging units. The number of the converging units in a preceding combining stage is greater than that of a succeeding combining stage. Each converging unit in the first combining stage combines three arrival signals from an antenna array in accordance with corresponding weights so as to form an output signal. Each converging unit in each of second to (T?1)th combining stages combines output signals of three corresponding converging units in an immediately preceding combining stage in accordance with corresponding weights so as to form an output signal. The converging unit of the Tth combining stage combines the output signals from the converging units in the (T?1)th combining stage in accordance with corresponding weights so as to form an output signal that serves as an array pattern.

Abstract: A beamformer includes a number (T) of consecutive combining stages. A Tth combining stage includes a converging unit. Each of first to (T?1)th combining stages includes a plurality of converging units. The number of the converging units in a preceding combining stage is greater than that of a succeeding combining stage. Each converging unit in the first combining stage combines three arrival signals from an antenna array in accordance with corresponding weights so as to form an output signal. Each converging unit in each of second to (T?1)th combining stages combines output signals of three corresponding converging units in an immediately preceding combining stage in accordance with corresponding weights so as to form an output signal. The converging unit of the Tth combining stage combines the output signals from the converging units in the (T?1)th combining stage in accordance with corresponding weights so as to form an output signal that serves as an array pattern.

Abstract: A method for determining an optimum sampling frequency to be performed by a power analyzer includes the following computer-implemented steps: sampling a time domain signal to obtain a sampling signal according to a predetermined sampling frequency; obtaining two reference sampling signals using higher and lower sampling frequencies compared to the predetermined sampling frequency; transforming the sampling signal and the reference sampling signals to frequency domain signals; computing a sum-of-amplitudes for each of the three frequency domain signals; estimating a minimum sum-of-amplitudes value and a corresponding re-sampling frequency; obtaining a new reference sampling signal using the re-sampling frequency; transforming the new reference sampling signal to a frequency domain signal, and computing a sum-of-amplitudes therefor; and re-estimating the minimum sum-of-amplitudes value and the corresponding re-sampling frequency.

Abstract: A method for establishing a simulating signal suitable for estimating a complex exponential signal includes the following computer-implemented steps: sampling a time domain signal of a physical system to obtain a sampling signal; transforming the sampling signal to a frequency domain signal using Fast Fourier Transform; determining parameters of the frequency domain signal; establishing a simulating signal; establishing a target function which is a deviation of the simulating signal from the sampling signal; obtaining correcting factors; iterating the target function using a gradient method and the correcting factors to obtain three sets of iterated signal parameters; obtaining corrected parameters using quadratic interpolation; and using the corrected parameters to correct the simulating signal, and establishing an updated target function. The simulating signal can be used to estimate dynamic behavior of the physical system if the updated target function converges to a tolerable range.

Abstract: A method for optimization of a frequency spectrum includes the following steps: sampling a time domain signal to obtain an initial sampling signal based upon a first subset of sample points; transforming the initial sampling signal to a frequency domain signal; determining a frequency parameter and an amplitude parameter for each of harmonic components of the frequency domain signal; establishing a leakage energy equation and a graduation shifting quantity; determining an optimum number of sample points that will result in minimum leakage energy; obtaining an adjusted sampling signal based on a second subset of the sample points, wherein the number of the sample points in the second subset is equal to the optimum number; and transforming the adjusted sampling signal to an optimized frequency domain signal having harmonic components associated with graduations of an optimized frequency spectrum, wherein the graduations are calculated based upon the graduation shifting quantity.