Noise measurement

About: Noise measurement is a research topic. Over the lifetime, 19776 publications have been published within this topic receiving 308180 citations.

Speed Measurement Error Suppression for PMSM Control System Using Self-Adaption Kalman Observer

Abstract: This paper proposes a self-adaption Kalman observer (SAKO) used in a permanent-magnet synchronous motor (PMSM) servo system. The proposed SAKO can make up measurement noise of the absolute encoder with limited resolution ratio and avoid differentiating process and filter delay of the traditional speed measuring methods. To be different from the traditional Kalman observer, the proposed observer updates the gain matrix by calculating the measurement noise at the current time. The variable gain matrix is used to estimate and correct the observed position, speed, and load torque to solve the problem that the motor speed calculated by the traditional methods is prone to large speed error and time delay when PMSM runs at low speeds. The state variables observed by the proposed observer are used as the speed feedback signals and compensation signal of the load torque disturbance in PMSM servo system. The simulations and experiments prove that the SAKO can observe speed and load torque precisely and timely and that the feedforward and feedback control system of PMSM can improve the speed tracking ability.

An Active Impulsive Noise Control Algorithm With Logarithmic Transformation

Abstract: To overcome the limitations of the existing algorithms for active impulsive noise control, an algorithm based on minimizing the squared logarithmic transformation of the error signal is proposed in this correspondence. The proposed algorithm is more robust for impulsive noise control and does not need the parameter selection and thresholds estimation according to the noise characteristics. These are verified by theoretical analysis and numerical simulations.

Noise spectrum tracking for speech enhancement

Abstract: A spectrum-based speech enhancement system estimates and tracks the noise spectrum of a mixed speech and noise signal. The system frames and windows a digitized signal and applies the frames to a fast Fourier transform processor to generate discrete Fourier transformed (DFT) signals representing the speech plus noise signal. The system calculates the power spectrum of each frame. The speech enhancement system employs a leaky integrator that is responsive to identified noise-only components of the signal. The leaky integrator has an adaptive time-constant which compensates for non-stationary environmental noise. In addition, the speech enhancement system identified noise-only intervals by using a technique that monitors the Teager energy of the signal. The transition between noise-only signals and speech plus noise signals is softened by being made non-binary. Once the noise spectrum has been estimated, it is used to generate gain factors that multiply the DFT signals to produce noise-reduced DFT signals. The gain factors are generated based on an audible noise threshold. The method generates audible a priori and a posteriori signal to noise ratio signals and then calculates audible gain signals from these values.

Analysis and Design of a Single-Resonator GaAs FET Oscillator with Noise Degeneration

Abstract: This paper presents an analysis of a low-noise dielectric resonator GaAs FET oscillator in a frequency-locked loop (FLL), which is used for FM noise degeneration. In this circuit, one resonator serves both as the frequency-determining element of the oscillator and as the dispersive element of the discriminator. The results of the analysis are used to generate design guidelines. These guidelines were followed in an experimental realization of an X-band circuit. The measured FM noise was--120 and--142 dBc/Hz at 10- and 100-kHz offset frequencies, respectively, and corresponded closely to predicted results.

Power System Tracking State Estimation and Bad Data Processing

Abstract: In this paper the tracking of the time yarying power system static state is analysed. The relative importance of the small measurement noise and the eventual occurrence of gross error in the measurements is used as a design criterion for the development of fast tracking estimators. The basic approach uses a pre-estimation bad data detection/ elimination scheme based on the exponential smoothing of past estimations and logical checks followed by an estimation stage. Three different estimation algorithms were tested: plain weighted least squares, quadratic square-root and linear criterion. Numerical results showing the performance of the three estimators in a simulated test case are also presented.