Papers by Keyword: Wavelet Transform (WT)

Abstract: In the paper dynamic electromechanical coupling between the structural model of the rotating machine drive system and the circuit model of the asynchronous motor has been investigated. By means of the computer model of the rotating machine drive system the results of experimental testing have been confirmed. From the obtained results of computations and measurements it follows that the coupling between the considered rotating system and the installed rotary dampers with the magneto-rheological fluid (MRF) results in effective energy dissipation leading to significant reduction of undesired torsional vibrations.

Abstract: Mammogram enhancement is important for the radiologist to diagnose and screen breast cancer. This paper proposes a method to improve contrast and denoising in mammogram using wavelet transform and sigmoid function. First, mammogram is decomposed using wavelet transform and detail coefficients are decreased in order to remove noises by soft thresholding. Inverse wavelet transform is then applied to obtain the denoised image. Finally, sigmoid function is applied to the image to enhance mammogram. Experimental results illustrate that the proposed method can improve contrast and denoise mammogram effectively.

Abstract: Wavelet transform denoising is an important application of wavelet analysis in signal and image processing. Several popular wavelet denoising methods are introduced including the Mallat forced denoising, the wavelet transform modulus maxima method and the nonlinear wavelet threshold denoising method. Their advantages and disadvantages are compared, which may be helpful in selecting the wavelet denoising methods. At the same time, several improvement methods are offered.

Abstract: As the meteorological parameter of numeric weather forecast model has systematic error, which leads to the restriction of forecast precision for photovoltaic electric field, the paper put forward a short-term output forecasting model of photovoltaic electric field based on wavelet transform. Wavelet transform algorithm that using 4 series of sym6 wavelet decomposition conducts a dynamic correction to the wind speed data outputted by numerical weather forecasting. Through combining other meteorological data, it formed a new amended meteorological data collection used to forecast the photovoltaic power; according to the two training set of both the original and the amended meteorological data, two prediction model based on original and amended neural network outputted by photovoltaic plant power are established. By comparing the measured data and model analysis data within a same period, it shows that the amended model can significantly reduce the RMSE of predict results and decrease the error from 70.66% to 70.66%, and increase the relative accuracy from 70.66% to 70.66%.

Abstract: This paper, both theoretically and numerically, investigates an effective reconstruction of EEG signal. An optimization model is presented, which unifies different sparse signals. The model is solved by employing the proximal algorithm. Based on the theoretical analysis, the simulation of EEG signal is performed. Sparse representation of EEG signal is got by the technique of wavelet transform and the signal denoising is also obtained. Then, by using compressed sensing, the EEG signal is reconstructed. Our results show that the reconstructed signal is in good agreement with the original signal and retains the leading characteristic.

Abstract: To improve image quality and a higher level of follow-up image process needed, it's of great importance to do the image denoising process first. A new image denoising method in two-dimensional (2-D) fractional time-frequency domain is proposed in this paper. Through the realization of 2-D fractional wavelet transform algorithm, the 2-D fractional wavelet transform theory is applied to image denoising, and compare with image denoising method based on 2-D wavelet transform. A large number of image denoising simulation studies have shown that, the Peak Signal to Noise Ratio of output images based on the proposed method can be effectively improved, and preserve detail information effectively and reduce the noise at the same time. It proved 2-D fractional wavelet transform is a new and effective time-frequency domain image denoising method.

Abstract: A multi-scale modeling method based on big data was proposed to establish neural network models for complex plant. Wavelet transform was used to decompose input and output parameters into different scales. The relationship between these parameters were researched in every scale. Then models in each scale were established and added together to form a multi-scale model. A model of coal mill current in power plant was established using the multi-scale modeling method based on big data. The result shows that, the method is effective.

Abstract: This paper proposed an improved method based on adaptive with threshold wavelet transform denoising, according to image is often affected by noise pollution in the process of acquisition and transmission, compared with the advantages and disadvantages of traditional digital filtering method. It extracts the structure information and details of the image. It can adaptively select wavelet transform of optimal decomposition level and soft threshold to achieve the optimal noise reduction effect. The Simulation results demonstrate that this theory can effectively filter Gaussian noise and Salt and pepper noise, at the same time well protect the image details and achieve better visual effects.

Abstract: Based on the analysis of the transient process of the electric line’s developing ground fault, this paper applies the oppositely-directed travelling wave fault location method to fault location in distribution network. Simultaneously, this paper chooses proper wavelet generating functions to find the modulus maximum of oppositely-directed travelling waves and summarizes the methods and steps of this oppositely-directed travelling wave fault location. Finally, PSCAD/EMTDC is used to simulate the single-phase ground fault to verify the oppositely-directed travelling wave fault location method.

Abstract: When fault distance is greater than a certain value, attenuation of high frequency fault signal over the line is greater than what the DC line boundary is subject to. To sensitively detect a fault and improve the reliability of UHVDC (Ultra High Voltage Direct Current) transmission line protection, a new protection scheme based on wavelet based direction element is proposed, where directional element and attenuation of high frequency energy are used to identify an internal fault. Extensive simulation results show that the proposed protection scheme is able to sensitively detect high impedance faults, identify the faulty pole.