Filtering and signal extraction are essential ap-plications in some areas such as medical, electrical, pattern recognition, and other disciplines. For example, in regions of automatic detection, it is necessary to isolate specific signals to study them or accomplish the training process to reach a high detection rate. This paper proposes a new technique of signal extraction based on sparse representation and the Orthogonal Matching Pursuit algorithm, using discrete sine transform and discrete cosine transform to generate the dictionaries. Then, the signal is represented in the base of the given dictionary and limited to the desired bandwidth, extracting the desired information with almost no changes in phase and amplitude, reaching almost vertical slopes in lateral bands.
Strong ground motion signals are the main information source regarding the energy input that affects existing structures. Large earthquakes in some regions are rare, so strong seismic records are scarce in many countries and in many types of surface soil. When available, it is necessary to extract all possible information from those signals about seismic parameters for understanding the seismic impact on infrastructure and to improve some design parameters in local seismic codes. After the Pedernales Mw7.8 earthquake in Ecuador, several strong motion accelerograms were registered in different types of soils for the first time in the country, given the opportunity to apply updated signal analysis methods, to compute different kinds of linear and nonlinear response spectra, and to propose changes to the current Ecuadorian seismic code. Results of this analysis and some proposed upgrades to the current code are presented in this paper.
Voltage and current sensors are the first keys in smart electricity meter design. They must meet accuracy, security, and reliability. Hence, these sensors become sophisticated and expensive. This paper proposes a transducer not only to meet charge electricity billing, but also to acquire waveforms to evaluate adverse power quality phenomena. The proposed transducer is based on an optocoupler to isolate the electrical network from the meter. The transducer design uses a suggested method to exploit properly the current transfer ratio to meet the accuracy and linearity needed in the power quality context. In addition, a method to estimate a correction factor to compensate for the tolerance in the component values of the transducer is given. The proposed transducer has been validated using Oread Lite® software to simulate different case studies related to power quality phenomena. Results show that the proposed transducer has an adequate performance for smart electricity meters that can be extended to evaluate adverse power quality phenomena.
Early fault detection in wind turbines has positive impacts on the costs of repair and maintenance. If the damage is early detected, the damage can be repaired before it increases and generates a complete failure. In this work, a methodology based on convolutional neural networks and the time-frequency representation of vibration signals for the detection of imbalance and bearing faults is presented. In general, the methodology consists of the acquisition of vibration signals from two damage types (blade imbalance and bearing fault) and the healthy condition. Then, a spectrogram function is applied to get an image from the time-frequency plane of the vibration signals. This image is segmented and analyzed by the convolutional neural network to detect the wind turbine condition. A MATLAB graphic user interface is developed to implement the proposed methodology. Results demonstrate the usefulness of the proposal as 100% of accuracy in the diagnosis is achieved.
One of the most used approaches to synchronize power electronic converters to electrical power systems is the phase-locked loop (PLL). PLLs with adaptive characteristics such as the PLL based on a double second order generalized integrator (DSOGI - PLL) are widely used in the synchronization of three-phase power converters, due to their adaptive filtering characteristics and the improvement that is obtained by adding a sequence component calculator before the loop filter. However, the accuracy of the PLL measurements, and therefore the calculation of the phase angle, is affected during transients, so that the frequency, phase angle, and voltage calculated by the PLL are a function of the disturbance type and the architecture of the PLL. This article proposes an improved DSOGI-PLL with a frequency -lock loop based on a double generalized second order integrator (DSOGI-FLL) which is more stable and shows a faster response than the conventional DSOGI-PLL. The main idea is to combine the strengths of these two algorithms into one architecture that will be called DSOGI-PLL with FLL. The performance of the proposed PLL is verified and validated under the processor in the loop (PIL) approach.
