Analisis Data Curah Hujan Kabupaten Ketapang dan Kota Pontianak Menggunakan Transformasi Wavelet

Data curah hujan di Kabupaten Ketapang dan Kota Pontianak dianalisis untuk mengetahui pola curah hujan di Kabupaten Ketapang dan Kota Pontianak. Data yang digunakan adalah data curah hujan bulanan selama 30 tahun (1986–2016), dengan menggunakan transformasi wavelet. Hasil penelitian ini menunjukkan bahwa metode tersebut dapat memperlihatkan pola curah hujan melalui Wavelet Power Spectrum (WPS) dan Global Wavelet Spectrum (GWS) disetiap stasiun pengamatan. Hasil dari WPS menunjukkan bahwa intensitas curah hujan yang tinggi di Kabupaten Ketapang adalah pada periode 1 tahun dan periode 3 tahun dengan pola hujan tahunan. Tingginya intensitas curah hujan dipengaruhi oleh fenomena El Niño Southern Oscillation (ENSO), yang merupakan hasil dari pengolahan data indeks ENSO dengan data curah hujan menggunakan cross wavelet. Di Kota Pontianak intensitas curah hujanyang tinggi terjadi pada periode 0,5 tahun dan periode 1 tahun dengan pola hujan musiman dan tahunan.

Combustion Instability Analysis Using Wavelets in Conventional Diesel Engine

Combustion instability affects the drivability, power, engine performance and efficiency. Elimination of combustion instabilities leads to increase in power for the same fuel economy. Effective controller can reduce combustion instabilities by understanding patterns in the cyclic variations. In this study, cyclic variations of combustion parameters were analyzed in a diesel engine using wavelet analysis. The experiments were conducted at varying loads and compression ratios at 1500 rpm. At steady state condition, cylinder pressure data of 2000 consecutive combustion cycles was measured. Continuous Wavelet Transform was used to capture non-stationary or transient features that might not have been detected using other transforms. Wavelet Power Spectrum (WPS) and Global Wavelet Spectrum were further used to determine the relationship between fluctuations in combustion parameters. Contour Plots were plotted based on WPS for visualizing the intensity and frequency of cyclic Variations. It was found that cyclic variability decreases with increase in engine load and compression ratio.

Continuous Wavelet and Hilbert-Huang Transforms Applied for Analysis of Active and Reactive Power Consumption

Analysis of power consumption presents a very important issue for power distribution system operators. Some power system processes such as planning, demand forecasting, development, etc.., require a complete understanding of behaviour of power consumption for observed area, which requires appropriate techniques for analysis of available data. In this paper, two different time-frequency techniques are applied for analysis of hourly values of active and reactive power consumption from one real power distribution transformer substation in urban part of Sarajevo city. Using the continuous wavelet transform (CWT) with wavelet power spectrum and global wavelet spectrum some properties of analysed time series are determined. Then, empirical mode decomposition (EMD) and Hilbert-Huang Transform (HHT) are applied for the analyses of the same time series and the results showed that both applied approaches can provide very useful information about the behaviour of power consumption for observed time interval and different period (frequency) bands. Also it can be noticed that the results obtained by global wavelet spectrum and marginal Hilbert spectrum are very similar, thus confirming that both approaches could be used for identification of main properties of active and reactive power consumption time series.

Wavelet analysis reveals heterogeneous time-dependent oscillations of individual mitochondria

Mitochondrial inner membrane potential oscillations in cardiac myocytes synchronize under oxidative or metabolic stress, leading to synchronized whole cell oscillations. Gaining information about the temporal properties of individual mitochondrial oscillators is essential to comprehend the network's intrinsic spatiotemporal organization. We have developed methods to detect individual mitochondrial tetramethylrhodamine ethyl ester fluorescence oscillations and assess their dynamical properties using wavelet analysis. We demonstrate that these advanced signal processing tools can provide quantitative spatiotemporal information about intermitochondrial coupling. We have found that the mean frequency of selected groups of continuously oscillating mitochondria was 16.49 ± 1.04 mHz, whereas the mean frequency in the normalized mean global wavelet spectrum was 22.84 ± 1.80 mHz ( n = 9 myocytes). In conclusion, this novel methodology will help shed new light on the dynamical properties of the mitochondrial network on the verge of synchronization.

Analysis of Seizure EEG in Kindled Epileptic Rats

Using wavelet analysis we have detected the presence of chirps in seizure EEG signals recorded from kindled epileptic rats. Seizures were induced by electrical stimulation of the amygdala and the EEG signals recorded from the amygdala were analyzed using a continuous wavelet transform. A time–frequency representation of the wavelet power spectrum revealed that during seizure the EEG signal is characterized by a chirp-like waveform whose frequency changes with time from the onset of seizure to its completion. Similar chirp-like time–frequency profiles have been observed in newborn and adult patients undergoing epileptic seizures. The global wavelet spectrum depicting the variation of power with frequency showed two dominant frequencies with the largest amounts of power during seizure. Our results indicate that a kindling paradigm in rats can be used as an animal model of human temporal lobe epilepsy to detect seizures by identifying chirp-like time–frequency variations in the EEG signal.