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Electronic Components, Functions, and Devices
Published in Muhammad H. Rashid, Ahmad Hemami, Electricity and Electronics for Renewable Energy Technology, 2017
Modulation and demodulation are among the backbones of telecommunication and broadcasting. But, they have other applications, too. To send low-frequency signals such as music and speech over the air (radio and TV broadcasting) or through intercontinental communication lines, they must be carried by electromagnetic waves with elevated frequencies. There is no other way than loading the information to be sent to a carrier signal (the one with high frequency). The action of loading or transferring the variation of the desired signal to the carrier signal is called modulation. In general, we may say modulation is changing the properties of a waveform with the contents of a signal for some desired purpose. This is shown below for analog signals. In Chapter 20 we see other applications, too (we can see pulse width modulation in the operation of rectifiers and inverters). Demodulation is the opposite action. It is the action of separating the modulating signal from the modulated signal. In this way the original signal is extracted and reconstructed from the carrier signal.
Basic Concepts of Electricity
Published in Stephan S. Jones, Ronald J. Kovac, Frank M. Groom, Introduction to COMMUNICATIONS TECHNOLOGIES, 2015
Stephan S. Jones, Ronald J. Kovac, Frank M. Groom
Certain electrical appliances require one frequency or a specific range of frequencies from a band of frequencies for effective functioning. The circuit developed to perform this filtering process is called a filter circuit or simply a filter. There are several types of filters (Exhibit 2.17): Low-pass filters: these circuits filter out the high frequencies, allowing only the low-frequency components to pass through the circuit.High-pass filters: these circuits filter out the low-frequency components and allow only the higher frequencies to pass through.Band-pass filters: these filters allow only a specific range of frequencies to pass through from a mix of various frequencies.Band-stop filters: these filters reject a particular range of frequencies, allowing all other frequencies to pass through the circuit. They are also known as band-elimination or notch filters.
Electromagnetic Compatibility
Published in Ahmad Shahid Khan, Saurabh Kumar Mukerji, Electromagnetic Fields, 2020
Ahmad Shahid Khan, Saurabh Kumar Mukerji
This type of interference may be due to the sources operating in audio frequency range. In general, this range starts from a very low frequency and ranges up to 20 kHz. This range is sometimes extended up to 100 kHz. The AFI may be due to mains hum from the power supply units, nearby power supply wiring, transmission lines, or substations. Audio processing equipment (viz. audio power amplifiers and loudspeakers) and demodulation of a high-frequency carrier wave (viz. FM radio transmission) may also act as sources in this frequency range.
Reducing the Cost of Calculations for Incremental Dynamic Analysis of Building Structures Using the Discrete Wavelet Transform
Published in Journal of Earthquake Engineering, 2022
Masoud Dadkhah, Reza Kamgar, Heisam Heidarzadeh
According to the above description, IDA consumes a lot of time and energy. Therefore, here a method is proposed to reduce the computational cost without a significant decrease in the precision of the results. Therefore, the earthquakes are filtered up to five levels with a discrete wavelet transform to obtain the main earthquake with fewer points. As can be seen from Fig. 1, a low-pass filter allows passing the low-frequency signals, while avoiding high-frequency signals. Also, a high-pass filter only passes high-frequency signals and does not pass low-frequency signals. Therefore, only high-frequency signals (Dj) pass through a high-pass filter, and only low-frequency signals (Aj) pass through a low-pass filter. In each level of decomposition, the calculated earthquake is applied to the structure, and IDA is performed. Finally, the responses of the frame are plotted for different intensities of the earthquake. The maximum response of the structure is plotted against the intensities of the earthquake for the IDA curve. Also, in this type of analysis, the behavior of the structure is considered to be nonlinear.
A Comprehensive Study of Wide-Area Damping Controller Requirements Through Real-Time Evaluation with Operational Uncertainties in Modern Power Systems
Published in IETE Journal of Research, 2022
In modern interconnected power systems, low-frequency electromechanical oscillations constitute a significant problem. The stable, secure, and reliable operation of the system is predominantly associated with decreasing these oscillations. Low-frequency inter-area oscillations (0.2–1.0 Hz) are the reason for major blackouts in the power systems. Inter-area oscillations modes are not effectively damped out by conventional methods such as power system stabilizers. PSSs primarily provide the damping to generators and damp out the mainly intra-plant modes of oscillations (2.0–3.0 Hz) and local-plant modes of oscillations (1.0–2.0 Hz). Poorly damped inter-area modes of oscillations affect the system stability. So, effectively damping out the low-frequency inter-area mode of oscillations, a wide-area damping control system is used in the modern interconnected power system to enhance the system stability, reliability, security, and power transfer capacity. Modern power systems are divided into two parts: physical power systems and cyber power systems. The communication system plays an important role in WAMS-based WADCS to transfer the wide-area signals because controller performance is dependent on fast and quality information signal flow. Delayed signals decrease the WADCS performance and affect the system’s stability and security.
Surface microseismic data denoising based on sparse autoencoder and Kalman filter
Published in Systems Science & Control Engineering, 2022
Xuegui Li, Shuo Feng, Nan Hou, Ruyi Wang, Hanyang Li, Ming Gao, Siyuan Li
The microseismic event has weak energy, high frequency, and short duration, so it is easily affected or covered by ambient noise. Because of these characteristics of microseismic data, it is necessary to carry out a series of treatments of microseismic data to accurately conduct the initial pick and the source localization. First, through pretreatment and reasonable filtering, the microseismic signal of the filtered background noise is consistent. Then select favourable polarization analysis and seismic events to do early pickup, and get the angle relative to the source and the time difference of vertical and horizontal wave. At the same time, according to the time difference, P-wave velocity model is set up to achieve the aim of accurate source positioning. The main frequency of surface microseismic data is significantly lower than that of well monitoring seismic data. The background interference in terrestrial microseismic data is also more complicated. There is no regularity in such interference in the time and space domain. Low-frequency and high-frequency interference can be suppressed by simple band-pass filtering. The random noise overlapping the real signal in the frequency domain is not easy to suppress. To improve the automatic identification of an effective event, it is necessary to suppress environmental noise. The environment of the microseismic monitoring detector is very complex. According to the microseismic signals, the effect is not ideal of using conventional filter to process. The denoising effect of surface microseismic data is directly related to fracturing effect interpretation, fracturing program adjustment, focal location and other tasks. Denoising is the key to the whole microseismic processing flow as expressed in Figure 2.