This document discusses the Fourier transform and its applications. It begins with an abstract that provides an overview of the Fourier transform technique for representing variables as complex exponentials. It then discusses some key properties and types of the Fourier transform. The main applications of the Fourier transform discussed are in signal processing, digital image processing, power distribution systems, mobile phones, medical engineering, and other fields such as quantum mechanics and data analysis.
This document discusses the Fourier transform and its applications to cell phones. It begins with background on the Fourier transform, developed by Joseph Fourier in 1807 to represent periodic signals as sums of sinusoids. The document then provides the mathematical definition of the Fourier transform, which transforms a function of time into a function of frequency. Examples are given of how the Fourier transform is used in cell phone communication, such as modulating voice signals to sine waves for transmission and using coordinates to locate cell towers during calls. The role of mathematics in cell phone design and operation is also summarized.
The document discusses the convergence of the Fourier transform. It provides an outline covering topics like the Fourier transform, Fourier series, the difference between them, and conditions for convergence like the Dirichlet condition. It also discusses Fourier analysis of discrete time signals and types of convergence like uniform and mean square convergence. Examples are given to illustrate concepts like Gibbs phenomenon where the Fourier approximation oscillates at points of discontinuity.
What is Fourier Transform
Spatial to Frequency Domain
Fourier Transform
Forward Fourier and Inverse Fourier transforms
Properties of Fourier Transforms
Fourier Transformation in Image processing
fast-Fourier-transform-presentation and Fourier transform for wave
in
signal possessing for
physics and
geophysics
spectra analysis
periodic and non periodic wave
data sampling
The Nyquist frequency
The discrete Fourier transform has many applications in science and engineering. For example, it is often used in digital signal processing applications such as voice recognition and image processing.
This document discusses Fast Fourier Transform (FFT). It begins by explaining that FFT is a faster version of the Discrete Fourier Transform (DFT) that calculates the same results but in less time by utilizing clever algorithms. It then discusses the types of FFT including decimation in time, decimation in frequency, radix 2 and 4 FFTs, and Winograd Fourier Transform Algorithm. Next, it describes how the FFT does not directly give the spectrum but discusses using MATLAB's fftshift function to show the spectrum from -fs/2 to fs/2. It concludes by discussing some advantages and disadvantages of FFT spectrum analyzer technology.
1. The document discusses Fourier transforms of discrete signals and sampling theory. It explains that continuous signals are digitized through sampling and the discrete time Fourier transform (DTFT) can be used to find the frequency spectrum of discrete signals.
2. It also covers the discrete Fourier transform (DFT) which is used when only a finite amount of data is available. The DFT breaks up a signal into its constituent frequencies.
3. Fast Fourier transform (FFT) algorithms like the radix-2 algorithm improve the efficiency of computing the DFT and allow it to be done in O(NlogN) time rather than O(N2) time.
This document discusses the Fourier transform and its applications to cell phones. It begins with background on the Fourier transform, developed by Joseph Fourier in 1807 to represent periodic signals as sums of sinusoids. The document then provides the mathematical definition of the Fourier transform, which transforms a function of time into a function of frequency. Examples are given of how the Fourier transform is used in cell phone communication, such as modulating voice signals to sine waves for transmission and using coordinates to locate cell towers during calls. The role of mathematics in cell phone design and operation is also summarized.
The document discusses the convergence of the Fourier transform. It provides an outline covering topics like the Fourier transform, Fourier series, the difference between them, and conditions for convergence like the Dirichlet condition. It also discusses Fourier analysis of discrete time signals and types of convergence like uniform and mean square convergence. Examples are given to illustrate concepts like Gibbs phenomenon where the Fourier approximation oscillates at points of discontinuity.
What is Fourier Transform
Spatial to Frequency Domain
Fourier Transform
Forward Fourier and Inverse Fourier transforms
Properties of Fourier Transforms
Fourier Transformation in Image processing
fast-Fourier-transform-presentation and Fourier transform for wave
in
signal possessing for
physics and
geophysics
spectra analysis
periodic and non periodic wave
data sampling
The Nyquist frequency
The discrete Fourier transform has many applications in science and engineering. For example, it is often used in digital signal processing applications such as voice recognition and image processing.
This document discusses Fast Fourier Transform (FFT). It begins by explaining that FFT is a faster version of the Discrete Fourier Transform (DFT) that calculates the same results but in less time by utilizing clever algorithms. It then discusses the types of FFT including decimation in time, decimation in frequency, radix 2 and 4 FFTs, and Winograd Fourier Transform Algorithm. Next, it describes how the FFT does not directly give the spectrum but discusses using MATLAB's fftshift function to show the spectrum from -fs/2 to fs/2. It concludes by discussing some advantages and disadvantages of FFT spectrum analyzer technology.
1. The document discusses Fourier transforms of discrete signals and sampling theory. It explains that continuous signals are digitized through sampling and the discrete time Fourier transform (DTFT) can be used to find the frequency spectrum of discrete signals.
2. It also covers the discrete Fourier transform (DFT) which is used when only a finite amount of data is available. The DFT breaks up a signal into its constituent frequencies.
3. Fast Fourier transform (FFT) algorithms like the radix-2 algorithm improve the efficiency of computing the DFT and allow it to be done in O(NlogN) time rather than O(N2) time.
The document discusses the Fast Fourier Transform (FFT) algorithm.
1) The FFT is a set of techniques that exploits symmetries in the Discrete Fourier Transform (DFT) to make its computation much faster. The speedup increases with larger DFT sizes.
2) The Cooley-Tukey algorithm decomposes an N-point DFT into smaller DFTs by splitting the indices, resulting in an algorithm that is proportional to NlogN operations rather than N^2.
3) The algorithm can be represented as a series of "butterfly" operations, with each butterfly requiring only 2 multiplications. This reduces the number of multiplications needed compared to direct computation of the DFT.
Fast Fourier Transform (FFT) is an algorithm that divides a signal into its frequency components, with each component being a sinusoidal oscillation with its own amplitude and phase. An FFT rapidly computes the Discrete Fourier Transform (DFT) by factorizing the DFT matrix, reducing the complexity from O(n2) to O(n log n). FFT is widely used for applications like filtering, encoding, and solving difference equations. There are two main types of FFT analysis: the discrete Fourier transform, which transforms a sequence into frequencies, and the inverse FFT, which transforms frequencies back into a sequence. FFT analysis is useful for measuring signal frequencies but requires adequate sampling to avoid aliasing lower frequencies as higher ones.
Lec 07 image enhancement in frequency domain iAli Hassan
The document discusses digital image processing and image enhancement in the frequency domain. It provides background on Fourier series and Fourier transforms, explaining that Fourier transforms allow representing even non-periodic functions as integrals of sines and cosines. The Fourier transform converts a signal from the time domain to the frequency domain. Two-dimensional Fourier transforms are used in image processing for applications like image enhancement, restoration, and encoding/decoding. The document also outlines the formulas for one-dimensional and two-dimensional discrete Fourier transforms and their inverses.
This document discusses optimized implementations of FFT processors for OFDM systems. It describes how FFT and IFFT are important computations for OFDM modulation and demodulation. It proposes an 8-point FFT processor using the radix-2 algorithm and R2MDC architecture. The processor eliminates complex multiplications using shift-and-add operations. It also concludes that the proposed FFT processor designs are suitable for MIMO OFDM standards like IEEE 802.11n and IEEE 802.16 WiMAX.
The document discusses Fast Fourier Transform (FFT) analysis. It begins by explaining what Fourier Transform and Discrete Fourier Transform (DFT) are and how they convert signals from the time domain to the frequency domain. It then states that FFT is an efficient algorithm for performing DFT, allowing it to be done much faster on computers. The document proceeds to describe different types of FFT algorithms like Cooley-Tukey, Prime Factor, Bruun's, and Rader's algorithms. It concludes by discussing characteristics of FFT like approximation, accuracy, and complexity bounds, as well as applications and how FFT can be used to analyze vibration signals in the frequency domain.
DSP_2018_FOEHU - Lec 08 - The Discrete Fourier TransformAmr E. Mohamed
The document provides an overview of the Discrete Fourier Transform (DFT). It begins by discussing limitations of the discrete-time Fourier transform (DTFT) and z-transform in that they are defined for infinite sequences and continuous variables. The DFT avoids these issues by being a numerically computable transform for finite discrete-time signals. It works by taking a finite signal, making it periodic, and computing its discrete Fourier transform which is a discrete frequency spectrum. This makes the DFT highly suitable for digital signal processing. The document then provides details on computation of the DFT and its relationship to the DTFT and z-transform.
Fast Fourier transform is an extension of discrete Fourier transform, It is based on divide and conquer algorithm,it is of two types, decimation in time and decimation in frequency algorithm
Transforms, such as the Fourier transform, make calculations involving signals easier by allowing analysis and computation to be done in either the time or frequency domain. The discrete Fourier transform (DFT) represents a signal as the sum of sinusoids at discrete frequencies. The DFT has several important properties including periodicity, linearity, time shifting, time reversal, and convolution. These properties allow signals to be analyzed and manipulated in the frequency domain.
Transforms, such as the Fourier transform, make calculations involving signals easier by allowing analysis and computation to be done in either the time or frequency domain. The discrete Fourier transform (DFT) transforms a discrete signal from the time domain to the frequency domain. The DFT has several important properties including periodicity, linearity, time shifting, time reversal, and convolution. These properties allow for analysis of signals and simplify computations involving discrete signals and transforms.
DSP_FOEHU - Lec 08 - The Discrete Fourier TransformAmr E. Mohamed
The document discusses the Discrete Fourier Transform (DFT). It explains that while the discrete-time Fourier transform (DTFT) and z-transform are not numerically computable, the DFT avoids this issue. The DFT represents periodic sequences as a sum of complex exponentials with frequencies that are integer multiples of the fundamental frequency. It can be viewed as computing samples of the DTFT or z-transform at discrete frequency points, allowing numerical computation. The DFT provides a link between the time and frequency domain representations of a finite-length sequence.
The document discusses sampling theory and analog-to-digital conversion. It begins by explaining that most real-world signals are analog but must be converted to digital for processing. There are three steps: sampling, quantization, and coding. Sampling converts a continuous-time signal to a discrete-time signal by taking samples at regular intervals. The sampling theorem states that the sampling frequency must be at least twice the highest frequency of the sampled signal to avoid aliasing. Finally, it provides an example showing how to calculate the minimum sampling rate, or Nyquist rate, given the highest frequency of a signal.
DSP_FOEHU - MATLAB 04 - The Discrete Fourier Transform (DFT)Amr E. Mohamed
The document discusses the discrete Fourier transform (DFT) and its implementation in MATLAB. It introduces the DFT as a numerically computable alternative to the discrete-time Fourier transform and z-transform. The DFT decomposes a sequence into its constituent frequency components. MATLAB functions like fft and ifft efficiently compute the DFT and inverse DFT using fast Fourier transform algorithms. Zero-padding a sequence provides more samples of its discrete-time Fourier transform without adding new information. Circular convolution relates to the DFT through its properties. Linear convolution can be computed from the DFT of zero-padded sequences.
This document discusses control systems and Bode diagrams. It includes:
1. An outline of the document with sections on frequency response and an introduction to Bode diagrams.
2. Descriptions of how frequency response is used to analyze systems and determine stability. It also describes how sinusoidal inputs produce harmonic outputs.
3. An introduction to Bode diagrams including how they were developed and that they consist of magnitude and phase plots versus log frequency. Bode diagrams provide a standard way to represent frequency response.
Vector space concepts can be used to represent energy signals. Any set of signals can be represented as linear combinations of orthogonal basis functions in an N-dimensional vector space. Each signal is determined by its vector of coefficients. This geometric representation in vector spaces allows defining properties like vector lengths, angles between vectors, and inner products. It provides a mathematical basis for analyzing signals and noise in communication systems.
The Fast Fourier Transform (FFT) is a collection of techniques that exploits symmetries in the Discrete Fourier Transform (DFT) calculation to significantly reduce the computational complexity from O(N^2) to O(NlogN). It divides the DFT calculation into smaller pieces by splitting the input sequence into even and odd parts, recursively applying this splitting to obtain a reduction in computation time. A graphical representation shows how the direct DFT calculation becomes more efficient using the FFT approach.
1) The document discusses different types of small-scale fading that can occur in radio propagation, including Rayleigh fading and Rician fading.
2) Rayleigh fading results when there is no line-of-sight path between transmitter and receiver. It follows a Rayleigh distribution.
3) Rician fading results when there is a dominant line-of-sight path in addition to other scattered paths. It follows a Rician distribution characterized by a Rician factor K.
Dsp 2018 foehu - lec 10 - multi-rate digital signal processingAmr E. Mohamed
This document discusses multi-rate digital signal processing and concepts related to sampling continuous-time signals. It begins by introducing discrete-time processing of continuous signals using an ideal continuous-to-discrete converter. It then covers the Nyquist sampling theorem and relationships between continuous and discrete Fourier transforms. It discusses ideal and practical reconstruction using zero-order hold and anti-imaging filters. Finally, it introduces the concepts of downsampling and upsampling in multi-rate digital signal processing systems.
Wavelet transform and its applications in data analysis and signal and image ...Sourjya Dutta
This document provides an introduction to wavelet transforms and their applications in data analysis, signal processing, and image processing. It discusses how wavelet transforms overcome limitations of Fourier transforms by using localized basis functions. Applications mentioned include decomposing signals into different frequency components over time and removing noise from data. Examples are provided to illustrate wavelet decomposition and denoising.
This document provides an overview of the contents and structure of a Digital Signal Processing lab manual for an undergraduate course. The manual covers experiments and programs that will be implemented in both software (using MATLAB, LabVIEW, or C programming) and hardware (using DSP boards from TI, Analog Devices, or Motorola). The experiments are intended to help students learn digital signal processing concepts and gain practical skills in implementing DSP algorithms and applications. Some example topics mentioned include discrete time signals and systems, Fourier analysis, FIR and IIR filter design, and speech/image processing. The manual provides a framework for students to complete their DSP lab assignments throughout the semester.
This document summarizes research using discrete wavelet transform (DWT) to characterize transients and diagnose faults in transformers. DWT is used to extract features from transformer current data during normal magnetization and abnormal inter-turn faults. This allows discrimination between the two conditions. Tests were performed on a 2KVA single-phase transformer. Results found DWT can provide information to predict faults in advance to prevent outages and reduce downtime.
Removal of Clutter by Using Wavelet Transform For Wind ProfilerIJMER
ABSTRACT: Removal of clutter in the radar wind profiler
is the utmost important consideration in radar. Wavelet
transform is very effective method to remove the clutter.
This paper presents a technique based on the wavelet
transform to remove the clutter. In this technique we used
Fourier transform and descrete wavelet transform after
that applied inverse discrete wavelet transform for signal.
These techniques applied for inphase and quadrature
phase, total spectrum and single range gate. Very
encouraging results got with this technique that have
shown practical possibilities for a real time
implementation and for applications related to frequency
domain.
Keywords: Wind profiler, wavelet transform, Fourier transform, clutter, signal processing
The document discusses the Fast Fourier Transform (FFT) algorithm.
1) The FFT is a set of techniques that exploits symmetries in the Discrete Fourier Transform (DFT) to make its computation much faster. The speedup increases with larger DFT sizes.
2) The Cooley-Tukey algorithm decomposes an N-point DFT into smaller DFTs by splitting the indices, resulting in an algorithm that is proportional to NlogN operations rather than N^2.
3) The algorithm can be represented as a series of "butterfly" operations, with each butterfly requiring only 2 multiplications. This reduces the number of multiplications needed compared to direct computation of the DFT.
Fast Fourier Transform (FFT) is an algorithm that divides a signal into its frequency components, with each component being a sinusoidal oscillation with its own amplitude and phase. An FFT rapidly computes the Discrete Fourier Transform (DFT) by factorizing the DFT matrix, reducing the complexity from O(n2) to O(n log n). FFT is widely used for applications like filtering, encoding, and solving difference equations. There are two main types of FFT analysis: the discrete Fourier transform, which transforms a sequence into frequencies, and the inverse FFT, which transforms frequencies back into a sequence. FFT analysis is useful for measuring signal frequencies but requires adequate sampling to avoid aliasing lower frequencies as higher ones.
Lec 07 image enhancement in frequency domain iAli Hassan
The document discusses digital image processing and image enhancement in the frequency domain. It provides background on Fourier series and Fourier transforms, explaining that Fourier transforms allow representing even non-periodic functions as integrals of sines and cosines. The Fourier transform converts a signal from the time domain to the frequency domain. Two-dimensional Fourier transforms are used in image processing for applications like image enhancement, restoration, and encoding/decoding. The document also outlines the formulas for one-dimensional and two-dimensional discrete Fourier transforms and their inverses.
This document discusses optimized implementations of FFT processors for OFDM systems. It describes how FFT and IFFT are important computations for OFDM modulation and demodulation. It proposes an 8-point FFT processor using the radix-2 algorithm and R2MDC architecture. The processor eliminates complex multiplications using shift-and-add operations. It also concludes that the proposed FFT processor designs are suitable for MIMO OFDM standards like IEEE 802.11n and IEEE 802.16 WiMAX.
The document discusses Fast Fourier Transform (FFT) analysis. It begins by explaining what Fourier Transform and Discrete Fourier Transform (DFT) are and how they convert signals from the time domain to the frequency domain. It then states that FFT is an efficient algorithm for performing DFT, allowing it to be done much faster on computers. The document proceeds to describe different types of FFT algorithms like Cooley-Tukey, Prime Factor, Bruun's, and Rader's algorithms. It concludes by discussing characteristics of FFT like approximation, accuracy, and complexity bounds, as well as applications and how FFT can be used to analyze vibration signals in the frequency domain.
DSP_2018_FOEHU - Lec 08 - The Discrete Fourier TransformAmr E. Mohamed
The document provides an overview of the Discrete Fourier Transform (DFT). It begins by discussing limitations of the discrete-time Fourier transform (DTFT) and z-transform in that they are defined for infinite sequences and continuous variables. The DFT avoids these issues by being a numerically computable transform for finite discrete-time signals. It works by taking a finite signal, making it periodic, and computing its discrete Fourier transform which is a discrete frequency spectrum. This makes the DFT highly suitable for digital signal processing. The document then provides details on computation of the DFT and its relationship to the DTFT and z-transform.
Fast Fourier transform is an extension of discrete Fourier transform, It is based on divide and conquer algorithm,it is of two types, decimation in time and decimation in frequency algorithm
Transforms, such as the Fourier transform, make calculations involving signals easier by allowing analysis and computation to be done in either the time or frequency domain. The discrete Fourier transform (DFT) represents a signal as the sum of sinusoids at discrete frequencies. The DFT has several important properties including periodicity, linearity, time shifting, time reversal, and convolution. These properties allow signals to be analyzed and manipulated in the frequency domain.
Transforms, such as the Fourier transform, make calculations involving signals easier by allowing analysis and computation to be done in either the time or frequency domain. The discrete Fourier transform (DFT) transforms a discrete signal from the time domain to the frequency domain. The DFT has several important properties including periodicity, linearity, time shifting, time reversal, and convolution. These properties allow for analysis of signals and simplify computations involving discrete signals and transforms.
DSP_FOEHU - Lec 08 - The Discrete Fourier TransformAmr E. Mohamed
The document discusses the Discrete Fourier Transform (DFT). It explains that while the discrete-time Fourier transform (DTFT) and z-transform are not numerically computable, the DFT avoids this issue. The DFT represents periodic sequences as a sum of complex exponentials with frequencies that are integer multiples of the fundamental frequency. It can be viewed as computing samples of the DTFT or z-transform at discrete frequency points, allowing numerical computation. The DFT provides a link between the time and frequency domain representations of a finite-length sequence.
The document discusses sampling theory and analog-to-digital conversion. It begins by explaining that most real-world signals are analog but must be converted to digital for processing. There are three steps: sampling, quantization, and coding. Sampling converts a continuous-time signal to a discrete-time signal by taking samples at regular intervals. The sampling theorem states that the sampling frequency must be at least twice the highest frequency of the sampled signal to avoid aliasing. Finally, it provides an example showing how to calculate the minimum sampling rate, or Nyquist rate, given the highest frequency of a signal.
DSP_FOEHU - MATLAB 04 - The Discrete Fourier Transform (DFT)Amr E. Mohamed
The document discusses the discrete Fourier transform (DFT) and its implementation in MATLAB. It introduces the DFT as a numerically computable alternative to the discrete-time Fourier transform and z-transform. The DFT decomposes a sequence into its constituent frequency components. MATLAB functions like fft and ifft efficiently compute the DFT and inverse DFT using fast Fourier transform algorithms. Zero-padding a sequence provides more samples of its discrete-time Fourier transform without adding new information. Circular convolution relates to the DFT through its properties. Linear convolution can be computed from the DFT of zero-padded sequences.
This document discusses control systems and Bode diagrams. It includes:
1. An outline of the document with sections on frequency response and an introduction to Bode diagrams.
2. Descriptions of how frequency response is used to analyze systems and determine stability. It also describes how sinusoidal inputs produce harmonic outputs.
3. An introduction to Bode diagrams including how they were developed and that they consist of magnitude and phase plots versus log frequency. Bode diagrams provide a standard way to represent frequency response.
Vector space concepts can be used to represent energy signals. Any set of signals can be represented as linear combinations of orthogonal basis functions in an N-dimensional vector space. Each signal is determined by its vector of coefficients. This geometric representation in vector spaces allows defining properties like vector lengths, angles between vectors, and inner products. It provides a mathematical basis for analyzing signals and noise in communication systems.
The Fast Fourier Transform (FFT) is a collection of techniques that exploits symmetries in the Discrete Fourier Transform (DFT) calculation to significantly reduce the computational complexity from O(N^2) to O(NlogN). It divides the DFT calculation into smaller pieces by splitting the input sequence into even and odd parts, recursively applying this splitting to obtain a reduction in computation time. A graphical representation shows how the direct DFT calculation becomes more efficient using the FFT approach.
1) The document discusses different types of small-scale fading that can occur in radio propagation, including Rayleigh fading and Rician fading.
2) Rayleigh fading results when there is no line-of-sight path between transmitter and receiver. It follows a Rayleigh distribution.
3) Rician fading results when there is a dominant line-of-sight path in addition to other scattered paths. It follows a Rician distribution characterized by a Rician factor K.
Dsp 2018 foehu - lec 10 - multi-rate digital signal processingAmr E. Mohamed
This document discusses multi-rate digital signal processing and concepts related to sampling continuous-time signals. It begins by introducing discrete-time processing of continuous signals using an ideal continuous-to-discrete converter. It then covers the Nyquist sampling theorem and relationships between continuous and discrete Fourier transforms. It discusses ideal and practical reconstruction using zero-order hold and anti-imaging filters. Finally, it introduces the concepts of downsampling and upsampling in multi-rate digital signal processing systems.
Wavelet transform and its applications in data analysis and signal and image ...Sourjya Dutta
This document provides an introduction to wavelet transforms and their applications in data analysis, signal processing, and image processing. It discusses how wavelet transforms overcome limitations of Fourier transforms by using localized basis functions. Applications mentioned include decomposing signals into different frequency components over time and removing noise from data. Examples are provided to illustrate wavelet decomposition and denoising.
This document provides an overview of the contents and structure of a Digital Signal Processing lab manual for an undergraduate course. The manual covers experiments and programs that will be implemented in both software (using MATLAB, LabVIEW, or C programming) and hardware (using DSP boards from TI, Analog Devices, or Motorola). The experiments are intended to help students learn digital signal processing concepts and gain practical skills in implementing DSP algorithms and applications. Some example topics mentioned include discrete time signals and systems, Fourier analysis, FIR and IIR filter design, and speech/image processing. The manual provides a framework for students to complete their DSP lab assignments throughout the semester.
This document summarizes research using discrete wavelet transform (DWT) to characterize transients and diagnose faults in transformers. DWT is used to extract features from transformer current data during normal magnetization and abnormal inter-turn faults. This allows discrimination between the two conditions. Tests were performed on a 2KVA single-phase transformer. Results found DWT can provide information to predict faults in advance to prevent outages and reduce downtime.
Removal of Clutter by Using Wavelet Transform For Wind ProfilerIJMER
ABSTRACT: Removal of clutter in the radar wind profiler
is the utmost important consideration in radar. Wavelet
transform is very effective method to remove the clutter.
This paper presents a technique based on the wavelet
transform to remove the clutter. In this technique we used
Fourier transform and descrete wavelet transform after
that applied inverse discrete wavelet transform for signal.
These techniques applied for inphase and quadrature
phase, total spectrum and single range gate. Very
encouraging results got with this technique that have
shown practical possibilities for a real time
implementation and for applications related to frequency
domain.
Keywords: Wind profiler, wavelet transform, Fourier transform, clutter, signal processing
Inverter fed Induction motor drives are deployed across a variety of industrial and commercial applications. Although the drives in the question are well known for their reliable operation in any type of environment, it becomes an important daunting critical task to have them in continuous operation as per the applications’ requirement. Identifying the faulty behavior of power electronic circuits which could lead to catastrophic failures is an attractive proposition. The cost associated with building systems devoted for monitoring and diagnosis is high, however such cost could be justified for the safety-critical systems. Commonly practiced methods for improving the reliability of the power electronic systems are: designing the power circuit conservatively or having parallel redundant operation of components or circuits and clearly these two methods are expensive. An alternative to redundancy is fault tolerant control, which involves drive control algorithm, that in the event of fault occurrence, allows the drive to run in a degraded mode. Such algorithms involve on-line processing of the signals and this requires Digital Signal Processing of the signals. This paper presents the FFT and Wavelet transform techniques for on-line monitoring and analyzing the signals such as stator currents.
The document discusses using Haar wavelets to solve optimal control problems numerically. It begins by explaining the limitations of indirect methods for solving optimal control problems and advantages of direct methods. It then provides background on wavelet theory, describing different types of wavelets and their properties. Haar wavelets are discussed as being useful for solving variational problems by reducing differential equations to algebraic equations. The document concludes that the Haar wavelet approach provides an effective numerical method for solving variational and optimal control problems compared to other existing techniques.
A Study of Ball Bearing’s Crack Using Acoustic Signal / Vibration Signal and ...INFOGAIN PUBLICATION
The field of fault diagnostic in rotating machinery is vast, including the diagnosis of items such as rotating shafts, rolling element bearings, couplings, gears and so on. Vibration analysis is the main condition monitoring technique for machinery maintenance. The different types of faults that are observed in these areas and the methods of their diagnosis are accordingly great, including vibration analysis, model-based techniques, and statistical analysis and artificial intelligence techniques. However, they have difficulties with certain applications whose behavior is non-stationary and transient nature.
A Study of Ball Bearing’s Crack Using Acoustic Signal / Vibration Signal and ...INFOGAIN PUBLICATION
The field of fault diagnostic in rotating machinery is vast, including the diagnosis of items such as rotating shafts, rolling element bearings, couplings, gears and so on. Vibration analysis is the main condition monitoring technique for machinery maintenance. The different types of faults that are observed in these areas and the methods of their diagnosis are accordingly great, including vibration analysis, model-based techniques, and statistical analysis and artificial intelligence techniques. However, they have difficulties with certain applications whose behavior is non-stationary and transient nature.
A Study of Ball Bearing’s Crack Using Acoustic Signal / Vibration Signal and ...INFOGAIN PUBLICATION
The field of fault diagnostic in rotating machinery is vast, including the diagnosis of items such as rotating shafts, rolling element bearings, couplings, gears and so on. Vibration analysis is the main condition monitoring technique for machinery maintenance. The different types of faults that are observed in these areas and the methods of their diagnosis are accordingly great, including vibration analysis, model-based techniques, and statistical analysis and artificial intelligence techniques. However, they have difficulties with certain applications whose behavior is non-stationary and transient nature.
Comparative Analysis of Natural Frequency of Transverse Vibration of a Cantil...IRJET Journal
This document presents a comparative analysis of the natural frequency of transverse vibration of a cantilever beam using analytical and experimental methods. Analytical calculations are performed to determine the natural frequencies of the first three modes of vibration of the cantilever beam. Experimental testing is conducted using an impact hammer, accelerometer, and FFT analyzer. The natural frequencies measured experimentally are found to be close to those calculated analytically. The results demonstrate that analytical and experimental methods can both accurately determine the natural frequencies of a cantilever beam's vibration.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Characterization of transients and fault diagnosis in transformer by discreteIAEME Publication
This document discusses using discrete wavelet transform (DWT) and artificial neural networks (ANN) to characterize transients and diagnose faults in transformers. It begins with an introduction to the problem and background on using the second harmonic component for discrimination. It then discusses why time-frequency information is needed and the advantages of wavelet transforms over Fourier transforms. The document describes collecting data from a test transformer under normal and faulted conditions. It explains using DWT for feature extraction and visualizing the wavelet decomposition levels to characterize magnetizing inrush versus inter-turn faults. Finally, it proposes using ANN trained on the wavelet spectral energies for automated discrimination between fault cases.
Application of Hilbert-Huang Transform in the Field of Power Quality Events A...idescitation
This paper discusses using the Hilbert-Huang Transform (HHT) to analyze power quality events. HHT can be applied to non-stationary and non-linear signals. It decomposes signals into Intrinsic Mode Functions (IMFs) using Empirical Mode Decomposition and then applies the Hilbert Transform to obtain the time-frequency-energy representation. The paper applies HHT to voltage sag, swell, and harmonics with sag signals. It shows the IMFs, instantaneous frequency, amplitude, and phase obtained from HHT have potential to better analyze power quality events compared to other time-frequency methods.
A Survey on Classification of Power Quality Disturbances in a Power SystemIJERA Editor
This document provides a survey of techniques for classifying power quality disturbances in a power system. It discusses various power quality issues and types of disturbances such as transients, interruptions, sags, swells, waveform distortions, and frequency variations. It then describes several signal processing techniques used for feature extraction, including Fourier transform, short-time Fourier transform, S-transform, Hilbert-Huang transform, Kalman filter, and wavelet transform. Finally, it reviews various classification methods such as artificial neural networks, fuzzy expert systems, adaptive neuro-fuzzy systems, genetic algorithms, and support vector machines that have been applied to classify power quality disturbances.
This document discusses using wavelet transforms to analyze vibration signals from bearings for condition monitoring. It describes performing discrete wavelet transforms and wavelet packet transforms on bearing vibration data to extract statistical features like wavelet energy, entropy, and FFT magnitudes. These features are then used as inputs to an artificial neural network to classify signals as normal or faulty. The results show wavelet-based vibration monitoring can successfully detect and classify bearing faults.
Fourier analysis techniques Fourier transforms- part 2Jawad Khan
contains solved problems on fourier series applications in electrical circuits and derivation of fourier transform equations with its properties, description and usage
The document discusses discrete Fourier series, discrete Fourier transform, and discrete time Fourier transform. It provides definitions and explanations of each topic. Discrete Fourier series represents periodic discrete-time signals using a summation of sines and cosines. The discrete Fourier transform analyzes a finite-duration discrete signal by treating it as an excerpt from an infinite periodic signal. The discrete time Fourier transform provides a frequency-domain representation of discrete-time signals and is useful for analyzing samples of continuous functions. Examples of applications are also given such as signal processing, image analysis, and wireless communications.
Design of Low Power Reconfigurable IIR filter with Row Bypassing MultiplierIRJET Journal
This document describes the design of low power reconfigurable IIR filters using row bypassing multipliers. It proposes two new designs for Hilbert transformers based on carry save adder (CSA) and ripple carry adder (RCA) row bypassing multipliers. The CSA design achieves 17% higher speed and 13% less area than the RCA design. Both designs allow dynamic reconfiguration of filter coefficients and reduce power consumption by turning off adders when multiplier operands are zero. The designs are implemented on FPGA to evaluate performance in terms of area, speed and power usage.
Implementation Of Grigoryan FFT For Its Performance Case Study Over Cooley-Tu...ijma
This document discusses the implementation and performance comparison of two fast Fourier transform (FFT) algorithms - the Cooley-Tukey FFT and the Grigoryan FFT - on three Xilinx FPGAs. The Grigoryan FFT uses a decomposition based on paired transforms, while the Cooley-Tukey FFT uses a radix-2 decomposition. Both algorithms were implemented on Virtex-II Pro, Virtex-5, and Virtex-4 FPGAs. The results showed that the Grigoryan FFT operated at higher sampling rates and was faster than the Cooley-Tukey FFT. Additionally, the Virtex-5 FPGA provided the highest speed for implementing the Grigoryan FFT compared
Similar to IRJET- A Brief Study on Fourier Transform and its Applications (20)
TUNNELING IN HIMALAYAS WITH NATM METHOD: A SPECIAL REFERENCES TO SUNGAL TUNNE...IRJET Journal
1) The document discusses the Sungal Tunnel project in Jammu and Kashmir, India, which is being constructed using the New Austrian Tunneling Method (NATM).
2) NATM involves continuous monitoring during construction to adapt to changing ground conditions, and makes extensive use of shotcrete for temporary tunnel support.
3) The methodology section outlines the systematic geotechnical design process for tunnels according to Austrian guidelines, and describes the various steps of NATM tunnel construction including initial and secondary tunnel support.
STUDY THE EFFECT OF RESPONSE REDUCTION FACTOR ON RC FRAMED STRUCTUREIRJET Journal
This study examines the effect of response reduction factors (R factors) on reinforced concrete (RC) framed structures through nonlinear dynamic analysis. Three RC frame models with varying heights (4, 8, and 12 stories) were analyzed in ETABS software under different R factors ranging from 1 to 5. The results showed that displacement increased as the R factor decreased, indicating less linear behavior for lower R factors. Drift also decreased proportionally with increasing R factors from 1 to 5. Shear forces in the frames decreased with higher R factors. In general, R factors of 3 to 5 produced more satisfactory performance with less displacement and drift. The displacement variations between different building heights were consistent at different R factors. This study evaluated how R factors influence
A COMPARATIVE ANALYSIS OF RCC ELEMENT OF SLAB WITH STARK STEEL (HYSD STEEL) A...IRJET Journal
This study compares the use of Stark Steel and TMT Steel as reinforcement materials in a two-way reinforced concrete slab. Mechanical testing is conducted to determine the tensile strength, yield strength, and other properties of each material. A two-way slab design adhering to codes and standards is executed with both materials. The performance is analyzed in terms of deflection, stability under loads, and displacement. Cost analyses accounting for material, durability, maintenance, and life cycle costs are also conducted. The findings provide insights into the economic and structural implications of each material for reinforcement selection and recommendations on the most suitable material based on the analysis.
Effect of Camber and Angles of Attack on Airfoil CharacteristicsIRJET Journal
This document discusses a study analyzing the effect of camber, position of camber, and angle of attack on the aerodynamic characteristics of airfoils. Sixteen modified asymmetric NACA airfoils were analyzed using computational fluid dynamics (CFD) by varying the camber, camber position, and angle of attack. The results showed the relationship between these parameters and the lift coefficient, drag coefficient, and lift to drag ratio. This provides insight into how changes in airfoil geometry impact aerodynamic performance.
A Review on the Progress and Challenges of Aluminum-Based Metal Matrix Compos...IRJET Journal
This document reviews the progress and challenges of aluminum-based metal matrix composites (MMCs), focusing on their fabrication processes and applications. It discusses how various aluminum MMCs have been developed using reinforcements like borides, carbides, oxides, and nitrides to improve mechanical and wear properties. These composites have gained prominence for their lightweight, high-strength and corrosion resistance properties. The document also examines recent advancements in fabrication techniques for aluminum MMCs and their growing applications in industries such as aerospace and automotive. However, it notes that challenges remain around issues like improper mixing of reinforcements and reducing reinforcement agglomeration.
Dynamic Urban Transit Optimization: A Graph Neural Network Approach for Real-...IRJET Journal
This document discusses research on using graph neural networks (GNNs) for dynamic optimization of public transportation networks in real-time. GNNs represent transit networks as graphs with nodes as stops and edges as connections. The GNN model aims to optimize networks using real-time data on vehicle locations, arrival times, and passenger loads. This helps increase mobility, decrease traffic, and improve efficiency. The system continuously trains and infers to adapt to changing transit conditions, providing decision support tools. While research has focused on performance, more work is needed on security, socio-economic impacts, contextual generalization of models, continuous learning approaches, and effective real-time visualization.
Structural Analysis and Design of Multi-Storey Symmetric and Asymmetric Shape...IRJET Journal
This document summarizes a research project that aims to compare the structural performance of conventional slab and grid slab systems in multi-story buildings using ETABS software. The study will analyze both symmetric and asymmetric building models under various loading conditions. Parameters like deflections, moments, shears, and stresses will be examined to evaluate the structural effectiveness of each slab type. The results will provide insights into the comparative behavior of conventional and grid slabs to help engineers and architects select appropriate slab systems based on building layouts and design requirements.
A Review of “Seismic Response of RC Structures Having Plan and Vertical Irreg...IRJET Journal
This document summarizes and reviews a research paper on the seismic response of reinforced concrete (RC) structures with plan and vertical irregularities, with and without infill walls. It discusses how infill walls can improve or reduce the seismic performance of RC buildings, depending on factors like wall layout, height distribution, connection to the frame, and relative stiffness of walls and frames. The reviewed research paper analyzes the behavior of infill walls, effects of vertical irregularities, and seismic performance of high-rise structures under linear static and dynamic analysis. It studies response characteristics like story drift, deflection and shear. The document also provides literature on similar research investigating the effects of infill walls, soft stories, plan irregularities, and different
This document provides a review of machine learning techniques used in Advanced Driver Assistance Systems (ADAS). It begins with an abstract that summarizes key applications of machine learning in ADAS, including object detection, recognition, and decision-making. The introduction discusses the integration of machine learning in ADAS and how it is transforming vehicle safety. The literature review then examines several research papers on topics like lightweight deep learning models for object detection and lane detection models using image processing. It concludes by discussing challenges and opportunities in the field, such as improving algorithm robustness and adaptability.
Long Term Trend Analysis of Precipitation and Temperature for Asosa district,...IRJET Journal
The document analyzes temperature and precipitation trends in Asosa District, Benishangul Gumuz Region, Ethiopia from 1993 to 2022 based on data from the local meteorological station. The results show:
1) The average maximum and minimum annual temperatures have generally decreased over time, with maximum temperatures decreasing by a factor of -0.0341 and minimum by -0.0152.
2) Mann-Kendall tests found the decreasing temperature trends to be statistically significant for annual maximum temperatures but not for annual minimum temperatures.
3) Annual precipitation in Asosa District showed a statistically significant increasing trend.
The conclusions recommend development planners account for rising summer precipitation and declining temperatures in
P.E.B. Framed Structure Design and Analysis Using STAAD ProIRJET Journal
This document discusses the design and analysis of pre-engineered building (PEB) framed structures using STAAD Pro software. It provides an overview of PEBs, including that they are designed off-site with building trusses and beams produced in a factory. STAAD Pro is identified as a key tool for modeling, analyzing, and designing PEBs to ensure their performance and safety under various load scenarios. The document outlines modeling structural parts in STAAD Pro, evaluating structural reactions, assigning loads, and following international design codes and standards. In summary, STAAD Pro is used to design and analyze PEB framed structures to ensure safety and code compliance.
A Review on Innovative Fiber Integration for Enhanced Reinforcement of Concre...IRJET Journal
This document provides a review of research on innovative fiber integration methods for reinforcing concrete structures. It discusses studies that have explored using carbon fiber reinforced polymer (CFRP) composites with recycled plastic aggregates to develop more sustainable strengthening techniques. It also examines using ultra-high performance fiber reinforced concrete to improve shear strength in beams. Additional topics covered include the dynamic responses of FRP-strengthened beams under static and impact loads, and the performance of preloaded CFRP-strengthened fiber reinforced concrete beams. The review highlights the potential of fiber composites to enable more sustainable and resilient construction practices.
Survey Paper on Cloud-Based Secured Healthcare SystemIRJET Journal
This document summarizes a survey on securing patient healthcare data in cloud-based systems. It discusses using technologies like facial recognition, smart cards, and cloud computing combined with strong encryption to securely store patient data. The survey found that healthcare professionals believe digitizing patient records and storing them in a centralized cloud system would improve access during emergencies and enable more efficient care compared to paper-based systems. However, ensuring privacy and security of patient data is paramount as healthcare incorporates these digital technologies.
Review on studies and research on widening of existing concrete bridgesIRJET Journal
This document summarizes several studies that have been conducted on widening existing concrete bridges. It describes a study from China that examined load distribution factors for a bridge widened with composite steel-concrete girders. It also outlines challenges and solutions for widening a bridge in the UAE, including replacing bearings and stitching the new and existing structures. Additionally, it discusses two bridge widening projects in New Zealand that involved adding precast beams and stitching to connect structures. Finally, safety measures and challenges for strengthening a historic bridge in Switzerland under live traffic are presented.
React based fullstack edtech web applicationIRJET Journal
The document describes the architecture of an educational technology web application built using the MERN stack. It discusses the frontend developed with ReactJS, backend with NodeJS and ExpressJS, and MongoDB database. The frontend provides dynamic user interfaces, while the backend offers APIs for authentication, course management, and other functions. MongoDB enables flexible data storage. The architecture aims to provide a scalable, responsive platform for online learning.
A Comprehensive Review of Integrating IoT and Blockchain Technologies in the ...IRJET Journal
This paper proposes integrating Internet of Things (IoT) and blockchain technologies to help implement objectives of India's National Education Policy (NEP) in the education sector. The paper discusses how blockchain could be used for secure student data management, credential verification, and decentralized learning platforms. IoT devices could create smart classrooms, automate attendance tracking, and enable real-time monitoring. Blockchain would ensure integrity of exam processes and resource allocation, while smart contracts automate agreements. The paper argues this integration has potential to revolutionize education by making it more secure, transparent and efficient, in alignment with NEP goals. However, challenges like infrastructure needs, data privacy, and collaborative efforts are also discussed.
A REVIEW ON THE PERFORMANCE OF COCONUT FIBRE REINFORCED CONCRETE.IRJET Journal
This document provides a review of research on the performance of coconut fibre reinforced concrete. It summarizes several studies that tested different volume fractions and lengths of coconut fibres in concrete mixtures with varying compressive strengths. The studies found that coconut fibre improved properties like tensile strength, toughness, crack resistance, and spalling resistance compared to plain concrete. Volume fractions of 2-5% and fibre lengths of 20-50mm produced the best results. The document concludes that using a 4-5% volume fraction of coconut fibres 30-40mm in length with M30-M60 grade concrete would provide benefits based on previous research.
Optimizing Business Management Process Workflows: The Dynamic Influence of Mi...IRJET Journal
The document discusses optimizing business management processes through automation using Microsoft Power Automate and artificial intelligence. It provides an overview of Power Automate's key components and features for automating workflows across various apps and services. The document then presents several scenarios applying automation solutions to common business processes like data entry, monitoring, HR, finance, customer support, and more. It estimates the potential time and cost savings from implementing automation for each scenario. Finally, the conclusion emphasizes the transformative impact of AI and automation tools on business processes and the need for ongoing optimization.
Multistoried and Multi Bay Steel Building Frame by using Seismic DesignIRJET Journal
The document describes the seismic design of a G+5 steel building frame located in Roorkee, India according to Indian codes IS 1893-2002 and IS 800. The frame was analyzed using the equivalent static load method and response spectrum method, and its response in terms of displacements and shear forces were compared. Based on the analysis, the frame was designed as a seismic-resistant steel structure according to IS 800:2007. The software STAAD Pro was used for the analysis and design.
Cost Optimization of Construction Using Plastic Waste as a Sustainable Constr...IRJET Journal
This research paper explores using plastic waste as a sustainable and cost-effective construction material. The study focuses on manufacturing pavers and bricks using recycled plastic and partially replacing concrete with plastic alternatives. Initial results found that pavers and bricks made from recycled plastic demonstrate comparable strength and durability to traditional materials while providing environmental and cost benefits. Additionally, preliminary research indicates incorporating plastic waste as a partial concrete replacement significantly reduces construction costs without compromising structural integrity. The outcomes suggest adopting plastic waste in construction can address plastic pollution while optimizing costs, promoting more sustainable building practices.
Introduction- e - waste – definition - sources of e-waste– hazardous substances in e-waste - effects of e-waste on environment and human health- need for e-waste management– e-waste handling rules - waste minimization techniques for managing e-waste – recycling of e-waste - disposal treatment methods of e- waste – mechanism of extraction of precious metal from leaching solution-global Scenario of E-waste – E-waste in India- case studies.
Comparative analysis between traditional aquaponics and reconstructed aquapon...bijceesjournal
The aquaponic system of planting is a method that does not require soil usage. It is a method that only needs water, fish, lava rocks (a substitute for soil), and plants. Aquaponic systems are sustainable and environmentally friendly. Its use not only helps to plant in small spaces but also helps reduce artificial chemical use and minimizes excess water use, as aquaponics consumes 90% less water than soil-based gardening. The study applied a descriptive and experimental design to assess and compare conventional and reconstructed aquaponic methods for reproducing tomatoes. The researchers created an observation checklist to determine the significant factors of the study. The study aims to determine the significant difference between traditional aquaponics and reconstructed aquaponics systems propagating tomatoes in terms of height, weight, girth, and number of fruits. The reconstructed aquaponics system’s higher growth yield results in a much more nourished crop than the traditional aquaponics system. It is superior in its number of fruits, height, weight, and girth measurement. Moreover, the reconstructed aquaponics system is proven to eliminate all the hindrances present in the traditional aquaponics system, which are overcrowding of fish, algae growth, pest problems, contaminated water, and dead fish.
Use PyCharm for remote debugging of WSL on a Windo cf5c162d672e4e58b4dde5d797...shadow0702a
This document serves as a comprehensive step-by-step guide on how to effectively use PyCharm for remote debugging of the Windows Subsystem for Linux (WSL) on a local Windows machine. It meticulously outlines several critical steps in the process, starting with the crucial task of enabling permissions, followed by the installation and configuration of WSL.
The guide then proceeds to explain how to set up the SSH service within the WSL environment, an integral part of the process. Alongside this, it also provides detailed instructions on how to modify the inbound rules of the Windows firewall to facilitate the process, ensuring that there are no connectivity issues that could potentially hinder the debugging process.
The document further emphasizes on the importance of checking the connection between the Windows and WSL environments, providing instructions on how to ensure that the connection is optimal and ready for remote debugging.
It also offers an in-depth guide on how to configure the WSL interpreter and files within the PyCharm environment. This is essential for ensuring that the debugging process is set up correctly and that the program can be run effectively within the WSL terminal.
Additionally, the document provides guidance on how to set up breakpoints for debugging, a fundamental aspect of the debugging process which allows the developer to stop the execution of their code at certain points and inspect their program at those stages.
Finally, the document concludes by providing a link to a reference blog. This blog offers additional information and guidance on configuring the remote Python interpreter in PyCharm, providing the reader with a well-rounded understanding of the process.
Understanding Inductive Bias in Machine LearningSUTEJAS
This presentation explores the concept of inductive bias in machine learning. It explains how algorithms come with built-in assumptions and preferences that guide the learning process. You'll learn about the different types of inductive bias and how they can impact the performance and generalizability of machine learning models.
The presentation also covers the positive and negative aspects of inductive bias, along with strategies for mitigating potential drawbacks. We'll explore examples of how bias manifests in algorithms like neural networks and decision trees.
By understanding inductive bias, you can gain valuable insights into how machine learning models work and make informed decisions when building and deploying them.
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODELgerogepatton
As digital technology becomes more deeply embedded in power systems, protecting the communication
networks of Smart Grids (SG) has emerged as a critical concern. Distributed Network Protocol 3 (DNP3)
represents a multi-tiered application layer protocol extensively utilized in Supervisory Control and Data
Acquisition (SCADA)-based smart grids to facilitate real-time data gathering and control functionalities.
Robust Intrusion Detection Systems (IDS) are necessary for early threat detection and mitigation because
of the interconnection of these networks, which makes them vulnerable to a variety of cyberattacks. To
solve this issue, this paper develops a hybrid Deep Learning (DL) model specifically designed for intrusion
detection in smart grids. The proposed approach is a combination of the Convolutional Neural Network
(CNN) and the Long-Short-Term Memory algorithms (LSTM). We employed a recent intrusion detection
dataset (DNP3), which focuses on unauthorized commands and Denial of Service (DoS) cyberattacks, to
train and test our model. The results of our experiments show that our CNN-LSTM method is much better
at finding smart grid intrusions than other deep learning algorithms used for classification. In addition,
our proposed approach improves accuracy, precision, recall, and F1 score, achieving a high detection
accuracy rate of 99.50%.