An Artificial Neural Network Developed in MATLAB-Simulink for Reconstruction a Distorted Secondary Current Waveform. Part 1

Recently, there has been an increased interest in the use of artificial neural networks in various branches of the electric power industry including relay protection. Аrtificial neural networks are one of the fastest growing areas in artificial intelligence technology. Recently, there has been an increased interest in the use of аrtificial neural networks in the electric power engineering, including relay protection. Existing microprocessor-based relay protection devices use a traditional digital signal processing of the monitored signals which is reduced to a multiplying the values of successive samples of the monitored current and voltage signals by predetermined coefficients in order to calculate their RMS values. In this case, the calculated RMS values often do not reflect the real processes occurring in the protected electrical equipment due to, for example, current transformer saturation because of the DC component presence in the fault current. When the current transformer is saturated, its secondary current waveform has a characteristic non-periodic distorted form, which is significantly differs from its primary (true) waveform, which causes underestimation of the calculated RMS value of the secondary current compared to its true value. In its turn, this causes to a trip time delay or even to a relay protection devices operation failure. The use of аrtificial neural networks in conjunction with a traditional digital signal processing provides a different approach to the functioning of both the measuring and logical parts of the microprocessor-based relay protection devices, which significantly increases the speed and reliability of such relay protection devices in comparison with their traditional implementation. A possible application of the аrtificial neural networks for the relay protection purposes is the fault occurrence detection and its type identification, current transformer secondary current waveform distortion restoration due to its saturation up to its true value, detection the distorted and undistorted sections of the current transformer secondary current waveform during its saturation, primary power equipment abnormal operating modes detection, for example, power transformer magnetizing current inrush. The article describes in detail the stages of the practical implementation of the аrtificial neural networks in the MATLAB-Simulink environment by the example of its use to restore the distorted current transformer secondary current waveform due to saturation.

Research on the Design of Digital Signal Processing Algorithm Based on Spark Parallel Calculation

Digital signal processing as a key and difficult point of network technology research and development, currently commonly used content such as LabVIEW. But from a practical point of view, while these techniques can be used to process real-time signals, they can’t handle historical offline data. The Spark parallel computing studied in this paper can be used to process offline signals. Therefore, on the basis of understanding the development trend of Spark parallel computing framework, the distributed Mallat algorithm is analyzed based on Spark parallel computing engine, and the application performance of the corresponding algorithm is verified.

Review Paper on Innovation of Advanced Noise Reduction Technique for Better Audibility Process

Now a days there are many people affected by hearing loss that make them disabled as they cannot communicate properly .The main complaint of people with hearing loss is low ability to deduce speech in a noisy environment. Hearing aid is a delicate instrument, which can acquire, process and feedback realistic signal in real time. In this matter various apparent opposition matching algorithm, various filtering methods, digital signal processing algorithm and echo cancellation are developed and implemented. The purpose of this object is to develop the digital signal processing based platform for digital hearing aid technique, which is for the people with hearing impairment using the low cost fuzzy orange pi model. To Perform this Application fuzzy algorithm is used which is quite easy to implement and required less operative computation. The algorithms are performed using MATLAB language which gives the best clarity and simulated functionality over MATLAB. Keywords: Speech Recognition, Noise Reduction, SNR, Fuzzy Masking Technique

Virtual Experimental Project Design in the Digital Signal Processing Course

This paper proposes the design and development of virtual experimental projects in the Digital Signal Processing course, using MATLAB, Proteus, and CCS platforms to develop a library of typical experimental cases for biomedical engineering majors and discusses the design process. Based on these typical cases, this paper explores the secondary design for innovative engineering practice case teaching, which can promote students’ understanding and mastery of digital signal processing theories, algorithms, and technologies in an intuitive, flexible, and efficient way; quickly build new innovative engineering case models and further cultivate students’ engineering application ability as well as innovative thinking.