scholarly journals Improving the Performance of Distance Relay Using Wavelet Transform

2021 ◽  
Vol 15 (4) ◽  
pp. 483-490
Author(s):  
Zeynab Mohabati ◽  
Maryam Khoddam
Keyword(s):  
Wavelet Transform ◽  
Transmission Lines ◽  
Power Grids ◽  
Digital Signals ◽  
Decision Tree Classifier ◽  
System Availability ◽  
Transmission Grid ◽  
System Protection ◽  
Economic Exploitation ◽  
Tree Classifier

With proliferation of power grids, different types of faults are more likely to occur. The purpose of system protection relays is to detect abnormal signals that indicate faults in the transmission system and to separate the fault section from the rest of the system to prevent the fault from propagating to other parts of the system. Proliferation of electronic devices led to creation of digital relays made of microprocessors. Hence, analog measurements are converted into digital signals for processing by microprocessors. Air grids are more likely to cause faults than other components of the power system; thus, disturbances affecting the system must be detected quickly and accurately. Therefore, the problem of fault detection and classification is an important factor for economic exploitation of the power grid. Accurate fault handling results in faster repair operations, better system availability, lower operating costs and timesavings. The proposed design in this study was based on detecting the type of fault caused in transmission lines. In order to improve the condition of the relays in the transmission grid, analysis of the signals reached to the relay on both sides of the line was used to detect the fault and its type. The main purpose was to quickly detect the type of fault using wavelet transform. For this purpose, the signal was sampled after the fault occurs and the feature signal was extracted after analysis by wavelet transform. These features were included in the decision tree classifier and the type of the fault was decided.

scholarly journals Distance Protection of Series Capacitor Compensated Lines: Practical Considerations, Industrial Status and Development

Electricity ◽  
2021 ◽  
Vol 2 (2) ◽  
pp. 168-186
Author(s):  
Md Tanbhir Hoq ◽  
Nathaniel Taylor
Keyword(s):  
Transmission Lines ◽  
Transmission Network ◽  
Distance Protection ◽  
Academic Literature ◽  
System Protection ◽  
The Status ◽  
In Series ◽  
Insight Into ◽  
Series Capacitor ◽  
Current Inversion

The introduction of series capacitors in transmission lines causes problems in terms of reliability and the security of distance protection relays. As distance protection is widely used in the transmission network, the challenge of applying it to series compensated lines has been taken up by utilities and relay manufacturers in various ways. In the field of power system protection, developments are largely driven by relay manufacturers, and are often not published in the academic literature; the status and trend of the relay manufacturer’s development are better found in their product manuals and patent activity. Further insight into specific implementations by transmission utilities can be found from publications in industry-led forums and some academic journals. This article surveys the status and development of distance protection for series compensated lines, with a focus on industrial implementation and practical considerations. Factors that influence the protection of series compensated lines are presented. Implementation examples reported by utilities are summarized as examples of the different situations encountered and the methods used to deal with them. It is observed that many utilities use communication-aided protection in series compensated lines, and distance protection is used with reduced reach. Solutions described in relay manuals are presented to demonstrate the manufacturers’ approaches to problems associated with series capacitor protection. While there are methods to counter voltage inversion, current inversion seems to represent a more serious challenge. A patent overview indicates the trends in this domain to be moving towards time-domain-based faster protection methods.

scholarly journals A Framework for AI-Assisted Detection of Patent Ductus Arteriosus from Neonatal Phonocardiogram

Healthcare ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 169
Author(s):  
Sergi Gómez-Quintana ◽  
Christoph E. Schwarz ◽  
Ihor Shelevytsky ◽  
Victoriya Shelevytska ◽  
Oksana Semenova ◽  
...  
Keyword(s):  
Patent Ductus Arteriosus ◽  
Heart Defects ◽  
Ductus Arteriosus ◽  
Area Under The Curve ◽  
Clinical Decision ◽  
Heart Sounds ◽  
Decision Tree Classifier ◽  
Support Tool ◽  
Tree Classifier ◽  
Patent Ductus

The current diagnosis of Congenital Heart Disease (CHD) in neonates relies on echocardiography. Its limited availability requires alternative screening procedures to prioritise newborns awaiting ultrasound. The routine screening for CHD is performed using a multidimensional clinical examination including (but not limited to) auscultation and pulse oximetry. While auscultation might be subjective with some heart abnormalities not always audible it increases the ability to detect heart defects. This work aims at developing an objective clinical decision support tool based on machine learning (ML) to facilitate differentiation of sounds with signatures of Patent Ductus Arteriosus (PDA)/CHDs, in clinical settings. The heart sounds are pre-processed and segmented, followed by feature extraction. The features are fed into a boosted decision tree classifier to estimate the probability of PDA or CHDs. Several mechanisms to combine information from different auscultation points, as well as consecutive sound cycles, are presented. The system is evaluated on a large clinical dataset of heart sounds from 265 term and late-preterm newborns recorded within the first six days of life. The developed system reaches an area under the curve (AUC) of 78% at detecting CHD and 77% at detecting PDA. The obtained results for PDA detection compare favourably with the level of accuracy achieved by an experienced neonatologist when assessed on the same cohort.

scholarly journals Optimization of Physical Activity Recognition for Real-Time Wearable Systems: Effect of Window Length, Sampling Frequency and Number of Features

2019 ◽  
Vol 9 (22) ◽  
pp. 4833 ◽  
Author(s):  
Ardo Allik ◽  
Kristjan Pilt ◽  
Deniss Karai ◽  
Ivo Fridolin ◽  
Mairo Leier ◽  
...  
Keyword(s):  
Physical Activity ◽  
Feature Selection ◽  
Real Time ◽  
Sampling Frequency ◽  
Classification Performance ◽  
Window Length ◽  
Decision Tree Classifier ◽  
Acceleration Signal ◽  
Wearable Systems ◽  
Tree Classifier

The aim of this study was to develop an optimized physical activity classifier for real-time wearable systems with the focus on reducing the requirements on device power consumption and memory buffer. Classification parameters evaluated in this study were the sampling frequency of the acceleration signal, window length of the classification fragment, and the number of classification features, found with different feature selection methods. For parameter evaluation, a decision tree classifier was created based on the acceleration signals recorded during tests, where 25 healthy test subjects performed various physical activities. Overall average F1-score achieved in this study was about 0.90. Similar F1-scores were achieved with the evaluated window lengths of 5 s (0.92 ± 0.02) and 3 s (0.91 ± 0.02), while classification performance with 1 s were lower (0.87 ± 0.02). Tested sampling frequencies of 50 Hz, 25 Hz, and 13 Hz had similar results with most classified activity types, with an exception of outdoor cycling, where differences were significant. Using forward sequential feature selection enabled the decreasing of the number of features from initial 110 features to about 12 features without lowering the classification performance. The results of this study have been used for developing more efficient real-time physical activity classifiers.

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