A Research on Suppression of SSO Based on the Real Time Digital Simulation

2013 ◽  
Vol 732-733 ◽  
pp. 1415-1419 ◽  
Author(s):  
Chun Lin Guo ◽  
Jian Ting Xu ◽  
Yang Zhao ◽  
Xiang Ning Xiao
Keyword(s):  
Real Time ◽  
Digital Simulation ◽  
Operation Mode ◽  
System Model ◽  
The Real ◽  
Model Based ◽  
Operation Modes ◽  
Simulation Results

According to the first project using SVC to mitigate SSO in China, this paper builds the system model based on real time digtal simulator,and gives an introduction to the sysem model. Under typical operation mode and fault conditions,the performance of SVC is fully validated,it also analysis and comparise the performance of SVC under different operation modes. Simulation results show that the SVC can mitigate the SSO phenomenon.

scholarly journals AdaGUM: An Adaptive Graph Updating Model-Based Anomaly Detection Method for Edge Computing Environment

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Xiang Yu ◽  
Chun Shan ◽  
Jilong Bian ◽  
Xianfei Yang ◽  
Ying Chen ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Anomaly Detection ◽  
Real Time ◽  
Detection Method ◽  
Edge Computing ◽  
Sensor Data ◽  
Computing Environment ◽  
The Real ◽  
Edge Node ◽  
Model Based

With the rapid development of Internet of Things (IoT), massive sensor data are being generated by the sensors deployed everywhere at an unprecedented rate. As the number of Internet of Things devices is estimated to grow to 25 billion by 2021, when facing the explicit or implicit anomalies in the real-time sensor data collected from Internet of Things devices, it is necessary to develop an effective and efficient anomaly detection method for IoT devices. Recent advances in the edge computing have significant impacts on the solution of anomaly detection in IoT. In this study, an adaptive graph updating model is first presented, based on which a novel anomaly detection method for edge computing environment is then proposed. At the cloud center, the unknown patterns are classified by a deep leaning model, based on the classification results, the feature graphs are updated periodically, and the classification results are constantly transmitted to each edge node where a cache is employed to keep the newly emerging anomalies or normal patterns temporarily until the edge node receives a newly updated feature graph. Finally, a series of comparison experiments are conducted to demonstrate the effectiveness of the proposed anomaly detection method for edge computing. And the results show that the proposed method can detect the anomalies in the real-time sensor data efficiently and accurately. More than that, the proposed method performs well when there exist newly emerging patterns, no matter they are anomalous or normal.

A Method for Real-Time Radar Signal Main Sorting

2013 ◽  
Vol 760-762 ◽  
pp. 567-571
Author(s):  
Hong Chao Wu ◽  
Wei Hua Xiao ◽  
Jian Feng Pu
Keyword(s):  
Real Time ◽  
Pulse Sequence ◽  
High Accuracy ◽  
Radar Signal ◽  
Sorting Algorithm ◽  
The Real ◽  
Sorting Algorithms ◽  
Key Technologies ◽  
Simulation Results ◽  
Sequence Simulation

The real-time radar signal sorting is one of the key technologies for electronic reconnaissance, first analyzes the defects of traditional main sorting algorithms, and then proposes a comprehensive main sorting algorithm. The method first uses the SDIF algorithm to sort PRI fixed and PRI stagger radar signal, then uses dynamic expansion association method to search PRI jitter radar signal. When using the SDIF algorithm, in order to improve the efficiency of extraction of PRI, first taking amplitude pretreatment, then only accumulate the signals whose amplitude meet certain requirements. After extracting PRI, extract to the original full pulse sequence. Simulation results show that the method of sorting has high accuracy and good real-time.

DSP-Based Implementation and Optimization of Auditory Filter-Bank

2013 ◽  
Vol 765-767 ◽  
pp. 2862-2865
Author(s):  
Jin Lun Chen
Keyword(s):  
Signal Processing ◽  
Real Time ◽  
Filter Bank ◽  
Audio Signal ◽  
Audio Signal Processing ◽  
Auditory Model ◽  
Auditory Filter ◽  
The Real ◽  
Model Based ◽  
Signal Processing Systems

The auditory filter-bank is the key component of auditory model, and its implementation involves a lot of computations. The time spent by an auditory filter-bank to finish its work has a significant effect on the real-time implementation of auditory model-based audio signal processing systems. In this paper, we give a brief introduction to the auditory filter-bank at the first, and then discuss its DSP-based implementation and optimization in details.

Active Vibration Control for Lathe Based Neural Network

2011 ◽  
Vol 84-85 ◽  
pp. 183-187 ◽  
Author(s):  
Jin Hua Wang ◽  
Wen Juan Huang ◽  
Hong Yan Zhang ◽  
Yao Gang Li
Keyword(s):  
Neural Network ◽  
Control System ◽  
Vibration Control ◽  
Active Vibration Control ◽  
System Model ◽  
Matlab Simulation ◽  
Model Based ◽  
Active Vibration ◽  
Simulation Results ◽  
Control System Model

In this paper, we took lathe as the research object, and established an active vibration control system model based on neural network AVC (Active Vibration Control) system, and the Matlab simulation results showed that the AVC system can reduce vibration effectively and improve the lathe’s accuracy.

scholarly journals The research of the real-time pricing model based on the cumulated points system in the demand response

2018 ◽  
Vol 145 ◽  
pp. 246-251
Author(s):  
Peipei Zhang ◽  
Xueyin Wang ◽  
Mei Sun ◽  
Mingzhuang Zhang ◽  
Xu Yan
Keyword(s):  
Real Time ◽  
Demand Response ◽  
Pricing Model ◽  
The Real ◽  
Model Based ◽  
Real Time Pricing

The Application of the Complex Modulation Zoom-FFT Based on Complex Analytical Bandpass Filter in Interhamonic Detection of Power System

2011 ◽  
Vol 354-355 ◽  
pp. 1012-1015
Author(s):  
Ya Mei Liu ◽  
Hong Geng Yang ◽  
Lan Fang Li
Keyword(s):  
Theoretical Analysis ◽  
Power System ◽  
Real Time ◽  
Spectrum Analysis ◽  
Bandpass Filter ◽  
The Real ◽  
Simulation Results ◽  
Real Time Detection ◽  
Complex Modulation

Interharmoics are the signals whose frequencies are between two harmonics. Besides the usual characterics of the harmonics, interharmonics will influence the present harmonic compensating equipment, and then result in failure compensation. Therefore, precise detection of interharmonics is very important and significant. Complex modulation Zoom-FFT (ZFFT) based on complex analytical bandpass filter is introduced in the real-time detection of the power system. Contrasting to the traditional zoom spectrum algorithms, the proposed algorithm is more suitable in the intensive spectrum analysis. Detailed theoretical analysis and simulation results are presented. The effectiveness of this algorithm is verified.

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