Design of Low-Noise, High-Density Signal Intelligent Detection System

2013 ◽  
Vol 380-384 ◽  
pp. 3882-3885
Author(s):  
Xiaoan Yang
Keyword(s):  
Phase Transition ◽  
Detection Method ◽  
Detection System ◽  
Low Noise ◽  
Weak Signal ◽  
High Effectiveness ◽  
Motion State ◽  
Intelligent Detection ◽  
Stable Performance ◽  
Engineering Practices

Using motion state of the equipment transducer to determine the presence of a weak signal is a common method of signal detection, whose core is to determine the system's phase change. There a many traditional ways to judge phase transition, but most of which have computational complexity and need a large amount of data which make them difficult to apply engineering practices. In order to solve these problems, this paper presents a detection method based on Lyapunov exponent classification with a small amount of data. This approach has some advantages such as requiring fewer observed values, small calculation amount, and able to automatically determine the phase transition without subjective factors involved etc. Experiments show that this method has stable performance, high effectiveness, strong practicality and promotion.

Design of Low-Noise and High-Density Signal Intelligent Detection System

2013 ◽  
Vol 760-762 ◽  
pp. 2229-2233
Author(s):  
Xiaoan Yang
Keyword(s):  
Phase Transition ◽  
Detection Method ◽  
Detection System ◽  
Low Noise ◽  
Weak Signal ◽  
High Effectiveness ◽  
Motion State ◽  
Intelligent Detection ◽  
Stable Performance ◽  
Engineering Practices

Using motion state of the equipment transducer to determine the presence of a weak signal is a common method of signal detection, whose core is to determine the system's phase change. There a many traditional ways to judge phase transition, but most of which have computational complexity and need a large amount of data which make them difficult to apply engineering practices. In order to solve these problems, this paper presents a detection method based on Lyapunov exponent classification with a small amount of data. This approach has some advantages such as requiring fewer observed values, small calculation amount, and able to automatically determine the phase transition without subjective factors involved etc. Experiments show that this method has stable performance, high effectiveness, strong practicality and promotion.

Weak Signal Detection Method in a Stronger Noise Background

2014 ◽  
Vol 568-570 ◽  
pp. 260-264
Author(s):  
Jun Wang ◽  
Jian Ming Bai
Keyword(s):  
Detection Method ◽  
Detection System ◽  
Feasibility Analysis ◽  
Weak Signal ◽  
Weak Signal Detection ◽  
Error Angle ◽  
Noise Background ◽  
Photoelectric Detection ◽  
Detection Technology ◽  
Detection Principle

When we use the laser auto collimation theodolite to measure the azimuth error angle of air target, the strong noise background reduces the spot imaging quality and seriously influences the measuring angle ability of the theodolite. In order to solve the problem, a photoelectric detection system used to detect the weak signal is designed based the correlation detection principle and the principle of correlation detection technology is introduced. We use Simulink software presenting a simulation to the detection system and do a feasibility analysis. Finally, it’s proved that the photoelectric detection system could suppress the strong noise background, improve the SNR greatly and detect the weak signal effectively.

Image detection and parameterization for different components in cross-sections of radial tires

2021 ◽  
pp. 095440702110236
Author(s):  
Chen Liu ◽  
Yude Dong ◽  
Yanli Wei ◽  
Jiangtao Wang ◽  
Hongling Li
Keyword(s):  
Image Processing ◽  
Digital Image Processing ◽  
Cross Sections ◽  
Digital Image ◽  
Detection Method ◽  
Detection System ◽  
Practical Significance ◽  
Vehicle Safety ◽  
Wire Steel ◽  
Good Detection

The internal structure analysis of radial tires is of great significance to improve vehicle safety and during tire research. In order to perform the digital analysis and detection of the internal composition in radial tire cross-sections, a detection method based on digital image processing was proposed. The research was carried out as follows: (a) the distribution detection and parametric analysis of the bead wire, steel belt, and carcass in the tire section were performed by means of digital image processing, connected domain extraction, and Hough transform; (b) using the angle of location distribution and area relationship, the detection data were optimized through coordinate and quantity relationship constraints; (c) a detection system for tire cross-section components was designed using the MATLAB platform. Our experimental results showed that this method displayed a good detection performance, and important practical significance for the research and manufacture of tires.

Weak Signal Frequency Detection Method Based on Generalized Duffing Oscillator

2011 ◽  
Vol 28 (4) ◽  
pp. 040502 ◽  
Author(s):  
Si-Hong Shi ◽  
Yong Yuan ◽  
Hui-Qi Wang ◽  
Mao-Kang Luo
Keyword(s):  
Detection Method ◽  
Duffing Oscillator ◽  
Signal Frequency ◽  
Weak Signal ◽  
Frequency Detection

Research on Several Key Techniques of Power Tool Rest Noise Detection System

2012 ◽  
Vol 630 ◽  
pp. 271-275
Author(s):  
Xiao Hong Lu ◽  
Yong Yan Shang ◽  
Peng Zhuo Han ◽  
Guang Jun Li ◽  
Wen Yi Wu
Keyword(s):  
Spectrum Analysis ◽  
Detection Method ◽  
Detection System ◽  
Sampled Data ◽  
Noise Detection ◽  
Machining Center ◽  
Cnc Lathe ◽  
Spectrum Transformation ◽  
Key Techniques

The scarcity and imperfection of power tool rest noise detection method have seriously limited the development of the industry of CNC lathe, lathe and milling composite machining center. A noise detection system based on LabVIEW is developed. The developed system adopts a noise sensor as noise detection component to test the noise information of the power tool rest. To enhance the anti-interference ability of this system, the sampled signals are amplified and adjusted by the signal disposal instrument. Through the spectrum transformation and spectrum analysis of the sampled noise signals, the noise causes of the power tool rest can be inquired and the concerned measurements can be taken to reduce the noise effectively. Finally, the sampled data is stored by the data saving function.

scholarly journals An Automata Based Intrusion Detection Method for Internet of Things

2017 ◽  
Vol 2017 ◽  
pp. 1-13 ◽  
Author(s):  
Yulong Fu ◽  
Zheng Yan ◽  
Jin Cao ◽  
Ousmane Koné ◽  
Xuefei Cao
Keyword(s):  
Open Access ◽  
Internet Of Things ◽  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Detection Method ◽  
Detection System ◽  
Network Communication ◽  
5G Networks ◽  
Machine To Machine ◽  
Security Of Iot

Internet of Things (IoT) transforms network communication to Machine-to-Machine (M2M) basis and provides open access and new services to citizens and companies. It extends the border of Internet and will be developed as one part of the future 5G networks. However, as the resources of IoT’s front devices are constrained, many security mechanisms are hard to be implemented to protect the IoT networks. Intrusion detection system (IDS) is an efficient technique that can be used to detect the attackers when cryptography is broken, and it can be used to enforce the security of IoT networks. In this article, we analyzed the intrusion detection requirements of IoT networks and then proposed a uniform intrusion detection method for the vast heterogeneous IoT networks based on an automata model. The proposed method can detect and report the possible IoT attacks with three types: jam-attack, false-attack, and reply-attack automatically. We also design an experiment to verify the proposed IDS method and examine the attack of RADIUS application.

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