Weak photoacoustic signal detection based on the differential duffing oscillator

2018 ◽  
Vol 32 (09) ◽  
pp. 1850103 ◽  
Author(s):  
Chenjing Li ◽  
Xuemei Xu ◽  
Yipeng Ding ◽  
Linzi Yin ◽  
Beibei Dou
Keyword(s):  
Signal Detection ◽  
Photoacoustic Spectroscopy ◽  
Detection System ◽  
Signal To Noise Ratio ◽  
Duffing Oscillator ◽  
Threshold Value ◽  
Photoacoustic Signal ◽  
Weak Signal ◽  
Weak Signal Detection ◽  
First Time

In view of photoacoustic spectroscopy theory, the relationship between weak photoacoustic signal and gas concentration is described. The studies, on the principle of Duffing oscillator for identifying state transition as well as determining the threshold value, have proven the feasibility of applying the Duffing oscillator in weak signal detection. An improved differential Duffing oscillator is proposed to identify weak signals with any frequency and ameliorate the signal-to-noise ratio. The analytical methods and numerical experiments of the novel model are introduced in detail to confirm its superiority. Then the signal detection system of weak photoacoustic based on differential Duffing oscillator is constructed, it is the first time that the weak signal detection method with differential Duffing oscillator is applied triumphantly in photoacoustic spectroscopy gas monitoring technology.

Weak Signal Detection System Based on Lock-in Amplifier Technology

2013 ◽  
Vol 389 ◽  
pp. 489-493
Author(s):  
Yong Lv ◽  
Chun Hui Niu ◽  
Yue Qiang Li ◽  
Qing Shan Chen ◽  
Xiao Ying Li ◽  
...  
Keyword(s):  
Signal Detection ◽  
Detection System ◽  
Signal To Noise Ratio ◽  
Weak Signal ◽  
Weak Signal Detection ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Low Pass ◽  
Phase Sensitive ◽  
Lock In

In order to detect the weak signal deeply buried in the noise, a weak signal detection system based on lock-in amplifier is proposed. The system includes the preamplifier circuit, active low pass filter circuit, AC amplifying circuit and phase sensitive demodulation circuit. Test results show that it can greatly increase the signal-to-noise ratio (SNR) up to 12.7db.

scholarly journals A Novel Weak Signal Detection Method of Electromagnetic LWD Based on a Duffing Oscillator

2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Aiping Wu ◽  
Saleh M. Mwachaka ◽  
Yanliang Pei ◽  
Qingqing Fu
Keyword(s):  
Signal Detection ◽  
Signal To Noise Ratio ◽  
Duffing Oscillator ◽  
Transformation Method ◽  
Scale Transformation ◽  
Weak Signal ◽  
Weak Signal Detection ◽  
Detection Mechanism ◽  
Detection Model ◽  
Nonlinear Dynamic Characteristics

The logging while drilling (LWD) electromagnetic weak signal detection model of a Duffing oscillator based on a one-dimensional nonlinear oscillator is established. The influences of noise on Duffing oscillator dynamic behavior of periodic driving force are discussed and evaluate the oscillator weak signal detection mechanism based on a phase change trajectory diagram. The improved Duffing oscillator is designed and applied to detect the electromagnetic logging signal resistivity at the drill bit using the time-scale transformation method. The simulation results show that the nonlinear dynamic characteristics of the Duffing oscillator are very noticeable, the Duffing circuit is very sensitive to detect the tested signal, and it has a reasonable level of immunity to noise. The smaller the amplitude of the tested signal, the more sensitive the circuit is to the signal, the better the antinoise system performance, and the lower the signal-to-noise ratio (SNR).

scholarly journals A Memristor Based Chaotic Oscillator for Weak Signal Detection and Its Circuitry Realization

2021 ◽  
Author(s):  
Kaifeng Dong ◽  
Kun Xu ◽  
Youyou Zhou ◽  
Chao Zuo ◽  
Leiming Wang ◽  
...  
Keyword(s):  
Signal Detection ◽  
Detection System ◽  
Signal To Noise Ratio ◽  
Detection Accuracy ◽  
Chaotic Oscillator ◽  
Weak Signal ◽  
Weak Signal Detection ◽  
Noise Performance ◽  
Detection Range ◽  
Implementation Scheme

Abstract A new type of weak signal detection system that combines the memristor and Van der pol-Duffing chaotic system has been proposed in this paper, and the dynamic characteristics of the system are studied. It is observed that the system can change from a chaotic state to a periodic state under different driving force amplitudes. Moreover, as compared with several classical chaotic oscillators, the numerical simulation results show that the system has stronger anti-noise performance with the detectable signal-to-noise ratio reaches -163dB, and has a wider detection range. Its detection accuracy is up to 1 × 10 −9 . More importantly, this paper provides the circuit implementation scheme of the system, and the weak signal can be detected with our designed circuit. This may offer a possible way for weak signal detection system with good performance in anti-noise performance, detection range and accuracy.

Research on the Weak Signal Detection of Bearing Fault Based on Duffing Oscillator

2018 ◽  
Author(s):  
Long Hao ◽  
Dan Liu ◽  
Fei Liu ◽  
QingXin Wang ◽  
Lin Liang ◽  
...  
Keyword(s):  
Signal Detection ◽  
Chaotic System ◽  
Signal To Noise Ratio ◽  
Duffing Oscillator ◽  
Detection Performance ◽  
Periodic Signal ◽  
Weak Signal ◽  
Weak Signal Detection ◽  
Chaotic State ◽  
Bearing Fault

In this paper, chaotic system is applied to identify and extract the weak signals of bearing early fault which are often submerged in strong background noise. Chaotic system is an effective method in weak signal detection because of its properties of noise immunity and sensitivity to the weak periodic signal. However, chaotic system is not completely immune to noise in critical chaotic state. Aiming at this problem, four indicators are used to evaluate the detection performance of Duffing oscillators. Then, the influence of Duffing oscillator parameters on the four indicators is studied in detail and a new method is proposed to improve the detection performance of Duffing oscillator. The simulation and experimental results show that the proposed method can accurately obtain the characteristic signals of early bearing fault in a lower signal-to-noise ratio (SNR) situation.

Variance Based Identification of Phase Transition in Duffing Oscillator for Weak Signal Detection

2011 ◽  
Vol 128-129 ◽  
pp. 354-358 ◽  
Author(s):  
Yuan Chang ◽  
Chun Wen Li ◽  
Yi Hao
Keyword(s):  
Phase Transition ◽  
Signal Detection ◽  
Periodic Motion ◽  
Sharp Increase ◽  
Duffing Oscillator ◽  
Periodic Signal ◽  
Weak Signal ◽  
Weak Signal Detection ◽  
Periodic Signals ◽  
Simulation Results

This paper studies the detection of weak signal detection using a Duffing Oscillator, which is sensitive to periodic signals but insensitive to noises. The system transits from chaotic to great periodic motion when coupled to the weak periodic signal to be detected. To efficiently determine the phase transition, a novel numerical criterion is proposed based on the sharp increase of variance when phase change happens. Simulation results verified the effectiveness of this method.

The Comparison between Chaos Algorithm and Music Algorithm Applied in Weak Signal Detection

2013 ◽  
Vol 427-429 ◽  
pp. 1552-1556
Author(s):  
Chen Zhang ◽  
Zhen Bin Gao ◽  
Jing Chun Li ◽  
Biao Huang
Keyword(s):  
Signal Detection ◽  
Array Signal Processing ◽  
Signal To Noise Ratio ◽  
Weak Signal ◽  
Weak Signal Detection ◽  
Music Algorithm ◽  
Verilog Hdl ◽  
Simulation Experiments ◽  
Chaos Algorithm ◽  
Core Part

Chaos algorithm is essential in weak signal detection because of its sensibility to weak signals and immunity to noise. This paper applies subspace algorithm which originates from array signal processing to weak signal detection field because of its lower signal to noise ratio. Firstly, the article introduces the principles of two algorithms, then analyses simulation experiments results of real signal data. After that, a conclusion for two algorithms comparison by estimation of computation cost, complexity of implementation and hardware resources occupied is drawn. At the end, the writer designs a duffing chaos module which is the core part of chaotic detection with verilog-hdl.

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