CN103067107A - Device and detection method based on superhet type stochastic resonance detection system - Google Patents

Abstract

The invention discloses to a device and a detection method based on a superhet type stochastic resonance detection system, and relates to a stochastic resonance detection device and a method which aims at solving the following two problems: (1) an existing stochastic resonance system is not suitable for a frequency signal where f 0 is greater than 1; and (2) a signal with a 108 magnitude frequency cannot be detected through a stochastic resonance system. An external signal to be tested is connected with an input end of a mixer, an signal output signal of the mixer is connected with an signal input end of an amplifier, an signal output end of the amplifier is connected a signal input end of a filter, an signal output end of the filter is connected with an signal input end of an analog-digital (A/D) converter, a data output end of the A/D converter is connected with a data input end of a bistable state stochastic resonance system leading into integral compensation, and data output end of the bistable state stochastic resonance system leading into the integral compensation is connected with a data input end of an external data processor. The stochastic resonance detection device and the method can be widely used for stochastic resonance detection for signals with the frequency of 1 to 108.

Description

Device and detection method based on the superhet Stochastic Resonance Detection System

Technical field

The present invention relates to the device and method that a kind of accidental resonance detects, belong to the signal detection technique field.

Background technology

At present, signal detection technique has very widely in a lot of fields to be used, such as biomedicine, electrochemistry, scientific research etc.Although people are in the research Detection of Weak Signals, develop a whole set of and suppressed theory and the method for noise, such as digital lock-in technique, Boxcar integrator and coherent detection technology etc., in Testing of Feeble Signals, played sizable effect, but when suppressing noise, measured signal also is suppressed or loses.In addition, these methods are to carry out in the framework of linear system mostly, such as arrowbandization and coherent detection technology, the averaging of time-domain signal, the stroke analysis of discrete signal etc.Therefore need to consider following several problems: 1 system itself is the source that produces noise.In whole information process chain, the system that relates to is more, and the probability that produces additional noise is also more.2 systems itself do not exist signal to noise ratio to increase function.On the contrary, along with the increase of input noise, system's output signal-to-noise ratio can constantly descend.Therefore finding a kind of Weak Signal Detection Method that can extract useful signal from noise is the problem demanding prompt solution that society faces.

The proposition of Stochastic Resonance Theory is for new thinking has been started in the detection of small-signal.Stochastic Resonance Theory shows, when the small-signal under the strong noise background is passed through a non linear system, if non-linear, the signal of system and noise reach certain coupling, background noise can strengthen the output of small-signal, improve output signal-to-noise ratio, but stochastic resonance system so that high-frequency signal detects is hindered, is only applicable to low frequency (f to the limitation of frequency input signal ₀＜＜1Hz) is to 10 ⁸The signal of magnitude frequency also can't detect by stochastic resonance system.

Summary of the invention

The present invention is not suitable for f in order to solve (1) existing stochastic resonance system ₀1 frequency signal; (2) 10 ⁸Two problems that the signal of magnitude frequency can't detect by stochastic resonance system, thus provide a kind of based on superhet accidental resonance checkout gear and method.

Based on the device of superhet Stochastic Resonance Detection System, it comprises frequency mixer, amplifier, filter, A/D converter, stochastic resonance system and local oscillation signal processor;

Outside measured signal links to each other with the measured signal input of described frequency mixer, and the carrier signal output of local oscillation signal processor links to each other with the carrier signal input of frequency mixer; The mixed frequency signal output of described frequency mixer links to each other with the mixed frequency signal input of amplifier, the mixed frequency signal output of amplifier links to each other with the mixed frequency signal input of filter, the frequency reducing signal output part of filter links to each other with the frequency reducing signal input part of A/D converter, the frequency reducing data output end of A/D converter links to each other with the frequency reducing data input pin of the bistable-state random resonance system that introduces integral compensation, and the peak spectrum data output end of introducing the bistable-state random resonance system of integral compensation links to each other with the peak spectrum data input pin of external data processor;

The bistable-state random resonance system of described introducing integral compensation comprises bistable-state random resonance system and penalty coefficient module, and the penalty coefficient output of described penalty coefficient module links to each other with the penalty coefficient input of stochastic resonance system.

Based on the method for the device of superhet Stochastic Resonance Detection System, it comprises the steps:

Step 1: with measured signal s (t)+n (t) input mixer;

Described measured signal s (t)+n (t) for be mixed with white Gaussian noise original signal; Original signal is s (t)=Acos (2 π f ₀T), white Gaussian noise is n (t); The scope of described measured signal frequency is 1Hz ~ 9 * 10 ⁸Hz;

Step 2: the carrier signal v that the local oscillation signal processor produces from the local oscillation signal processor _c(t) lower-frequency limit begins to extract carrier signal v _c(t), the frequency interval of extraction is Δ f, and Δ f is the non-zero arbitrary value; Obtain the carrier signal v of several extractions _c(t);

Carrier signal v with each extraction _c(t) with the described measured signal s of step 1 (t)+n (t) while input mixer, the initial time of measured signal s (t)+n (t) input mixer is t=0;

The carrier signal v that described local oscillation signal processor produces _c(t) be v _c(t)=cos (2 π f _cAnd carrier signal v t), _c(t) frequency range is identical with the frequency range of measured signal s (t)+n (t);

Step 3; Several carrier signals v with the described extraction of step 2 _c(t) carry out mixing, obtain several mixed frequency signals with measured signal s (t)+n (t) respectively; The described measured signal s (t) that carries out mixing+n (t) is the measured signal s (t)+n (t) of 0.1 second time cycle;

Described each mixed frequency signal is [s (t)+n (t)] v _c(t), through optical mixing process, obtain respectively frequency reducing signal x ₁(t), up-conversion signal x ₂(t) with noise ξ (t); Described frequency reducing signal x ₁(t) be

Up-conversion signal x ₂(t) be $x_2\left(t\right)=\frac{1}{2}A\cos \left[2\mathrm{\π}(f_0+f_c)t\right];$

Step 4: with several mixed frequency signals [s (t)+n (t)] v of step 3 acquisition _c(t) difference input amplifier, several mixed frequency signals [s (t)+n (the t)] v after obtaining to amplify _c(t);

Step 5: with several mixed frequency signals [s (t)+n (the t)] v after the amplification of step 4 acquisition _c(t) the difference input filter obtains several mixed frequency signals [s (t)+n (t)] v _c(t) several frequency reducing signals x in ₁(t);

Step 6: with described several frequency reducing signals of step 5 x ₁(t) input a/d converter is by A/D converter frequency reducing signal x just ₁(t) be converted to several frequency reducing signals x ₁(t) digital signal;

Step 7: with several frequency reducing signals x of step 6 acquisition ₁(t) the bistable-state random resonance system of integral compensation is introduced in digital signal input, introduces the bistable-state random resonance system (6) of integral compensation with several frequency reducing signals x ₁The peak spectral amplitude of digital signal (t) exports ppu to.

Employing the present invention is based on the device and method of superhet Stochastic Resonance Detection System, and its advantage comprises:

(1) the bistable-state random resonance system makes f for introducing the stochastic resonance system of integral compensation ₀1 signal produces accidental resonance;

(2) by introducing the superhet technology, before entering the bistable-state random resonance system, input signal is carried out mixing, make the frequency reducing signal of generation satisfy the accidental resonance condition, further improved the frequency range that the bistable-state random resonance system can detect.

Description of drawings

Fig. 1 is based on the apparatus structure schematic diagram of superhet Stochastic Resonance Detection System;

Fig. 2 is based on the method flow diagram of superhet Stochastic Resonance Detection System.

Embodiment

Embodiment one, in conjunction with Fig. 1 this embodiment is described.Based on the device of superhet Stochastic Resonance Detection System, it comprises frequency mixer 1, amplifier 3, filter 4, A/D converter 5, stochastic resonance system 6 and local oscillation signal processor 2;

Outside measured signal links to each other with the measured signal input of described frequency mixer 1, and the carrier signal output of local oscillation signal processor 2 links to each other with the carrier signal input of frequency mixer 1; The mixed frequency signal output of described frequency mixer 1 links to each other with the mixed frequency signal input of amplifier 3, the mixed frequency signal output of amplifier 3 links to each other with the mixed frequency signal input of filter 4, the frequency reducing signal output part of filter 4 links to each other with the frequency reducing signal input part of A/D converter 5, the frequency reducing data output end of A/D converter 5 links to each other with the frequency reducing data input pin of the bistable-state random resonance system 6 that introduces integral compensation, and the peak spectrum data output end of introducing the bistable-state random resonance system 6 of integral compensation links to each other with the peak spectrum data input pin of external data processor 7;

The bistable-state random resonance system 6 of described introducing integral compensation comprises bistable-state random resonance system 8 and penalty coefficient module 9, and the penalty coefficient output of described penalty coefficient module 9 links to each other with the penalty coefficient input of stochastic resonance system 8.

Embodiment two, adopt the detection method based on the device of superhet Stochastic Resonance Detection System of embodiment one, it comprises the steps:

Step 1: with measured signal s (t)+n (t) input mixer 1;

Described measured signal s (t)+n (t) for be mixed with white Gaussian noise original signal; Original signal is s (t)=Acos (2 π f ₀T), white Gaussian noise is n (t); The scope of described measured signal frequency is 1Hz ~ 9 * 10 ⁸Hz;

Step 2: the carrier signal v that local oscillation signal processor 2 produces from local oscillation signal processor 2 _c(t) lower-frequency limit begins to extract carrier signal v _c(t), the frequency interval of extraction is Δ f, and Δ f is the non-zero arbitrary value; Obtain the carrier signal v of several extractions _c(t);

Carrier signal v with each extraction _c(t) with the described measured signal s of step 1 (t)+n (t) while input mixer 1, the initial time of measured signal s (t)+n (t) input mixer 1 is t=0;

The carrier signal v that described local oscillation signal processor 2 produces _c(t) be v _c(t)=cos (2 π f _cAnd carrier signal v t), _c(t) frequency range is identical with the frequency range of measured signal s (t)+n (t);

Step 3; Several carrier signals v with the described extraction of step 2 _c(t) carry out mixing, obtain several mixed frequency signals with measured signal s (t)+n (t) respectively; The described measured signal s (t) that carries out mixing+n (t) is the measured signal s (t)+n (t) of 0.1 second time cycle;

Described each mixed frequency signal is [s (t)+n (t)] v _c(t), through optical mixing process, obtain respectively frequency reducing signal x ₁(t), up-conversion signal x ₂(t) with noise ξ (t); Described frequency reducing signal x ₁(t) be

Up-conversion signal x ₂(t) be $x_2\left(t\right)=\frac{1}{2}A\cos \left[2\mathrm{\π}(f_0+f_c)t\right];$

The principle of described mixing is:

$x\left(t\right)=[s\left(t\right)+n\left(t\right)]v_c\left(t\right)$

$=\frac{1}{2}A\cos \left[2\mathrm{\π}(f_0-f_c)t\right]+\frac{1}{2}A\cos \left[2\mathrm{\π}(f_0+f_c)t\right]+n\left(t\right)\cos \left(2\mathrm{\π}{f}_{c}t\right)$

Step 4: with several mixed frequency signals [s (t)+n (t)] v of step 3 acquisition _c(t) difference input amplifier 3, several mixed frequency signals [s (t)+n (the t)] v after obtaining to amplify _c(t);

Step 5: with several mixed frequency signals [s (t)+n (the t)] v after the amplification of step 4 acquisition _c(t) difference input filter 4 obtains several mixed frequency signals [s (t)+n (t)] v _c(t) several frequency reducing signals x in ₁(t);

Step 6: with described several frequency reducing signals of step 5 x ₁(t) input a/d converter 5, by A/D converter 5 with frequency reducing signal x ₁(t) be converted to several frequency reducing signals x ₁(t) digital signal;

Step 7: with several frequency reducing signals x of step 6 acquisition ₁(t) the bistable-state random resonance system 6 of integral compensation is introduced in digital signal input, introduces the bistable-state random resonance system 6 of integral compensation with several frequency reducing signals x ₁The peak spectral amplitude of digital signal (t) exports ppu 7 to.

What embodiment three, this embodiment and embodiment two were different is that the principle of introducing the bistable-state random resonance system 6 of integral compensation described in the step 7 is:

Stochastic resonance system has been described the reciprocal transition phenomenon that Brownian Particles is occured in the non linear system by acting on of cyclical signal and noise under the overdamp.The equation of description Particles Moving-Langevin equation is:

$\frac{d_x}{d_y}=\mathrm{ax}-{\mathrm{<figure-callout\; id="3"\; label="bx"\; filenames="HDA00002686273400011.png"\; state="\{\{state\}\}">bx</figure-callout>}}^3+\frac{1}{2}A\cos \left[2\mathrm{\&pi;}(f_0-f_c)t\right]+\mathrm{\&xi;}\left(t\right)$

The bistable-state random resonance system (6) that introduces integral compensation improves stochastic resonance system for introducing integral compensation:

$\frac{d_x}{d_y}=\{\mathrm{ax}-{\mathrm{<figure-callout\; id="3"\; label="bx"\; filenames="HDA00002686273400011.png"\; state="\{\{state\}\}">bx</figure-callout>}}^3+\frac{1}{2}A\cos [2\mathrm{\&pi;}(f_0-f_c)t]+\mathrm{\&xi;}\left(t\right)\}\&times;\mathrm{Gain}$

Wherein, Gain is the integral compensation coefficient, and Gain 〉=2 π (f ₀-f ₀).

Stochastic resonance system has increased integral compensation, becomes the bistable-state random resonance system 6 that introduces integral compensation, and the signal frequency that can process increases to 10 ²The Hz magnitude.Stochastic resonance system becomes frequency and amplitude relation with the relation of Time And Frequency by the FFT shift conversion, and exports it to external data processor 7.External data processor 7 fits to continuous peak spectral amplitude with each mixed frequency signal x (t) by frequency and the amplitude relation that stochastic resonance system obtains, and calculates frequency corresponding to amplitude maximum, and described frequency is the frequency f of original signal ₀, the carrier signal v of described frequency for extracting _c(t) frequency f _cBecause known to measured signal s (t)+n (t) and carrier signal v _cStochastic resonance system had maximum spectrum peak when frequency (t) was identical, namely by frequency f corresponding to spectrum peak maximum _cIt is exactly the frequency f of measured signal s (t)+n (t) ₀, finish testing process.

Employing the present invention is based on the device and method of superhet Stochastic Resonance Detection System, and the bistable-state random resonance system makes f for introducing the stochastic resonance system of integral compensation ₀1 signal produces accidental resonance; By introducing the superhet technology, before entering the bistable-state random resonance system, input signal is carried out mixing, make the frequency reducing signal of generation satisfy the accidental resonance condition, further improved the frequency range that the bistable-state random resonance system can detect.

Claims (3)

1. based on the device of superhet Stochastic Resonance Detection System, it is characterized in that it comprises bistable-state random resonance system (6) and the local oscillation signal processor (2) of frequency mixer (1), amplifier (3), filter (4), A/D converter (5), introducing integral compensation;

Outside measured signal links to each other with the measured signal input of described frequency mixer (1), and the carrier signal output of local oscillation signal processor (2) links to each other with the carrier signal input of frequency mixer (1); The mixed frequency signal output of described frequency mixer (1) links to each other with the mixed frequency signal input of amplifier (3), the mixed frequency signal output of amplifier (3) links to each other with the mixed frequency signal input of filter (4), the frequency reducing signal output part of filter (4) links to each other with the frequency reducing signal input part of A/D converter (5), the frequency reducing data output end of A/D converter (5) links to each other with the frequency reducing data input pin of the bistable-state random resonance system (6) that introduces integral compensation, and the peak spectrum data output end of introducing the bistable-state random resonance system (6) of integral compensation links to each other with the peak spectrum data input pin of external data processor (7);

The bistable-state random resonance system (6) of described introducing integral compensation comprises bistable-state random resonance system (8) and penalty coefficient module (9), and the penalty coefficient output of described penalty coefficient module (9) links to each other with the penalty coefficient input of stochastic resonance system (8).

2. adopt the detection method of the device based on the superhet Stochastic Resonance Detection System claimed in claim 1, it is characterized in that it comprises the steps:

Step 1: with measured signal s (t)+n (t) input mixer (1);

Described measured signal s (t)+n (t) for be mixed with white Gaussian noise original signal; Original signal is s (t)=Acos (2 π f ₀T), white Gaussian noise is n (t); The scope of described measured signal frequency is 1Hz ~ 9 * 10 ⁸Hz;

Step 2: the carrier signal v that local oscillation signal processor (2) produces from local oscillation signal processor (2) _c(t) lower-frequency limit begins to extract carrier signal v _c(t), the frequency interval of extraction is Δ f, and Δ f is the non-zero arbitrary value; Obtain the carrier signal v of several extractions _c(t);

Carrier signal v with each extraction _c(t) with the described measured signal s of step 1 (t)+n (t) while input mixer (1), the initial time of measured signal s (t)+n (t) input mixer (1) is t=0;

The carrier signal v that described local oscillation signal processor (2) produces _c(t) be v _c(t)=cos (2 π f _cAnd carrier signal v t), _c(t) frequency range is identical with the frequency range of measured signal s (t)+n (t);

Step 3; Several carrier signals v with the described extraction of step 2 _c(t) carry out mixing, obtain several mixed frequency signals with measured signal s (t)+n (t) respectively; The described measured signal s (t) that carries out mixing+n (t) is the measured signal s (t)+n (t) of 0.1 second time cycle;

Described each mixed frequency signal is [s (t)+n (t)] v _c(t), through optical mixing process, obtain respectively frequency reducing signal x ₁(t), up-conversion signal x ₂(t) with noise ξ (t); Described frequency reducing signal x ₁(t) be Up-conversion signal x ₂(t) be $x_2\left(t\right)=\frac{1}{2}A\cos \left[2\mathrm{\&pi;}(f_0+f_c)t\right];$

Step 4: with several mixed frequency signals [s (t)+n (t)] v of step 3 acquisition _c(t) difference input amplifier (3), several mixed frequency signals [s (t)+n (the t)] v after obtaining to amplify _c(t);

Step 5: with several mixed frequency signals [s (t)+n (the t)] v after the amplification of step 4 acquisition _c(t) difference input filter (4) obtains several mixed frequency signals [s (t)+n (t)] v _c(t) several frequency reducing signals x in ₁(t);

Step 6: with described several frequency reducing signals of step 5 x ₁(t) input a/d converter (5), by A/D converter (5) with frequency reducing signal x ₁(t) be converted to several frequency reducing signals x ₁(t) digital signal;

Step 7: with several frequency reducing signals x of step 6 acquisition ₁(t) the bistable-state random resonance system (6) of integral compensation is introduced in digital signal input, introduces the bistable-state random resonance system (6) of integral compensation with several frequency reducing signals x ₁The peak spectral amplitude of digital signal (t) exports ppu (7) to.

3. the detection method of the device based on the superhet Stochastic Resonance Detection System according to claim 2 is characterized in that the principle of introducing the bistable-state random resonance system (6) of integral compensation described in the step 7 is:

Stochastic resonance system has been described the reciprocal transition phenomenon that Brownian Particles is occured in the non linear system by acting on of cyclical signal and noise under the overdamp.The equation of description Particles Moving-Langevin equation is:

$\frac{d_x}{d_y}=\mathrm{ax}-{\mathrm{bx}}^3+\frac{1}{2}A\cos \left[2\mathrm{\&pi;}(f_0-f_c)t\right]+\mathrm{\&xi;}\left(t\right)$

The bistable-state random resonance system (6) that introduces integral compensation improves stochastic resonance system for introducing integral compensation:

$\frac{d_x}{d_y}=\{\mathrm{ax}-{\mathrm{bx}}^3+\frac{1}{2}A\cos [2\mathrm{\&pi;}(f_0-f_c)t]+\mathrm{\&xi;}\left(t\right)\}\&times;\mathrm{Gain}$

Wherein, Gain is the integral compensation coefficient, and Gain 〉=2 π (f ₀-f _c).

Images