CN110333546A - Improve the system and method for proton magnetic precession Signal-to-Noise - Google Patents
Improve the system and method for proton magnetic precession Signal-to-Noise Download PDFInfo
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Abstract
The present invention provides the system and methods for improving proton magnetic precession Signal-to-Noise, the present invention uses the tuning that rotary proton class sensor is realized by the method that PCA algorithm, svd algorithm and fft algorithm combine, and effectively overcoming existing tuning algorithm tuned speed, tuning precision is low slowly, under interference environment, the defects of detuning phenomena easily occurs；While reducing tuning period, improve the tuning precision of rotary proton class sensor, selection of the Wide measuring range to tuning capacitance can be achieved, improve the signal-to-noise ratio of later period measuring signal, applied to rotary proton class magnetometer, optical pumped magnetometer and nuclear magnetic resonance rotary proton FID signal imager etc. by the instrument of rotary proton class sensor, instrument performance is effectively improved.
Description
Technical field
The present invention relates to weak magnetic fields measurement technical fields, and in particular to the system for improving proton magnetic precession Signal-to-Noise
And method.
Background technique
Rotary proton class magnetometer is a kind of for measuring the magnetic-field measurement of slowly varying low-intensity magnetic field or System for Low DC Magnetic Field field
Instrument, sensor, that is, rotary proton class sensor are inductance element.Measuring principle is using certain shooting condition by inductance
Proton in the solution be active, proton can be drawn around external magnetic field i.e. earth magnetic field is stablized after removing shooting condition
More's precessional motion, generates FID (Free Induction Decay) signal, and precession frequency is proportional to external magnetic field；Therefore it is sharp
FID signal is incuded with inductance, is amplified, shaping and measures frequency, external magnetic field value can be obtained.With other magnetic-field measurements
Technology is compared, and rotary proton class magnetometer has the characteristics that high-precision, high sensitivity, is widely used and space exploration, near-earth
The fields such as table detection, hydrospace detection, geomagnetic field measuring, military technology.Since the signal-to-noise ratio of FID signal is to measure frequency-measurement accuracy
Therefore key factor to increase the signal-to-noise ratio that sensor exports FID signal, improves frequency-measurement accuracy, need to be by variable capacitance and sensing
Device is in parallel, is tuned, this variable capacitance is tuning capacitance.
Currently, the sensor that most rotary proton class magnetometers use tune scheme for scanning method, preset capacitance method,
Blindly automatically track method and double measurement automatic follow-up tuning method.And the methodical core operating principle of institute is identical: excitation sensing
Device, switches tuning capacitance, the crest voltage of detection output FID signal, and corresponding tuning capacitance capacitance is just at maximum peak voltage
It is the values for tuning of sensor；Only difference is that the means of detection crest voltage.Chinese patent CN103995298A is announced
A kind of optimum choice proton magnetometer matches the method for humorous capacitor, in that patent, it is first determined a fixed tuning capacitance
Then capacitance is gradually adjusted to determine final tuning capacitance capacitance.
There are still following problems in the design of sensor tuning algorithm for existing rotary proton class magnetometer: 1) tuning speed
Degree is universal relatively slow, about needs several seconds, when the actual measurement of field, when change of magnetic field strength is larger, generally requires again to biography
Sensor is tuned, and brings big inconvenience to user；2) humorous FID signal pole is not matched due to the output of rotary proton class magnetometer
Its is faint, it is easy to be interfered by noise signal, noise is relatively low, once instrument, which is in, interferes biggish environment, frequency spectrum easily occurs
Analytical error is larger to be caused " to lack of proper care ", and instrument is caused to can not work normally.
Summary of the invention
The technical problem to be solved in the present invention is that for above-mentioned existing rotary proton class magnetometer at present in sensor
Technical problem present on the design of tuning algorithm is provided in the system and method solution for improving proton magnetic precession Signal-to-Noise
State technological deficiency.
The system for improving proton magnetic precession Signal-to-Noise, the system for improving proton magnetic precession Signal-to-Noise, such as Fig. 1 institute
Show, including dynamical nuclear polarization weak magnetic sensor, exciting circuit, tuning circuit, amplifying circuit, narrow-band filtering circuit, comparison circuit,
Collector, FPGA and controller；
Dynamical nuclear polarization sensor receives the pumping signal that exciting circuit issues, and induces FID signal, and pass to tuning
Circuit；After tuning circuit is tuned signal, amplifying circuit is passed to；After amplifying circuit amplifies signal, by its point
Supplementary biography passs narrow-band filtering circuit, comparison circuit and collector；After narrow band filter carries out bandpass filtering to signal, passed
It is defeated by comparison circuit；After comparison circuit carries out shaping to signal, passes it to FPGA and carry out later period signal processing；Collector with
Controller connection, carries out the acquisition and processing of data；Controller is connect with exciting circuit, controls unlatching and the pass of pumping signal
It closes；Controller is connect with FPGA, carries out frequency measurement to FID signal；Controller is connected with narrow band filter, adjusts its narrowband
Centre frequency.
Further, controller is used for by driving exciting circuit stimulus sensor internal solution that sensor is made to export first
FID signal, waits preset time after the completion of excitation, driving collector acquires first FID signal, generates discrete data；Root
Space matrix is constructed according to the discrete data, and principal component is carried out to the space matrix using PCA algorithm and svd algorithm respectively
Separation and singular value decomposition obtain reconstruct data with cancelling noise；The reconstruct data are handled using fft algorithm, described in acquisition
The corresponding first frequency value of maximum peak voltage in first FID signal frequency spectrum；By the inductance value of the sensor and described first
Frequency values substitute into LC resonance equations first capacitor value, and drive tuning circuit by the tuning capacitance with the sensor parallel
Capacitance be switched to the first capacitor value by zero；
It is also used to drive exciting circuit stimulus sensor internal solution that sensor is made to export the second FID signal again, swashs
Preset time is waited after the completion of encouraging, driving FPGA measures the second frequency value of second FID signal；By the electricity of the sensor
Inductance value and the second frequency value substitute into the second capacitance of LC resonance equations, and drive tuning circuit by the tuning capacitance
Capacitance second capacitance is switched to by the first capacitor value；
It is also used to drive exciting circuit stimulus sensor internal solution that sensor is made to export third FID signal again；Its
It is also used to set the second frequency value for the centre frequency of the narrow-band filtering circuit；It is also used to drive FPGA measurement whole
The third frequency values of the third FID signal after shape, and the FID that the third frequency values are detected as the sensor
The rate-adaptive pacemaker of signal.
Further, exciting circuit, which is used for the stimulus sensor internal solution under the driving of controller, makes sensor output the
One FID signal；It, which is also used to the stimulus sensor internal solution under the driving of the controller, makes sensor export the 2nd FID letter
Number；It, which is also used to the stimulus sensor internal solution under the driving of the controller, makes sensor export third FID signal.
Further, tuning circuit is used for the appearance of the tuning capacitance with the sensor parallel under the driving of controller
Value is switched to the first capacitor value by zero；It is also used under the driving of the controller by the capacitance of the tuning capacitance by
The first capacitor value is switched to second capacitance；It is also used to the tuning capacitance under the driving of the controller
Capacitance the third capacitance is switched to by second capacitance.
Further, the first FID signal is amplified, is used for waiting preset time after the completion of motivating by amplifying circuit
It is acquired in the collector；It is also used to motivate after the completion of wait preset time, the second FID signal is amplified, for than
Compared with circuit shaping；It is also used to wait preset time after the completion of motivating, and amplifies to the third FID signal, for described
Narrow-band filtering circuit filtering；Narrow-band filtering circuit, which is used for the frequency centered on second frequency value, believes amplified 3rd FID
It number is filtered, is used for comparison circuit shaping.
Further, comparison circuit is used to amplified second FID signal carrying out shaping, measures for FPGA；It is also
For carrying out shaping to the filtered third FID signal, measured for the FPGA.
Further, FPGA is used to measure the second frequency value of the second FID signal under the driving of the controller；It is also
For measuring the third frequency values of the third FID signal after shaping.
Further, collector generates discrete data for acquiring first FID signal under the driving of controller.
The method for improving proton magnetic precession Signal-to-Noise, it is real based on the system for improving proton magnetic precession Signal-to-Noise
It is existing, comprising:
S1, dynamical nuclear polarization sensor 400ms is motivated using controller driving exciting circuit, exports the first FID signal, and
Signal is passed into tuning circuit, tuning circuit passes it to collector after amplifying signal；
After the completion of S2, the sample rate that collector is set, sampling number, acquisition signal time, frequency resolution and excitation etc.
To preset time, first FID signal is acquired using the collector set, generates discrete data, and send data to
Controller；
S3, space matrix is constructed according to the discrete data using controller, and using PCA and svd algorithm to the sky
Between matrix carry out principal component separation and singular value decomposition respectively with cancelling noise, obtain reconstruct data；
S4, in the controller handles the reconstruct data using fft algorithm, obtains in the first FID signal frequency spectrum most
The corresponding first frequency value of big crest voltage；
The inductance value of the sensor and the first frequency value are substituted into LC resonance equations by S5, in the controller
First capacitor value, and be switched to by zero with the capacitance in the tuning circuit of the sensor parallel using controller driving described
First capacitor value；
S6, exciting circuit is driven using controller, stimulus sensor 100ms exports the second FID signal again, and excitation is completed
After wait preset time, and transmit a signal to tuning circuit, after tuning after transmit a signal to amplifying circuit, it is amplified will
Signal is transmitted to comparison circuit and carries out shaping to signal, and the signal after shaping is transmitted to FPGA；Described in being obtained using FPGA
The second frequency value of second FID signal；The inductance value of the sensor and the second frequency value are substituted into LC resonance formula to ask
The second capacitance is solved, and electric by described first with the capacitance in the tuning circuit of the sensor parallel using controller driving
Capacitance is switched to second capacitance；
S7, exciting circuit is driven using controller, stimulus sensor 100ms exports third FID signal again, and excitation is completed
After wait preset time, and transmit a signal to tuning circuit, after tuning after transmit a signal to amplifying circuit；Utilize controller
Narrow-band filtering circuit is driven, using the second frequency value as its centre frequency to the 3rd FID after amplifying circuit
Signal is filtered, and the filtered third FID signal is transmitted to comparison circuit and carries out shaping, and by the letter after shaping
Number it is transmitted to FPGA；The third frequency values of the third FID signal after shaping are obtained using FPGA, and by the third frequency
The frequency for the FID signal that value is detected as the sensor.
Further, step S3 is specifically included:
After S31, controller driving exciting circuit first time stimulus sensor generate the first FID signal, by amplifying circuit
It is amplified, then it is recorded using collector, obtains discrete data x=[x1,x2,…,xn], and be transmitted to
Controller；
S32, new space matrix m is constructed using controller:
S33, in the controller carries out principal component analysis to space matrix m using PCA algorithm, by purified signal and makes an uproar
Acoustical signal is separated, to obtain new discrete data x '=[x1’,x2’,…,xn']；
S34, new space matrix Σ is constructed using controller:
S35, in the controller uses svd algorithm to carry out singular value decomposition to the space matrix Σ further to reject
Noise obtains reconstruct data.
Compared with prior art, the beneficial effects of the present invention are:
1, using PCA algorithm in such a way that svd algorithm combines, inhibit to be attached on FID signal on software view
Unknown noise；
2, using program-controlled narrow-band filtering wave circuit, making an uproar outside FID signal center frequency-band is further suppressed on hardware view
Sound；
3, by the tuning manner of soft or hard combination, effectively overcome that existing tuning algorithm tuned speed is slow, under interference environment
Tuning precision is low, the defects of detuning phenomena easily occurs.
Detailed description of the invention
Present invention will be further explained below with reference to the attached drawings and examples, in attached drawing:
Fig. 1 is the system construction drawing of raising proton magnetic precession Signal-to-Noise of the invention；
Fig. 2 is the method flow diagram of raising proton magnetic precession Signal-to-Noise of the invention；
Fig. 3 is filter effect of embodiment of the present invention comparison diagram.
Specific embodiment
For a clearer understanding of the technical characteristics, objects and effects of the present invention, now control attached drawing is described in detail
A specific embodiment of the invention.
The system for improving proton magnetic precession Signal-to-Noise, as shown in Figure 1, including dynamical nuclear polarization weak magnetic sensor, swashing
Encourage circuit, tuning circuit, amplifying circuit, narrow-band filtering circuit, comparison circuit, collector, FPGA and controller；
Dynamical nuclear polarization sensor receives the pumping signal that exciting circuit issues, and induces FID signal, and pass to tuning
Circuit；After tuning circuit is tuned signal, amplifying circuit is passed to；After amplifying circuit amplifies signal, by its point
Supplementary biography passs narrow-band filtering circuit, comparison circuit and collector；After narrow band filter carries out bandpass filtering to signal, passed
It is defeated by comparison circuit；After comparison circuit carries out shaping to signal, passes it to FPGA and carry out later period signal processing；Collector with
Controller connection, carries out the acquisition and processing of data；Controller is connect with exciting circuit, controls unlatching and the pass of pumping signal
It closes；Controller is connect with FPGA, carries out frequency measurement to FID signal；Controller is connected with narrow band filter, adjusts its narrowband
Centre frequency.
Controller is used for by driving exciting circuit stimulus sensor internal solution that sensor is made to export the first FID signal,
Preset time is waited after the completion of excitation, driving collector acquires first FID signal, generates discrete data；According to it is described from
It dissipates data and constructs space matrix, and principal component separation and surprise are carried out to the space matrix using PCA algorithm and svd algorithm respectively
Different value is decomposed with cancelling noise, and reconstruct data are obtained；The reconstruct data are handled using fft algorithm, obtain the first FID letter
The corresponding first frequency value of maximum peak voltage in number frequency spectrum；The inductance value of the sensor and the first frequency value are substituted into
LC resonance equations first capacitor value, and drive tuning circuit by the capacitance of the tuning capacitance with the sensor parallel by zero
It is switched to the first capacitor value；
It is also used to drive exciting circuit stimulus sensor internal solution that sensor is made to export the second FID signal again, swashs
Preset time is waited after the completion of encouraging, driving FPGA measures the second frequency value of second FID signal；By the electricity of the sensor
Inductance value and the second frequency value substitute into the second capacitance of LC resonance equations, and drive tuning circuit by the tuning capacitance
Capacitance second capacitance is switched to by the first capacitor value；
It is also used to drive exciting circuit stimulus sensor internal solution that sensor is made to export third FID signal again；Its
It is also used to set the second frequency value for the centre frequency of the narrow-band filtering circuit；It is also used to drive FPGA measurement whole
The third frequency values of the third FID signal after shape, and the FID that the third frequency values are detected as the sensor
The rate-adaptive pacemaker of signal.
Exciting circuit, which is used for the stimulus sensor internal solution under the driving of controller, makes sensor export the first FID letter
Number；It, which is also used to the stimulus sensor internal solution under the driving of the controller, makes sensor export the second FID signal；It is also
For under the driving of the controller stimulus sensor internal solution make sensor export third FID signal.
Collector generates discrete data for acquiring first FID signal under the driving of controller.
Tuning circuit is for cutting the capacitance of the tuning capacitance with the sensor parallel by zero under the driving of controller
It is changed to the first capacitor value；It is also used to the capacitance of the tuning capacitance under the driving of the controller by described first
Capacitance is switched to second capacitance；It is also used under the driving of the controller by the capacitance of the tuning capacitance by
Second capacitance is switched to the third capacitance.
First FID signal is amplified for waiting preset time after the completion of motivating, is used for the acquisition by amplifying circuit
Device acquisition；It is also used to wait preset time after the completion of motivating, and the second FID signal is amplified, comparison circuit shaping is used for；
It is also used to wait preset time after the completion of motivating, and amplifies to the third FID signal, is used for the narrow-band filtering circuit
Filtering.
Narrow-band filtering circuit is used for the frequency centered on second frequency value and filters to amplified third FID signal
Wave is used for comparison circuit shaping；
Comparison circuit is used to amplified second FID signal carrying out shaping, measures for FPGA；It is also used to filtering
The third FID signal afterwards carries out shaping, measures for the FPGA.
FPGA is used to measure the second frequency value of the second FID signal under the driving of the controller；It is also used to measure
The third frequency values of third FID signal after shaping.
The method for improving proton magnetic precession Signal-to-Noise, as shown in Figure 2, comprising:
S1, dynamical nuclear polarization sensor 400ms is motivated using controller driving exciting circuit, exports the first FID signal, and
Signal is passed into tuning circuit, tuning circuit passes it to collector after amplifying signal；
S2, exponentially decay due to FID signal, it is therefore necessary to which suitable A/D sample rate and sampling number are set, it is known that ground
Signal magnetic field range is 20,000nT~100,000nT, is 850Hz according to the frequency range that FID signal can be obtained in magnetic rotaion comparison formula
~4,300Hz, therefore, in specific embodiment, the sample rate that collector is arranged is 10kHz, and sampling number is 2048 points, acquisition letter
Number time is about 205ms, frequency resolution 10kHz/2048=4.88Hz.Preset time 5ms is waited after the completion of excitation, is conducive to
Interference caused by circuit oscillation is excluded, first FID signal is acquired using the aforementioned collector set, generates dispersion number
According to, and send data to controller；
S3, space matrix is constructed according to the discrete data using controller, and uses PCA (principal component analysis) and SVD
(singular value decomposition) algorithm carries out principal component separation and singular value decomposition respectively to the space matrix with cancelling noise, is weighed
Structure data, specifically include:
After S31, controller driving exciting circuit first time stimulus sensor generate the first FID signal, by amplifying circuit
It is amplified, then it is recorded using collector, obtains discrete data x=[x1,x2,…,xn], and be transmitted to
Controller；
S32, new space matrix m is constructed using controller:
S33, in the controller carries out principal component analysis to space matrix m using PCA algorithm, by purified signal and makes an uproar
Acoustical signal is separated, to obtain new discrete data x '=[x1’,x2’,…,xn']；
S34, new space matrix Σ is constructed using controller:
S35, in the controller uses svd algorithm to carry out singular value decomposition to the space matrix Σ further to reject
Noise obtains reconstruct data；
S4, in the controller obtains described first using data are reconstructed described in FFT (fast Fourier transform) algorithm process
The corresponding first frequency value of maximum peak voltage in FID signal frequency spectrum；
The inductance value of the sensor and the first frequency value are substituted into LC resonance equations by S5, in the controller
First capacitor value, and be switched to by zero with the capacitance in the tuning circuit of the sensor parallel using controller driving described
First capacitor value.LC resonance formula is as follows:
In formula, f0, L and C be respectively frequency variable, inductance variable and capacitor variable；
S6, exciting circuit is driven using controller, stimulus sensor 100ms exports the second FID signal again, and excitation is completed
Preset time 5ms is waited afterwards, and transmits a signal to tuning circuit, amplifying circuit is transmitted a signal to after tuned, through amplifying
After transmit a signal to comparison circuit shaping carried out to signal, and the signal after shaping is transmitted to FPGA；It is obtained using FPGA
The second frequency value of second FID signal；It is public that the inductance value of the sensor and the second frequency value are substituted into LC resonance
Formula solves the second capacitance, and using controller driving and the capacitance in the tuning circuit of the sensor parallel by described the
One capacitance is switched to second capacitance；
S7, exciting circuit is driven using controller, stimulus sensor 100ms exports third FID signal again, and excitation is completed
Preset time 5ms is waited afterwards, and transmits a signal to tuning circuit, transmits a signal to amplifying circuit after tuned；Utilize control
Device processed drives narrow-band filtering circuit, using the second frequency value as its centre frequency to the third after amplifying circuit
FID signal is filtered, and the filtered third FID signal is transmitted to comparison circuit and carries out shaping, and will be after shaping
Signal be transmitted to FPGA；The third frequency values of the third FID signal after shaping are obtained using FPGA, and by the third
The frequency for the FID signal that frequency values are detected as the sensor.
The induction FID that the present invention exports rotary proton class sensor using the mode that PCA algorithm is combined with svd algorithm
Signal carries out principal component analysis and singular value decomposition processing respectively, can further suppress unknown noise, improves FID signal noise
Than；By the way of third harmonic tuning, first time actuated sensor exports the first FID signal, passes through PCA algorithm and svd algorithm pair
Signal carries out noise reduction process, and obtains an initial centre frequencies f in conjunction with fft algorithm1；Second of actuated sensor output second
FID signal, measurement FID signal frequency obtain f2, and secondary tune is completed with the centre frequency of this frequency adjustment narrow-band filtering circuit
It is humorous；Third time actuated sensor exports third FID signal, and measurement passes through the FID signal frequency f after narrow-band filtering at this time3, and with
This frequency finally tunes centre frequency as system.
As shown in figure 3, when to be followed successively by tuning capacitance be zero, collector is collected amplify through amplifying circuit it is untuned
The untreated frequency spectrum of FID signal, this FID signal are through existing auto-correlation algorithm (Auto Correlation) treated frequency spectrum
With the frequency spectrum of this FID signal gained reconstruct data composition after PCA&SVD algorithm process of the present invention；Comparison can be found through the present invention
Frequency spectrum after PCA&SVD algorithm process is distincter, and signal-to-noise ratio is higher.
To the currently used tuning method based on peak detection method and auto-correlation algorithm and the present invention is based on PCA&SVD algorithms
Third harmonic tuning method be tuned the comparative experiments of precision and speed, with the timer of controller to three kinds of tuning algorithm institute's used times
Between carry out timing.According to the design parameter of experiment porch, in same test magnetic field environment: testing location magnetic field is about 49,
323nT, i.e. 2100Hz；Sensor resonant -3dB frequency range: 2072Hz~2128Hz, sensors inductance value 34mH, in conjunction with LC
Resonance equation obtains tuning capacitance capacitance range: 168nF~173nF.As long as the tuning capacitance capacitance that i.e. three kinds of algorithms obtain exists
Within the scope of this, it can illustrate to tune successfully.In glitch-free environment, 5 observation is carried out to three kinds of methods respectively, result is such as
Shown in table 1.
The measurement result of the lower three kinds of methods of the noiseless environment of table 1
As can be seen from Table 1, from the point of view of the speed of tuning, since three kinds of algorithms are sequential programme structure, so program
The execution time is definite value, and the time used in peak detection method is about 5 times of auto-correlation algorithm and PCA&SVD algorithm；From the essence of tuning
From the point of view of degree, the obtained tuning capacitance value of three kinds of algorithms is within the scope of 168nF~173nF, more accurately.It can be said that
Bright, under noiseless environment, the performance of auto-correlation algorithm and PCA&SVD algorithm is suitable.
In the environment of interference, 5 observation is carried out to above-mentioned three kinds of methods respectively, the results are shown in Table 2.
The measurement result of the lower three kinds of methods of 2 interference environment of table
As can be seen from Table 2, when external environment has interference, the tuning precision of peak detection method and auto-correlation algorithm is bright
Aobvious decline, obtained tuning capacitance capacitance can make rotary proton class sensor detuning phenomena occur, reduce the signal-to-noise ratio of signal, from
And to apply has the instrument of rotary proton class sensor can not work normally；And the test result of PCA&SVD algorithm not by
To any influence, tuning precision is high, speed is fast and has repeatability.
In conclusion the present invention, which is used, realizes rotary proton by the method that PCA algorithm, svd algorithm and fft algorithm combine
The tuning of class sensor, effectively overcomes that existing tuning algorithm tuned speed is slow, tuning precision is low under interference environment, easy loses
The defects of adjusting phenomenon；While reducing tuning period, the tuning precision of rotary proton class sensor is improved, it can be achieved that wide measurement
Selection of the range to tuning capacitance improves the signal-to-noise ratio of later period measuring signal, is applied to rotary proton class magnetometer, optical pumping magnetic force
Instrument and nuclear magnetic resonance rotary proton FID signal imager etc. effectively improve instrument by the instrument of rotary proton class sensor
Performance.
The embodiment of the present invention is described with above attached drawing, but the invention is not limited to above-mentioned specific
Embodiment, the above mentioned embodiment is only schematical, rather than restrictive, those skilled in the art
Under the inspiration of the present invention, without breaking away from the scope protected by the purposes and claims of the present invention, it can also make very much
Form, all of these belong to the protection of the present invention.
Claims (10)
1. the system for improving proton magnetic precession Signal-to-Noise, which is characterized in that improving proton magnetic precession Signal-to-Noise is
System, as shown in Figure 1, including dynamical nuclear polarization weak magnetic sensor, exciting circuit, tuning circuit, amplifying circuit, narrow-band filtering electricity
Road, comparison circuit, collector, FPGA and controller；
Dynamical nuclear polarization sensor receives the pumping signal that exciting circuit issues, and induces FID signal, and passes to tuning electricity
Road；After tuning circuit is tuned signal, amplifying circuit is passed to；After amplifying circuit amplifies signal, distinguished
Pass to narrow-band filtering circuit, comparison circuit and collector；After narrow band filter carries out bandpass filtering to signal, transmitted
To comparison circuit；After comparison circuit carries out shaping to signal, passes it to FPGA and carry out later period signal processing；Collector and control
Device connection processed, carries out the acquisition and processing of data；Controller is connect with exciting circuit, controls the open and close of pumping signal；
Controller is connect with FPGA, carries out frequency measurement to FID signal；Controller is connected with narrow band filter, adjusts in its narrowband
Frequency of heart.
2. the system according to claim 1 for improving proton magnetic precession Signal-to-Noise, which is characterized in that controller is used for
By driving exciting circuit stimulus sensor internal solution that sensor is made to export the first FID signal, waited after the completion of excitation default
Time, driving collector acquire first FID signal, generate discrete data；Space matrix is constructed according to the discrete data,
And PCA algorithm and svd algorithm is used to carry out principal component separation and singular value decomposition respectively to the space matrix with cancelling noise,
Obtain reconstruct data；The reconstruct data are handled using fft algorithm, obtain peak-peak electricity in the first FID signal frequency spectrum
Press corresponding first frequency value；The inductance value of the sensor and the first frequency value are substituted into LC resonance equations first
Capacitance, and drive tuning circuit that the capacitance of the tuning capacitance with the sensor parallel is switched to the first capacitor by zero
Value；
It is also used to drive exciting circuit stimulus sensor internal solution that sensor is made to export the second FID signal again, has motivated
At rear waiting preset time, FPGA is driven to measure the second frequency value of second FID signal；By the inductance value of the sensor
The second capacitance of LC resonance equations is substituted into the second frequency value, and drives tuning circuit by the appearance of the tuning capacitance
Value is switched to second capacitance by the first capacitor value；
It is also used to drive exciting circuit stimulus sensor internal solution that sensor is made to export third FID signal again；It is also used
In setting the second frequency value for the centre frequency of the narrow-band filtering circuit；After it is also used to that FPGA is driven to measure shaping
The third FID signal third frequency values, and the FID signal that the third frequency values are detected as the sensor
Rate-adaptive pacemaker.
3. the system according to claim 1 for improving proton magnetic precession Signal-to-Noise, which is characterized in that exciting circuit is used
In under the driving of controller stimulus sensor internal solution make sensor export the first FID signal；It is also used in the control
Stimulus sensor internal solution makes sensor export the second FID signal under the driving of device processed；It is also used in the controller
Drive lower stimulus sensor internal solution that sensor is made to export third FID signal.
4. the system according to claim 1 for improving proton magnetic precession Signal-to-Noise, which is characterized in that tuning circuit is used
In the capacitance of the tuning capacitance with the sensor parallel is switched to the first capacitor value by zero under the driving of controller；
It is also used under the driving of the controller capacitance of the tuning capacitance being switched to described by the first capacitor value
Two capacitances；It is also used under the driving of the controller switch the capacitance of the tuning capacitance by second capacitance
For the third capacitance.
5. the system according to claim 1 for improving proton magnetic precession Signal-to-Noise, which is characterized in that amplifying circuit is used
Preset time is waited after the completion of excitation, the first FID signal is amplified, and is acquired for the collector；It is also used to swash
Preset time is waited after the completion of encouraging, the second FID signal is amplified, and is used for comparison circuit shaping；It is also used to motivate completion
After wait preset time, the third FID signal is amplified, be used for the narrow-band filtering circuit filtering；Narrow-band filtering electricity
Road is used for the frequency centered on second frequency value and is filtered to amplified third FID signal, is used for comparison circuit shaping.
6. the system according to claim 1 for improving proton magnetic precession Signal-to-Noise, which is characterized in that comparison circuit is used
In amplified second FID signal is carried out shaping, measured for FPGA；It is also used to believe filtered 3rd FID
Number carry out shaping, for the FPGA measure.
7. the system according to claim 1 for improving proton magnetic precession Signal-to-Noise, which is characterized in that FPGA is used for
The second frequency value of the second FID signal is measured under the driving of the controller；It is also used to measure the third FID signal after shaping
Third frequency values.
8. the system according to claim 1 for improving proton magnetic precession Signal-to-Noise, which is characterized in that collector is used for
First FID signal is acquired under the driving of controller, generates discrete data.
9. the method for improving proton magnetic precession Signal-to-Noise is realized based on the system for improving proton magnetic precession Signal-to-Noise,
It is characterised by comprising:
S1, dynamical nuclear polarization sensor 400ms is motivated using controller driving exciting circuit, exports the first FID signal, and will letter
Number tuning circuit is passed to, tuning circuit passes it to collector after amplifying signal；
It is waited after the completion of S2, the sample rate that collector is set, sampling number, acquisition signal time, frequency resolution and excitation pre-
If the time, first FID signal is acquired using the collector set, generates discrete data, and send data to control
Device；
S3, space matrix is constructed according to the discrete data using controller, and using PCA and svd algorithm to the spatial moment
Battle array carries out principal component separation and singular value decomposition respectively with cancelling noise, obtains reconstruct data；
S4, in the controller handles the reconstruct data using fft algorithm, obtains maximum peak in the first FID signal frequency spectrum
The corresponding first frequency value of threshold voltage；
The inductance value of the sensor and the first frequency value are substituted into LC resonance equations first by S5, in the controller
Capacitance, and described first is switched to by zero with the capacitance in the tuning circuit of the sensor parallel using controller driving
Capacitance；
S6, exciting circuit is driven using controller, stimulus sensor 100ms exports the second FID signal again, after the completion of excitation etc.
To preset time, and tuning circuit is transmitted a signal to, transmits a signal to amplifying circuit after tuned, it is amplified by signal
It is transmitted to comparison circuit and shaping is carried out to signal, and the signal after shaping is transmitted to FPGA；Described second is obtained using FPGA
The second frequency value of FID signal；The inductance value of the sensor and the second frequency value are substituted into LC resonance equations the
Two capacitances, and using the capacitance in the tuning circuit of controller driving and the sensor parallel by the first capacitor value
It is switched to second capacitance；
S7, exciting circuit is driven using controller, stimulus sensor 100ms exports third FID signal again, after the completion of excitation etc.
To preset time, and tuning circuit is transmitted a signal to, transmits a signal to amplifying circuit after tuned；It is driven using controller
Narrow-band filtering circuit, using the second frequency value as its centre frequency to the third FID signal after amplifying circuit
It is filtered, and the filtered third FID signal is transmitted to comparison circuit and carries out shaping, and the signal after shaping is passed
Transport to FPGA；The third frequency values of the third FID signal after shaping are obtained using FPGA, and the third frequency values are made
For the frequency for the FID signal that the sensor detects.
10. the method according to claim 9 for improving proton magnetic precession Signal-to-Noise, which is characterized in that step S3 tool
Body includes:
After S31, controller driving exciting circuit first time stimulus sensor generate the first FID signal, by amplifying circuit to it
It amplifies, then it is recorded using collector, obtain discrete data x=[x1,x2,…,xn], and it is transmitted to control
Device；
S32, new space matrix m is constructed using controller:
S33, in the controller carries out principal component analysis to space matrix m using PCA algorithm, purified signal and noise is believed
It number is separated, to obtain new discrete data x '=[x1’,x2’,…,xn']；
S34, new space matrix Σ is constructed using controller:
S35, in the controller uses svd algorithm to carry out singular value decomposition to the space matrix Σ with further cancelling noise,
Obtain reconstruct data.
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