CN114353844B - Fiber bragg grating signal demodulation method - Google Patents
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Abstract
The invention discloses a fiber bragg grating signal demodulation method, which comprises the following steps: generating light waves with different wavelengths by setting parameters of a laser generating device to obtain an original signal containing noise; the method comprises the steps of (1) adopting a wavelet denoising mode for an original signal containing noise to obtain a signal for eliminating common noise; performing optimal prediction variable threshold processing on the signal for eliminating the common noise to obtain a special clutter denoising signal; the special clutter specifically refers to light waves of which the peak value exceeds other peak values by a certain preset value; carrying out 5-point smoothing treatment on the special clutter de-noised signal to obtain a smoothed signal; deriving the smoothed signal to obtain a peak differential signal; setting a threshold value, and retaining the signal when the peak differential signal is greater than the threshold value; and when the signal is smaller than the threshold value, indicating that the signal drifts, and performing early warning processing. The beneficial effects of the invention are as follows: the noise processing speed of the fiber grating signal is improved, and the signal processing speed is simple and accurate in calculation.
Description
Technical Field
The invention relates to the field of grating signal processing, in particular to a fiber grating signal demodulation method.
Background
Compared with the transmission means of the prior electronic sensor, the fiber Bragg grating sensor (FBG) has been paid attention to the characteristics of passivity, intrinsic safety, electromagnetic interference resistance, easiness in networking and the like in the application process. The sensitivity of the FBG sensor to the physical parameters of the measured object is represented by the drift of the central wavelength of the reflected optical signal, wherein the most important factors are temperature, stress and the like. The change of the physical quantity to be measured changes the refractive index and period of the fiber core of the grating, so that the central wavelength of the fiber core of the grating is influenced to drift to a certain extent. Based on the characteristics, the FBG sensing method can be packaged in a certain mode according to the characteristics of different sensing physical quantities, and senses various to-be-measured temperatures, pressures, displacements and the like, so that the key technology for further practical application of the FBG sensing method is how to accurately measure the micro-drift of the central wavelength of the FBG sensing method
However, the prior art has the following defects:
1. is greatly affected by external interference. The unbalanced Mach-Zehnder interferometry and the unbalanced Michelson interferometry are suitable for being used in the aspect of dynamic measurement, but are extremely susceptible to the influence of external parameter changes;
2. the chirp phenomenon is liable to occur. The sensitivity of the matched grating method is higher, but the chirp phenomenon is easy to occur, and the measurement range is limited to a certain extent;
3. the accuracy is not sufficient. The edge filtering method and the CCD light splitting method have the defects in the aspects of determining a reasonable working interval, demodulation precision and frequency respectively;
4. the demodulation range is limited. The tunable F-P filtering method uses the most common demodulation method, but at a high scanning rate, the inherent nonlinear effect and demodulation range have a certain limiting effect on the demodulation performance of the system, and the system is complex.
Disclosure of Invention
In order to solve the technical problems, the technical scheme of the invention provides a fiber bragg grating signal demodulation method, which is a method for carrying out peak searching based on slopes on two sides of a grating signal waveform, and comprises the following steps:
s101: and (3) grating signal acquisition: generating light waves with different wavelengths by setting parameters of a laser generating device; the light wave is distributed to the FBG fiber bragg grating through the coupler, returns through the light path, and is demodulated through photoelectric conversion to obtain an original signal containing noise;
s102: denoising the common signal: the method comprises the steps of (1) adopting a wavelet denoising mode for an original signal containing noise to obtain a signal for eliminating common noise;
s103: special clutter denoising: performing optimal prediction variable threshold processing on the signal for eliminating the common noise to obtain a special clutter denoising signal; the special clutter specifically refers to light waves of which the peak value exceeds other peak values by a certain preset value;
s104: obtaining a smooth signal; carrying out 5-point smoothing treatment on the special clutter de-noised signal to obtain a smoothed signal;
s105: peak differential signal acquisition: deriving the smoothed signal to obtain a peak differential signal;
s106: drift monitoring: setting a threshold value, and retaining the signal when the peak differential signal is greater than the threshold value; and when the signal is smaller than the threshold value, indicating that the signal drifts, and performing early warning processing.
Further, the laser generating device parameters are an output wavelength range, a scanning frequency and a stepping frequency.
Further, the light waves with different wavelengths specifically refer to: the laser generating device is arranged at C wave band from wavelength lambda 1 To wavelength lambda 2 The signals of different wavelengths are periodically scanned out in steps delta.
Further, the specific process of step S102 is as follows:
s201: performing scale wavelet decomposition on an original signal containing noise in a wavelet denoising mode;
s202: extracting wavelet coefficients of signals under each scale, and removing the wavelet coefficients;
s203: and reconstructing the signal by adopting inverse wavelet transformation to obtain a signal for eliminating common noise.
Further, in step S103, the optimal prediction variable threshold is specifically expressed as follows:
wherein th 3 The optimal prediction variable threshold value; η' = (s N -N x )/N x ,S N Is N x Sum of squares of individual wavelet decomposition coefficients; />Is a soft threshold; />Is a hard threshold; sign () represents a sign function; lambda (lambda) x Is a preset threshold.
Further, the optimal prediction variable thresholding in step S103 specifically refers to: and when the clutter peak value exceeds the optimal prediction variable, eliminating the clutter peak value, otherwise, keeping the clutter peak value.
In step S105, the peak differential signal is specifically a solution of the peak abscissa X by peak differential Peak to peak ：
X Peak to peak ＝(X 1 +X 2 )/2
Wherein X is 1 For K 1MAX Corresponding abscissa; k (K) 1MAX The positive maximum value of the slope exists corresponding to the peak differentiation; x is X 2 For K -1MAX Corresponding abscissa; k (K) -1MAX The slope that exists for peak differentiation corresponds to the inverse maximum.
Compared with the prior art, the invention has the beneficial effects that: the noise processing speed of the fiber grating signal is improved, and the signal processing speed is simple and accurate in calculation.
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FIG. 1 is a schematic flow chart of a fiber grating signal demodulation method provided by the invention;
FIG. 2 is a schematic diagram of the output mode of the scanning laser module of the present invention;
FIG. 3 is a schematic representation of the noise-containing raw signal obtained after one cycle of scanning in accordance with the present invention;
FIG. 4 is a signal after common noise cancellation;
FIG. 5 is a flow chart of the basic principle of wavelet denoising according to the present invention;
FIG. 6 is a signal diagram of special clutter denoising;
fig. 7 is a schematic diagram of a peak differential signal.
Detailed Description
The present invention will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
The invention provides a fiber grating signal demodulation method. Referring to fig. 1, fig. 1 is a flow chart of the method of the present invention; the method comprises the following steps:
s101: and (3) grating signal acquisition: generating light waves with different wavelengths by setting parameters of a laser generating device; the light wave is distributed to the FBG fiber bragg grating through the coupler, returns through the light path, and is demodulated through photoelectric conversion to obtain an original signal containing noise;
as one embodiment, the laser generating device of the present invention employs a scanning laser module;
the light waves with different wavelengths specifically refer to: the laser generating device is arranged at C wave band from wavelength lambda 1 To wavelength lambda 2 Periodically scanning and outputting signals with different wavelengths by a step delta;
referring to fig. 2, fig. 2 is an output mode of the scanning laser module. As an example, the scanning laser module of the present invention periodically scans out different wavelength signals in steps 1GHZ (or 8 pm) from 1528nm to 1568nm in the C-band, and the module includes two trigger output signals, trigger output signal 2 (the second count output in fig. 1) generating a rising edge at the first wavelength output at the beginning of each scanning period, and trigger output signal 1 (the first count output in the figure) generating a rising edge at each wavelength output. The principle is as follows:
the user's amplifying and sampling circuit starts counting at the rising edge of the trigger output signal 2 of each period, samples the value of each path PD at each rising edge of the trigger output signal 1 while counting the trigger output signal 1 before the next rising edge of the trigger output signal 2.
The peak wavelength position of the final PD can be calculated by scanning the start wavelength, the step size, and the count value of the trigger output signal 1.
In this process, the core is a scanning laser module, and the output wavelength range, the scanning frequency, the output mode and the step size of the scanning laser are set by the host computer.
Preferably, the laser is arranged in the system in steps of 1GHz, and the wavelength with the circulating output power of 20mW in the range of 196250-191150GHz is arranged.
For example: the module scans the initial wavelength to 191700GHZ, the scanning step length is 1GHZ, the peak response of PD is at trigger output signal 1=1001 through the counting and PD sampling of trigger output signal 1, and the emission wavelength of the fiber bragg grating can be easily counted through calculating the peak wavelength position to 191700+1001x1-1= 192700 GHZ.
Referring to fig. 2, the output signals 1 and 2 are synchronous signals, wherein the output synchronous signal 1 is denoted as S 1 The output synchronization signal 2 is denoted as S 2 。
When the S2 trigger is to set the initial wavelength as lambda 0 Each time the synchronization signal 1 is triggered, the trigger time is Δt, and there are:
λ t1 ＝Δλn t1 +λ 0
λ t2 ＝Δλn 2 +λ 0
the circuit acquisition signal is set to be deltat/10 in order to improve the calculation accuracy.
Assuming that N sets of data points are now acquired, each set of data points has coordinates (λ i ,I i ) I=1, 2,3 Λn. there are:
when the measured physical quantity such as temperature, strain, concentration and the like changes, the grating period (temperature and strain) or the effective refractive index (concentration) of the fiber core changes, the light meeting the central wavelength is reflected and the wavelength shifts. I.e. the centre wavelength is defined by lambda B Drift to lambda' B When the upper computer triggers continuous scanning, the original signal containing noise can be obtained.
The image features of the FBG reflection spectrum have a narrow band. The side mode has the characteristics of high inhibition ratio, high reflectivity, steeper and smooth two sides of the spectrum, approximate Gaussian curve of the whole spectrum and the like, but the obtained reflection spectrum is deformed due to the influence of external factors such as grating materials, manufacturing processes and the like. Referring to fig. 3, fig. 3 is a diagram of a noise-containing original signal, specifically a noise-containing original grating peak value, obtained after scanning a period according to the present invention;
s102: denoising the common signal: the method comprises the steps of (1) adopting a wavelet denoising mode for an original signal containing noise to obtain a signal for eliminating common noise;
the specific process of step S102 is as follows:
s201: performing scale wavelet decomposition on an original signal containing noise in a wavelet denoising mode;
as an embodiment, the present invention further explains the wavelet de-noising correlation principle as follows:
let L be 2 (R) is a wavelet function space,is a square integrable function, the function space is +.>The functional space formed, i.e.)>
Fourier transform of->Satisfies the following formula:
wherein the method comprises the steps ofIs wavelet base>Is->Is a fourier transform function of (a).
The function, which generally has better time-frequency locality, can be a wavelet basis function.
S202: extracting wavelet coefficients of signals under each scale, and removing the wavelet coefficients;
as an embodiment, the noise-containing signal of the FBG is denoised by wavelet transformation, namely, the signal is decomposed into wavelet coefficients by translational transformation and scale expansion transformation of wavelet basis functions, and the wavelet basis functions are used for the noise-containing signalAfter expansion and translation, the device becomes:
g in 1 And h 1 The scale-up factor and the translation factor respectively,is given as g 1 And h 1 Due to g 1 And h 1 Is continuously transformed. Arbitrary function f of L2 (R) space 1 (t) in a smallBo Ji (wave radical)>Under expansion, then is a function f 1 The continuous wavelet transform of (t) has the transform formula:
wherein the method comprises the steps ofConjugation is carried out to obtain +.>The transformed function is a two-dimensional function, so that wavelet transformation is a process of transforming signals from one dimension to two dimensions, and is beneficial to analysis of time-frequency characteristics.
S203: and reconstructing the signal by adopting inverse wavelet transformation to obtain a signal for eliminating common noise.
As one example, the inverse transform and wavelet transform processes are reversed and can be expressed as:
referring to fig. 4, fig. 4 is a signal after common noise is removed; referring to fig. 5, fig. 5 is a flowchart illustrating the basic principle of wavelet denoising according to the present invention;
s103: special clutter denoising: performing optimal prediction variable threshold processing on the signal for eliminating the common noise to obtain a special clutter denoising signal; the special clutter specifically refers to light waves of which the peak value exceeds other peak values by a certain preset value;
as an example, it can be seen from fig. 4 that the signal after noise cancellation is significantly better than that of fig. 2, but there are two more prominent abnormal peaks after the 1 st and 2 nd peaks in fig. 4, so that the prominent miscellaneous peaks are eliminated by using a threshold method;
the invention adopts the optimal prediction variable threshold value, which is the combination of a soft threshold value and a hard threshold value method;
in step S103, the optimal prediction variable threshold is specifically expressed as follows:
wherein th 3 The optimal prediction variable threshold value; η' = (s N -N x )/N x ,S N Is N x Sum of squares of individual wavelet decomposition coefficients; />Is a soft threshold; />Is a hard threshold; sign () represents a sign function; lambda (lambda) x Is a preset threshold.
The optimal prediction variable thresholding in step S103 specifically refers to: and when the clutter peak value exceeds the optimal prediction variable, eliminating the clutter peak value, otherwise, keeping the clutter peak value. Referring to fig. 6, fig. 6 is a schematic diagram of special clutter denoising.
S104: obtaining a smooth signal; carrying out 5-point smoothing treatment on the special clutter de-noised signal to obtain a smoothed signal;
as an example, the method of the present invention for 5-point smoothing processing is explained as follows.
The principle of the 5-point smoothing process, specifically the 5-point moving average process, is to weight average five adjacent data points as follows:
where n is the number of data points, i=1, 2. The number of smoothing times was set to 1000 times.
S105: peak differential signal acquisition: deriving the smoothed signal to obtain a peak differential signal;
the smoothed signal becomes smoothed and then differentiated, the first derivative reflects the change in slope of the spectral curve, while the gaussian function has a larger slope change near the peak, i.e.:
Δx＝dx
Δy＝y(x+Δx)-y(x)
dy＝f'(x)dx
therefore, the spectrum after the smoothing is subjected to one-time derivation, and the slope of the peak waist on the left side and the right side of the approximate Gaussian curve peak is found, so that the central point of the maximum value and the minimum value of the same peak is the central wavelength of the grating. Referring to fig. 7, fig. 7 is a schematic diagram of a peak differential signal.
S106: drift monitoring: setting a threshold value, and retaining the signal when the peak differential signal is greater than the threshold value; and when the signal is smaller than the threshold value, indicating that the signal drifts, and performing early warning processing.
As one embodiment, the current value of the threshold G is set to be reserved when the current value of the threshold G is larger than the threshold G, and when the current value is smaller than the threshold, the current value is set to be zero, namely:
it can be seen from FIG. 7 that the differential graph corresponding to each peak has a slope forward maximum K 1MAX And an inverse maximum value K -1MAX ，K 1MAX The corresponding abscissa is X 1 ，K -1MAX The corresponding abscissa is X 2 Namely the abscissa of the peak:
X peak to peak ＝(X 1 +X 2 )/2
When the stress or the temperature changes, the central wavelength is shifted, a threshold interval is set, whether the monitoring range is met or not is judged through the shift quantity of the peak value center, and if the monitoring range is not met, the pre-alarm processing is carried out through signal transmission.
It should be understood that the sequence number of each step in the foregoing embodiment does not mean that the execution sequence of each process should be determined by the function and the internal logic of each process, and should not limit the implementation process of the embodiment of the present application in any way.
The beneficial effects of the invention are as follows:
1. and quickly removing noise: different noises can be generated by the difference of the hardware circuits, and the noise can be removed rapidly through an algorithm, so that the detection requirement of an online monitoring system can be met.
2. The center wavelength is rapidly determined: since the waveform is dynamic in real time, scanning of the center wavelength is critical and the wavelength of the center can be quickly located by an algorithm.
3. The calculation is not complicated: after data acquisition, noise reduction is carried out, a threshold value is determined, a differential state is obtained after moving average is carried out, and the central wavelength is determined through slope determination.
The above-described embodiments of the present invention do not limit the scope of the present invention. Any other corresponding changes and modifications made in accordance with the technical idea of the present invention shall be included in the scope of the claims of the present invention.
Claims (5)
1. A demodulation method of fiber grating signals is characterized in that: the method comprises the following steps:
s101: and (3) grating signal acquisition: generating light waves with different wavelengths by setting parameters of a laser generating device; the light wave is distributed to the FBG fiber bragg grating through the coupler, returns through the light path, and is demodulated through photoelectric conversion to obtain an original signal containing noise;
s102: denoising the common signal: the method comprises the steps of (1) adopting a wavelet denoising mode for an original signal containing noise to obtain a signal for eliminating common noise;
s103: special clutter denoising: performing optimal prediction variable threshold processing on the signal for eliminating the common noise to obtain a special clutter denoising signal; the special clutter specifically refers to light waves of which the peak value exceeds other peak values by a certain preset value;
in step S103, the optimal prediction variable threshold is specifically expressed as follows:
s104: obtaining a smooth signal; carrying out 5-point smoothing treatment on the special clutter de-noised signal to obtain a smoothed signal;
s105: peak differential signal acquisition: deriving the smoothed signal to obtain a peak differential signal;
in step S105, the peak differential signal is specifically a solution of the peak abscissa X by peak differential Peak to peak ：
X Peak to peak ＝(X 1 +X 2 )/2
Wherein X is 1 For K 1MAX Corresponding abscissa; k (K) 1MAX The positive maximum value of the slope exists corresponding to the peak differentiation; x is X 2 For K -1MAX Corresponding abscissa; k (K) -1MAX Slope inverse maximum value corresponding to peak differentiation;
s106: drift monitoring: setting a threshold value, and retaining the signal when the peak differential signal is greater than the threshold value; and when the signal is smaller than the threshold value, indicating that the signal drifts, and performing early warning processing.
2. The fiber grating signal demodulation method as claimed in claim 1, wherein: the parameters of the laser generating device are an output wavelength range, a scanning frequency and a stepping frequency.
3. The fiber grating signal demodulation method as claimed in claim 2, wherein: the light waves with different wavelengths specifically refer to: the laser generating device is arranged at C wave band from wavelength lambda 1 To wavelength lambda 2 The signals of different wavelengths are periodically scanned out in steps delta.
4. The fiber grating signal demodulation method as claimed in claim 1, wherein: the specific process of step S102 is as follows:
s201: performing scale wavelet decomposition on an original signal containing noise in a wavelet denoising mode;
s202: extracting wavelet coefficients of signals under each scale, and removing the wavelet coefficients;
s203: and reconstructing the signal by adopting inverse wavelet transformation to obtain a signal for eliminating common noise.
5. The fiber grating signal demodulation method as claimed in claim 1, wherein: the optimal prediction variable thresholding in step S103 specifically refers to: and when the clutter peak value exceeds the optimal prediction variable, eliminating the clutter peak value, otherwise, keeping the clutter peak value.
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2000222387A (en) * | 1999-01-28 | 2000-08-11 | Shimadzu Corp | Peak detection method using wavelet transformation |
| CN105160070A (en) * | 2015-08-05 | 2015-12-16 | 中国电子科技集团公司第四十一研究所 | Self-adapting peak search method for spectrum of semiconductor laser |
| CN107843744A (en) * | 2017-10-27 | 2018-03-27 | 中南大学 | The Wavelength demodulation system and Wavelength demodulation method of optical fibre grating acceleration sensor |
| CN108154065A (en) * | 2016-12-02 | 2018-06-12 | 光子瑞利科技（北京）有限公司 | A kind of circumference early warning fiber-optic vibration signal acquisition and the method for denoising |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| JP2000222387A (en) * | 1999-01-28 | 2000-08-11 | Shimadzu Corp | Peak detection method using wavelet transformation |
| CN105160070A (en) * | 2015-08-05 | 2015-12-16 | 中国电子科技集团公司第四十一研究所 | Self-adapting peak search method for spectrum of semiconductor laser |
| CN108154065A (en) * | 2016-12-02 | 2018-06-12 | 光子瑞利科技（北京）有限公司 | A kind of circumference early warning fiber-optic vibration signal acquisition and the method for denoising |
| CN107843744A (en) * | 2017-10-27 | 2018-03-27 | 中南大学 | The Wavelength demodulation system and Wavelength demodulation method of optical fibre grating acceleration sensor |
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