CN-122017323-A - Frequency spectrum drift feedback method for improving real-time phase detection precision

CN122017323ACN 122017323 ACN122017323 ACN 122017323ACN-122017323-A

Abstract

The invention discloses a frequency spectrum drift feedback method for improving real-time phase detection precision in plasma density diagnosis. The method comprises the steps of taking an FPGA as a core platform, collecting reference and measurement signals containing three frequency components through an ADC, carrying out windowing FFT after cross-clock domain processing and ping pong storage to obtain frequency spectrum information, extracting frequency positions and dynamic tracking variation values of three peaks in two paths of signals through a multi-spectral peak identification and tracking algorithm, transmitting the frequency positions and dynamic tracking variation values to an upper computer to draw a trend curve, comparing actual frequencies with theoretical window widths, feeding back frequency spectrum drift early warning if the actual frequencies are out of range, otherwise, carrying out dynamic filtering on window widths of self-adaptive calculation of all frequency points, and finally outputting three paths of phase differences through IFFT, complex conjugate multiplication and arctangent operation. The method realizes real-time high-precision calculation of the phase difference of the multi-frequency signals, can adaptively process spectrum drift, effectively prevents spectrum peaks from overlapping, and remarkably improves the real-time performance, precision and reliability of plasma density diagnosis.

Inventors

YING YUE
DING BAOGANG
LI YAJUN

Assignees

华东师范大学
应悦

Dates

Publication Date: 20260512
Application Date: 20260209

Claims (7)

1. The utility model provides a frequency spectrum drift feedback method for improving real-time phase detection precision, which is characterized by comprising the following steps: S1, after a system receives an upper computer instruction, synchronously acquiring an external continuously input reference signal and a measurement signal through an ADC chip, wherein the reference signal and the measurement signal both comprise three signal components with different frequencies; S2, performing cross-clock domain processing on the acquired reference signals and the acquired measurement signals respectively, performing ping-pong storage operation on the processed signals, and performing subsequent pipeline processing on the data segments; s3, windowing the two paths of signal data segments processed in the step S2, and respectively performing Fast Fourier Transform (FFT) to obtain frequency domain information of the reference signal and the measurement signal; S4, analyzing frequency domain information, carrying out multi-spectral peak identification and tracking operation on the frequency domain information of each path of signal, identifying three amplitude maxima and corresponding actual frequency points, respectively comparing and calculating three dynamic tracking change values of the current processing data segment and the three frequency points stored after the last segment of data processing to track the positions of the actual frequency points in real time, uploading the three values and the three actual frequency point data to an upper computer to respectively draw corresponding frequency dynamic change trend curves, and comparing each actual frequency point with a preset theoretical frequency window width range. If any actual frequency point exceeds the corresponding theoretical frequency window width range, judging that the frequency spectrum drift occurs, sending a frequency spectrum drift early warning instruction to the upper computer, and if all the actual frequency points are located in the corresponding theoretical frequency window width range, executing step S5. And S5, calculating the self-adaptive window width range for each frequency point based on the three actual frequency points identified in the step S4. For the spectrum data of each signal, only reserving the data in the range of the self-adaptive window width, setting the data out of the range to zero, and simultaneously feeding back the self-adaptive window width data corresponding to the three actual frequency points to the upper computer; s6, respectively performing Inverse Fast Fourier Transform (IFFT) on the two paths of spectrum data processed in the step S5, then calculating phase differences corresponding to the three frequency components through complex conjugate multiplication and arctangent operation, and transmitting three groups of phase difference results to an upper computer.
2. The spectrum drift feedback method of real-time phase detection according to claim 1, wherein the multi-spectral peak identifying and tracking operation in step S4 specifically comprises: Three peak variables d 0 、d 1 、d 2 and corresponding frequency point position variables p 0 、p 1 、p 2 of the current data segment are set, three frequency point variables p 0 '、p 1 '、p 2 ' stored in the previous segment of data are set, and the dynamic tracking change value delta 0 、Δ 1 、Δ 2 and the initial value are all 0. Traversing the input frequency spectrum amplitude data stream, and for each current data d i , performing the following operations, wherein the corresponding frequency point position is p i : If d i >d 0 , assigning the current value of d 0 and the frequency point position p 0 thereof to d 1 and the corresponding frequency point position p 1 thereof, assigning the current value of d 1 and the frequency point position p 1 thereof to d 2 and the corresponding frequency point position p 2 thereof, letting d 0 =d i and recording the frequency point position p 0 =p i thereof; If the above condition is not satisfied and d 1 <d i <d 0 is satisfied, assigning the current value of d 1 and the frequency point position p 1 thereof to d 2 and the corresponding frequency point position p 2 thereof, and making d 1 =d i and recording the frequency point position p 1 =p i ,d 0 and the corresponding frequency point position p 0 thereof to remain unchanged; if the two conditions are not satisfied and d 2 <d i <d 1 is satisfied, d 2 =d i is made and the frequency point positions p 2 =p i ,d 0 and d 1 and the corresponding frequency point positions p 0 and p 1 are recorded to be unchanged; If the current data does not meet any of the conditions, all variables are kept unchanged; After the traversal is completed, d 0 、d 1 、d 2 is the identified three maximum peaks, and the corresponding frequency point position variable p 0 、p 1 、p 2 is the three actual frequency points. Comparing and calculating the p 0 '、p 1 '、p 2 'with the saved p 0 '、p 1 '、p 2 ', and executing the following operations: Δ 0 =p 0 -p 0 ';Δ 1 =p 1 -p 1 ';Δ 2 =p 2 -p 2 '. After execution, the p 0 、p 1 、p 2 value is saved to p 0 '、p 1 '、p 2 for the next trace operation.
3. The method for spectrum drift feedback for real-time phase detection according to claim 1, wherein the calculating the adaptive window width range in step S5 specifically comprises: Setting the current three peak frequency points as n 0 、n 1 、n 2 in sequence from low to high; If the requirement is satisfied that n i+1 -n i >6 for all i (i=0, 1), and the minimum distance between each n i and the spectrum zero point and the spectrum center point n k is greater than 3, a fixed window width range [ n i -3, n i +3] is allocated to each n i ; If the above condition is not satisfied, the dynamic window width [ L i , R i ] (integer part) is calculated for each frequency point n i according to the following rule: For n 0 , the left boundary L 0 is L 0 =n 0 /2 if the distance between n 0 and the spectrum zero point is less than or equal to 3, otherwise L 0 =n 0 -3, and the right boundary R 0 is R 0 =n 0 +(n 1 -n 0 )/2 if n 1 -n 0 is less than or equal to 6, otherwise R 0 =n 0 +3; For n 1 , the left boundary L 1 is L 1 =n 0 +(n 1 -n 0 )/2+1 if n 1 -n 0 is less than or equal to 6, otherwise L 1 =n 1 -3, and the right boundary R 1 is R 1 =n 1 +(n 2 -n 1 )/2 if n 2 -n 1 is less than or equal to 6, otherwise R 1 =n 1 +3; For n 2 , the left boundary L 2 is L 2 =n 1 +(n 2 -n 1 /2+1 if n 2 -n 1 is less than or equal to 6, otherwise L 2 =n 2 -3, and the right boundary R 2 is R 2 =n 2 +(n k -n 2 /2 if n k -n 2 is less than or equal to 6, otherwise R 2 =n 2 +3.
4. A phase measurement system comprising a spectral drift feedback mechanism, characterized in that the system is adapted to implement the method of any of claims 1 to 3, the system comprising: the signal acquisition module is used for continuously and synchronously acquiring reference signals and measurement signals containing three different frequency components through the ADC chip; the data preprocessing module is used for performing cross-clock domain processing and ping-pong storage on the two acquired signals and segmenting the data to support the subsequent module pipelining processing; The frequency spectrum analysis module is used for respectively carrying out windowing and Fourier transform (FFT) on the two paths of signals after pretreatment to obtain respective frequency domain information; the spectral peak identification, tracking and drift judging module is used for executing a multi-spectral peak identification and tracking algorithm to acquire three actual frequency points and corresponding dynamic tracking variation values thereof, uploading the three actual frequency points to an upper computer in real time, comparing the three actual frequency points with corresponding theoretical ranges, judging whether a spectral drift phenomenon occurs or not, and generating corresponding feedback instructions; the self-adaptive window width calculation and filtering module is used for calculating the respective self-adaptive window width range according to the three actual frequency points and filtering corresponding frequency spectrum data; The phase calculation module is used for performing IFFT transformation on the filtered frequency spectrum to obtain six groups of complex time domain signals, and performing pairwise complex conjugate multiplication and arctangent operation on the six groups of complex time domain signals to obtain three groups of phase difference results; And the communication interface module is used for receiving instructions and feeding back data with the upper computer.
5. The frequency spectrum drift feedback method for real-time phase detection according to claim 1, wherein the method is characterized in that the real-time performance and accuracy of plasma electron density detection are remarkably improved, the self-adaptive processing mechanism has excellent universality, not only completely meets the severe requirements of fusion experiments on the frequency stability of laser signals, but also provides reliable basis for experimenters to monitor plasma states in real time and adjust parameters in time, thereby comprehensively enhancing the stability and operation reliability of the system.
6. The method for identifying, tracking and calculating the window width of the multiple spectral peaks and the self-adapting window width according to claim 2 and 3, wherein the method can calculate the proper left window width and right window width for each peak according to the distribution of the actual peak points in each section of data spectrum, and compare the calculated left window width and the calculated right window width with the peak points of the previous section of data to judge the change trend. The method has the advantages that the effective spectrum interval containing main frequency energy is reserved to the greatest extent, and meanwhile, the interference of harmonic waves and noise is filtered to a certain extent, so that the problem of spectrum peak overlapping possibly caused by spectrum drift is effectively solved, and reliable data is provided for subsequent high-precision phase calculation.
7. The phase measurement system comprising the spectrum drift feedback mechanism according to claim 4, wherein the system greatly improves the processing speed and real-time performance of related data in fusion experiments, realizes extremely low and strictly controllable whole-course delay from external signal acquisition to phase result and drift state feedback, can continuously and stably monitor the experimental state of plasma in real time, and completely meets the strict requirements of the field of plasma diagnosis on high real-time performance and high precision.

Description

Frequency spectrum drift feedback method for improving real-time phase detection precision Technical Field The invention relates to the technical field of plasma density diagnosis, and particularly discloses a feedback method for spectrum drift, which improves real-time phase detection accuracy. Background The energy is a basic stone for human development, and the controllable nuclear fusion is regarded as the core of future energy due to the clean and efficient characteristics. The density, temperature and constraint time of the plasma are precisely controlled to realize fusion, wherein the real-time mastering of the plasma density parameters is particularly critical. Therefore, accurate diagnosis and monitoring of the electron density and the current density of the plasma are necessary, and the method is an important precondition for guaranteeing the progress of fusion research and the safe operation of the reactor. The far infrared laser diagnosis technology is widely applied to diagnosis of high-temperature plasmas because of various measurement means and no unnecessary disturbance and impurity pollution to plasmas, and in a nuclear fusion reaction device, the measurement of the electron density and the current density of the plasmas by using a far infrared laser polarization interferometer and the real-time feedback control become important means. The three-wave polarization interferometry is a common measurement method, and uses a laser to output three laser beams with slightly different frequencies, and polarization and interference signals can be obtained through optical beam combination and beam splitting design without additional grating modulation, so that errors caused by modulation are avoided, and measurement stability and accuracy are improved. The working principle of the device is that one of three beams of light is used as reference light and is directly coupled with a third beam of intrinsic light to enter a reference detector, and the other beam of light is used as detection light, passes through plasma, is influenced by the refractive index of the light to generate phase change, and is then coupled with the intrinsic light to enter the detector. The two paths of detectors respectively output a reference signal and a measurement signal which comprise three intermediate frequency. By comparing the phase difference of the two signals, the Faraday rotation angle and the plasma electron density can be calculated, and then the polar magnetic field distribution and the plasma current density are inverted. The schematic diagram is shown in figure 1. The stability of signal frequency in a three-wave polarization interference system is a key precondition for ensuring the accuracy of phase measurement. In the three-wave polarization interference system, three beat frequency signals generated by three lasers respectively correspond to beat frequencies of local oscillation light and left-right circular polarized light, and a fixed frequency spectrum sequence is required to be kept so as to realize correct physical quantity calculation. However, due to drift of the laser output frequency, even if the spectral order is unchanged, the beat peaks may be alternated, overlapped or excessively close, as shown in fig. 2, thereby generating serious crosstalk in the data processing, introducing significant noise to the system, and even possibly causing errors in the phase measurement results. Meanwhile, a long-term slow drift can accumulate huge systematic errors, and finally, the requirement of phase detection is difficult to meet. Therefore, the real-time monitoring of whether the laser signal has drift phenomenon or not and timely feedback have a vital effect on maintaining the stability of the signal and guaranteeing the accuracy of the system measurement result. The traditional phase detection technology mainly depends on software calculation, and is difficult to feed back plasma key parameters in real time, so that the monitoring instantaneity of key physical quantities such as electron density, current density and the like is poor. In addition, the structure and the function of a future nuclear fusion reactor are increasingly complex, the signal frequency to be detected is increased increasingly and possibly unstable, the spectrum peak is easy to overlap when the spectrum analysis is carried out, the precision of data processing and phase detection is seriously influenced, the error of a phase calculation result is finally larger, and the precise and safe regulation and control of a controllable nuclear fusion device are difficult to realize. Meanwhile, the prior art relies on manual judgment of signal frequency drift to maintain intermediate frequency signal stability, and flexibility and expansibility are obviously limited. Therefore, how to realize real-time monitoring and timely feedback of the stability of the mixed signals containing multiple frequencies, so as to reduce phase calculation errors