FBG / FPI multi-physical-quantity optical fiber sensing high-speed data acquisition and processing method based on FPGA

Abstract

The invention discloses an FBG / FPI multi-physical-quantity optical fiber sensing high-speed data collecting and processing method based on an FPGA, and belongs to the technical field of optical fiber sensing. The multi-physical-quantity optical fiber sensor comprises an FBG sensor, an FPI sensor and an FBG-FPI cascade sensor. The method comprises the steps that an ADC module samples spectrums returned by the sensors according to a control time sequence provided by an FPGA main control chip; carrying out pretreatment on the acquired spectrum data, wherein the pretreatment comprises the steps of judging the type of the sensing unit and segmenting the acquired spectrum; sending the sensing spectrum data obtained after segmentation into corresponding data processing modules according to the sensing types of the sensing spectrum data; and splicing and sending the processed resolving results of the different sensing units according to a specific rule. According to the invention, multiple physical quantities including vibration, pressure, temperature and strain can be sensed at the same time, and the sensor has the characteristics of large sensing capacity, high demodulation resolution and fast demodulation speed.

Description

Technical Field

[0001] The present invention relates to the field of optical fiber sensing technology, and more specifically, to an FPGA-based FBG / FPI multi-physical quantity optical fiber sensing high-speed data acquisition and processing method. Background Art

[0002] Fiber optic sensors, due to their resistance to electromagnetic interference, corrosion resistance, high sensitivity, and small size, are widely used in fields such as earthquake monitoring, medical diagnosis, and structural health testing. As quasi-distributed sensors, fiber Bragg Grating (FBG) and Fabry-Perot Interferometer (FPI) fiber optic sensors offer higher measurement accuracy and faster response speeds than conventional fiber optic distributed sensors. They are also sensitive to multiple physical quantities and are therefore ideal for simultaneous, high-precision measurement of multiple physical quantities, including vibration, pressure, temperature, and strain. Furthermore, composite sensors formed by cascading FBG and FPI sensing elements can further broaden the types of physical quantities that can be monitored and enhance the sensing capacity of the entire sensor network. Consequently, they are widely favored in the field of multi-physical quantity sensing.

[0003] To realize the sensing function of multiple physical quantities and meet the needs of diverse application scenarios, a flexible combination of multiple FBG sensors, FPI sensors and FBG-FPI cascade sensors is required. Each sensor is responsible for monitoring one or two physical quantities. To achieve multi-point measurement, there are certain requirements for the number of sensors distributed on the monitoring target. Therefore, compared with general fiber optic sensors, the entire data processing process of multi-physical quantity fiber optic sensing will have more time-consuming steps. Moreover, with the continuous expansion of the scale of fiber optic sensing networks in the future and the continuous improvement of the demodulation resolution requirements of fiber optic sensors, high-speed data real-time processing has become an urgent problem to be solved in this field. Summary of the Invention

[0004] In response to the existing technical bottlenecks, the purpose of the present invention is to: based on the data processing method provided by the present invention, the sensing device can achieve simultaneous multi-point, high-resolution, and high-speed sensing of various physical quantities including vibration, pressure, temperature, and strain.

[0005] To achieve the above technical objectives, the present invention proposes a FPGA-based FBG / FPI multi-physical quantity fiber optic sensing high-speed data acquisition and processing method, comprising the following steps:

[0006] caching a collected sensing spectrum of a multi-physical quantity sensor, wherein the sensing spectrum carries information of multiple physical quantities related to the monitored environment, and the multi-physical quantity sensor includes an FBG sensing element and / or an FPI sensing element;

[0007] While caching the current data, the sensor spectrum after the previous cache is pre-processed to obtain the FBG sensor spectrum and the FPI sensor spectrum, wherein the FBG sensor spectrum is sent to the FBG data processing module, and the FPI sensor spectrum is sent to the FPI data processing module through a polling mechanism;

[0008] In the FBG data processing module, the FBG sensing spectrum is demodulated based on the Gaussian fitting method to obtain the FBG reflection center wavelength, which can reflect the physical quantity monitored by the FBG;

[0009] In the FPI data processing module, the FPI sensing spectrum is demodulated based on the DFT method to obtain the cavity length value of the FP cavity in the FPI. The cavity length value can reflect the physical quantity monitored by the FPI;

[0010] The demodulation results are spliced together as the final output.

[0011] Furthermore, the step of caching the collected sensing spectrum includes:

[0012] The ADC module outputs the sensing spectrum data under the excitation clock provided by the FPGA, turns on the write enable of the dual-port RAM, and writes the data synchronously to the dual-port RAM. After the ADC module outputs, the write enable is turned off. After the write enable is turned off, the read enable of the dual-port RAM is turned on, and the previously written data is read under the control of the data processing domain excitation clock provided by the FPGA. After the data is read out, the write enable is turned off.

[0013] Furthermore, the step of pre-processing the buffered sensing spectrum includes:

[0014] According to the spectral characteristics of the two sensor elements, FBG and FPI, the sensor element type of the multi-physical quantity sensor is determined;

[0015] For the sensing spectrum containing two sensing elements, the distribution position of the FBG sensing spectrum in the composite spectrum is determined, and the composite spectrum is segmented according to its position to form the FBG sensing spectrum and the FPI sensing spectrum.

[0016] Furthermore, the step of determining the type of the sensing element includes:

[0017] Set the spectral intensity threshold and correspond a group of continuous data points with intensity higher than the threshold to one FBG element;

[0018] The collected sensing spectrum is Fourier transformed, and each characteristic peak in the non-DC region of the spectrum corresponds to an FPI element.

[0019] Furthermore, when the composite spectrum is segmented to form the FBG sensing spectrum and the FPI sensing spectrum, a group of continuous data points with intensities higher than a threshold is used as the initial FBG sensing spectrum, and the remaining spectrum after removing the initial FBG sensing spectrum data points is interpolated to form the FPI sensing spectrum; the interpolated value is used as the baseline of the FBG sensing spectrum on the composite spectrum, and the baseline is subtracted from the initial FBG sensing spectrum to obtain the FBG sensing spectrum for demodulation.

[0020] Furthermore, the workflow of transmitting FPI sensing spectrum through polling mechanism is as follows:

[0021] Set up parallel data processing modules. Initially, both modules are in idle state.

[0022] After obtaining the FPI sensor spectrum in the pre-processing step, the working status of the two data processing modules is queried in turn, and a data processing module in the idle state is selected, the FPI sensor spectrum is sent to the module, and its working status is changed to busy;

[0023] After a data processing module completes its calculation work, its working state is reset to idle state, waiting for the next data reception.

[0024] Furthermore, the FBG data processing module includes a shift register module, a peak data judgment and selection module, a Gaussian fitting module, and a sliding average module;

[0025] The workflow of the FBG data processing module is:

[0026] The input FBG sensing spectrum enters the shift register module with a limited length and shifts once under each clock excitation;

[0027] In each clock cycle, the peak data judgment and selection module performs peak judgment on the data in the shift register module and selects a certain number of FBG reflection peak data points for storage;

[0028] The Gaussian fitting module calculates the reflection center wavelength of each FBG element in turn by Gaussian fitting the FBG reflection peak data points;

[0029] The sliding average module performs window sliding average on the reflection center wavelength of each FBG element continuously output by the Gaussian fitting module, and uses the average value as the final calculated reflection center wavelength.

[0030] Furthermore, the FPI data processing module includes a spectrum shaping module, a discrete Fourier transform (DFT) module, a coordinate rotation digital computer (CORDIC) module, a phase unwrapping module, and a finite impulse response (FIR) filter module.

[0031] The workflow of the FPI data processing module is as follows:

[0032] The spectrum shaping module performs standardization on the input FPI sensing spectrum;

[0033] The normalized spectrum enters the DFT module, and the complex spectrum data obtained after DFT transformation enters the CORDIC module to further obtain the amplitude and phase of the complex spectrum data;

[0034] The unwrapping module unwraps the phase data and further calculates the cavity length data of the FP cavity based on the amplitude;

[0035] The FIR filter module filters the cavity length data output by the dewrapping module, and uses the filtered result as the final calculated cavity length value of the FP cavity.

[0036] Furthermore, the FBG data processing module and the FPI data processing module process the FBG sensing spectrum and the FPI sensing spectrum synchronously and in parallel in the FPGA.

[0037] Furthermore, the workflow of the FPI data processing module is divided into multiple processing steps of similar time consumption through pipeline technology, and registers for storing intermediate data are inserted between each step, and each processing step is executed simultaneously.

[0038] The present invention has the following beneficial effects:

[0039] The present invention automatically identifies the type of sensor element and segments the composite spectrum through spectral intensity threshold recognition and Fourier transform characteristic peak detection, enabling a single device to synchronously demodulate multiple physical quantities such as vibration, pressure, temperature, and strain. The independently operated FBG processing module works synchronously with the FPI processing module, and within the FPI module, the processing time is compressed to 1 / 3 of that of a single step through a three-stage pipeline step. The polling scheduling mechanism of the dual FPI modules dynamically allocates tasks to avoid processing bottlenecks. The cross-clock domain dual-port RAM design ensures the complete transmission of 30kHz high-frequency sampling data. This invention breaks through the efficiency bottleneck of traditional serial processing and provides a high-throughput, high-precision real-time demodulation platform for large-scale fiber optic sensor networks.

[0040] The present invention realizes unified high-speed and high-precision processing of FBG, FPI and FBG-FPI cascade sensors of unknown types and quantities, can simultaneously sense multiple physical quantities including vibration, pressure, temperature and strain, and has the characteristics of large sensing capacity, high demodulation resolution and fast demodulation speed. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 This is a flow chart of the FPGA-based FBG / FPI multi-physical quantity optical fiber sensing high-speed data acquisition and processing method proposed by the present invention.

[0042] Figure 2 This is a flowchart for using dual-port RAM to process data across clock domains.

[0043] Figure 3 To transmit spectral data to the FPI data processing module through a polling mechanism.

[0044] Figure 4 Schematic diagram of the pipeline execution of each processing step in the FPI data processing module.

[0045] Figure 5 Schematic diagram of a sensing device constructed according to the present invention.

[0046] Figure 6 This is the sensor spectrum of the collected FBG-FPI cascade sensor.

[0047] Figure 7 Demodulation stability of FBG-FPI cascade sensor. DETAILED DESCRIPTION

[0048] To make the objectives, technical solutions, and advantages of the present invention more apparent, the present invention will be described in detail and completely below with reference to the accompanying drawings and embodiments. It is apparent that the embodiments described are merely representative embodiments and are only a portion of the embodiments of the present invention, not all of them. The selected embodiments are intended to illustrate the present invention and are not intended to limit the present invention. Furthermore, those skilled in the art may combine or combine different embodiments of the present invention or technical features of different embodiments, unless they conflict with each other.

[0049] Example 1:

[0050] The embodiments of the present invention are used to describe the specific implementation details of the method proposed in the present invention, so that those skilled in the art can fully understand the present invention.

[0051] The present invention proposes a FBG / FPI multi-physical quantity optical fiber sensing high-speed data acquisition and processing method based on FPGA, comprising the following steps: Figure 1 As shown:

[0052] S1, collects and caches the sensing spectrum of the multi-physical quantity sensor, and at the same time reads out the previously cached spectrum data and performs pre-processing.

[0053] Here, the multi-physics sensor is:

[0054] one or more FBG sensors;

[0055] one or more FPI sensors;

[0056] Or a combination of one or more FBG sensors and one or more FPI sensors.

[0057] The sensing spectrum collected by the multi-physical quantity sensor carries a variety of physical quantity information related to the monitored environment, such as vibration, pressure, temperature, and strain. Two clock domains are set up inside the FPGA, namely the data acquisition domain and the data processing domain. The clock frequency of the data processing domain is higher than that of the data acquisition domain. In the data acquisition domain, the ADC module samples the spectrum returned by the multi-physical quantity fiber optic sensor according to the control timing provided by the FPGA main control chip. The transmission of the sampled data to the data processing domain has the problem of cross-clock domain security. Therefore, a dual-port RAM is used for data cross-clock domain processing and data caching to ensure the integrity of the transmitted data, including the following steps, such as Figure 2 As shown:

[0058] The ADC module outputs the sensing spectrum data under the excitation clock provided by the FPGA, turns on the write enable of the dual-port RAM, and writes the data synchronously to the dual-port RAM. After the ADC module output is completed, the write enable is turned off.

[0059] After the write enable is turned off, the read enable of the dual-port RAM is turned on. Under the control of the data processing domain excitation clock provided by the FPGA, the data that was previously cached is read out. After the data is read out, the read enable is turned off.

[0060] It should be noted that the ADC module is only one feasible option among many data sampling devices. Technicians in the same field can choose other data sampling devices according to their actual situation.

[0061] The buffered sensor spectrum is pre-processed to determine the type of sensor element of the sensor to be tested based on the spectral characteristics of the FBG and FPI sensor elements. The specific steps are as follows:

[0062] Set the spectrum intensity threshold, and correspond a group of continuous data points with intensity higher than the threshold to a FBG element, which is recorded as a data point on the reflection spectrum of the FBG element. The position of the central data point on the spectrum is recorded as p m , m is the sequence number of FBG elements arranged on the spectrum;

[0063] The collected sensing spectrum is Fourier transformed, and each characteristic peak in the non-DC region of the spectrum corresponds to an FPI element.

[0064] After determining the sensor element type, do the following different processing:

[0065] The sensor with only FBG elements transmits its sensing spectrum to the FBG data processing module;

[0066] The sensor with only FPI elements transmits its sensing spectrum to the FPI data processing module;

[0067] For sensors with both FBG and FPI elements, the sensing spectrum is segmented:

[0068] Remove the coordinates in (p m -n,p m The data points within the range of n (n) are used as the preliminary FBG sensor spectrum. The FPI sensor spectrum is obtained by interpolating the remaining spectrum, and the interpolated value is used as the baseline of the FBG spectrum on the composite spectrum. The baseline is subtracted from the preliminary FBG sensor spectrum to obtain the final FBG sensor spectrum for demodulation. In this embodiment, 2≤n≤5, preferably, n=2, and the interpolation method is linear interpolation.

[0069] S2, the spectral data of the FBG sensor element after pre-processing is sent to the FBG data processing module, and the spectral data of the FPI sensor element is sent to the FPI data processing module in a timely manner through the polling mechanism. The data processing in the two modules is carried out simultaneously.

[0070] Compared with the FBG data processing module, the FPI data processing module has more time-consuming steps. In order to enable the two modules to receive the corresponding spectra at the same time and ensure the consistency of the working timing of the two modules, the spectral data of the FPI sensor element is transmitted through the polling mechanism. The specific steps are as follows: Figure 3 As shown:

[0071] Set up two parallel FPI data processing modules, denoted as data processing module 1 and data processing module 2. Initially, both are in idle state.

[0072] After obtaining the FPI sensor spectrum in the pre-processing step, the working status of the two data processing modules is queried in turn, and a data processing module in the idle state is selected, the FPI sensor spectrum is sent to the module, and its working status is changed to busy;

[0073] After a data processing module completes its calculation work, its working state is reset to idle state, waiting for the next data reception.

[0074] S3, in the FBG data processing module, the FBG spectrum data is demodulated based on the Gaussian fitting method to obtain the reflection center wavelength of the FBG.

[0075] The FBG data processing module includes a shift register module, a peak data judgment and selection module, a Gaussian fitting module, and a sliding average module. The workflow is as follows:

[0076] A flag register is set up. After the sensor is determined to be a composite sensor through the sensing spectrum, the flag register is set to 1. If it is an FBG sensor, the flag register is set to 0.

[0077] The flag register is judged. When it is 1, the peak value of the FBG sensor spectrum has been determined by pre-processing and is directly passed to the Gaussian fitting module. When it is 0, the FBG sensor spectrum is passed to the shift register module with a limited length and shifted once under each clock excitation.

[0078] In each clock cycle, the peak data judgment and selection module performs peak judgment on the data in the shift register module. After determining the peak value, it selects and saves a certain number of FBG reflection peak data points.

[0079] The Gaussian fitting module calculates the reflection center wavelength of each FBG element in turn by Gaussian fitting the FBG reflection peak data;

[0080] The sliding average module performs sliding average of a suitable window on the reflection center wavelength continuously output by the Gaussian fitting module, and uses the average value as the final calculated reflection center wavelength.

[0081] S4, in the FPI data processing module, the DFT method is used to demodulate the FPI spectrum data to obtain the cavity length value of the FP cavity in the FPI.

[0082] The FPI data processing module includes a spectrum shaping module, a DFT module, a CORDIC module, a phase unwrapping module, and a FIR filter module. The workflow is as follows:

[0083] The spectrum shaping module performs standardization processing on the spectral data: the light source intensity envelope is pre-stored in the FPGA ROM to remove the envelope of each frame of the sensor spectrum. After removing the envelope, the average light intensity of the entire frame is calculated and the average value is subtracted from the spectral data to remove DC from the spectrum. The processed spectrum is interpolated and passed to the DFT module.

[0084] After the spectrum enters the DFT module, the complex spectrum data obtained by DFT transformation is further sent to the CORDIC module to obtain the amplitude and phase of the spectrum data;

[0085] The unwrapping module unwraps the phase data and further calculates the cavity length of the FP cavity;

[0086] The FIR filter module filters the cavity length data output by the dewrapping module. The filter coefficient is also pre-stored in the ROM of the FPGA, and the filtered result is used as the final calculated cavity length value of the FP cavity.

[0087] According to the time-consuming characteristics of the workflow, such as Figure 4 As shown in the figure, pipeline technology is used to divide the process into three steps with similar time consumption: normalization and interpolation (step 1), DFT transformation (step 2), phase unwrapping and result filtering (step 3). Registers for storing intermediate data are inserted between the three steps, and each step is executed simultaneously, reducing the time consumption of the entire data processing process to about 1 / 3 of the original time consumption.

[0088] S5, judging the flag register of step S3, if it is 1, splicing the FBG and FPI demodulation results according to the rules agreed with the user, and then sending them to the user end; if it is 0, directly sending the results to the user end.

[0089] Example 2:

[0090] According to the data processing method proposed in the present invention, the following Figure 5 The sensor device shown in the figure is connected to a FBG-FPI cascade multi-physical quantity sensor. The FP cavity in the FPI sensor element has a length of about 600 μm and a spectral sampling rate of 30 kHz. The composite sensing spectrum collected by the device is as follows: Figure 6 As shown, the data is collected continuously for 60 seconds. During this period, the FPGA demodulates each frame of the spectrum according to the steps S1-S4. In order to facilitate display, the demodulated results are downsampled by 1kHz. The results are shown in Figure 7 Figure (a) shows the static stability of the FBG element, and Figure (b) shows the distribution of the center wavelength of the FBG element's reflection under static conditions. This indicates that the center wavelength of the experimentally demodulated FBG sensor element is concentrated at (1566.550±0.002) nm, with a calculated mean square error (MSE) of 0.60 pm. Figure (c) shows the static stability of the FPI element, and Figure (d) shows the distribution of the FP cavity length of the FPI element under static conditions. This indicates that the variation in the FP cavity length of the experimentally demodulated FPI sensor element is concentrated within ±0.6 nm, with a calculated mean square error (MSE) of 0.18 nm. Multiple sensors were replaced and stability tests were performed. The results showed that the sensor setup constructed using the data processing method proposed in this invention achieved a demodulation resolution of less than 1 pm for FBG and less than 0.3 nm for FPI, demonstrating that the high-speed data acquisition and processing method proposed in this invention can support the designed sensor device in achieving high-resolution and high-speed sensing.

[0091] Obviously, the above is only a representative embodiment of the present invention, and the present invention is not limited to the above embodiment. Any deformation formed by simply deriving, modifying, and improving the contents disclosed in the present invention without performing creative work should be deemed to be within the scope of protection of the present invention.

Claims

1. A FBG / FPI multi-physical quantity optical fiber sensing high-speed data acquisition and processing method based on FPGA, characterized in that: include: caching a collected sensing spectrum of a multi-physical quantity sensor, wherein the sensing spectrum carries information of multiple physical quantities related to the monitored environment, and the multi-physical quantity sensor includes an FBG sensing element and / or an FPI sensing element; While caching the current data, the sensor spectrum after the previous cache is pre-processed to obtain the FBG sensor spectrum and the FPI sensor spectrum, wherein the FBG sensor spectrum is sent to the FBG data processing module, and the FPI sensor spectrum is sent to the FPI data processing module through a polling mechanism; In the FBG data processing module, the FBG sensing spectrum is demodulated based on the Gaussian fitting method to obtain the FBG reflection center wavelength, which can reflect the physical quantity monitored by the FBG; In the FPI data processing module, the FPI sensing spectrum is demodulated based on the DFT method to obtain the cavity length value of the FP cavity in the FPI. The cavity length value can reflect the physical quantity monitored by the FPI; The demodulation results are spliced together as the final output.

2. The FPGA-based FBG / FPI multi-physical quantity optical fiber sensing high-speed data acquisition and processing method according to claim 1, characterized in that: The steps of caching the collected sensor spectrum include: The ADC module outputs the sensing spectrum data under the excitation clock provided by the FPGA, turns on the write enable of the dual-port RAM, and writes the data synchronously to the dual-port RAM. After the ADC module output is completed, the write enable is turned off. After the write enable is turned off, the read enable of the dual-port RAM is turned on, and the previously written data is read out under the control of the data processing domain excitation clock provided by the FPGA. After the data is read out, the write enable is turned off.

3. The FPGA-based FBG / FPI multi-physical quantity optical fiber sensing high-speed data acquisition and processing method according to claim 1, characterized in that: The steps of pre-processing the buffered sensor spectrum include: According to the spectral characteristics of the two sensor elements, FBG and FPI, the sensor element type of the multi-physical quantity sensor is determined; For the sensing spectrum containing two sensing elements, the distribution position of the FBG sensing spectrum in the composite spectrum is determined, and the composite spectrum is segmented according to its position to form the FBG sensing spectrum and the FPI sensing spectrum.

4. The FPGA-based FBG / FPI multi-physical quantity optical fiber sensing high-speed data acquisition and processing method according to claim 3, characterized in that: The steps to determine the sensing element type include: Set the spectral intensity threshold and correspond a group of continuous data points with intensity higher than the threshold to one FBG element; The collected sensing spectrum is Fourier transformed, and each characteristic peak in the non-DC region of the spectrum corresponds to an FPI element.

5. The FPGA-based FBG / FPI multi-physical quantity optical fiber sensing high-speed data acquisition and processing method according to claim 4, characterized in that: When the composite spectrum is segmented to form the FBG sensing spectrum and the FPI sensing spectrum, a group of continuous data points with intensities higher than a threshold are used as the initial FBG sensing spectrum. The remaining spectrum after removing the initial FBG sensing spectrum data points is interpolated to form the FPI sensing spectrum. The interpolated value is used as the baseline of the FBG sensing spectrum on the composite spectrum, and the baseline is subtracted from the initial FBG sensing spectrum to obtain the FBG sensing spectrum for demodulation.

6. The FPGA-based FBG / FPI multi-physical quantity optical fiber sensing high-speed data acquisition and processing method according to claim 1, characterized in that: The workflow of transmitting FPI sensor spectra through polling mechanism is as follows: setting up parallel data processing modules, and initially, both of them are in idle state; After obtaining the FPI sensor spectrum in the pre-processing step, the working status of the two data processing modules is queried in turn, and a data processing module in the idle state is selected, the FPI sensor spectrum is sent to the module, and its working status is changed to busy; After a data processing module completes its calculation work, its working state is reset to idle state, waiting for the next data reception.

7. The FPGA-based FBG / FPI multi-physical quantity optical fiber sensing high-speed data acquisition and processing method according to claim 1, characterized in that: The FBG data processing module includes a shift register module, a peak data judgment and selection module, a Gaussian fitting module, and a sliding average module; The workflow of the FBG data processing module is: The input FBG sensing spectrum enters the shift register module with a limited length and shifts once under each clock excitation; In each clock cycle, the peak data judgment and selection module performs peak judgment on the data in the shift register module and selects a certain number of FBG reflection peak data points for storage; The Gaussian fitting module calculates the reflection center wavelength of each FBG element in turn by Gaussian fitting the FBG reflection peak data points; The sliding average module performs window sliding average on the reflection center wavelength of each FBG element continuously output by the Gaussian fitting module, and uses the average value as the final calculated reflection center wavelength.

8. The FPGA-based FBG / FPI multi-physical quantity optical fiber sensing high-speed data acquisition and processing method according to claim 1, characterized in that: The FPI data processing module includes a spectrum shaping module, a DFT module, a CORDIC module, a phase unwrapping module, and an FIR filtering module; The workflow of the FPI data processing module is as follows: The spectrum shaping module performs standardization on the input FPI sensing spectrum; The normalized spectrum enters the DFT module, and the complex spectrum data obtained after DFT transformation enters the CORDIC module to further obtain the amplitude and phase of the complex spectrum data; The unwrapping module unwraps the phase data and further calculates the cavity length data of the FP cavity based on the amplitude; The FIR filter module filters the cavity length data output by the dewrapping module, and uses the filtered result as the final calculated cavity length value of the FP cavity.

9. The FPGA-based FBG / FPI multi-physical quantity optical fiber sensing high-speed data acquisition and processing method according to claim 1, characterized in that: The FBG data processing module and the FPI data processing module process the FBG sensing spectrum and the FPI sensing spectrum synchronously and in parallel in the FPGA.

10. The FPGA-based FBG / FPI multi-physical quantity optical fiber sensing high-speed data acquisition and processing method according to claim 8, characterized in that: The workflow of the FPI data processing module is divided into multiple processing steps of similar time consumption through pipeline technology. Registers for storing intermediate data are inserted between each step, and each processing step is executed simultaneously.

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