A tunnel monitoring method and system based on optical fiber sensing

Abstract

The present invention discloses a tunnel monitoring method and system based on fiber optic sensing, belonging to the technical field of tunnel monitoring. In the present invention, the sensing arm and the reference arm of a balanced Michelson interferometer are used to collect tiny vibration signals of tunnel disasters. By applying a short-time temperature impact to the light source, phase noise is actively introduced and amplified to make the interference signal elliptical arc ≥ 2π, combined with the light intensity signal I 3( t ) to achieve dynamic light intensity calibration, thereby eliminating the interference of light source fluctuations on the interference signal, generating a complete closed elliptical fitting curve, and achieving high-precision demodulation of tunnel disaster early warning and dynamic elimination of light source fluctuation interference. Using the trigger signal TRIG of a 64 kHz square wave as the carrier, coupling the digital quantities of the time stamp TOD and the pulse per second PPS to modulate the duty cycle, generating a composite synchronization signal and broadcasting it to all nodes to achieve synchronous sampling of each node, which can significantly improve the accuracy of data acquisition, processing, and correlation analysis of each node.

Description

Technical Field

[0001] The present invention relates to the technical field of tunnel monitoring, and particularly to a tunnel monitoring method and system based on optical fiber sensing. Background Art

[0002] Although optical fiber sensing technology has been widely used in the field of tunnel monitoring, traditional solutions have systematic defects in actual deployment. Existing technologies usually rely on mechanical phase modulation devices such as piezoelectric ceramics (PZT), which generate interference phase differences by changing the length of the optical fiber reference arm through mechanical vibration. For example, a Lissajous ellipse that can be demodulated is generated by periodically driving the PZT. However, such mechanical structures have extremely poor stability in the harsh environments of high temperature, high humidity, and frequent vibration in tunnels. The driving module has high power consumption (>10W) and large volume. In long-term operation, the piezoelectric material is prone to fatigue failure, and the average service life is less than 5 years. More critically, PZT modulation requires continuous high-frequency vibration to cover weak signals, resulting in the superposition of light source power fluctuations and nonlinear errors, further affecting the demodulation accuracy. This problem directly causes a sharp increase in hardware maintenance costs and a high missed detection rate (>50%) of weak vibration signals. Especially when the phase change amplitude <0.1rad, existing algorithms are difficult to achieve effective demodulation due to the interference of non-linear light intensity noise.

[0003] Traditional ellipse fitting requires obtaining complete closed ellipse data points to calculate phase parameters, but it is only applicable to interference signals with large curvatures. When processing short arc segment signals generated by weak vibrations, due to the superposition interference of light source intensity drift and detector bias voltage, the normalization parameters are distorted and the ellipse fitting residuals exceed the limit (>0.05). The algorithm has low accuracy and high false alarm rate. It regards the maintenance of light source stability and signal demodulation as isolated links: the temperature control module is only used to suppress the temperature drift of the light source and does not actively utilize the dynamic change of temperature; the light intensity signal is only used as an auxiliary parameter for noise suppression and does not participate in the dynamic normalization calibration of interference signals.

[0004] In addition, the inefficiency of the multi-node synchronization system restricts the practical application value of long-distance tunnel monitoring. Existing technologies mostly adopt GPS synchronization or independent crystal oscillator modules. The former is difficult to achieve due to signal shielding in tunnels, and the latter is affected by the cumulative drift of the crystal oscillator, resulting in a trigger signal deviation exceeding 1μs, seriously restricting the accuracy of multi-point correlation analysis of vibration events. Some solutions attempt to reduce the delay by adding dedicated clock cables, but the complex wiring increases the system installation cost by 60%. These problems expose the inherent defects of the separated design of synchronization signals and data streams under the traditional simplex transmission architecture.

[0005] In summary, the prior art has the following core defects: 1. Modulation depends on external devices such as PZT, resulting in high system cost and low reliability; 2. Small-arc ellipse fitting fails, making it difficult to detect weak vibration signals generated in tunnels; 3. Light source fluctuations and polarization drift interfere with signal stability, with low monitoring accuracy and high false alarm rate; 4. The synchronization accuracy of multiple nodes is insufficient, making it difficult to achieve large-scale collaborative monitoring. To address the above problems, an innovative fiber optic sensing solution is urgently needed to break through the bottleneck of the prior art and provide a high-precision, low-cost, and easily expandable solution for tunnel safety monitoring. Summary of the Invention

[0006] To address the above problems, a tunnel monitoring method and system based on fiber optic sensing are provided. In the present invention, the sensing arm and reference arm of a balanced Michelson interferometer are used to collect minute vibration signals of tunnel disasters. By applying a short-term temperature shock to the light source, phase noise is actively introduced and amplified to make the interference signal elliptical arc ≥ 2π, combined with the light intensity signal I 3( t ) to achieve dynamic light intensity calibration, thereby eliminating the interference of light source fluctuations on the interference signal, generating a complete closed elliptical fitting curve, and achieving high-precision demodulation of tunnel disaster early warning and dynamic elimination of light source fluctuation interference. Using the trigger signal TRIG of a 64 kHz square wave as the carrier, coupling the digital quantities of the time stamp TOD and the pulse per second PPS to modulate the duty cycle, generating a composite synchronization signal and broadcasting it to all nodes to achieve synchronous sampling of each node, which can significantly improve the accuracy of data acquisition, processing, and correlation analysis of each node.

[0007] To achieve the above object, the technical solution adopted by the present invention is: A tunnel monitoring method based on fiber optic sensing, including the following steps: Step 1: The two returned light intensity signals input by the 3×3 coupler of the interferometer and the third light intensity signal directly output can be expressed as:

[0008]

[0009] Among them, I ( t ) is the output light intensity of the light source; k 1、 k 2、 k 3 are the fixed loss coefficients in the corresponding optical paths respectively;

[0010] Step 2: Apply a short-term temperature shock to the light source to make the phase noise of the interference signal ≥ 2 π , and collect the two interference signals y 1( t ) and y 2( t ) through the interferometer;

[0011] Step 3: Combine the two interference signalsy 2( t ) and y 2( t ) are respectively divided by the optical intensity signal I 3( t ) to eliminate the optical intensity fluctuation, and V 1 and V 2 are obtained;

[0012] Step 4: Obtain the fitting parameters from V 1 and V 2 through the ellipse fitting algorithm. After the light source returns to the working temperature, synchronously collect the two-path interference signals, and then construct the quadrature signal in combination with the fitting parameters;

[0013] Step 5: Demodulate the phase of the quadrature signal through the differential cross-multiplication algorithm to obtain the phase difference θ s ;

[0014] Step 6: Broadcast the composite synchronization signal coupling the time-of-day timestamp TOD, the pulse per second PPS, and the trigger signal TRIG to each node to trigger each node to synchronously collect the vibration signal.

[0015] Preferably, the short-time temperature shock is to apply a temperature shock of 50 ms - 150 ms to the light source, so that the temperature of the light source jumps from the working temperature to the target temperature.

[0016] Preferably, the working temperature is 20°C - 30°C, and the target temperature is 40°C - 60°C.

[0017] Preferably, the two-path interference signals y 1( t ) and y 2( t ) in Step 2 are expressed as:

[0018]

[0019] Wherein, θ s is the phase difference caused by the micro-vibration; β is the fixed phase difference; is the phase noise brought by the short-time temperature shock; g 1 and g 2 are the fixed loss coefficients output by the two-path interference signals.

[0020] Preferably, V 1 and V 2 in Step 3 are expressed as:

[0021]

[0022] And the V 1 and V in 2 k 1, k 2, k 3, g 1 and g 2 are both fixed values, and it can be obtained that:

[0023]

[0024] Among them, a 1 and a 2 are the DC biases of the two interference signals, b 1 and b 2 are the AC amplitudes of the two interference signals.

[0025] Preferably, the quadrature signal in step 4 can be expressed as:

[0026]

[0027] Among them, θ s is the phase difference caused by the micro-vibration; β is the fixed phase difference.

[0028] Preferably, the differential cross-multiplication algorithm is as follows:

[0029]

[0030] Among them, and represent two quadrature signals.

[0031] Preferably, the composite synchronization signal uses the trigger signal TRIG of a 64KHz square wave as the carrier signal.

[0032] Preferably, the composite synchronization signal modulates the duty cycle of the square wave of the carrier signal through the digital quantities of the time stamp TOD and the second pulse PPS to achieve the modulation of the composite synchronization signal.

[0033] A tunnel monitoring system based on fiber optic sensing includes a plurality of nodes for collecting and demodulating vibration signals, and a cloud server for statistical analysis, tunnel disaster identification and early warning; the nodes include a synchronization signal modulation module, a data acquisition and screening module, and a network; the synchronization signal modulation module obtains the time stamp TOD from the network, and combines the second pulse PPS and the trigger signal TRIG generated by itself to modulate into a composite synchronization signal and broadcast it to all nodes; after each node obtains the composite synchronization signal, it demodulates the corresponding time stamp TOD, second pulse PPS and trigger signal TRIG, and at the same time triggers node synchronous sampling, and uses the above tunnel monitoring method to demodulate the phase difference of the vibration signal in real timeθ s The phase difference θ s is uploaded to the data acquisition and screening module through a cable. After the data acquisition and screening module aggregates and aligns the real-time vibration signals of all nodes, vibration events are screened out. The vibration events are uploaded to the cloud server through the network for further statistical analysis to realize the early warning of tunnel disasters.

[0034] Preferably, the nodes are arranged in series in the tunnel through a cable. The distance between the nodes is ≤ 100 meters, and the number of nodes is ≤ 8.

[0035] Due to the adoption of the above technical solutions, the present invention has the following beneficial effects.

[0036] (1) By applying a short-time temperature impact of 50 ms - 150 ms to the light source, the present invention promotes the dynamic change of the light source wavelength and light intensity, thereby actively introducing and expanding phase noise to make the interference signal elliptical arc ≥ 2π. By dividing the two interference signals by the light intensity signal I 3( t ), the interference of the light source fluctuation on the interference signal is eliminated, and a complete closed elliptical curve is generated. It solves the technical problems that the traditional elliptical fitting algorithm fails to fit due to light intensity drift and short arc segment interference during weak vibration (phase change < 0.1 rad) and has a high false alarm rate, and can significantly improve the stability and accuracy of the elliptical fitting algorithm.

[0037] (2) By dividing the two interference signals by the light intensity signal I 3( t ), the interference of the light source fluctuation on the interference signal is eliminated. Through dynamic light intensity calibration, the influence of light intensity fluctuation on the amplitude of the interference signal is eliminated, so that V 1 and V 2 only reflect the phase change, and the demodulation accuracy of weak vibration signals is improved. It solves the technical problems that the superposition of light source light intensity drift and detector bias voltage leads to the distortion of the normalization parameter and affects the demodulation accuracy.

[0038] (3) Using the trigger signal TRIG of a 64 kHz square wave as the carrier, the digital quantities of the time stamp TOD and the pulse per second PPS are coupled to modulate the duty cycle, and a composite synchronization signal is generated and broadcast to all nodes. By combining each node to obtain and demodulate the corresponding time stamp TOD, pulse per second PPS and trigger signal TRIG, synchronous sampling of each node is realized. It solves the technical problems that the traditional GPS synchronization is affected by tunnel shielding and the independent crystal oscillator module has cumulative drift (deviation > 1 μs), resulting in insufficient multi-node synchronization accuracy. Its synchronous sampling accuracy reaches the ns level, and the accuracy of multi-node data correlation analysis can be significantly improved.

[0039] (4) The present invention collects the tiny vibration signals of tunnel disasters through the sensing arm and the reference arm of a balanced Michelson interferometer, combines temperature shock and composite synchronization signals to achieve high-precision monitoring of the tiny vibration signals and dynamic elimination of light source fluctuation interference. At the same time, external devices such as PZT are cancelled, reducing the cost and complexity of the system, and significantly improving the reliability and device life. By serially deploying 8 nodes in the tunnel, it meets the monitoring requirements for full coverage of various long tunnels. Through collaborative analysis by a cloud server, the reliability of tunnel disaster early warning can be significantly improved, and the early warning response time can be shortened. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] The following discusses in detail the fabrication and application of the preferred embodiments of the present invention. It should be understood that the present invention provides many applicable inventive concepts, which can be embodied in various specific environments. The specific embodiments discussed are only for illustrating the specific ways of manufacturing and using the present invention, and do not limit the scope of the present invention. For those of ordinary skill in the art, other drawings can also be obtained based on these drawings without creative efforts.

[0041] Figure 1 It is the Lissajous figure of the interference signal of the present invention.

[0042] Figure 2 It is the system structure diagram of the present invention.

[0043] Figure 3 It is the node structure diagram of the system of the present invention.

[0044] Among them, Figure 1-1 It is the Lissajous figure after being processed by a conventional ellipse fitting algorithm; Figure 1-2 It is the Lissajous figure of ellipse fitting after short-time temperature shock; Figure 1-3 It is the Lissajous figure of ellipse fitting after being processed by the method of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0045] The following discusses in detail the fabrication and application of the preferred embodiments of the present invention. It should be understood that the present invention provides many applicable inventive concepts, which can be embodied in various specific environments. The specific embodiments discussed are only for illustrating the specific ways of manufacturing and using the present invention, and do not limit the scope of the present invention.

[0046] The present invention collects the minute vibration signals of tunnel disasters through the sensing arm and the reference arm of a balanced Michelson interferometer, combines temperature shock and composite synchronization signals to achieve high-precision monitoring of minute vibration signals and dynamic elimination of light source fluctuation interference, and at the same time cancels external devices such as PZT, reducing the cost and complexity of the system, and significantly improving the reliability and device life; it is serially deployed at 8 nodes in the tunnel to meet the monitoring requirements for full coverage of various long tunnels; through the collaborative analysis of the cloud server, the reliability of tunnel disaster warning can be significantly improved, and the warning response time can be shortened.

[0047] The following will be described in detail Figures 1-3 in conjunction with the accompanying

[0048] A tunnel monitoring method based on fiber optic sensing includes the following steps: Step 1: The two return light intensity signals input by the 3×3 coupler of the interferometer and the third light intensity signal directly output are expressed as:

[0049]

[0050] wherein, I ( t ) is the output light intensity of the light source; k 1, k 2, k 3 are respectively the fixed loss coefficients in the corresponding optical paths.

[0051] Step 2: Apply a short-term temperature shock to the light source to make the phase noise of the interference signal ≥ 2 π , and collect the two interference signals y 1( t ) and y 2( t ) through the interferometer:

[0052]

[0053] wherein, θ s is the phase difference caused by minute vibration; β is the fixed phase difference; is the phase noise brought by the short-term temperature shock; g 1 and g 2 are the fixed loss coefficients of the two interference signal outputs.

[0054] The two interference signals y 1( t ) and y 2( t ) of k 1, k 2, k 3, g 1 and gSince both are constant values, we can obtain:

[0055]

[0056] Among them, a 1 and a 2 are the DC biases of the two interference signals, b 1 and b 2 are the AC amplitudes of the two interference signals.

[0057] The short-term temperature shock is to apply a temperature shock of 50 ms - 150 ms to the light source, so that the temperature of the light source jumps from the operating temperature to the target temperature. The operating temperature is 20°C - 30°C, and the target temperature is 40°C - 60°C. In this embodiment, the operating temperature is set to 25°C, and the target temperature is 50°C.

[0058] Step 3: Divide the two interference signals y 2( t ) and y 2( t ) by the light intensity signal I 3( t ) respectively to eliminate the light intensity fluctuation, and obtain V 1 and V 2:

[0059] .

[0060] By dividing the two interference signals by the light intensity signal I 3( t ), the interference of the light source fluctuation on the interference signal is eliminated. Through dynamic light intensity calibration, the influence of the light intensity fluctuation on the amplitude of the interference signal is eliminated, so that V 1 and V 2 only reflect the phase change, so as to improve the demodulation accuracy of the weak vibration signal. Solve the technical problems such as the distortion of the normalization parameter caused by the superposition of the light source light intensity drift and the detector bias voltage, which affects the demodulation accuracy.

[0061] Step 4: Obtain the fitting parameters from V 1 and V 2 through the ellipse fitting algorithm. After the light source returns to the operating temperature, synchronously collect the two interference signals, and then construct an orthogonal signal in combination with the fitting parameters:

[0062]

[0063] Among them, θ s is the phase difference caused by the micro-vibration; βis a fixed phase difference. The comparison diagrams of the Lissajous figures processed by the conventional ellipse fitting algorithm, the Lissajous figures of ellipse fitting after short-time temperature shock in step 2, and the Lissajous figures of ellipse fitting after being processed by the method of the present invention are as follows Figure 1 shown

[0064] Step 5: Perform phase demodulation on the orthogonal signals through a differential cross-multiplication algorithm to obtain the phase difference of the vibration signals θ s ; The differential cross-multiplication algorithm is as follows

[0065]

[0066] where and represent two orthogonal signals

[0067] Step 6: Broadcast a composite synchronization signal coupling the time stamp TOD, the pulse per second PPS, and the trigger signal TRIG to each node to trigger each node to synchronously collect vibration signals. The composite synchronization signal uses the trigger signal TRIG of a 64KHz square wave as the carrier signal. The composite synchronization signal modulates the duty cycle of the square wave of the carrier signal through the digital quantities of the time stamp TOD and the pulse per second PPS to achieve the modulation of the composite synchronization signal

[0068] The present invention uses the trigger signal TRIG of a 64kHz square wave as the carrier, couples the digital quantities of the time stamp TOD and the pulse per second PPS to modulate the duty cycle, generates a composite synchronization signal and broadcasts it to all nodes. By combining each node to obtain and demodulate the corresponding time stamp TOD, the pulse per second PPS, and the trigger signal TRIG, synchronous sampling of each node is achieved. It solves the technical problems that the traditional GPS synchronization is affected by tunnel shielding and the independent crystal oscillator module has cumulative drift (deviation > 1μs), resulting in insufficient multi-node synchronization accuracy. Its synchronous sampling accuracy reaches the ns level, which can significantly improve the accuracy of multi-node data correlation analysis

[0069] such as Figure 2A tunnel monitoring system based on fiber optic sensing as shown includes multiple nodes for collecting and demodulating vibration signals. The nodes are arranged in series in the tunnel through cables, the distance between the nodes is ≤ 100 meters, and the number of nodes is ≤ 8; a cloud server for statistical analysis, tunnel disaster identification and warning; the nodes include a synchronous signal modulation module, a data acquisition and screening module, and a network; the synchronous signal modulation module obtains the time-of-day (TOD) from the network, and combines the pulse per second (PPS) and trigger signal (TRIG) generated by itself to modulate into a composite synchronous signal and broadcast it to all nodes; after each node obtains the composite synchronous signal, it demodulates the corresponding TOD, PPS and TRIG, simultaneously triggers the nodes to synchronously sample, and uses the above tunnel monitoring method to demodulate the phase difference of the vibration signal in real time θ s , the phase difference θ s is uploaded to the data acquisition and screening module through the cable. The data acquisition and screening module summarizes and aligns the real-time vibration signals of all nodes and then screens out vibration events. The vibration events are uploaded to the cloud server through the network for further statistical analysis to realize the early warning of tunnel disasters.

[0070] The following will be further elaborated in detail in conjunction with the attached Figures 1-3 drawings.

[0071] As Figure 1 shown, the Lissajous figure comparison diagram of the interference signal of the present invention. In this embodiment, a balanced Michelson interferometer is used as the acquisition unit for the tiny vibration signals of tunnel disasters at each node. The balanced Michelson interferometer includes a 3×3 coupler, a Faraday rotator mirror, and sensitive optical fibers of the same length, which are respectively wound around an elastomer and a mass block to form the sensing arm and reference arm of the interferometer. When tiny vibration signals are generated in the early stage of tunnel disasters, it will cause changes in the optical path difference between the sensing arm and reference arm of the interferometer. The optical intensity signals of the two returned lights reflected by the Faraday rotator mirror and the optical intensity signal of the third path are expressed as:

[0072]

[0073] Among them, I ( t ) is the output optical intensity of the light source; k 1、 k 2、 k 3 are respectively the fixed loss coefficients in the corresponding optical paths.

[0074] Among them I 1( t ) and I 2( t)In the 3×3 coupler, they converge and interfere. The two interference signals (Interference Signal 1 and Interference Signal 2) with a fixed phase difference that are collected can be expressed as:

[0075]

[0076] where g 1 and g 2 are the fixed loss coefficients of the two interference light outputs.

[0077] Substituting the three optical intensity signals into the expression of the two interference signals, we can obtain:

[0078]

[0079] where θ s is the phase change caused by vibration, β is the fixed phase difference.

[0080] Since the fixed phase difference β = 2 π / 3 of the two interference signals output by the 3×3 coupler cannot be directly solved, and the method of ellipse fitting needs to be used to solve it. Generally, due to the too small vibration amplitude of the external vibration signal, the ellipse fitting algorithm cannot accurately fit the small-arc curve, resulting in fitting failure. The small-arc curve Lissajous Figure 1-1 is shown as follows. The conventional method is to introduce devices such as PZT that can cause phase modulation signals on the interferometer to modulate the phase of the interference light signal to achieve the purpose of closing the elliptical arc. However, in actual use, it is easily restricted by the volume, cost, service life, etc. of these devices.

[0081] In view of this, this embodiment proposes to close the elliptical arc by applying a short-time temperature shock to the light source to achieve the purpose of successful fitting. The short-time temperature shock is to increase the target temperature of the temperature control module by SOC to prompt the temperature control module to quickly control the TEC heating in the light source to achieve the purpose that the light source is subjected to temperature shock during light emission, thereby causing changes in the light emission intensity and wavelength of the light source and introducing a certain amount of phase noise. The interference signal collected at this time can be expressed as:

[0082]

[0083] During the temperature adjustment period of the short-time temperature shock, the light intensity I ( t ) in the above formula is no longer a constant value, and at the same time, the phase noise is added to the phase. The Lissajous Figure 1-2 at this time is shown as follows. Although the elliptical arc exceeds 2 π , but due to the light intensity I (t ) The change of () results in the elliptic curve not being able to close completely, and accurate parameters still cannot be fitted.

[0084] The present invention divides two interference signals by the optical intensity signal respectively I 3( t ) to obtain:

[0085]

[0086] Among them, k 1, k 2, k 3, g 1 and g 2 are both fixed values. After arrangement, it can be written as:

[0087]

[0088] Among them, a 1 and a 2 are the DC biases of the two signals, b 1 and b 2 are the AC amplitudes.

[0089] Due to the phase noise brought by short-term temperature shock , the Lissajous figure at this time already shows a complete ellipse, as Figure 1-3 shown. At this time V 1 and V 2 satisfy the general equation of the ellipse:

[0090]

[0091] According to the collected and calculated V 1 and V 2 sets of data, using the conventional ellipse fitting algorithm, the A , B , C , D , E 5 coefficients of the general equation can be obtained, and then a 1, a 2, b 1, b 2, cos β sin β these 6 fitting parameters can be obtained.

[0092] The SOC adjusts the temperature control module to control the light source to return to the normal working temperature. After waiting for it to stabilize, the phase noise introduced by the short-term temperature shock will disappear. Then, using the a 1, a 2, b1. b 2. cos β and sin β These six parameters can be used to construct a pair of orthogonal signals containing the phase difference of the vibration signal to be measured, which can be expressed as:

[0093]

[0094] Finally, the phase θ s is obtained by using the conventional differential cross - multiplication algorithm. The differential cross - multiplication algorithm is as follows:

[0095]

[0096] where and represent two orthogonal signals.

[0097] Then, the composite synchronization signal of the coupled timestamp TOD, pulse per second PPS, and trigger signal TRIG is broadcast to each node to trigger each node to synchronously collect vibration signals. The composite synchronization signal uses the trigger signal TRIG of a 64KHz square wave as the carrier signal. The composite synchronization signal modulates the duty cycle of the square wave of the carrier signal through the digital quantities of the timestamp TOD and the pulse per second PPS to achieve the modulation of the composite synchronization signal, and finally realizes the synchronous sampling of each node. This method solves the technical problems that traditional GPS synchronization is affected by tunnel shielding and the independent crystal oscillator module has cumulative drift (deviation > 1μs), resulting in insufficient synchronization accuracy of multiple nodes. Its synchronous sampling accuracy reaches the nanosecond level, which can significantly improve the accuracy of multi - node data correlation analysis.

[0098] For the embodiments of the tunnel monitoring method and system of the present invention, the present invention adopts the following specific implementation steps to achieve synchronous sampling and high - precision monitoring and early warning of tunnel disasters. As Figure 3 shown, the specific steps executed in this embodiment are as follows: Step S1: Power on and start the light source, set the target temperature of the temperature control module to 25°C, and wait for the temperature control module to automatically complete the temperature adjustment operation. At this time, the light source emits light stably at the target temperature of 25°C.

[0099] Step S2: Through the SOC, set the ADC trigger source to internal timer trigger in sequence, the sampling rate is 10Ksps - 64Ksps, and the sampling rate in this embodiment is set to 20Ksps; the sampling bit number is 16bit, and the gain is the amplification multiple stored inside the SOC. The amplification multiple stored inside the SOC in this embodiment is 2 times.

[0100] Step S3: Set the target temperature of the temperature control module to 40°C - 60°C. The target temperature set in this embodiment is 50°C. Start the ADC to synchronously collect the three optical intensity signals, namely interference signal 1, interference signal 2, and optical intensity signal, so that the ADC collects data during the short-term temperature shock period of 50ms - 150ms for the light source. The duration of the short-term temperature shock in this embodiment is 100ms.

[0101] Step S4: After collecting for 100ms, 2000 data points are collected for each signal. At this time, turn off the ADC, and at the same time set the target temperature of the temperature control module back to 25°C.

[0102] Step S5: Divide the two collected interference signals by the optical intensity signal respectively I 3( t ) and then perform the ellipse fitting algorithm to obtain and save 6 fitting parameters, and wait for the working temperature of the light source to automatically stabilize at 25°C to eliminate the phase noise introduced by the short-term temperature shock .

[0103] Step S6: Set the ADC trigger source to the external trigger signal TRIG, set the sampling frequency of the ADC to 64Ksps, and the sampling bit number to 16bit. After the SOC obtains the second pulse PPS signal, start the ADC to synchronously collect the above-mentioned three optical intensity signals.

[0104] Step S7: During continuous ADC acquisition, when 640 data points, that is, one frame of data, are collected for each signal, divide the two interference signals by the optical intensity signal respectively I 3( t ) to eliminate the optical intensity fluctuation, and then combine the 6 fitting parameters obtained by the ellipse fitting calculation to construct an orthogonal signal.

[0105] Step S8: Use the differential cross-multiplication algorithm to calculate the phase difference of the vibration signal to be measured θ s , and then after filtering, downsampling, and packing, send it to the host computer through the network for screening processing, screen out vibration events, and upload them to the cloud server through the network for further analysis and statistics to achieve early warning of tunnel disasters.

[0106] Such as Figure 2The system structure diagram of the present invention is shown. It includes multiple nodes for collecting and demodulating vibration signals. The nodes are arranged in series through cables in the tunnel. The distance between the nodes is ≤ 100 meters, and the number of nodes is ≤ 8. A cloud server for statistical analysis, tunnel disaster identification and warning. The node includes a synchronous signal modulation module, a data acquisition and screening module, and a network. The synchronous signal modulation module obtains the timestamp TOD from the network, and combines the second pulse PPS and the trigger signal TRIG generated by itself to modulate into a composite synchronous signal and broadcast it to all nodes. After each node obtains the composite synchronous signal, it demodulates the corresponding timestamp TOD, second pulse PPS and trigger signal TRIG, and at the same time triggers the nodes to synchronously sample, and demodulates the phase difference of the vibration signal in real time according to the above tunnel monitoring method. θ s , the phase difference θ s is uploaded to the data acquisition and screening module through the cable. The data acquisition and screening module aggregates and aligns the real-time vibration signals of all nodes, and then screens out the vibration events. The vibration events are uploaded to the cloud server through the network for further statistical analysis to realize the warning of tunnel disasters.

[0107] Specifically, the nodes are arranged in the construction area. Each node is connected to the upper computer in series by a cable. The synchronous signal modulation module obtains the timestamp TOD from the network, and combines the second pulse PPS and the trigger signal TRIG generated by itself to modulate into a composite synchronous signal and broadcast it to all nodes. After the node obtains the composite synchronous signal, it demodulates the timestamp TOD, second pulse PPS and trigger signal TRIG, triggers the ADC to synchronously sample, and demodulates the vibration signal in real time, and uploads it to the data acquisition and screening module through the serial cable. The data acquisition and screening module aggregates and aligns the real-time data of all nodes, then screens out the vibration events, and uploads them to the cloud server through the network for further analysis and statistics to realize the warning of tunnel disasters.

[0108] As Figure 3 shown is the node structure diagram of the present invention. The node includes an SOC, an ADC, a gain, a temperature control module, a semiconductor light source, an isolator, a photodetector 1, a photodetector 2, a photodetector 3, a 3×3 coupler, a mass block, an elastomer, a Faraday rotator mirror, a synchronous signal demodulation module, a network card, and a switch.

[0109] The SOC is a system-on-chip, which is the core processing module of the node. It is mainly used to set the target temperature of the temperature control module, control the operation of the ADC and receive the three-channel optical intensity signals collected by it, and calculate, filter, downsample, and package these three signals and then send them to the network card; the ADC is an analog-to-digital chip used to convert the received analog signal into a digital signal; the gain is used to adjust the amplitude of the signal output by the photodetector so that its peak-to-peak value reaches 2V; the temperature control module controls the thermoelectric cooler (TEC) in the semiconductor light source in a hardware PID manner, enabling the light source to work at a stable target temperature, and the target temperature is adjusted by the SOC.

[0110] The semiconductor light source is used to generate a laser signal, and it is internally provided with a TEC module and a temperature sensor module; the isolator is an optical device used to control the unidirectional transmission of optical signals to ensure that the semiconductor light source is not interfered by the backlight; the photodetector is a functional device that converts an optical signal into an electrical signal output; the 3×3 coupler is an optical device used to split or combine optical signals among 3 optical fibers; the mass block is made of metal, and copper is used in this embodiment. Its outer circle is wound with a sensitive optical fiber to form the reference arm of the interferometer; the elastomer is made of rubber, and silicone is used in this embodiment. Its outer circle is wound with a sensitive optical fiber to form the sensing arm of the interferometer.

[0111] The Faraday rotator mirror is mainly used to stabilize and control the polarization state of the optical signal. The reference signal light and the modulation signal light are reflected by the Faraday rotator mirror and then enter the 3×3 coupler, and then enter the photodetector 1 and the photodetector 2; the synchronous signal demodulation module receives the synchronous signal and demodulates the timestamp TOD, the second pulse PPS, and the trigger signal TRIG in real time, and sends the timestamp TOD to the SOC. The second pulse PPS is used to trigger the external interrupt of the SOC, and the trigger signal TRIG is used to trigger the synchronous sampling of the ADC; the network card is used as the vibration data transmission medium of the node; the switch is used for the network port expansion and data forwarding of the node.

[0112] The principle of this embodiment is as follows: The temperature control module controls the semiconductor light source to output laser at a constant temperature of 25°C. After passing through the isolator, it enters the 3×3 coupler and is divided into three beams of light. The first beam of light and the second beam of light form the reference light and the signal light of the balanced Michelson interferometer. After being reflected by the Faraday rotator mirror, they return to the 3×3 coupler, converge and interfere. The interfered signals are respectively output to the photodetector 1 and the photodetector 2. The third beam of light is directly output to the photodetector 3 after exiting from the 3×3 coupler.

[0113] The photodetector 1, photodetector 2, and photodetector 3 convert the optical signals corresponding to the reference light, sensing light, and the third beam of light into electrical signals, and output three paths of light. Among them, the first path of light and the second path of light are collected by the ADC after gain amplification, and the third path of light is directly collected by the ADC. At this time, the SOC starts the ADC according to the second pulse PPS. After startup, the ADC is triggered by the trigger signal TRIG to synchronously collect the optical signals of the three paths of light and output them to the SOC for vibration signal demodulation processing. The SOC performs data demodulation processing on the vibration signal phase difference according to the above tunnel monitoring method. θ s The SOC combines the timestamp TOD, packs and batches the data, and sends it to the host computer through the network card and switch. The host computer summarizes and aligns the real-time data of all nodes, performs event screening, and uploads it to the cloud server through the network for further analysis and statistics, so as to realize the real-time monitoring and early warning of tunnel disasters.

[0114] In the present invention, the sensing arm and the reference arm of the balanced Michelson interferometer are used to collect the tiny vibration signals of tunnel disasters. By combining temperature shock and composite synchronization signals, high-precision monitoring of tiny vibration signals and dynamic elimination of light source fluctuation interference are achieved. At the same time, external devices such as PZT are cancelled, reducing the cost and complexity of the system, and significantly improving the reliability and device life. By serially deploying 8 nodes in the tunnel, the monitoring requirements for full coverage of various long tunnels are met. Through the collaborative analysis of the cloud server, the reliability of tunnel disaster early warning can be significantly improved, and the early warning response time can be shortened.

[0115] Although the specification has been described in detail, it should be understood that various changes, substitutions, and alterations can be made without departing from the spirit and scope of the present invention defined by the appended claims. In addition, the specific embodiments described do not limit the scope of the present invention. Those of ordinary skill in the art can easily understand based on the present invention that the currently existing or future-developed processes, machines, manufactures, compositions of matter, means, methods, or steps can perform functions substantially the same as those of the embodiments of the present invention or obtain substantially the same results. Therefore, the appended claims are intended to include such processes, machines, manufactures, compositions of matter, means, methods, or steps within their scope.

Claims

1. A tunnel monitoring method based on optical fiber sensing, characterized in that: Including the following steps: Step 1: The laser output by the light source enters the 3×3 coupler through the isolator and is split into three paths. Two of the paths are reflected by the interferometer and then form two return light intensity signals which are output to the 3×3 coupler for interference, and the third light intensity signal is directly output to the photodetector; the two return light intensity signals and the third light intensity signal are expressed as: I1(t) = k1I(t) I2(t) = k2I(t) I3(t) = k3I(t) wherein, I(t) is the output light intensity of the light source; k1, k2, and k3 are respectively the fixed loss coefficients in the corresponding optical paths; Step 2: Apply a short-time temperature shock to the light source to make the phase noise of the interference signal ≥2π, and collect two interference signals y1(t) and y2(t) through the interferometer; Step 3: Divide the two interference signals y1(t) and y2(t) by the light intensity signal I3(t) respectively to eliminate the light intensity fluctuation, and obtain V1 and V2; Step 4: Obtain the fitting parameters from V1 and V2 through the ellipse fitting algorithm. After the light source returns to the working temperature, synchronously collect the two interference signals, and then construct the orthogonal signal in combination with the fitting parameters; Step 5: Perform phase demodulation on the orthogonal signal through the differential cross - multiplication algorithm to obtain the phase difference θ of the vibration signal s ; Step 6: Broadcast the composite synchronization signal of the coupled time stamp TOD, the pulse per second PPS, and the trigger signal TRIG to each node to trigger each node to synchronously collect the vibration signal.

2. The tunnel monitoring method based on optical fiber sensing according to claim 1, wherein: The short-time temperature shock is to apply a temperature shock of 50 ms - 150 ms to the light source, so that the temperature of the light source jumps from the working temperature to the target temperature.

3. The tunnel monitoring method based on optical fiber sensing according to claim 2, characterized in that: The working temperature is 20°C - 30°C, and the target temperature is 40°C - 60°C.

4. The tunnel monitoring method based on optical fiber sensing according to claim 1, characterized in that: The two interference signals y1(t) and y2(t) in Step 2 are expressed as: where θ s is the phase difference caused by minute vibration; β is the fixed phase difference; is the phase noise brought about by short-time temperature shock; g1 and g2 are the fixed loss coefficients of the outputs of the two interference signals.

5. The tunnel monitoring method based on optical fiber sensing according to claim 1, characterized in that: V1 and V2 in Step 3 are expressed as: And k1, k2, k3, g1, and g2 in V1 and V2 are all constant values, and it can be obtained that: Among them, a1 and a2 are the DC biases of the two interference signals, b1 and b2 are the AC amplitudes of the two interference signals; β is the fixed phase difference; is the phase noise caused by short-term temperature shock; g1 and g2 are the fixed loss coefficients output by the two interference signals.

6. The tunnel monitoring method based on fiber optic sensing according to claim 1, characterized in that: The orthogonal signal in Step 4 is expressed as: V1′ = cosθ s = (V1 - a1) / b1 V2′ = sinθ s = [V2 - a2 - b2cosθ s cosβ] / b2sinβ where θ s is the phase difference caused by minute vibration; β is the fixed phase difference; a1 and a2 are the DC biases of the two interference signals, and b1 and b2 are the AC amplitudes of the two interference signals.

7. The tunnel monitoring method based on optical fiber sensing according to claim 1, characterized in that: The differential cross-multiplication algorithm is as follows: wherein, V1′ and V2′ represent two orthogonal signals.

8. The tunnel monitoring method based on optical fiber sensing according to claim 1, characterized in that: The composite synchronization signal uses the trigger signal TRIG of a 64KHz square wave as the carrier signal; the composite synchronization signal modulates the duty cycle of the square wave of the carrier signal through the digital quantities of the time stamp TOD and the pulse per second PPS to realize the modulation of the composite synchronization signal.

9. A tunnel monitoring system based on fiber optic sensing, characterized in that: It includes multiple nodes for collecting and demodulating vibration signals, and a cloud server for statistical analysis, tunnel disaster identification and early warning; the nodes include a synchronous signal modulation module, a data acquisition and screening module, and a network; the synchronous signal modulation module obtains the timestamp TOD from the network, and combines the second pulse PPS and the trigger signal TRIG generated by itself to modulate into a composite synchronous signal and broadcast it to all nodes; after each node obtains the composite synchronous signal, it demodulates the corresponding timestamp TOD, second pulse PPS and trigger signal TRIG, and at the same time triggers node synchronous sampling, and uses the tunnel monitoring method described in any one of claims 1-8 to demodulate the phase difference θ of the vibration signal in real time s , the phase difference θ s is uploaded to the data acquisition and screening module through a cable. After the data acquisition and screening module aggregates and aligns the real-time vibration signals of all nodes, vibration events are screened out. The vibration events are uploaded to the cloud server through the network for further statistical analysis to realize the early warning of tunnel disasters.

10. A tunnel monitoring system based on fiber optic sensing as claimed in claim 9, characterized in that: The nodes are arranged in series in the tunnel through cables, the distance between the nodes ≤100 meters, and the number of nodes ≤8.

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