A Shake-Stabilized Alignment System for Fiber Optic Spatial Wireless Sensing and Detection

Abstract

This application belongs to the field of fiber optic spatial wireless sensing technology, specifically disclosing a shake-stabilizing alignment system for fiber optic spatial wireless sensing detection. The system is installed at the signal demodulation end and includes a gimbal unit that adjusts the attitude of the signal demodulation end according to a first control signal; a piezoelectric ceramic fine-tuning unit that adjusts the attitude of the transceiver collimator according to a second control signal; and an alignment control unit that acquires position coordinate data, attitude data, image data, and reflected light spot coordinate data to calculate the first and second control signals. The system controls the output light from the signal demodulation end to accurately return to the signal demodulation end after being reflected by the fiber optic sensing end. This technical solution, through dual-drive of gimbal coarse adjustment and piezoelectric ceramic fine adjustment, multi-source data fusion, and dynamic benchmark calibration, improves the optical path alignment accuracy to approximately 0.01°, significantly enhancing the accuracy and stability of optical path alignment and adapting to dynamic detection scenarios in fiber optic spatial wireless sensing.

Description

Technical Field

[0001] This application is a divisional application of invention patent application 2026100378380, entitled "An Anti-shake Alignment System for Fiber Optic Spatial Wireless Sensing Detection," with the parent application date of January 13, 2026, and the authorization announcement date of April 15, 2026. This application belongs to the field of fiber optic spatial wireless sensing technology, and more specifically, relates to an anti-shake alignment system for fiber optic spatial wireless sensing detection. Background Technology

[0002] Traditional fiber optic sensing technology typically requires laying fiber optic cables between the remote sensing end and the local demodulation end for signal transmission. However, this method is unsuitable for sensing and detection in temporary areas, large areas, hazardous areas, and areas where cabling is not feasible (rotating parts, moving parts, historical buildings). Fiber optic spatial wireless sensing technology can perfectly circumvent these problems, such as... Figure 1 As shown, a passive fiber optic sensing end is fixed at the point to be tested. A mobile vehicle carrying a signal demodulation end is then moved to the vicinity of the fiber optic sensing end to align the optical path and read the reflected light signal returned from the fiber optic sensing end, thereby obtaining the status information of the point to be tested. This technology requires no wiring and is highly scalable. The mobile vehicle can carry the signal demodulation end and sequentially read the reflected light signals from a large number of fiber optic sensing ends by moving according to a planned route.

[0003] In fiber optic spatial wireless sensing technology, the reflected light signal from the fiber optic sensing end needs to maintain a stable wireless optical path connection under dynamic, non-contact conditions, which requires highly precise anti-shake alignment technology. Currently, fiber optic spatial wireless sensing technology generally suffers from insufficient anti-shake alignment technology between the fiber optic sensing end and the signal demodulation end, which severely limits the widespread engineering application of fiber optic spatial wireless sensing technology. Summary of the Invention

[0004] In view of the shortcomings of the prior art, the purpose of this application is to provide a shake-stabilization alignment system for fiber optic spatial wireless sensing and detection, which aims to solve the technical problem of insufficient shake-stabilization alignment accuracy in the existing fiber optic spatial wireless sensing technology.

[0005] This application relates to a shake-stabilization alignment system for fiber optic spatial wireless sensing and detection. The shake-stabilization alignment system is installed at the signal demodulation end and specifically includes: The four-quadrant detection unit and the signal demodulation end share an optical path and are used to acquire the coordinate data of the reflected light spot of the reflected light returned from the optical fiber sensing end. The positioning unit is used to acquire the position coordinate data of the signal demodulation end; An attitude sensing unit is used to acquire attitude data from the signal demodulation terminal; An image acquisition unit is used to acquire image data from the optical fiber sensing end; An alignment control unit is used to generate a first control signal and a second control signal, and send the first control signal to the gimbal unit and the second control signal to the piezoelectric ceramic fine-tuning unit; the first control signal is generated based on the attitude deviation calculation of the signal demodulation end, and the attitude deviation is derived based on the attitude data; the second control signal is generated based on the reflected light spot angle deviation calculated based on the light intensity loss of the reflected light, and the light intensity loss is derived based on the reflected light intensity data obtained by the signal demodulation end; the gimbal unit has a fixed end connected to a moving vehicle and a movable end on which the signal demodulation end is mounted, used to adjust the attitude of the signal demodulation end according to the received first control signal; A piezoelectric ceramic fine-tuning unit, wherein the fixed end of the piezoelectric ceramic fine-tuning unit is connected to the signal demodulation end, and the movable end of the piezoelectric ceramic fine-tuning unit is connected to the transceiver collimator in the signal demodulation end, for adjusting the attitude of the transceiver collimator according to the received second control signal.

[0006] Preferably, the alignment control unit includes an optical loss adjustment subunit; The optical loss adjustment subunit is used to obtain reflected light intensity data from the signal demodulation terminal; The light intensity loss is obtained from the difference between the reflected light intensity data and the reference reflected light intensity data; Substituting the light intensity loss into the loss deviation mapping model, we obtain the reflected light spot angle deviation used to compensate for the light intensity loss. Based on the reflected light spot angle deviation, a second control signal is generated and sent to the piezoelectric ceramic fine-tuning unit to control the transceiver collimator to adjust its attitude, so that the reflected light from the fiber optic sensing end enters the transceiver collimator.

[0007] Preferably, the alignment control unit includes a loss deviation mapping model construction subunit; The loss deviation mapping model construction subunit is used to obtain reflected light intensity data from the signal demodulation end, reflective spot coordinate data from the four-quadrant detection unit, and position coordinate data from the positioning unit; The distance value is obtained from the position coordinate data and the position coordinate data of the fiber optic sensor end under test; The difference between the reflected spot coordinate data and the reference reflected spot coordinate data is used to obtain the reflected spot coordinate deviation; The angle deviation of the reflected light spot is obtained by the arctangent of the coordinate deviation of the reflected light spot and the distance value. The light intensity loss is obtained from the difference between the reflected light intensity data and the reference reflected light intensity data; A loss deviation mapping model is constructed by fitting the mapping relationship between the light intensity loss and the reflected light spot angle deviation.

[0008] Preferably, the loss deviation mapping model is as follows:

[0009]

[0010] in, It is the reflected light intensity data. This is the baseline reflected light intensity data; These are model coefficients; It is a deviation in the angle of the reflected light spot; It is the reference reflected light spot angle.

[0011] Preferably, the alignment control unit includes a gimbal adjustment subunit, used to acquire attitude data from the attitude sensing unit, and obtain the attitude deviation from the difference between the reference attitude data and the attitude data; calculate the first control signal based on the attitude deviation and send it to the gimbal unit, controlling the gimbal unit to adjust the attitude of the signal demodulation end, so that the reflected light from the fiber optic sensing end enters the signal demodulation end.

[0012] Preferably, the alignment control unit includes a reference calibration subunit for calibrating reference attitude data, reference reflected light spot coordinate data, and reference reflected light intensity data in response to calibration trigger conditions. The intensity data of the reflected light is obtained from the signal demodulation terminal and used as the calibrated reference reflected light intensity data. The coordinate data of the reflected light spot is obtained from the four-quadrant detection unit, and the attitude data is obtained from the attitude sensing unit. The reflection spot coordinate deviation is obtained from the difference between the reflection spot coordinate data and the reference reflection spot coordinate data; the attitude deviation is obtained from the difference between the attitude data and the reference attitude data. A coordinate attitude deviation mapping model is constructed by fitting multiple sets of mapping relationships between attitude deviations and reflected light spot coordinate deviations; The output deviation of the coordinate attitude deviation mapping model is used as a correction factor to calibrate the reference reflected light spot coordinate data; the attitude deviation is used as a correction factor to calibrate the reference attitude data. The calibration triggering conditions include, but are not limited to: triggering at a preset time interval or triggering when the coordinate deviation of the reflected light spot obtained from multiple consecutive acquisitions exceeds a preset deviation threshold.

[0013] Preferably, the four-quadrant detection unit includes a visible light source, a beam splitter, a beam combiner, and a four-quadrant detector. The visible light source emits a visible light signal, which is combined with a sensing light signal by the beam combiner and emitted as a single beam signal to the fiber optic sensing end. The reflected light signal reflected back from the fiber optic sensing end is split into a reflected sensing light signal and a reflected visible light signal by the beam splitter, and the reflected visible light signal enters the four-quadrant detector.

[0014] Preferably, the gimbal unit adopts a three-axis adjustment structure, wherein the X-axis of the gimbal unit is used to adjust the roll angle of the signal demodulation end, the Y-axis of the gimbal unit is used to adjust the pitch angle of the signal demodulation end, and the Z-axis of the gimbal unit is used to adjust the yaw angle of the signal demodulation end. The piezoelectric ceramic fine-tuning unit adopts a three-axis adjustment structure. The X-axis of the piezoelectric ceramic fine-tuning unit is used to adjust the heading angle of the transceiver collimator, the Y-axis is used to adjust the pitch angle of the transceiver collimator, and the Z-axis is used to adjust the forward and backward displacement of the transceiver collimator.

[0015] Preferably, it also includes a mobile vehicle displacement control unit, used to acquire image data from the image acquisition unit and position coordinate data from the positioning unit; The distance value is obtained from the position coordinate data and the position coordinates of the fiber optic sensor end under test; The emitted light spot of the signal demodulation end is identified from the image data, and the position pixel deviation is obtained from the center position of the emitted light spot and the center position of the optical path opening of the fiber optic sensing end. The position pixel deviation is converted into a translation angle deviation using the distance value, and the movement direction of the mobile vehicle is obtained from the translation angle deviation. Due to the translation angle deviation and the distance value The distance traveled by the mobile vehicle can then be calculated. : ; The direction and distance of movement are sent to the mobile vehicle, and the mobile vehicle is controlled to move carrying the signal demodulation end, so that the emitted light from the signal demodulation end enters the optical fiber sensing end.

[0016] Preferably, it also includes a mobile vehicle attitude control unit: Used to acquire image data from the image acquisition unit; The emitted light spot of the signal demodulation end is identified from the image data, and the ellipticity of the emitted light spot is calculated by elliptic fitting. If the ellipticity is greater than the preset ellipticity, the relationship between the major axis of the light spot and the vertical and horizontal directions is further calculated. If the major axis is closer to the vertical direction, the deviation type of the moving vehicle is determined to be pitch angle deviation; otherwise, the deviation type of the moving vehicle is determined to be roll angle deviation. The attitude adjustment deviation value is calculated based on the ellipticity and the preset calibration coefficient. The deviation type and the attitude adjustment deviation value are sent to the mobile vehicle, and the mobile vehicle is controlled to adjust the attitude of the signal demodulation end, so that the emitted light from the signal demodulation end is perpendicularly incident on the optical fiber sensing end.

[0017] Overall, the technical solution conceived in this application has the following advantages compared with the prior art: (1) This application uses gimbal adjustment and piezoelectric ceramic fine adjustment as dual drives, and calculates control signals by light intensity, attitude, position, four quadrant coordinates of reflected light and image data. Compared with the existing alignment stabilization technology (about 0.5°), the alignment accuracy of this application (about 0.01°) is significantly improved (more than 10 times).

[0018] (2) The present application system implements an alignment adjustment method based on reflected light intensity data. It establishes a loss deviation mapping model, which inversely calculates the reflected light spot angle deviation through the light intensity loss of reflected light, and further calculates the control signal based on the reflected light spot angle deviation to control the piezoelectric ceramic fine adjustment unit to achieve high-precision alignment adjustment.

[0019] (3) This application implements an optical path alignment adjustment method based on multi-source data fusion, which performs weighted fusion of reflected spot coordinate data, attitude data and image data, and then calculates control signals based on the fused data to control the piezoelectric ceramic fine-tuning unit to achieve high-precision alignment adjustment.

[0020] (4) This application implements an optical path alignment adjustment method based on Kalman filtering. It uses the reflected light spot coordinate data, attitude data, position coordinate data and image data to obtain the control signal through time synchronization and Kalman filtering correction calculation to control the piezoelectric ceramic fine adjustment unit to achieve high-precision alignment adjustment, and to offset high-frequency jitter and attitude data zero bias drift.

[0021] (5) The technical solution of this application uses dynamic calibration technology to calibrate the reference reflected light intensity data, reference attitude data and reference reflected light spot coordinate data, which provides an accurate calculation reference for alignment control, thereby achieving stable high-precision alignment.

[0022] (6) The technical solution of this application integrates the optical path of the four-quadrant detection unit into the sensing optical path, thereby accurately obtaining the alignment deviation through the coordinate data of the reflected light spot, and further improving the alignment accuracy. Attached Figure Description

[0023] Figure 1 This is a schematic diagram of the fiber optic spatial wireless sensing technology mentioned in the background section of this application.

[0024] Figure 2 This is a schematic diagram of the anti-shake alignment system provided in the embodiments of this application.

[0025] Figure 3 This is a schematic diagram of the internal connections and signal flow of the anti-shake alignment system provided in the embodiments of this application.

[0026] Figure 4 This is a schematic diagram of the optical path of the four-quadrant detection unit provided in the embodiments of this application.

[0027] Figure 5 This is a schematic diagram of the optical path of the fiber optic sensing end provided in the embodiments of this application.

[0028] Figure 6 This is a control flowchart of the alignment control unit provided in an embodiment of this application. Detailed Implementation

[0029] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0030] In this application, the terms "first" and "second," etc., are used to distinguish different objects, not to describe a specific order of objects. For example, "first response message" and "second response message," etc., are used to distinguish different response messages, not to describe a specific order of response messages.

[0031] In this application, the term "electrical connection" can refer to a direct circuit connection or a signal transmission via a communication protocol.

[0032] In the embodiments of this application, the terms "exemplary" or "for example" are used to indicate that something is an example, illustration, or description. Any embodiment or design that is described as "exemplary" or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design. Specifically, the use of the terms "exemplary" or "for example" is intended to present the relevant concepts in a specific manner.

[0033] In the description of the embodiments of this application, unless otherwise stated, "multiple" means two or more, for example, multiple processing units means two or more processing units, multiple elements means two or more elements, etc.

[0034] First, the technical terms involved in the embodiments of this application will be introduced.

[0035] An inertial measurement unit (IMU) is a sensor used to measure the angular velocity and linear acceleration of an object.

[0036] Real-Time Kinematic (RTK) is a satellite positioning technology that can provide absolute position coordinates at the centimeter or even millimeter level.

[0037] A quadrant detector (QD) is an optical position sensor that detects the position of a reflected light spot on its sensitive surface.

[0038] The Proportional-Integral-Derivative Control Algorithm (PID) is a technique that uses three pieces of information—the current error, the accumulated past error, and the future trend of error—to calculate a control quantity to adjust the controlled object.

[0039] The technical solution of this application will be further described below with reference to embodiments thereof. Figure 2 As shown, the image stabilization alignment system of this application is installed at the signal demodulation end to adjust the position and attitude of the signal demodulation end, thereby achieving optical path alignment between the signal demodulation end and the fiber optic sensing end. It includes a gimbal unit, an alignment control unit, an attitude sensing unit, a positioning unit, an image acquisition unit, a four-quadrant detection unit, and a piezoelectric ceramic fine-tuning unit. The positional relationship and main functions of each unit are shown below: The four-quadrant detection unit and the signal demodulation end share an optical path and are used to acquire the coordinate data of the reflected light spot of the reflected light returned from the optical fiber sensing end. The positioning unit is used to acquire the position coordinate data of the signal demodulation end; An attitude sensing unit is used to acquire attitude data from the signal demodulation terminal; An image acquisition unit is used to acquire image data from the optical fiber sensing end; An alignment control unit is used to generate a first control signal and a second control signal, and sends the first control signal to the gimbal unit and the second control signal to the piezoelectric ceramic fine-tuning unit. The first control signal is generated based on the attitude deviation calculation of the signal demodulation end, and the attitude deviation is derived from the attitude data. The second control signal is generated based on at least one of the light intensity loss of the reflected light, multi-source data deviation, and Kalman filter data. The light intensity loss is derived from the reflected light intensity data obtained by the signal demodulation end. The multi-source data deviation is obtained by weighted fusion of the reflected light spot coordinate data, attitude data, and image data. The Kalman filter data is obtained by performing time synchronization and Kalman filter correction on the reflected light spot coordinate data, attitude data, position coordinate data, and image data. A gimbal unit, the fixed end of which is connected to a mobile vehicle, and the movable end of which is attached to the signal demodulation terminal, for adjusting the attitude of the signal demodulation terminal according to the received first control signal; A piezoelectric ceramic fine-tuning unit, wherein the fixed end of the piezoelectric ceramic fine-tuning unit is connected to the signal demodulation end, and the movable end of the piezoelectric ceramic fine-tuning unit is connected to the transceiver collimator in the signal demodulation end, for adjusting the attitude of the transceiver collimator according to the received second control signal.

[0040] For the connection relationships between the various units within the system and the specific signal flow directions, please refer to [link / reference]. Figure 3 As shown.

[0041] The fixed end of the gimbal unit is connected to the mobile vehicle, and the movable end of the gimbal unit is attached to the signal demodulation terminal. The gimbal unit adopts a three-axis electric gimbal (X / Y / Z axis). The X-axis of the gimbal unit is used to adjust the roll angle of the signal demodulation terminal, the Y-axis of the gimbal unit is used to adjust the pitch angle of the signal demodulation terminal, and the Z-axis of the gimbal unit is used to adjust the yaw angle of the signal demodulation terminal.

[0042] The fixed end of the piezoelectric ceramic fine-tuning unit is connected to the signal demodulation end, and the moving end is connected to the transceiver collimator in the signal demodulation end. The piezoelectric ceramic fine-tuning unit adopts a three-axis adjustment structure (X / Y / Z axes). The X-axis is used to adjust the yaw angle of the transceiver collimator, the Y-axis is used to adjust the pitch angle, and the Z-axis is used to adjust the forward and backward displacement. The attitude sensing unit uses an IMU. The positioning unit uses an RTK. The image acquisition unit uses a high-definition vision camera. The four-quadrant detection unit uses a QD (Quadrant Detector).

[0043] In this embodiment, the four-quadrant detection unit and the signal demodulation end share a common optical path, see details below. Figure 4 As shown: The first optical signal (650nm) and the second optical signal (1520nm~1560nm) emitted by the light source module are combined and then emitted together from the transceiver collimator to the fiber optic sensing end via the circulator. The first optical signal (650nm) and the second optical signal (1520nm~1560nm) returned from the fiber optic sensor are then received by the signal demodulation unit via a transceiver collimator. After passing through a circulator, the first optical signal (650nm) and the second optical signal (1520nm~1560nm) enter the beam splitter. The beam splitter returns the first optical signal (650nm) to the four-quadrant detection unit (QD), and the beam splitter returns the second optical signal (1520nm~1560nm) to the demodulation module.

[0044] In this embodiment, achieving optical path alignment between the signal demodulation end and the fiber optic sensing end requires preliminary preparation and system configuration, as follows: Mobile vehicle, using a low-vibration drone model; The signal demodulation unit is equipped with a light source module, including a 650nm red indicator laser and a 1550nm single-mode laser. Wavelength stability ).

[0045] The four-quadrant detection unit and the signal demodulation end share an optical path module; the optical path module includes a beam combiner (for combining 1550nm and 650nm laser beams), a circulator (1 port in, 2 ports out, 2 ports in, 3 ports out), a transceiver collimator, and a beam splitter (distributing 10% of the reflected light to the four-quadrant detector and 90% to the demodulation module); the four-quadrant detection unit is equipped with an optical fiber beam splitter (model compatible with FC / APC interface), with a splitting ratio of 10:90 (10% of the optical power is distributed to the QD for alignment detection, and 90% of the optical power is transmitted to the FBG for sensor signal acquisition), insertion loss ≤0.2dB, operating wavelength range 1520-1620nm, and return loss ≥50dB.

[0046] The image acquisition unit uses an industrial area scan camera with a pixel physical size. ,focal length (Compatible with 8mm~12mm adjustable); dedicated sampling frequency of 30fps for spot recognition; adaptive exposure time range of 5ms~50ms (5ms~10ms in strong light, 30ms~50ms in fog / low light); gain adjustment range of 1-5 times to ensure spot recognition stability under different lighting conditions. The four-quadrant detection unit uses a four-quadrant detector (QD, position resolution 0.001mm). The positioning unit uses RTK-GPS (positioning accuracy ±1cm, sampling frequency 5Hz). The attitude sensing unit uses a high-precision IMU (zero-bias stability 0.01° / h, sampling frequency 2000Hz). The optical path opening at the fiber optic sensing end is circular, with a diameter... The edge of the optical path opening is marked with a high-contrast black border (2mm wide). A high-reflectivity target is attached to the surrounding area of ​​the optical path opening. The high-reflectivity target adopts a concentric ring structure (outer circle diameter). Inner diameter The coaxiality tolerance between the target center and the opening center is ≤0.1mm, and the target reflectivity is ≥90% (500nm~1600nm band), which enhances the robustness of red spot recognition.

[0047] The gimbal uses a three-axis motorized gimbal (alignment accuracy 0.01°, response time 5ms), and the piezoelectric ceramic fine-tuning unit uses a piezoelectric ceramic fine-tuning component (…). Temperature drift coefficient ≤ 0.01μm / ℃ (operating range -20℃ to 60℃), using a piecewise linear temperature drift compensation algorithm: when hour, ;when hour, ;when hour, ( The ambient temperature is expressed in degrees Celsius (°C). Displacement is used to compensate for temperature drift (unit: μm).

[0048] In this embodiment, the gimbal unit is fixed to the drone fuselage (low-vibration model) by a shock-absorbing bracket.

[0049] The piezoelectric ceramic fine-tuning unit is a triaxial piezoelectric ceramic actuator (X / Y / Z axis). The fixed end of the piezoelectric ceramic fine-tuning unit is connected to the signal demodulation end, and the moving end of the piezoelectric ceramic fine-tuning unit is connected to the transceiver collimator in the signal demodulation end. The micron-level displacement of the piezoelectric ceramic fine-tuning unit can be directly transmitted to the transceiver collimator.

[0050] The gimbal unit is the coarse adjustment component, the piezoelectric ceramic fine adjustment unit is the fine adjustment component, and the transceiver collimator is the final adjustment target. The two are mechanically connected to form a hierarchical linkage of coarse adjustment and fine adjustment. There is no direct interaction of electrical signals. Both are controlled by the alignment control unit to issue control signals to perform the adjustment.

[0051] The fiber optic sensing end is equipped with a sensing fiber optic grating with a center wavelength of 1550nm (wavelength tolerance ±0.5nm), reflectivity ≥95%, 3dB bandwidth of 0.1nm, return loss ≥50dB, fiber type Corning SMF-28e, grating length of 15mm, and coating type of acrylate, which is suitable for fiber optic sensing and optical path coupling requirements.

[0052] Camera calibration and parameter preset: Camera intrinsic parameter calibration is completed using OpenCV to obtain focal length f, principal point coordinates (cx, cy), and distortion parameters for accurate mapping of pixel coordinates to physical angles; Target area preset at ground control station: A pixel coordinate system is established with the center of the camera image as the origin, and the desired position of the optical path opening of the fiber optic sensor end in the image is set as the central rectangular area (side length 50 pixels, corresponding to an actual size of 10mm), and the preset ellipticity threshold ε≥0.9 (the ratio of the minor axis to the major axis of the ellipse, which is close to 1 when it is a circular spot).

[0053] Algorithm initialization: Load the preset red spot recognition model, using the LAB color space threshold ( Lock the red area, disable camera auto gain and white balance to avoid ambient light interference; initialize UAV PID control parameters: UAV translation control ( ), UAV attitude control ( ), adapted to the response characteristics of drones.

[0054] like Figure 5 The diagram shows the optical path of the fiber optic sensing end. The incident light enters the fiber optic sensing end through the optical path opening, and after being reflected by the internal sensing grating, it is reflected again from the optical path opening to the signal demodulation end.

[0055] like Figure 6 As shown, the specific control flow of the alignment control unit includes the following steps: I. Coarse Adjustment of Mobile Vehicles: 1. Real-time recognition and feature extraction of red light spots (1) Image data preprocessing: The camera acquires image data from the fiber optic sensor in real time. Environmental noise is removed by Gaussian filtering (kernel size 5×5). Morphological opening operation (corrosion followed by dilation) is used to eliminate burrs on the edge of the light spot caused by dust and shadows, thereby enhancing the integrity of the light spot outline. (2) Spot segmentation and filtering: Based on a preset color threshold, through... The function extracts the red color block, with the following filtering criteria: (Eliminating stray light interference) (Distinguish the red light spot from other red interference objects) (Ensure that it is a laser spot and not ambient reflected light); (3) Feature parameter extraction: Ellipse fitting (least square method) is performed on the selected red light spots to obtain the center coordinates of the light spots. Given the major axis length 'a' and the minor axis length 'b', calculate the ellipticity. Simultaneously, the Canny edge detection algorithm is used to identify the black border of the sensor opening and extract the center coordinates of the opening. With the radius of the opening .

[0056] 2. Adjustment of the position of the mobile vehicle Using a "pixel deviation-physical displacement" mapping logic, the UAV is driven to translate through PID closed-loop control until the center of the light spot emitted from the signal demodulation end coincides with the center of the opening at the fiber optic sensing end. (1) Deviation calculation: Calculate the center of the light spot With the center of the opening Pixel deviation The distance between the signal demodulation end measured by RTK and the fiber optic sensing end under test is obtained. Through formula ( The physical size of a pixel, in units The pixel deviation is converted into the drone's translation angle deviation, and then the movement distance is obtained. : ; (For example: At that time, a 1-pixel deviation corresponds to an actual displacement of 0.2mm). (2) Determining the direction of movement: If The drone needs to move to the right; Then shift to the left; Then move forward; Then it will shift backward, and the speed of the shift is positively correlated with the magnitude of the deviation. (to avoid light spot loss) (3) After receiving the direction and distance of movement, the UAV calculates the PID control command and performs closed-loop convergence: the UAV moves step by step according to the PID control command, and updates the center coordinates of the spot in real time until... When the light spot falls into the preset central rectangular area (±25 pixels), it completely covers the sensor opening. The translation adjustment stops, and the current RTK coordinate data is recorded.

[0057] 3. Adjusting the attitude of the mobile vehicle Utilizing the correlation between "spot morphology and attitude deviation" (when there is a pitch / roll angle between the UAV and the sensor, the vertically incident circular spot will be stretched into an ellipse; the larger the angle deviation, the smaller the ellipticity), the UAV's attitude can be adjusted to restore the spot to a circular shape: (1) Ellipticity calculation: Image data is acquired from the image acquisition unit, the outgoing light spot of the signal demodulation end is identified from the image data, the outgoing light spot is fitted with an ellipse, and the ellipticity of the light spot is calculated. (2) Deviation calculation: If ellipticity Calculate the angle between the major axis of the light spot and the coordinate axes of the image. If the major axis is closer to the vertical direction This is determined to be a pitch angle deviation of the drone; if the major axis is closer to the horizontal direction... The deviation was determined to be a roll angle deviation; attitude adjustment deviation value. (k is the calibration coefficient, calibrated experimentally) That is, an ellipticity of 0.8 corresponds to an angular deviation of 3°. (3) Attitude Adjustment: The UAV adjusts its attitude according to the type of deviation and the attitude adjustment deviation value: When there is a pitch angle deviation, if the upper half of the long axis of the light spot is longer, the UAV needs to tilt up (reduce the pitch angle); if the lower half is longer, it needs to tilt down (increase the pitch angle); when there is a roll angle deviation, if the left half of the long axis of the light spot is longer, the UAV needs to roll to the left; if the right half is longer, it needs to roll to the right. To prevent the light spot from detaching from the aperture area; (4) Convergence verification: Real-time monitoring of ellipticity changes, when When the optical path is stable for three consecutive frames, it is determined that the optical path is perpendicular, the attitude adjustment stops, and the current IMU attitude data is recorded. At this time, the red light spot covers the sensor opening in a circular shape. .

[0058] 4. Alignment state locking and connection (1) Alignment status verification: The hovering stability of the drone was confirmed by fusing RTK and IMU data. Simultaneously, the continuity of the light spot coverage is detected (no separation from the aperture area for 10 consecutive frames); in other embodiments, the following conditions are used for judgment: If the ellipticity of the light spot is greater than the threshold (near-circular light spot), the ellipticity of the light spot is calculated as follows: Ellipticity = Minor axis length / Major axis length (calculated by extracting the light spot contour through the camera image edge detection algorithm, fitting an ellipse). The light spot covers the optical path opening at the fiber optic sensing end. The standard for light spot coverage is: the offset between the center of the light spot and the center of the opening is ≤0.3mm, and more than 90% of the light spot area is located within the opening area.

[0059] (2) Alignment data synchronization: After the drone's hovering stability and light spot coverage continuity meet the requirements, initialize the baseline parameters: The current RTK coordinate data is used as the reference position coordinate data, the current IMU attitude data is used as the reference attitude data, the current reflected light spot coordinate data is used as the reference reflected light spot coordinate data, the current image data is used as the reference image data, and the current reflected light intensity is used as the reference reflected light intensity data.

[0060] Then, the gimbal unit performs further coarse adjustments based on the reference parameters to achieve the transition of alignment accuracy from the millimeter level to the micrometer level.

[0061] 5. Anti-interference optimization and robust design (1) Ambient light adaptive: When the ambient light intensity is >10000 Lux (such as strong direct light), the threshold range of the red spot is automatically adjusted (the range of A channel is narrowed to 20-127), and the laser output power is increased (by 30%) to ensure the success rate of spot recognition. ; (2) Recapture of lost spot: If the spot is lost due to drone movement or obstruction, the following fast recapture mechanism is activated: the drone returns to the location coordinates of the most recently recorded position, the laser remains on, the camera expands the recognition range (200×200 pixel area in the center of the image), the template matching algorithm is used to quickly locate the opening of the fiber optic sensor end, and steps 1-3 are executed again. (3) Multi-feature redundancy verification: When the spot recognition is interfered with, the black border feature of the sensor opening is combined with the contour matching algorithm to help locate the opening position, avoid alignment failure caused by a single spot feature, and improve the adaptability to complex scenes.

[0062] II. Fine-tuning of the gimbal unit and piezoelectric ceramic fine-tuning unit 1. Dynamic reference calibration Design dynamic calibration trigger conditions: The system is triggered at fixed time intervals; in some embodiments, dynamic calibration is set to be triggered every 30 seconds. Alternatively, it can be triggered when the coordinate deviation of the reflected light spot detected by QD is greater than a preset deviation value multiple times. In some embodiments, dynamic calibration is triggered when the coordinate deviation of the reflected light spot detected is greater than 0.05mm 10 times consecutively.

[0063] Dynamic calibration of reference data is performed in response to calibration trigger conditions: The intensity data of the reflected light is obtained from the signal demodulation end, specifically from the demodulation module of the signal demodulation end, and used as the calibrated reference reflected light intensity data. The gimbal unit is driven to make four fine adjustments, each within a range of ±0.03°. Based on the zero-bias stability of the IMU (0.01° / h) and the zero-bias stability of the attitude sensing unit (IMU) (0.01° / h), this adjustment range can completely cover the range of zero-bias variation, while avoiding the reflected light spot from detaching from the optical path opening at the fiber optic sensing end due to large adjustments. The criteria for determining "spot stability" after fine adjustment are: the spot offset of five consecutive QD detections is ≤0.01mm, and the light intensity fluctuation is ≤0.05dB. After each adjustment, once the light spot stabilizes, record the reflected light spot coordinate data acquired by QD and the IMU attitude data. Then, subtract the reference reflected light spot coordinate data from the reflected light spot coordinate data to obtain the reflected light spot coordinate deviation for each adjustment. The attitude deviation is obtained by subtracting the reference attitude data from the attitude data. .

[0064] The four sets obtained from the four fine-tunings Substitute the preset coordinate attitude deviation mapping model (the coordinate attitude deviation mapping model is constructed by fitting the mapping relationship between attitude deviation and reflected spot coordinate deviation using the least squares method): ; ; The parameters are obtained by solving the equations. .

[0065] The calibrated reference reflected light spot coordinate data are: ; The calibrated reference attitude data are as follows: ; Here , and To obtain any set of attitude deviations when fine-tuning the gimbal unit.

[0066] After dynamic calibration is completed, the original reference value is directly replaced with the calibrated reference without the need for weighted fusion, ensuring that the reference data matches the current environment in real time.

[0067] 2. Adjusting the gimbal unit based on attitude deviation Real-time acquisition of IMU attitude data , (Roll angle, pitch angle, yaw angle), and calculate attitude deviations based on reference data: ; The first control signal is used to drive the gimbal unit's action based on the attitude deviation calculation: Using a PID algorithm based on attitude deviation , Calculate the rotation angles for pitch and yaw respectively: ; Among them, preset parameters are used. , It's a posture deviation. It is the rotation angle of the pitch angle or heading angle.

[0068] attitude deviation Substitute into the above formula In the middle, the pitch angle (Y-axis) and rotation angle of the gimbal unit are obtained. ; attitude deviation Substitute into the above formula In the middle, the yaw angle (Z-axis) rotation angle of the gimbal unit is obtained. ; The single-axis rotation of the gimbal unit is driven by a stepper motor. The rotation angle of the motor is proportional to the number of input pulses (the gimbal unit alignment accuracy is 0.01°, corresponding to a stepper motor step angle of 0.01° / pulse).

[0069] Pulse count calculation: (N is the number of pulses, with positive pulses corresponding to clockwise rotation and negative pulses corresponding to counterclockwise rotation).

[0070] Dual-axis signal output: The number of pulses corresponding to the pitch angle rotation. N The output is sent to the pitch axis motor of the gimbal unit. The number of pulses corresponding to the yaw angle rotation is output to the yaw axis motor of the gimbal unit, and the rotation speed is controlled by the pulse frequency (the higher the frequency, the faster the rotation), ultimately realizing the dual-axis coordinated rotation of the gimbal unit to counteract the attitude deviation of the UAV.

[0071] 3. Piezoelectric ceramic fine-tuning unit based on optical loss adjustment (1) Construct a loss deviation mapping model Continuously acquire reflected light spot coordinate data from QD, reflected light intensity data from the signal demodulation end (specifically, reflected light intensity data acquired from the demodulation module in the signal demodulation end), and position coordinate data from RTK. The distance value is obtained from the position coordinate data and the position coordinate data of the fiber optic sensor end under test. : ; in, It is the location coordinate data obtained by RTK. It is the position coordinate data of the fiber optic sensor under test (pre-stored in the system, for example, the position coordinate data of the fiber optic sensor under test is pre-stored in the system as nodes of the planned route).

[0072] The reflection spot coordinate deviation is obtained from the difference between the current reflection spot coordinate data and the reference reflection spot coordinate data. .

[0073] The deviation of the reflected light spot angle is calculated using the following formula. :

[0074]

[0075] Data of reflected light intensity Substituting into the following formula, we obtain the light intensity loss rate:

[0076] in, This is the baseline reflected light intensity data.

[0077] The angular deviation of multiple sets of reflected light spots and corresponding multiple sets of light intensity losses Substitute the values ​​into the pre-designed light intensity loss angle deviation mapping model (the loss deviation mapping model is constructed by fitting the mapping relationship between light intensity loss and reflected spot angle deviation using the least squares method):

[0078]

[0079] Obtain the coefficient ,in, The reference reflected light spot angle is:

[0080]

[0081] in, , These are the coordinate data of the reference reflected light spot.

[0082] (2) The reflected light intensity data acquired in real time by the demodulation module Substituting these values ​​into the above light intensity loss angle deviation mapping model, we obtain the corresponding reflected light spot angle deviation. .

[0083] (3) Based on the deviation of the reflected light spot angle Generate the second control signal to adjust the piezoelectric ceramic fine-tuning unit: The following formula is used to convert the reflected light spot angle deviation into a piezoelectric ceramic displacement to offset the light intensity loss: ; in, For the deviation of the reflected light spot angle ( ), As a preset proportionality coefficient, in this embodiment, the preset is... . For displacement.

[0084] when hour, The displacement of the piezoelectric ceramic fine-tuning component on the X-axis causes the transceiver collimator to deflect at a micrometer-level angle along the heading angle (horizontal direction); when hour, The displacement of the piezoelectric ceramic fine-tuning component on the Y-axis causes the transceiver collimator to deflect at the micrometer level along the pitch angle (vertical direction).

[0085] Based on the following formula, displacement This is converted into the voltage output by the piezoelectric ceramic trimmer on the corresponding axis piezoelectric ceramic electrode: ; For example: like Then the displacement Output voltage .

[0086] like (Reverse deviation), then displacement Output voltage (Positive and negative voltages correspond to the expansion and contraction directions of the piezoelectric ceramic).

[0087] The X / Y / Z axis deviations are calculated and compensated independently, and the drive voltage is output synchronously. The adjustment response time is <10μs, avoiding the superposition of deviations of other axes caused by single-axis adjustment.

[0088] 4. Piezoelectric ceramic fine-tuning unit based on multi-source data deviation adjustment (1) Real-time acquisition of reflected spot coordinate data obtained by QD, attitude data obtained by IMU and image data obtained by camera; The reflection spot coordinate deviation is obtained from the difference between the current reflection spot coordinate data and the reference reflection spot coordinate data. .

[0089] The attitude deviation is obtained from the difference between the current attitude data and the reference attitude data. .

[0090] The camera's viewing angle deviation is obtained from the reference image data, the current image data, and the position coordinate data of the fiber optic sensor. Specifically: The coordinates of the first optical path opening at the fiber optic sensing end are obtained from the current image data. The coordinates of the second optical path opening at the fiber optic sensing end are obtained from the reference image data. The aperture coordinate deviation is obtained from the difference between the aperture coordinates of the first optical path and the aperture coordinates of the second optical path; The aperture coordinate deviation is converted into the camera viewing angle deviation using the intrinsic parameters (focal length, pixel size) of the image acquisition unit.

[0091] (2) The multi-source data deviation is obtained by weighted summation of the reflected light spot coordinate deviation, attitude deviation, and camera viewing angle deviation according to the preset weights. The X-axis deviation and Y-axis deviation of the multi-source data deviation are as follows: ; ; The , The reference attitude data is obtained by subtracting the reference attitude data from the current attitude data. , It is obtained by subtracting the reference reflected spot coordinate data from the current reflected spot coordinate data.

[0092] In this embodiment, the weights are determined by fitting experimental data from 100 different environments (vibration, illumination, distance) and the final weight allocation is as follows: QD deviation weight 0.5, IMU attitude deviation weight 0.3, RTK distance deviation weight 0.1, and camera view deviation weight 0.1.

[0093] (3) Generate a second control signal based on multi-source data deviation to adjust the piezoelectric ceramic fine-tuning component: Utilizing angular deviation and Adjusting the piezoelectric ceramic fine-tuning unit: Based on angle deviation and Generate the second control signal to adjust the piezoelectric ceramic fine-tuning unit: The following formula is used to convert the reflected light spot angle deviation into a piezoelectric ceramic displacement to offset the light intensity loss: ; in, For the deviation of the reflected light spot angle ( ), In this embodiment, as a preset scaling factor, . For displacement.

[0094] when hour, The displacement of the piezoelectric ceramic fine-tuning component on the X-axis causes the transceiver collimator to deflect at a micrometer-level angle along the heading angle (horizontal direction); when hour, The displacement of the piezoelectric ceramic fine-tuning component on the Y-axis causes the transceiver collimator to deflect at the micrometer level along the pitch angle (vertical direction).

[0095] Based on the following formula, displacement This is converted into the voltage output by the piezoelectric ceramic trimmer on the corresponding axis piezoelectric ceramic electrode: ; For example: like Then the displacement Output voltage .

[0096] like (Reverse deviation), then displacement Output voltage (Positive and negative voltages correspond to the expansion and contraction directions of the piezoelectric ceramic).

[0097] The X / Y / Z axis deviations are calculated and compensated independently, and the drive voltage is output synchronously. The adjustment response time is <10μs, avoiding the superposition of deviations of other axes caused by single-axis adjustment.

[0098] 5. Piezoelectric ceramic fine-tuning unit based on Kalman filter adjustment (1) Data processing Real-time acquisition of reflected light spot coordinate data obtained by QD, attitude data obtained by IMU, position coordinate data obtained by RTK, and image data obtained by camera; the frequency of reflected light spot coordinate data is 2000Hz, the frequency of attitude data is 2000Hz, the frequency of position coordinate data is 5Hz, and the frequency of image data is 30fps.

[0099] Using the highest frequency of data acquisition as a benchmark (in this embodiment, the frequency of IMU data acquisition is 2000Hz as a benchmark), other low-frequency data are linearly interpolated, and image data is interpolated using nearest neighbor interpolation. All data are uniformly at a frequency of 2000Hz to ensure consistent data timing and meet the synchronization delay ≤5μs. The ultimate goal of Kalman filtering in this application is to calculate the true deviation value (position deviation) from the "raw data of sensor noise interference". , , angle deviation , This true deviation is then used to drive the fine-tuning of the piezoelectric ceramic. The state equation is responsible for "predicting the deviation," while the observation equation is responsible for "correcting the prediction using sensor data." Together, they achieve noise-free deviation estimation. Furthermore, the dimensions of all matrices / vectors are as follows: the state vector is 4×1 (4 deviations), so the matrix dimensions of the state equation and the observation equation must match (for example, the state transition matrix A is 4×4).

[0100] (2) Determine the state equation ; in, Let this be the current state vector. ,in, and It is the deviation between the x-axis and y-axis directions in the position coordinate data. It is the roll angle deviation in the attitude data. It refers to the pitch angle deviation in the attitude data.

[0101] Here is the state transition matrix: ; This is the optimal state at the previous moment; To control the input matrix:

[0102] To control the input vector:

[0103] For the process noise vector:

[0104] , , , They are respectively noise, noise, noise, noise.

[0105] Through the state equations, we obtained The "predicted value" of the time deviation. (neglect Because it is extremely small, this prediction is "noise-free but may have a slight lag" (for example, if the deviation at the previous moment was 0.01 mm, the current prediction is also 0.01 mm), and it needs to be corrected using the observation equation.

[0106] (3) Determine the observation equation

[0107] in, ; and For the roll and pitch angles in the attitude data; , For position coordinate data Direction coordinates and Direction coordinates; and For the coordinate data of the reflected light spot Direction coordinates and Direction coordinates; and These are the coordinates of the optical path opening at the fiber optic sensing end in the image data, obtained from image data identification.

[0108] For the observation matrix, ; It is the observation noise vector; With the observation equation, the prediction bias can be used. Calculate theoretical observations Comparison with theoretical observations and actual sensor data , calculate the deviation Then, the prediction bias is corrected by Kalman gain to obtain the true bias after denoising. ; (4) Specific steps of Kalman filtering: (41) Predict the current deviation using the state equation (Based on the actual deviation at the previous moment, noise-free but potentially inaccurate); (42) Calculate the theoretical observation values ​​using the observation equation. And compare with actual sensor data The error is obtained; (43) Using Kalman gain (derived from process noise covariance matrix) and observation noise covariance matrix (Matrix calculation) Balances "prediction error" and "observation error" to make corrections. To obtain the true deviation at the current moment ; (44) Next sampling period (after 0.5ms), become Repeat steps 1-3 to continuously output noise-free true deviation values, drive the piezoelectric ceramic fine adjustment, and achieve high-precision alignment of 0.01°.

[0109] Process noise covariance matrix (corresponding to state vector) The uncertainty is: ; in, It is a natural constant.

[0110] Observation noise covariance matrix ; (5) The filtered true state vector The coordinate deviation of the reflected light spot is converted into the angle deviation of the reflected light spot: The distance value is obtained from the position coordinate data and the position coordinate data of the fiber optic sensor end under test. : ; in, It is the location coordinate data obtained by RTK. It is the position coordinate data of the fiber optic sensor under test (pre-stored in the system).

[0111] Position deviation in the X-axis direction of the reflected light spot coordinate deviation Converted into angular deviation .

[0112] Position deviation in the Y-axis direction of the reflected light spot coordinate deviation Converted into angular deviation .

[0113] The reflected light spot angle deviation is used as Kalman filter data to generate a second control signal to adjust the piezoelectric ceramic fine-tuning component; based on the reflected light spot angle deviation... Generate a second control signal to adjust the piezoelectric ceramic fine-tuning unit; for specific steps, please refer to part (3) of step 3, which can be followed without further explanation.

[0114] Based on the methods in the above embodiments, this application provides an electronic device that may include a processor, a communications interface, a memory, and a communication bus, wherein the processor, communications interface, and memory communicate with each other via the communication bus. The processor may invoke logical instructions stored in the memory to execute the methods in the above embodiments.

[0115] Furthermore, the logical instructions in the aforementioned memory can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application.

[0116] Based on the methods in the above embodiments, this application provides a computer-readable storage medium storing a computer program that, when run on a processor, causes the processor to execute the methods in the above embodiments.

[0117] Based on the methods in the above embodiments, this application provides a computer program product that, when run on a processor, causes the processor to execute the methods in the above embodiments.

[0118] It is understood that the processor in the embodiments of this application can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. A general-purpose processor can be a microprocessor or any conventional processor.

[0119] The method steps in this application embodiment can be implemented in hardware or by a processor executing software instructions. The software instructions can consist of corresponding software modules, which can be stored in random access memory (RAM), flash memory, read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), registers, hard disks, portable hard disks, CD-ROMs, or any other form of storage medium known in the art. An exemplary storage medium is coupled to the processor, enabling the processor to read information from and write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and the storage medium can reside in an ASIC.

[0120] In the above embodiments, implementation can be achieved entirely or partially through software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented entirely or partially as a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted through the computer-readable storage medium. The computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid-state disk (SSD)).

[0121] It is understood that the various numerical designations used in the embodiments of this application are merely for the convenience of description and are not intended to limit the scope of the embodiments of this application.

[0122] Those skilled in the art will readily understand that the above description is merely a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A shake-stabilized alignment system for fiber optic spatial wireless sensing and detection, characterized in that, The image stabilization alignment system is installed at the signal demodulation end and specifically includes: The four-quadrant detection unit and the signal demodulation end share an optical path and are used to acquire the coordinate data of the reflected light spot of the reflected light returned from the optical fiber sensing end. The positioning unit is used to acquire the position coordinate data of the signal demodulation end; An attitude sensing unit is used to acquire attitude data from the signal demodulation terminal; An image acquisition unit is used to acquire image data from the optical fiber sensing end; An alignment control unit is used to generate a first control signal and a second control signal, and send the first control signal to the gimbal unit and the second control signal to the piezoelectric ceramic fine-tuning unit; the first control signal is generated based on the attitude deviation calculation of the signal demodulation end, and the attitude deviation is derived based on the attitude data; the second control signal is generated based on the reflected light spot angle deviation calculated based on the light intensity loss of the reflected light, and the light intensity loss is derived based on the reflected light intensity data obtained by the signal demodulation end; the gimbal unit has a fixed end connected to a moving vehicle and a movable end on which the signal demodulation end is mounted, used to adjust the attitude of the signal demodulation end according to the received first control signal; A piezoelectric ceramic fine-tuning unit, wherein the fixed end of the piezoelectric ceramic fine-tuning unit is connected to the signal demodulation end, and the movable end of the piezoelectric ceramic fine-tuning unit is connected to the transceiver collimator in the signal demodulation end, for adjusting the attitude of the transceiver collimator according to the received second control signal.

2. The anti-shake alignment system according to claim 1, characterized in that, The alignment control unit includes an optical loss adjustment subunit; The optical loss adjustment subunit is used to obtain reflected light intensity data from the signal demodulation terminal; The light intensity loss is obtained from the difference between the reflected light intensity data and the reference reflected light intensity data; Substituting the light intensity loss into the loss deviation mapping model, we obtain the reflected light spot angle deviation used to compensate for the light intensity loss. Based on the reflected light spot angle deviation, a second control signal is generated and sent to the piezoelectric ceramic fine-tuning unit to control the transceiver collimator to adjust its attitude, so that the reflected light from the fiber optic sensing end enters the transceiver collimator.

3. The anti-shake alignment system according to claim 1, characterized in that, The alignment control unit includes a loss deviation mapping model construction subunit; The loss deviation mapping model construction subunit is used to obtain reflected light intensity data from the signal demodulation end, reflective spot coordinate data from the four-quadrant detection unit, and position coordinate data from the positioning unit; The distance value is obtained from the position coordinate data and the position coordinate data of the fiber optic sensor end under test; The difference between the reflected spot coordinate data and the reference reflected spot coordinate data is used to obtain the reflected spot coordinate deviation; The angle deviation of the reflected light spot is obtained by the arctangent of the coordinate deviation of the reflected light spot and the distance value. The light intensity loss is obtained from the difference between the reflected light intensity data and the reference reflected light intensity data; A loss deviation mapping model is constructed by fitting the mapping relationship between the light intensity loss and the reflected light spot angle deviation.

4. The anti-shake alignment system according to claim 2 or 3, characterized in that, The loss deviation mapping model is specifically as follows: in, It is the reflected light intensity data. This is the baseline reflected light intensity data; These are model coefficients; It is a deviation in the angle of the reflected light spot; It is the reference reflected light spot angle.

5. The anti-shake alignment system according to claim 1, characterized in that, The alignment control unit includes a gimbal adjustment subunit, which is used to acquire attitude data from the attitude sensing unit and obtain the attitude deviation from the difference between the reference attitude data and the attitude data. Based on the attitude deviation, the first control signal is calculated and sent to the gimbal unit to control the gimbal unit to adjust its attitude, thereby allowing the reflected light from the fiber optic sensor to enter the signal demodulation terminal.

6. The anti-shake alignment system according to claim 1, characterized in that, The alignment control unit includes a reference calibration subunit, used to calibrate reference attitude data, reference reflected light spot coordinate data, and reference reflected light intensity data in response to calibration trigger conditions. The intensity data of the reflected light is obtained from the signal demodulation terminal and used as the calibrated reference reflected light intensity data. The coordinate data of the reflected light spot is obtained from the four-quadrant detection unit, and the attitude data is obtained from the attitude sensing unit. The reflection spot coordinate deviation is obtained from the difference between the reflection spot coordinate data and the reference reflection spot coordinate data; the attitude deviation is obtained from the difference between the attitude data and the reference attitude data. A coordinate attitude deviation mapping model is constructed by fitting multiple sets of mapping relationships between attitude deviations and reflected light spot coordinate deviations; The output deviation of the coordinate attitude deviation mapping model is used as a correction factor to calibrate the reference reflected light spot coordinate data; the attitude deviation is used as a correction factor to calibrate the reference attitude data. The calibration triggering conditions include, but are not limited to: triggering at a preset time interval or triggering when the coordinate deviation of the reflected light spot obtained from multiple consecutive acquisitions exceeds a preset deviation threshold.

7. The anti-shake alignment system according to claim 1, characterized in that, The four-quadrant detection unit includes a visible light source, a beam splitter, a beam combiner, and a four-quadrant detector. The visible light source emits a visible light signal, which is combined with a sensing light signal by the beam combiner and emitted as a single beam to the fiber optic sensing end. The reflected light signal reflected back from the fiber optic sensing end is split into a reflected sensing light signal and a reflected visible light signal by the beam splitter, and the reflected visible light signal enters the four-quadrant detector.

8. The anti-shake alignment system according to claim 1, characterized in that, The gimbal unit adopts a three-axis adjustment structure, wherein the X-axis of the gimbal unit is used to adjust the roll angle of the signal demodulation end, the Y-axis of the gimbal unit is used to adjust the pitch angle of the signal demodulation end, and the Z-axis of the gimbal unit is used to adjust the yaw angle of the signal demodulation end. The piezoelectric ceramic fine-tuning unit adopts a three-axis adjustment structure. The X-axis of the piezoelectric ceramic fine-tuning unit is used to adjust the heading angle of the transceiver collimator, the Y-axis is used to adjust the pitch angle of the transceiver collimator, and the Z-axis is used to adjust the forward and backward displacement of the transceiver collimator.

9. The anti-shake alignment system according to claim 1, characterized in that, It also includes a mobile vehicle displacement control unit, used to acquire image data from the image acquisition unit and position coordinate data from the positioning unit; The distance value is obtained from the position coordinate data and the position coordinates of the fiber optic sensor end under test; The emitted light spot of the signal demodulation end is identified from the image data, and the position pixel deviation is obtained from the center position of the emitted light spot and the center position of the optical path opening of the fiber optic sensing end. The position pixel deviation is converted into a translation angle deviation using the distance value, and the movement direction of the mobile vehicle is obtained from the translation angle deviation. Due to the translation angle deviation and the distance value The distance traveled by the mobile vehicle can then be calculated. : ； The direction and distance of movement are sent to the mobile vehicle, and the mobile vehicle is controlled to move carrying the signal demodulation end, so that the emitted light from the signal demodulation end enters the optical fiber sensing end.

10. The anti-shake alignment system according to claim 1, characterized in that, It also includes the mobile vehicle attitude control unit: Used to acquire image data from the image acquisition unit; The emitted light spot of the signal demodulation end is identified from the image data, and the ellipticity of the emitted light spot is calculated by elliptic fitting. If the ellipticity is greater than the preset ellipticity, the relationship between the major axis of the light spot and the vertical and horizontal directions is further calculated. If the major axis is closer to the vertical direction, the deviation type of the moving vehicle is determined to be pitch angle deviation; otherwise, the deviation type of the moving vehicle is determined to be roll angle deviation. The attitude adjustment deviation value is calculated based on the ellipticity and the preset calibration coefficient. The deviation type and the attitude adjustment deviation value are sent to the mobile vehicle, and the mobile vehicle is controlled to adjust the attitude of the signal demodulation end, so that the emitted light from the signal demodulation end is perpendicularly incident on the optical fiber sensing end.

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