A method for calibrating a fiber shape sensor based on a 3D printed model

Abstract

The application belongs to the technical field of three-dimensional reconstruction, and particularly relates to a fiber shape sensing calibration method based on a 3D printing model. A 3D printing calibration model with a space spiral groove structure is designed and prepared, so that the fiber sensor can be naturally embedded in the groove, and additional torsional strain and axial strain can be effectively avoided without gluing or clamping, and the accuracy of the calibration result is improved.

Description

Technical Field

[0001] This application belongs to the field of three-dimensional reconstruction technology, specifically relating to a fiber optic shape sensing calibration method based on a 3D printed model. Background Technology

[0002] Fiber optic shape sensing technology is a technique that reconstructs three-dimensional spatial morphology by measuring the strain distribution of optical fibers under bending and torsion. Compared with traditional electrical sensors and visual measurement methods, fiber optic shape sensing has significant advantages such as small size, light weight, strong resistance to electromagnetic interference, long-distance distributed measurement capability, and adaptability to complex environments. It is widely used in fields such as minimally invasive medical devices, aerospace structural health monitoring, flexible robots, and precision engineering measurement.

[0003] In multi-core helical fiber shape sensing, by arranging multiple outer core fibers within the fiber cross-section and introducing a helical structure, bending and torsion information can be sensed simultaneously. Combined with the continuous distribution of curvature and bending direction angle, high-precision shape reconstruction of the fiber in three-dimensional space is achieved. Therefore, multi-core helical fiber is considered one of the important technical routes for achieving high-resolution three-dimensional shape sensing. However, in practical applications, the measurement accuracy of multi-core fiber shape sensing systems is highly dependent on the accuracy of system parameters. Due to the unavoidable pitch deviation and core position error during fiber manufacturing and packaging, as well as the non-constant optical parameters of each fiber in a multi-core fiber, it is usually necessary to calibrate the fiber sensor before use, including but not limited to: bending sensitivity coefficient, torsion sensitivity coefficient, and the relative positional relationship between the cores.

[0004] Existing fiber optic shape sensing calibration methods mostly employ one of the following approaches: 1) gluing or fixing the fiber to the surface of a two-dimensional or three-dimensional calibration fixture with known curvature; 2) forcibly attaching the fiber to the calibration curve or mold using clamps, adhesives, or tensioning structures. These methods have significant shortcomings in practical use. First, gluing or clamping methods easily introduce additional axial tensile or torsional loads into the fiber, resulting in unwanted additional strain components superimposed on the measured strain, reducing the accuracy of the calibration results. Second, during three-dimensional curve calibration, it is often difficult to ensure natural fit of the fiber during spatial laying, easily leading to local slippage or torsional accumulation, causing inconsistencies between the theoretical shape and the actual stress state of the fiber. Summary of the Invention

[0005] To address the aforementioned problems, this application designs a fiber optic shape sensing calibration method that is simple in structure, has good repeatability, and avoids introducing additional torsional and tensile strain, thereby improving the accuracy and stability of multi-core fiber optic three-dimensional shape sensing systems. The technical solution of this application is as follows:

[0006] A fiber optic shape sensing calibration method based on a 3D printed model includes the following steps:

[0007] S1. Draw a 3D printing calibration model, wherein the calibration model adopts a spiral plate epitaxial structure;

[0008] S2. Place the optical fiber in a natural straight line and use an optical frequency domain reflection system to obtain the reference Rayleigh scattering optical frequency domain signal;

[0009] S3. Lay the optical fiber naturally along the spiral groove of the 3D printed model in the groove to obtain the frequency domain signal of Rayleigh scattered light.

[0010] S4. Obtain the strain signal of the multi-core optical fiber;

[0011] S5. Based on strain data and combined with the known three-dimensional spatial geometric parameters of the calibration model, establish the mapping relationship between fiber optic measurement data and theoretical data, including information such as curvature, bending direction angle, and torsion angle, and calibrate or correct the bending sensitivity coefficient and torsion sensitivity coefficient of the fiber optic sensor.

[0012] S6. Substitute the calibration parameters obtained in step S5 into the fiber shape reconstruction algorithm to invert the three-dimensional spatial shape of the fiber and compare it with the theoretical three-dimensional spatial coordinates of the calibration model.

[0013] Preferably, step S1, the design and preparation process includes:

[0014] Central support structure: A cylinder is constructed as the central support, with its axis serving as the central axis of the calibration model, providing overall structural support and spatial positioning reference;

[0015] Spiral blade extension structure construction: A spiral blade structure with a set thickness is formed by extending outward along the axial direction on the side of a cylinder; Multi-radius spiral curve construction: While keeping the pitch constant, by adjusting the radial distance of the spiral blade relative to the central axis, spiral lines with different spatial radii are drawn on the upper surface of the spiral blade, thereby constructing a variety of three-dimensional spatial curves with known curvature and deflection.

[0016] Spiral groove cutting: Cutting the spiral lines on the spiral blade to form spiral grooves for laying optical fibers;

[0017] Model preparation: The central support, spiral plate and spiral groove are integrated and prepared by 3D printing process.

[0018] Preferably, no additional axial tension or torsion is applied during the fiber laying process.

[0019] Preferably, in step S5, for a helical curve with radius R and pitch P, the theoretical curvature is... and torsion It can be represented as:

[0020] (1);

[0021] (2);

[0022] Therefore, the reference bending direction angle under the constraints of this model Its expression is:

[0023] (3);

[0024] In the formula, s represents the arc length coordinate obtained by integrating along the central axis of the fiber from the starting end of the fiber;

[0025] Based on the structural characteristics of multi-core optical fibers, the axial strain generated by each outer core under bending and torsion is expressed by the following formula:

[0026] (4);

[0027] (5);

[0028] in, and The first The radial distance and azimuth angle of the outer core relative to the central axis. It is the initial spin angle of the optical fiber. It is the torsion angle. It is the bending sensitivity coefficient. It is torsional strain. It is common mode strain.

[0029] Preferably, when the torsion is small, the torsional strain is... and torsion rate The relationship is approximately linear.

[0030] (6);

[0031] (7);

[0032] in, It is the spin rate. It is the torsional sensitivity coefficient. , , These are the strains of the three outer cores, and r is the fiber core pitch.

[0033] Furthermore, using the obtained axial strain data of the multi-core optical fiber, the measured bending direction angle after compensation based on the calculated measured curvature and torsion angle is compared with the theoretical model to establish the mapping relationship between the optical fiber measurement and the reference curvature and bending direction angle. The bending sensitivity coefficient and torsion sensitivity coefficient are calibrated or corrected by least squares fitting or other parameter estimation methods, thereby obtaining the calibrated optical fiber sensing parameters.

[0034] Compared with the prior art, the beneficial effects of this application are as follows:

[0035] By designing and fabricating a 3D-printed calibration model with a spatial spiral groove structure, the fiber optic sensor can be naturally embedded in the groove. Without the need for adhesives or clamps, it can effectively avoid introducing additional torsional and axial strains, thereby improving the accuracy of the calibration results. Attached Figure Description

[0036] Figure 1 The flowchart shows the fiber optic shape sensing calibration method based on a 3D printed model.

[0037] Figure 2 3D modeling drawings designed for computer graphics software;

[0038] Figure 3 To compare the reconstructed shape before and after calibration with the theoretical 3D curve. Detailed Implementation

[0039] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention. Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0040] The fiber optic shape sensing calibration method based on a 3D printed model described in this invention will be further explained below with reference to specific embodiments.

[0041] A fiber optic shape sensing calibration method based on a 3D printed model, the specific steps of which are as follows:

[0042] Step 1: Use computer graphics software to create a 3D printed calibration model. The calibration model adopts a helical epitaxial structure, and its design and fabrication process includes:

[0043] (1) Construction of the central support. A cylinder is constructed as the central support, and its axis is the central axis of the calibration model, which is used to provide overall structural support and spatial positioning reference.

[0044] (2) Construction of spiral blade extension structure. A spiral blade structure with a thickness of 0.5 cm is formed by extending outward along the axial direction on the side of the cylinder, and the pitch is 10 cm.

[0045] (3) Construction of multi-radius spiral curves. While keeping the pitch constant, by adjusting the radial distance of the spiral blade relative to the central axis, spirals with different spatial radii (6cm, 8cm, 10cm) are drawn on the upper surface of the spiral blade, thereby constructing a variety of three-dimensional spatial curves with known curvature and deflection.

[0046] (4) Spiral groove cutting. The spiral lines on the spiral plate are cut to form a spiral groove for laying optical fibers. The groove depth is 0.1cm and the groove width is 0.1cm.

[0047] Figure 2 A 3D model drawing created according to the steps described above is presented.

[0048] Model fabrication. The central support, spiral blades, and spiral grooves were fabricated as a single unit using 3D printing technology, with a printing tolerance within ±0.1mm.

[0049] Step 2: Place the optical fiber in a natural straight line and use an optical frequency domain reflection system to obtain the reference Rayleigh scattered optical frequency domain signal.

[0050] Step 3: Lay the optical fiber naturally along the spiral groove of the 3D printed model without applying any additional axial tension or torsion during the laying process, and obtain the Rayleigh scattering light frequency domain signal for measurement.

[0051] Step 4: Process the data from Step 2 and Step 3 to obtain the strain signal of the multi-core optical fiber.

[0052] Step 5: For any spiral groove path, the curvature of its space curve and torsion It can be determined by the model design parameters. For example, for a helical curve with radius R and pitch P, its theoretical curvature and torsion can be expressed as:

[0053] (1);

[0054] (2);

[0055] Therefore, the reference bending direction angle under the constraints of this model Its expression is:

[0056] (3);

[0057] Based on the structural characteristics of multi-core optical fibers, the axial strain generated by each outer core under bending and torsion can be expressed as follows:

[0058] (4);

[0059] (5);

[0060] in, and The first The radial distance and azimuth angle of the outer core relative to the central axis. It is the initial spin angle of the optical fiber. and These are the curvature and the angle of curvature. It is the torsion angle. It is the bending sensitivity coefficient. It is torsional strain. It is common mode strain.

[0061] When the torsion is small, the torsional strain will be... and torsion rate The relationship is approximately linear.

[0062] (6);

[0063] (7);

[0064] in, It is the spin rate. It is the torsional sensitivity coefficient.

[0065] Using the axial strain data of the obtained multi-core optical fiber, the measured curvature and the measured bending direction angle after compensation based on the above formula are compared with the theoretical model to establish the mapping relationship between optical fiber measurement and reference curvature and bending direction angle. The bending sensitivity coefficient and the torsion sensitivity coefficient are calibrated or corrected by least squares fitting or other parameter estimation methods to obtain the calibrated optical fiber sensing parameters.

[0066] Step Six: Substitute the calibration parameters obtained in Step Five into the fiber shape reconstruction algorithm to invert the three-dimensional spatial shape of the fiber and compare it with the theoretical three-dimensional spatial coordinates of the calibration model to verify the accuracy of the calibration method.

[0067] Figure 3 A comparison of the reconstructed shape before and after calibration with the theoretical 3D curve (pitch 10cm, radius 6cm) is presented, with the fiber axial length being 31cm. The results show that this invention achieves high-precision fiber shape sensing calibration by naturally embedding the fiber into a 3D-printed calibration model with a helical epitaxial structure without introducing additional torsion, and by utilizing the model's known curvature and deflection parameters to calibrate the bending and torsion sensitivity of the multi-core fiber.

[0068] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A fiber optic shape sensing calibration method based on a 3D printed model, characterized in that, Includes the following steps: S1. Draw a 3D printing calibration model, wherein the calibration model adopts a spiral plate epitaxial structure; S2. Place the optical fiber in a natural straight line and use an optical frequency domain reflection system to obtain the reference Rayleigh scattering optical frequency domain signal; S3. Lay the optical fiber naturally along the spiral groove of the 3D printed model to obtain the Rayleigh scattering light frequency domain signal; no additional axial tension or torsion is applied during the fiber laying process; S4. Obtain the strain signal of the multi-core optical fiber; S5. Based on strain data and combined with the known three-dimensional spatial geometric parameters of the calibration model, establish the mapping relationship between fiber optic measurement data and theoretical data, including curvature, bending direction angle, and torsion angle information, and calibrate or correct the bending sensitivity coefficient and torsion sensitivity coefficient of the fiber optic sensor. For radius R Pitch is P The spiral curve, its theoretical curvature and torsion It can be represented as: (1)； (2)； Therefore, the reference bending direction angle under the constraints of this model Its expression is: (3)； In the formula, s represents the arc length coordinate obtained by integrating along the central axis of the fiber from the starting end of the fiber; Based on the structural characteristics of multi-core optical fibers, the axial strain generated by each outer core under bending and torsion is expressed by the following formula: (4)； (5)； in, and The first The radial distance and azimuth angle of the outer core relative to the central axis. It is the initial spin angle of the optical fiber. It is the torsion angle. It is the bending sensitivity coefficient. It is torsional strain. It is common mode strain; S6. Substitute the calibration parameters obtained in step S5 into the fiber shape reconstruction algorithm to invert the three-dimensional spatial shape of the fiber and compare it with the theoretical three-dimensional spatial coordinates of the calibration model.

2. The fiber optic shape sensing calibration method based on a 3D printed model according to claim 1, characterized in that, Step S1, the design and preparation process, includes: Central support structure: A cylinder is constructed as the central support, with its axis serving as the central axis of the calibration model, providing overall structural support and spatial positioning reference; Spiral blade extension structure construction: A spiral blade structure with a set thickness is formed by extending outward along the axial direction on the side of a cylinder; Multi-radius spiral curve construction: While keeping the pitch constant, by adjusting the radial distance of the spiral blade relative to the central axis, spiral lines with different spatial radii are drawn on the upper surface of the spiral blade, thereby constructing a variety of three-dimensional spatial curves with known curvature and deflection. Spiral groove cutting: Cutting the spiral lines on the spiral blade to form spiral grooves for laying optical fibers; Model preparation: The central support, spiral plate and spiral groove are integrated and prepared by 3D printing process.

3. The fiber optic shape sensing calibration method based on a 3D printed model according to claim 1, characterized in that, When the torsion is small, the torsional strain will be... and torsion rate The relationship is approximately linear. (6)； (7)； in, It is the spin rate. It is the torsional sensitivity coefficient. , , These are the strains of the three outer cores, and r is the fiber core pitch.

4. The fiber optic shape sensing calibration method based on a 3D printed model according to claim 3, characterized in that, Using the axial strain data of the obtained multi-core optical fiber, the measured bending direction angle after compensation of the measured curvature and torsion angle is compared with the theoretical model to establish the mapping relationship between the optical fiber measurement and the reference curvature and bending direction angle. The bending sensitivity coefficient and torsion sensitivity coefficient are calibrated or corrected by the parameter estimation method to obtain the calibrated optical fiber sensing parameters.

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