CN1692871A - Device and method for detecting three-dimensional curve shape of flexible endoscope - Google Patents

Abstract

The invention relates to a three-dimensional shape detection device and method of a flexible endoscope. The detection device is composed of a flexible detection rod, a fiber grating demodulation device and a computer connection. Two groups of fiber gratings are arranged in a group on the flexible detection rod along the axial direction, and each fiber grating is distributed uniformly along the axial direction for grating detection. points to form a fiber grating sensor network. The detection method includes steps such as determining the proportional coefficient of the optical fiber grating, obtaining wavelength signals, collecting curvature information, and drawing shape curves. The endoscope three-dimensional curve shape detection device of the present invention has simple composition and convenient detection method, and can realize real-time detection.

Description

Device and method for detecting three-dimensional curve shape of flexible endoscope

technical field

The invention relates to an endoscope shape detection device and method, in particular to a three-dimensional curve shape detection device and method based on a fiber grating sensor network.

Background technique

Colonoscopy endoscopic examination has become the most commonly used and most accurate means of locating and qualitatively diagnosing colorectal tumors, and it is of great value in the diagnosis of tumor lesions. Based on the current technology, doctors cannot understand the shape of the endoscope in the human intestinal tract, and can only perform inspections and operations based on personal experience. Unexpected knot loop phenomenon occurs, even perforation, which brings greater pain and danger to the patient. The current general method is to carry out the operation guidance method by X-rays, but this method has great harm to the medical staff and the patient's body. By transforming the colon endoscope so that it has the ability to detect the shape of the colon endoscope in the patient's body, it can provide great convenience for doctors to carry out examination and treatment, and can further reduce the impact on the colon tissue during the process of entering and withdrawing the mirror. Potential damage, reduce patient pain.

In terms of endoscopic shape perception technology, the existing technology is only OLYMPUS based on US patent 6,059,718, etc., using the principle of magnetic field positioning, installing electromagnetic emission equipment on the target to emit a space magnetic field with a known structure, according to the sensor at a certain point in space The magnetic field strength signal obtained by induction and the known spatial distribution law of the emitted magnetic field are used to calculate the spatial coordinate position of the point and the attitude angle of the sensor. Using several same devices, sampling is performed every other sampling period, the sampling data reflects the change of the continuous magnetic field, and the spatial position of each sensor is obtained through calculation, and then the computer is used to fit these discrete points into a continuous curve. Three-dimensional display can be performed on the computer to realize the spatial positioning and tracking of the soft body, which is susceptible to electromagnetic interference in the operating room.

Contents of the invention

The object of the present invention is to provide a real-time detection device and method for the three-dimensional curve shape of a flexible endoscope, which uses optical detection means to avoid electromagnetic interference arising from the magnetic field positioning principle.

The object of the present invention is achieved in that a flexible endoscope three-dimensional curve shape detection device comprises a flexible detection rod (4) and is characterized in that: the device is composed of the flexible detection rod (4) and a light source (1 ), a fiber grating demodulation device (2) and a computer (3) are connected in sequence, and two groups of fiber gratings (5) in a group are arranged axially on the flexible detection rod (4), and each The optical fiber gratings (5) are respectively uniformly distributed with grating detection points along the axial direction, thereby constituting the optical fiber grating sensing network.

The above-mentioned multiple groups of fiber gratings are two groups of four fiber gratings in total, and the four fiber gratings (5) are uniformly pasted on the outer wall of the flexible detection rod (4) along the circumferential direction, and the two groups of fiber gratings are symmetrically distributed on the cross-section of the flexible detection rod. Above, the two fiber gratings in each group are separated by 90°.

The above-mentioned computer is equipped with software to convert the signal into a curve shape.

A method for detecting the three-dimensional curve shape of a flexible endoscope, which uses the above-mentioned three-dimensional curve shape detection device for a flexible endoscope to detect, and is characterized in that the method at least includes the following steps:

①Determine the scaling factor of the fiber grating

Before the detection starts, first use the arc spline curve calibration method to determine the proportional coefficient K between the strain signal of each group of fiber gratings on the flexible detection rod and the curvature of the curve;

② Obtain strain signal

The flexible detection rod is placed on the measured part, and the bending signal of the flexible detection rod is sensed by the fiber grating in real time, thereby obtaining the strain signals of multiple discrete points on the surface of the flexible detection rod;

③Collect strain signal

The strain signals of multiple discrete points are converted into digital wavelength signals by corresponding multiple fiber grating demodulation instruments, which are collected by the computer in real time;

④Calculation of curvature

The computer performs circular spline curve calibration processing on the real-time collected signals to obtain the corresponding relationship between the wavelength signal change value and the curvature value of the flexible detection rod, and calculates the curvature of multiple discrete points on the flexible detection rod according to this relationship;

⑤ Draw a shape curve

The computer uses a recursive method to draw the shape curve of the measured object according to the curvature of multiple discrete points on the flexible detection rod.

The above-mentioned three-dimensional curve shape detection method, wherein, the arc spline curve calibration method described in step ① is: for each group of fiber gratings, first measure the center of the fiber grating of the flexible detection rod under several known curvature radii ρ For the wavelength λ, the proportional coefficient under each curvature radius ρ is obtained according to the formula K=λ×ρ, and then the average value thereof is taken as the proportional coefficient K of each group of fiber gratings.

The above-mentioned three-dimensional curve shape detection method, wherein the recursive method described in step 5. is to obtain the coordinate values of each point on the curve according to the following curve fitting equation, and then fit into a continuous curve:

x=o(i-1)x+(ρi-1-ρ _i )cosθ _i-1 +ρicosθ

y=o _(i-1)y +(ρ _i-1 -ρ _i )sinθ _i-1 +ρ _i sinθ

In the formula, θ _i-1 ≤ θ ≤ θ _i θ _i = θ _i-1 + Δθ = θ _i-1 + s/ρ ₁ .

Compared with the prior art, the present invention has the following obvious advantages and characteristics due to the adoption of the above technology:

1. Since the entire detection system is mainly composed of fiber grating sensing network, demodulator and computer, no additional auxiliary detection equipment is needed, so the composition of the entire system is simple, and no radiation will cause harm to the human body.

2. Since the three-dimensional curve shape detection technology of the present invention is to place a plurality of curvature detection fiber gratings on the entire measured curve, the curvature detection of multiple points is carried out in parallel, so the whole shape detection system can realize real-time detection. This detection technology can be applied not only to the detection of curves in the cavity, but also to the detection of curves in any space, and can achieve high real-time responsiveness.

3. The optical fiber grating sensing method has the advantages of small size and large measurement range, and can perform dynamic large strain measurement in a small size.

The endoscope three-dimensional curve shape detection device of the present invention has simple composition, simple and convenient detection method, and can realize real-time detection.

Description of drawings

Fig. 1 is a schematic structural view of a three-dimensional curve shape detection device of the present invention, in which figure (a) is a schematic diagram of the device system, and figure (b) is a schematic diagram of the arrangement of a fiber grating sensor of a flexible detection rod and a partial enlarged view at "A" .

Figure 2 is a schematic diagram of the fiber grating sensor network topology.

Fig. 3 is a curve diagram of the relationship between the curvature and the change value of the central wavelength of a group of fiber grating detection flexible detection rods in six bending states according to an embodiment of the present invention.

Fig. 4 is a schematic diagram of reconstruction based on discrete point curvature information.

Fig. 5 is a photogram of the actual shape curve of the flexible detection rod according to an embodiment of the present invention.

Fig. 6 is a reappearance diagram of the actual shape curve of the flexible detection rod according to an embodiment of the present invention.

Detailed ways

A preferred embodiment of the present invention is described as follows in conjunction with accompanying drawing:

Please refer to Fig. 1, the flexible endoscope three-dimensional curve shape detection device is composed of a flexible detection rod (4), a wavelength demodulation device (2) and a computer (3) sequentially connected through optical fiber jumpers and signal lines. A sensing network composed of two groups of four optical fiber gratings is arranged evenly along the axial direction on the flexible detection rod (4). There are two fiber gratings (5) in each group, and the two fiber gratings (5) in each group are symmetrically pasted on both sides of the flexible detection rod (4). In the computer (3) there is software for converting the signal into a curve shape.

The detection process of the three-dimensional curve shape detection method of the present invention is shown in FIG. 2 . The method is implemented by the above-mentioned three-dimensional curve shape detection device of the flexible endoscope, and the steps are as follows:

Before detection starts, first determine the proportional coefficient K of each group of fiber gratings (5) on the flexible detection rod (4) with the arc spline calibration method; the arc spline calibration method is: for each group of fiber gratings (5 ), first measure the fiber grating center wavelength λ of the flexible detection rod (4) under several known curvature radii ρ, and obtain the proportional coefficient under each curvature radius ρ according to the formula K=λ×ρ, and then take the average The value is used as the proportional coefficient K of each group of fiber gratings (5).

When testing, the flexible detection rod (4) is placed on the measured part, and the bending signal of the flexible detection rod (4) is sensed by the fiber grating (5) in real time, thereby obtaining the strain of multiple discrete points on the surface of the flexible detection rod (4) Signal;

The strain signals at multiple discrete points are collected in real time by the computer (3) via the corresponding multiple fiber grating center wavelength signals;

The computer (3) performs arc spline curve calibration processing according to the real-time collected signal to obtain the corresponding relationship between the central wavelength signal and the curvature value of the flexible detection rod (4), and calculates the upper surface of the flexible detection rod (4) according to this relationship. the curvature of multiple discrete points;

Finally, the computer uses a specific recursive method to draw the shape curve of the measured object according to the curvature of multiple discrete points on the flexible detection rod (3).

The detection principle of the three-dimensional curve shape detection device of the present invention is: the output center wavelength λ of each fiber grating (5) pasted on the flexible detection rod (4) is inversely proportional to the curvature radius ρ of the point where the fiber grating is located, and proportional to the curvature n :

λ=K/ρ=K×n

where K is the proportionality factor. The proportionality coefficient K is obtained by calibration method of arc spline curve. The specific calibration method is, for each group of fiber gratings (5), first measure the fiber grating center wavelength λ of the flexible detection rod 4 under several known curvature radii ρ, and calculate according to the formula λ=K/ρ=K×n Get the proportional coefficient under each known curvature radius ρ, take its average value as the proportional coefficient K of each group of fiber gratings (5). In this way, the curvature of the point where the fiber grating (5) on the flexible detection rod 4 is located can be calculated by the output center wavelength value λ of each fiber grating measured by the signal acquisition card and the coefficient K obtained from calibration.

Carry out vector synthesis of the two curvature components in the {B _i } coordinate system, the size of the synthesized curvature vector k _i is:

$<span\; class="notranslate">\; |</span>{\mathrm{<span\; class="notranslate">\; k</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; |</span><span\; class="notranslate">\; =</span>\sqrt{{{\mathrm{<span\; class="notranslate">\; <figure-callout\; id="2"\; label="k\; ai"\; filenames="A20051002585400101.png"\; state="\{\{state\}\}">k</figure-callout></span><figure-callout\; id="2"\; label="k\; ai"\; filenames="A20051002585400101.png"\; state="\{\{state\}\}">\; </figure-callout>}}_{\mathrm{<span\; class="notranslate">\; </span>}}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; +</span>{{\mathrm{<span\; class="notranslate">\; <figure-callout\; id="2"\; label="k\; bi"\; filenames="A20051002585400101.png"\; state="\{\{state\}\}">k</figure-callout></span><figure-callout\; id="2"\; label="k\; bi"\; filenames="A20051002585400101.png"\; state="\{\{state\}\}">\; </figure-callout>}}_{\mathrm{<span\; class="notranslate">\; </span>}}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}}$

The angle α _i between k _i and k _ai

${\mathrm{<span\; class="notranslate">\; \&alpha;</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; =</span>\left\{\begin{array}{c}\mathrm{<span\; class="notranslate">\; \&pi;</span>}<span\; class="notranslate">\; /</span>\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; k</span>}}_{\mathrm{<span\; class="notranslate">\; ai</span>}}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 0</span>}<span\; class="notranslate">\; ,</span>{\mathrm{<span\; class="notranslate">\; k</span>}}_{\mathrm{<span\; class="notranslate">\; bi</span>}}<span\; class="notranslate">\; ></span>\mathrm{<span\; class="notranslate">\; 0</span>}<span\; class="notranslate">\; )</span>\\ <span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; \&pi;</span>}<span\; class="notranslate">\; /</span>\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; k</span>}}_{\mathrm{<span\; class="notranslate">\; ai</span>}}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 0</span>}<span\; class="notranslate">\; ,</span>{\mathrm{<span\; class="notranslate">\; k</span>}}_{\mathrm{<span\; class="notranslate">\; bi</span>}}<span\; class="notranslate">\; <</span>\mathrm{<span\; class="notranslate">\; 0</span>}<span\; class="notranslate">\; )</span>\\ \mathrm{<span\; class="notranslate">\; 0</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; k</span>}}_{\mathrm{<span\; class="notranslate">\; ai</span>}}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 0</span>}<span\; class="notranslate">\; ,</span>{\mathrm{<span\; class="notranslate">\; k</span>}}_{\mathrm{<span\; class="notranslate">\; bi</span>}}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 0</span>}<span\; class="notranslate">\; )</span>\\ {\mathrm{<span\; class="notranslate">\; tg</span>}}^{<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; k</span>}}_{\mathrm{<span\; class="notranslate">\; bi</span>}}<span\; class="notranslate">\; /</span>{\mathrm{<span\; class="notranslate">\; k</span>}}_{\mathrm{<span\; class="notranslate">\; ai</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; k</span>}}_{\mathrm{<span\; class="notranslate">\; ai</span>}}<span\; class="notranslate">\; ></span>\mathrm{<span\; class="notranslate">\; 0</span>}<span\; class="notranslate">\; )</span>\\ {\mathrm{<span\; class="notranslate">\; tg</span>}}^{<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; k</span>}}_{\mathrm{<span\; class="notranslate">\; bi</span>}}<span\; class="notranslate">\; /</span>{\mathrm{<span\; class="notranslate">\; k</span>}}_{\mathrm{<span\; class="notranslate">\; ai</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; \&pi;</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; k</span>}}_{\mathrm{<span\; class="notranslate">\; ai</span>}}<span\; class="notranslate">\; <</span>\mathrm{<span\; class="notranslate">\; 0</span>}<span\; class="notranslate">\; )</span>\end{array}\right.$

After obtaining the curvatures of several discrete points on the flexible detection rod (4), a curve fitting equation based on a recursive method can be obtained according to the following steps.

1. Synthesis of two curvature components

2. Solve the position of point i+1 in the world coordinate system

3. Establishment of a new motion coordinate system {B _i+1 }

4. Derivation of the conversion relationship between {B _i+1 } and the world coordinate system

$\left\{\begin{array}{c}{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; 1</span>}}\\ {\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; 1</span>}}\\ {\mathrm{<span\; class="notranslate">\; z</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; 1</span>}}\\ \mathrm{<span\; class="notranslate">\; 1</span>}\end{array}\right\}<span\; class="notranslate">\; =</span>{<span\; class="notranslate">\; [</span>{\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; ]</span>}^{<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 1</span>}}\left\{\begin{array}{c}{\mathrm{<span\; class="notranslate">\; da</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}\\ \mathrm{<span\; class="notranslate">\; d</span>}{\mathrm{<span\; class="notranslate">\; b</span>}}_{\mathrm{<span\; class="notranslate">\; <figure-callout\; id="1"\; label="i\; dc\; i"\; filenames="A20051002585400101.png"\; state="\{\{state\}\}">i</figure-callout></span><figure-callout\; id="1"\; label="i\; dc\; i"\; filenames="A20051002585400101.png"\; state="\{\{state\}\}">\; </figure-callout>}}& \\ {\mathrm{<span\; class="notranslate">\; dc</span>}}_{}{\mathrm{<span\; class="notranslate">\; i</span>}}_{}\\ \mathrm{<span\; class="notranslate">\; 1</span>}\end{array}\right\}$

The coordinate values of each point on the curve are obtained, and then a continuous curve is fitted to realize the redisplay of the measured curve, and the shape curve of the flexible detection rod (4) is drawn.

The following is a further description of the detection principle and detection process of the three-dimensional curve shape detection device and detection method of the present invention through a specific embodiment:

On a flexible detection rod 1 with a length of 90 centimeters and an outer diameter of 0.75 millimeters, 10 groups of optical fiber gratings 5 of type 1 are evenly arranged, and the distance between each group of optical fiber gratings 5 is 10 centimeters, as shown in FIG. 3 . In this way, the output signals of the 4 channels of fiber gratings are collected and demodulated in real time through one of the output center wavelengths of each fiber grating. For the proportionality coefficient K of each group of fiber gratings 5, when ρ=infinity (straight line), 90 centimeters, 70 centimeters, 50 centimeters, 40 centimeters, 30 centimeters, 25 centimeters, and 20 centimeters of bending state, the flexible detection rod (4) is calibrated The output center wavelength λ of each fiber grating is calculated according to the formula K=λρ, and the proportional coefficients in each bending state are calculated, and then obtained by calculating the average value. Fig. 4 shows the relationship between the curvature and the output center wavelength λ of a certain group of fiber gratings (5) detecting the 8 bending states of the flexible detection rod 3, thereby obtaining the proportional coefficient K through a calibration method, wherein The straight line is a graph of the relationship between λ and 1/ρ (curvature n) drawn according to K after averaging.

The basic idea to solve the spatial curve reconstruction is to establish a motion coordinate system determined by the curve tangent and curvature components on the space curve, determine the kinship plane by the curvature vector in the motion coordinate system, perform the bending calculation of the curve in the kinship plane, and Carry out kinematic analysis of the kinematic coordinate system.

Then the shape curve is reconstructed according to the curvature of 10 points on the flexible detection rod (4). Since the shape curve of the flexible detection rod (4) is continuous, when the arc length s is sufficiently small, the curve can be regarded as composed of many circular arc segments or straight line segments with different radii, as shown in Figure 5 Show. Among them, the tangent direction of the starting point is used as the x-axis. In order to obtain the curvature of sufficiently small s, linear interpolation between known curvature points (obtained by the detection of the fiber grating (5)) can be used. In this example, 9 points are inserted between two points with an interval of 10 cm to form 10 arc segments, namely:

$\left\{\begin{array}{c}{\mathrm{<span\; class="notranslate">\; k</span>}}_{\mathrm{<span\; class="notranslate">\; ai</span>}}<span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; m</span>}}_{\mathrm{<span\; class="notranslate">\; ai</span>}}<span\; class="notranslate">\; *</span>{\mathrm{<span\; class="notranslate">\; the\; s</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; no</span>}}_{\mathrm{<span\; class="notranslate">\; ai</span>}}\\ {\mathrm{<span\; class="notranslate">\; k</span>}}_{\mathrm{<span\; class="notranslate">\; ai</span>}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; m</span>}}_{\mathrm{<span\; class="notranslate">\; ai</span>}}<span\; class="notranslate">\; *</span>{\mathrm{<span\; class="notranslate">\; the\; s</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; no</span>}}_{\mathrm{<span\; class="notranslate">\; ai</span>}}\\ {\mathrm{<span\; class="notranslate">\; k</span>}}_{\mathrm{<span\; class="notranslate">\; bi</span>}}<span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; m</span>}}_{\mathrm{<span\; class="notranslate">\; bi</span>}}<span\; class="notranslate">\; *</span>{\mathrm{<span\; class="notranslate">\; the\; s</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; no</span>}}_{\mathrm{<span\; class="notranslate">\; bi</span>}}\\ {\mathrm{<span\; class="notranslate">\; k</span>}}_{\mathrm{<span\; class="notranslate">\; bi</span>}}<span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; m</span>}}_{\mathrm{<span\; class="notranslate">\; bi</span>}}<span\; class="notranslate">\; *</span>{\mathrm{<span\; class="notranslate">\; the\; s</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; no</span>}}_{\mathrm{<span\; class="notranslate">\; bi</span>}}\end{array}\right.$

In this way, the curvature of each arc can be easily calculated. After knowing s and the radius of curvature of each arc segment, the curve reconstruction recursive method based on the curvature of discrete points shown in Figure 5 can be used to obtain the coordinates of the center of the arc segment, so that the entire measured curve can be displayed again. come out. Fig. 6 is the reconstruction diagram of the actual shape curve of the flexible detection rod (3) of this embodiment.

Claims (6)

1. flexible endoscope three-D curved line shape testing device, comprise that a flexible test rod (4) is characterized in that: device is linked in sequence with a light source (1), a fiber grating demodulation device (2) and a computer (3) by described flexible test rod (4) and forms, two many groups fiber gratings (5) that become a group are set on described flexible test rod (4) vertically, and every fiber grating (5) is uniform vertically grating test point respectively, thereby constitutes optical fiber grating sensing network.

2. flexible endoscope three-D curved line shape testing device according to claim 1, it is characterized in that: described many group fiber gratings (5) are two groups of totally four fiber gratings, four fiber gratings (5) are along circumferentially sticking in uniform way on the outer wall of flexible test rod (4), and two groups of fiber gratings are symmetrically distributed on the flexible test rod cross section, and every group two fiber gratings are separated by 90 °.

3. flexible endoscope three-D curved line shape testing device according to claim 1 is characterized in that: described computer is provided with the software that conversion of signals is become curve shape in (3).

4. a flexible endoscope three-D curved line shape detection method adopts the described flexible endoscope three-D curved line shape testing device of claim 1 to detect, and it is characterized in that: this method may further comprise the steps at least:

1. determine the proportionality coefficient of the corresponding curvature of fiber grating: before detecting beginning, at first determine respectively to organize on the flexible test rod (4) strain signal of fiber grating (5) and the proportionality coefficient K between curvature of curve with the arc-spline curve scaling method;

2. obtain strain signal: flexible test rod (4) is placed tested position, and the crooked signal of flexible test rod (4) obtains the strain signal of the surperficial a plurality of discrete points of flexible test rod (4) thus by fiber grating (5) real-time perception;

3. gather strain signal: the strain signal of a plurality of discrete points converts digital signal to through the fiber Bragg grating (FBG) demodulator device (2) of correspondence; Gather in real time by computer (3);

4. calculate curvature: computer (3) carries out arc-spline curve according to the signal of gathering in real time and demarcates the corresponding relation that obtains after handling between wavelength change signal and flexible test rod (4) curvature value, and calculates the curvature that flexible test rod (4) is gone up a plurality of discrete points according to this relation;

5. draw pattern curve: computer (3) is drawn out the pattern curve of testee with recurrence method according to the curvature of the last a plurality of discrete points of flexible test rod (4).

5. flexible endoscope three-D curved line shape detection method according to claim 4, it is characterized in that: the arc-spline curve scaling method of step described in 1. is: for every group of fiber grating (5), measure the output wavelength changing value of the demodulation instrument of flexible test rod (4) under several known curvature radius ρ earlier, obtain proportionality coefficient under each radius of curvature ρ according to formula K=u * ρ, get its meansigma methods then and organize the proportionality coefficient K of fiber grating (5) as each.

6. flexible endoscope 3D shape fit equation according to claim 4 is obtained the coordinate figure of each point on the curve, fits to successive curve then:

$x=o_{(i-1)x}+({\mathrm{\&rho;}}_{i-1}+{\mathrm{\&rho;}}_1)\cos {\mathrm{\&theta;}}_{i-1}+{\mathrm{\&rho;}}_i\cos \mathrm{\&theta;}$

$y=o_{(i-1)y}+({\mathrm{\&rho;}}_{i-1}-{\mathrm{\&rho;}}_i){\sin \mathrm{\&theta;}}_{i-1}+{\mathrm{\&rho;}}_i\sin \mathrm{\&theta;}$

In the formula, θ _I-1≤ θ≤θ _iθ _i=θ _I-1+ Δ θ=θ _I-1+ s/ ρ ₁

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