Fiber bragg grating sensor measuring method for helicopter blade waving and shimmy decoupling position

Abstract

A helicopter blade waving and shimmy decoupling position measuring method based on fiber bragg grating sensors comprises the following steps that a plurality of fiber bragg grating sensors are evenly pasted on the upper surface and the lower surface of a to-be-measured section of a helicopter blade in parallel from the front edge to the rear edge of the blade; flapping and shimmy bending moments are loaded on the blades respectively, and strain values corresponding to the flapping and shimmy bending moments are obtained through measurement; according to the position of the sensor and strain measurement data thereof, adopting a Kriging interpolation method to carry out interpolation on point positions with the same spacing, and obtaining an estimated value of a corresponding spatial position; establishing shimmy / flapping and flapping / shimmy decoupling coefficient evaluation functions; global traversal is carried out on the interpolation result, evaluation function values are calculated and sorted, and finally a decoupling position is determined.

Description

Technical Field

[0001] The invention belongs to the technical field of helicopter rotor load identification, and specifically proposes a method for measuring the flapping and shimmying decoupling position of helicopter blades based on a fiber grating sensor. Background Art

[0002] In the development of helicopters, the measurement of rotor loads is a key step. Due to the differences in blade airfoils and the particularity of the rotor's own motion, the following challenges are faced when studying loads and deformations: flapping loads will cause strain responses in the swing direction, and swing loads will also produce strains in the swing direction, leading to coupling problems. In order to reveal the specific relationship between load and strain, the coupling relationship must be separated.

[0003] For the decoupling and calibration test of helicopter blade loads, the traditional method mainly relies on strain gauges for measurement. However, the size limitation of the strain gauge means that the measured strain value can only reflect the average state of the local area, and it is difficult to obtain the complex strain distribution on the blade surface, especially in the high stress gradient area. In addition, the strain gauge adopts a single-point measurement mode, and each strain gauge needs to be connected to the strain gauge through two wires, which not only increases the complexity of the test system, but also imposes an additional weight burden on the structure, especially in the scenario where multi-point measurement needs to be arranged. The impact is more significant. More importantly, as a measurement device based on electrical signals, the strain gauge is susceptible to external interference in a complex electromagnetic environment, resulting in signal distortion. At present, fiber grating sensors have been gradually applied to the decoupling and calibration test of helicopter blade loads. Compared with traditional electrical measurement technology, fiber grating sensors rely on optical signals for strain measurement, are completely unaffected by electromagnetic interference, and have excellent anti-interference performance. In addition, fiber grating sensors can be deployed in series, and one optical fiber can be connected to dozens of sensors in series, which greatly simplifies the wiring difficulty and significantly reduces the weight of the measurement system. It is particularly worth emphasizing that the fiber Bragg grating sensor is extremely small in size, with a diameter of about 250 microns and a minimum length that can be controlled within 3 mm. It can achieve high-precision strain measurement and is particularly suitable for monitoring strain changes in high stress gradient areas and realizing multi-point distributed monitoring.

[0004] The key to helicopter blade load decoupling is to accurately locate the position on the blade surface that is only affected by a single load. Since modern helicopter blades are usually made of anisotropic composite materials and supplemented with honeycomb structures, traditional material mechanics theory and finite element simulation are difficult to accurately predict the decoupling position. In actual engineering, empirical trial and error methods are often relied upon to determine the decoupling position, but this method is inefficient and costly, especially for blades with short chord lengths. The accurate positioning of the decoupling position is more challenging and difficult to effectively judge. Summary of the invention

[0005] Purpose of the invention: In view of the difficulty, low efficiency and high cost of helicopter blade load decoupling position determination, the present invention proposes a method for determining the helicopter blade flapping and swing load decoupling position based on fiber grating sensors. The method first evenly arranges fiber grating sensors on the upper and lower surfaces of a specific blade section, then applies specific flapping and swing loads to the blade, and records the strain values ​​measured by the sensors. Next, the Kriging method is used to interpolate and estimate the strain values ​​of equally spaced points on the upper and lower surfaces of the blade. Finally, by traversing the interpolation results and performing a global search, the position combination with the smallest coupling coefficient is found, thereby accurately locating the decoupling position.

[0006] Technical solution: To achieve the above purpose, the present invention adopts the following technical solution: A fiber grating sensor determination method for the decoupling position of helicopter blade flapping and shimmying comprises the following steps: Step 1: Select a section on the helicopter blade to be tested and paste it on the upper and lower surfaces of the blade at equal distances and in parallel. The coordinates of the fiber Bragg grating sensor on the upper surface are: (1) The coordinates of the fiber grating sensor on the lower surface are: (2) Step 2: Apply a swing load perpendicular to the chord to the blade, with the direction from the upper surface to the lower surface, and the action point is at the 1 / 4 chord of the blade. Record the upper surface The strain measured by a fiber Bragg grating sensor is: (3) The strain measured by the surface fiber Bragg grating sensor is recorded as: (4) Step 3: According to equations (1) (3) and (2) (4), the strain interpolation of points 1 mm apart on the upper and lower surfaces of the blade is performed using the Kriging method; the strain interpolation set of the upper surface under the flapping load is obtained: , the strain interpolation set of the lower surface ; Step 4: Load the helicopter blade with a shimmy load that coincides with the chord line, with the direction from the leading edge to the trailing edge; repeat steps 2 and 3, and use the Kriging interpolation algorithm to obtain the strain interpolation set under the shimmy load. The upper surface is , the lower surface is ; Step 5: Construct the decoupling coefficient evaluation function, which is the swing-flapping decoupling coefficient , as shown in formula (8), the flapping-swaying decoupling coefficient , as shown in formula (9): (8) (9) (10) Among them, the swing-flapping decoupling coefficient Used to evaluate the decoupling position of the flapping sensor under flapping loads; flapping-to-flap decoupling coefficient Used to evaluate the decoupling position of the flapping sensor under the action of flapping load; the flapping-flapping decoupling coefficient and flap-sway decoupling coefficient The decoupling coefficient evaluation function of formula (10) is obtained by summing up , the smaller the function value is, the closer it is to the ideal decoupling position; Step 6: Under the action of flapping load and swing load, traverse the strain data set of the upper and lower surfaces of the blade obtained by Kriging interpolation, and substitute it into Formula (8) and Formula (9) to calculate the decoupling coefficient evaluation function value corresponding to each decoupling position combination; arrange the calculation results of all combinations in ascending order; after eliminating unreasonable combinations, the combination ranked first is the final flapping and swing decoupling position.

[0007] The present invention first evenly arranges fiber grating sensors on the upper and lower surfaces of a specific section of the blade, then applies specific flapping and shimmying loads to the blade and records the strain values ​​measured by the sensors. Next, the Kriging method is used to interpolate and estimate the strain values ​​of equally spaced points on the upper and lower surfaces of the blade. Finally, by traversing the interpolation results and performing a global search, the position combination with the smallest coupling coefficient is found, thereby accurately locating the decoupling position. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] Figure 1 Schematic diagram of the fiber Bragg grating sensor body.

[0009] Figure 2 Schematic diagram of swing load loading.

[0010] Figure 3 Schematic diagram of shimmy load loading. DETAILED DESCRIPTION

[0011] The fiber grating sensor determination method of the flapping and swing decoupling position of a helicopter blade of the present invention comprises the following steps: a plurality of fiber grating sensors are evenly and parallelly pasted from the leading edge to the trailing edge of the blade on the upper and lower surfaces of the section to be measured of the helicopter blade; flapping and swing bending moments are respectively loaded on the blade to measure and the corresponding strain values ​​are obtained; according to the sensor position and its strain measurement data, the Kriging interpolation method is used to interpolate at points with the same spacing to obtain an estimated value of the corresponding spatial position; an evaluation function of the swing / flapping and the flap / swing decoupling coefficient is established; the interpolation results are globally traversed, the evaluation function values ​​are calculated and sorted, and the decoupling position is finally determined.

[0012] The specific steps include: Step 1: If Figure 1 As shown in the figure, select a section on the helicopter blade to be tested and paste it on the upper and lower surfaces of the blade at equal distances and in parallel. The coordinates of the fiber Bragg grating sensor on the upper surface are: (1) The coordinates of the fiber grating sensor on the lower surface are: (2) Step 2: Apply a swing load perpendicular to the chord to the blade, with the direction from the upper surface to the lower surface, and the action point is at the 1 / 4 chord of the blade. Record the upper surface The strain measured by a fiber Bragg grating sensor is: (3) The strain measured by the surface fiber Bragg grating sensor is recorded as: (4) like Figure 2 As shown in the figure, the flapping load loading schematic diagram of the present invention, the blade is placed horizontally, the chord is parallel to the horizontal plane, and the blade root is fixed. The flapping load is vertically downward, and the action point is the 1 / 4 chord position.

[0013] Step 3: According to equations (1) (3) and (2) (4), the Kriging method is used to perform strain interpolation on points 1 mm apart on the upper and lower surfaces of the blade. The strain distribution of helicopter blades is closely related to the spatial position. The Kriging interpolation method provides the best unbiased estimation result by fully considering the spatial autocorrelation of strain data. It effectively obtains the spatial variation law of strain distribution. Under normal circumstances, the positioning accuracy of the fiber Bragg grating sensor manually drawn on the blade surface is difficult to exceed 0.5 mm, so a spacing of 1 mm is selected for interpolation.

[0014] Taking the interpolation process of the blade upper surface as an example, we first construct a semivariogram to describe the correlation of spatial data, that is, the distance between data points and the first The measurement points and The relationship between the strain values ​​measured at the two measuring points. The upper and lower surfaces of the cross section are interpolated separately, assuming that the upper surface is parallel to the Fiber Bragg grating sensor, then .

[0015] (5) As shown in formula (5), the spherical model can be used to construct the semivariogram function, where is the distance between two points, The distance is The point logarithm of and are the strain values ​​at two points.

[0016] Then, different weights are assigned to known data points. The weights are determined based on the spatial distance between the points and the spatial correlation. The weights are calculated using the following matrix equation: : (6) in, is the Lagrange multiplier, ensuring the unbiasedness constraint. is the semivariogram represented by formula (5), which generally includes spherical model, exponential model, Gaussian model and linear model. Represents the coordinates of the interpolation point, put this Substituting into formula (6), we can get Here we put Replaced with To make it look more eye-catching.

[0017]

[0018] Solving this system of equations gives us the weight vector , and then the weight vector Substituting into formula (7), we can calculate The value of the position. Represents completed The interpolation of points. Represents the known points That is, the one that is attached parallel to the upper surface. A fiber grating sensor.

[0019] Finally, the strain interpolation set under the swinging load is calculated by formula (7): : (7) Using the same method, the strain interpolation set of the lower surface can also be calculated: .

[0020] Step 4: Load the helicopter blade with a shimmy load that coincides with the chord line, with the direction from the leading edge to the trailing edge. Repeat steps 2 and 3, and use the Kriging interpolation algorithm to obtain the strain interpolation set under the shimmy load. The upper surface is , the lower surface is .

[0021] like Figure 3 As shown in the figure, the schematic diagram of the shimmy load loading of the present invention is that the blade is placed vertically, the chord is perpendicular to the horizontal plane, and the blade root is fixed. The shimmy load is vertically downward, and the action point is the 1 / 4 chord position.

[0022] Step 5: Construct the decoupling coefficient evaluation function, which is the swing-flapping decoupling coefficient , as shown in formula (8), the flapping-swaying decoupling coefficient , as shown in formula (9): Assuming that under the swing load and the flapping load, the interpolation values ​​at the same coordinate position are obtained values. represents the strain value under lag load, represents the strain value under flap load, and then substitute them into formula (8) in pairs to calculate the decoupling coefficient. So, and Represents the coordinate position The strain under the shimmy load and the strain value under the flapping load obtained by interpolation at ; and Represents the coordinate position The strain under the shimmy load and the strain value under the flapping load are interpolated at .

[0023] (8) (9) (10) Among them, the swing-flapping decoupling coefficient Used to evaluate the decoupling position of the heave sensor under flapping loads. Ideally , the two fiber Bragg grating sensors located at the swing decoupling position should measure almost the same strain value, that is, the strain difference is close to zero. This means that the swing sensor will not be affected by the swing load, and the load is effectively decoupled. Similarly, the swing-swing decoupling coefficient Used to evaluate the decoupling position of flapping sensors under shear loads. Ideally , that is, the sensor attached to the swing decoupling position is completely unaffected by the swing load. and flap-sway decoupling coefficient Sum to get the decoupling coefficient evaluation function As shown in formula (10), the smaller the function value is, the closer it is to the ideal decoupling position.

[0024] Step 6: Under the action of flapping load and swing load, traverse the strain data set of the upper and lower surfaces of the blade obtained by Kriging interpolation, and substitute it into formula (8) and formula (9) to calculate the decoupling coefficient evaluation function value corresponding to each decoupling position combination. Then, the calculation results of all combinations are arranged in ascending order. After eliminating unreasonable combinations, the combination ranked first is the final flapping and swing decoupling position.

Claims

1. A method for measuring the position of helicopter blade flapping and swing decoupling using a fiber Bragg grating sensor, characterized in that: The following steps are involved: Step 1: Select a section on the helicopter blade to be tested and paste it on the upper and lower surfaces of the blade at equal distances and in parallel. The coordinates of the fiber Bragg grating sensor on the upper surface are: （1） The coordinates of the fiber grating sensor on the lower surface are: （2） Step 2: Apply a swing load perpendicular to the chord to the blade, with the direction from the upper surface to the lower surface, and the action point is at the 1 / 4 chord of the blade. Record the upper surface The strain measured by a fiber Bragg grating sensor is: （3） The strain measured by the surface fiber Bragg grating sensor is recorded as: （4） Step 3: According to equations (1) (3) and (2) (4), the strain interpolation of points 1 mm apart on the upper and lower surfaces of the blade is performed using the Kriging method; the strain interpolation set of the upper surface under the flapping load is obtained: , the strain interpolation set of the lower surface ; Step 4: Load the helicopter blade with a shimmy load that coincides with the chord line, with the direction from the leading edge to the trailing edge; repeat steps 2 and 3, and use the Kriging interpolation algorithm to obtain the strain interpolation set under the shimmy load. The upper surface is , the lower surface is ; Step 5: Construct the decoupling coefficient evaluation function, which is the swing-flapping decoupling coefficient , as shown in formula (8), the flapping-swaying decoupling coefficient , as shown in formula (9): （8） （9） （10） Among them, the swing-flapping decoupling coefficient Used to evaluate the decoupling position of the flapping sensor under flapping loads; flapping-to-flap decoupling coefficient Used to evaluate the decoupling position of the flapping sensor under the action of flapping load; the flapping-flapping decoupling coefficient and flap-sway decoupling coefficient The decoupling coefficient evaluation function of formula (10) is obtained by summing up , the smaller the function value is, the closer it is to the ideal decoupling position; Step 6: Under the action of flapping load and swing load, traverse the strain data set of the upper and lower surfaces of the blade obtained by Kriging interpolation, and substitute it into Formula (8) and Formula (9) to calculate the decoupling coefficient evaluation function value corresponding to each decoupling position combination; arrange the calculation results of all combinations in ascending order; after eliminating unreasonable combinations, the combination ranked first is the final flapping and swing decoupling position.

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