Moment decoupling method in rotor load identification based on fiber Bragg grating sensors

Abstract

The present invention provides a bending moment decoupling method for fiber Bragg grating sensing measurement of helicopter blade dynamic loads, belonging to the technical field of helicopter rotor load identification. The method aims at the characteristics of complex distribution, large measurement range, dense measuring points, sensitivity to additional mass, high dynamic response, and being in complex environments such as rotational vibration in the measurement of rotor blade dynamic loads. A bending moment decoupling and calibration method based on a combined bridge circuit of fiber Bragg grating sensors is proposed. By static bending moment calibration of the blade and dynamic bending moment measurement during flight, the flap bending moment, lead-lag bending moment, and torque can be decoupled, and the dynamic bending moment of the rotor blade during operation can be measured in real time.

Description

Technical Field

[0001] The present invention belongs to the technical field of helicopter rotor load identification, and specifically proposes a method for decoupling bending moments in rotor load identification based on fiber Bragg grating sensors. Background Art

[0002] The rotor is the core component that provides power and control for a helicopter. Dynamic monitoring of the blade structural load is the main basis for analyzing the dynamic characteristics of the rotor blade and verifying the blade design, directly affecting the strength, performance, and flight characteristics of the helicopter.

[0003] For decades, the strain signals of rotor blades have mainly been obtained through traditional strain gauges. However, traditional strain gauges are easily affected by external environments such as temperature and humidity, and experimental results are prone to deviation. Moreover, one electrical sensor can only connect to one channel and can only measure the signal at one location, which requires a large number of wires to meet the measurement needs. Therefore, the additional mass generated will introduce certain errors to the experimental results. Particularly seriously, the signals measured by resistance strain gauges have high noise, poor signal quality, and large measurement errors.

[0004] Therefore, considering the harsh working environment of helicopter blades and the relatively large external interference, fiber Bragg grating sensors are selected as the measurement components. Compared with traditional strain gauges, fiber Bragg grating sensors have the following advantages: high sensitivity; wide frequency band and large measurement range; anti-electromagnetic interference, high voltage resistance, corrosion resistance, good confidentiality, and safe and reliable in flammable and explosive environments; light weight, small volume, bendable, easy to change shape, and good adaptability; convenient to cooperate with fiber telemetry technology to achieve remote measurement and control; capable of real-time measurement, on-line monitoring, and automatic control, etc. During the actual bending moment measurement process, due to the complex working environment of the blade and the asymmetry of the blade profile, there are coupling problems in the measured flapping moment, lead-lag moment, and torque. Therefore, this paper proposes a method for decoupling and calibrating the flapping moment, lead-lag moment, and torque of the blade structure based on fiber Bragg grating sensors. Summary of the Invention

[0005] Object of the Invention: Aiming at the deficiencies of traditional strain gauges in the dynamic detection of blade structural dynamic loads, the present invention proposes a method for decoupling and calibrating the flapping moment, lead-lag moment, and torque of a helicopter blade structure based on fiber Bragg grating sensors. This method uses fiber Bragg grating sensors to measure the strain in the flapping, lead-lag, and torsion directions of the blade profile, calculates the influence coefficients in the flapping, lead-lag, and torsion cases through static calibration experiments, and substitutes the measured dynamic strain and the calculated influence coefficients into the equation to calculate the decoupled blade structural dynamic load.

[0006] Technical Solution: To achieve the above object, the technical solution adopted by the present invention includes the following steps:

[0007] A method for decoupling bending moment in dynamic load measurement of a blade structure based on a fiber grating sensor, characterized in that it comprises the following steps:

[0008] Step 1: Fiber Bragg grating sensor layout; specifically:

[0009] On each blade section, the fiber Bragg grating sensor layout is divided into "flapping layout", "swing layout" and "torsion layout". The flapping layout is to arrange a fiber Bragg grating sensor FBG1 and FBG2 at the two intersections of the "flapping bending neutral axis" and the blade section to be measured, that is, at the 1 / 4 chord line from the leading edge of the blade along the blade radial direction; the swing layout is to arrange the fiber Bragg grating sensor FBG3 radially at the intersection of the leading edge of the blade and the section to be measured, and arrange FBG4 5mm away from the trailing edge of the blade and the section to be measured; the torsion layout is to arrange FBG5 and FBG6 at the 1 / 4 chord line from the leading edge on the upper surface of the blade along the direction of ±45° to the blade radial direction.

[0010] Step 2: Collect the strain information of fiber grating sensors FBG1-FBG6 under graded loading in the flapping direction and calculate the flapping moment calibration parameter Δε h , calibrate the blade flapping bending moment; specifically:

[0011] The chord line of the airfoil of the blade structure to be calibrated is kept horizontal, the root of the blade is fixed on the blade root fixing fixture, and a flapping direction load m is applied to the blade structure at the loading section. h , 2m h 、3m h 、4m h , record the strain information of each fiber Bragg grating sensor under each loading state.

[0012] Fiber Bragg grating sensors are easily affected by temperature. The strain measured by FBG1 and FBG2 is determined by the swinging moment M of the section. h and temperature are generated, respectively:

[0013] ε1=ε h1 +ε t

[0014] ε2=ε h2 +ε t

[0015] Where, ε1 and ε2 are the values ​​measured by fiber grating sensors FBG1 and FBG2; ε h1 , ε h2 is the strain in the swinging direction; ε t is the strain of the fiber Bragg grating sensor caused by temperature. The strain difference between FBG1 and FBG2 in the swinging direction is:

[0016] Δε h =εh2 -ε h1

[0017] The calibration coefficient of the flapping direction is:

[0018]

[0019] Repeat the flapping direction grading load experiment several times, and calculate the calibration coefficient K under each grading load h The average value of The relationship equation between the blade flapping moment and the flapping strain can be obtained:

[0020]

[0021] Step 3: Collect the strain information of the fiber Bragg grating sensors FBG1 - FBG6 under the action of the flapping direction grading load, and calculate the flapping moment calibration parameter Δε b , and calibrate the blade flapping moment; specifically:

[0022] The chord line of the airfoil of the blade structure to be calibrated is perpendicular to the ground. Fix the blade root on the blade root fixing fixture, and apply a flapping direction load m b , 2m b , 3m b , 4m b at the loading section, and record the strain information of each fiber Bragg grating sensor under each loading state.

[0023] The fiber Bragg grating sensor is vulnerable to temperature. The strains measured by FBG3 and FBG4 are caused by the section flapping moment M b and temperature, and are respectively:

[0024] ε3 = ε b1 + ε t

[0025] ε4 = ε b2 + ε t

[0026] In the formula, ε3 and ε4 are the values measured by the fiber Bragg grating sensors FBG3 and FBG4; ε b1 , ε b2 are the strains in the flapping direction; ε t is the strain generated by the fiber Bragg grating sensor affected by temperature. The strain difference generated by FBG3 and FBG4 in the flapping direction is:

[0027] Δε b = ε b2 - ε b1

[0028] The calibration coefficient of the flapping direction is:

[0029]

[0030] Repeat the flapping direction step - loading experiment several times and calculate the calibration coefficient K under each step - loading. b The average value of Then the relationship equation between the flapping moment and the flapping strain of the blade can be obtained:

[0031]

[0032] Step 4: Collect the strain information of the fiber - Bragg grating sensors FBG1 - FBG6 under the step - loading in the torsion direction and calculate the torque calibration parameter Δε. n , and calibrate the torsional moment of the blade; specifically:

[0033] Make the chord line of the airfoil section to be calibrated of the blade structure perpendicular to the ground, fix the blade root on the blade root fixing fixture, and apply a torsional load m n , 2m n , 3m n , 4m n at the loading section, and record the strain information of each fiber - Bragg grating sensor under each loading state.

[0034] The fiber - Bragg grating sensor is vulnerable to temperature. The strains measured by FBG5 and FBG6 are caused by the section torque M n and temperature, and are respectively:

[0035] ε5 = ε n1 + ε t

[0036] ε6 = ε n2 + ε t

[0037] In the formula, ε5 and ε6 are the values measured by the fiber - Bragg grating sensors FBG5 and FBG6; ε n1 , ε n2 are the strains in the torsion direction; ε t is the strain generated by the fiber - Bragg grating sensor affected by temperature. The strain difference generated by FBG5 and FBG6 in the torsion direction is:

[0038] Δε n = ε n2 - ε n1

[0039] The calibration coefficient in the torsion direction is:

[0040]

[0041] Repeat the torsion - direction step - loading experiment several times and calculate the calibration coefficient K under each step - loading.n The average value The relationship equation between blade torque and torsional strain can be obtained as follows:

[0042]

[0043] Step Five: Calculate the flapping, lagging, and torsional coupling coefficients according to the flapping, lagging, and torsional coupling strain values measured in Steps Two, Three, and Four; specifically:

[0044] The influence coefficient equation of lagging caused by flapping:

[0045]

[0046] The influence coefficient equation of torsion caused by flapping:

[0047]

[0048] In the formula, M hb , M hn are the equivalent lagging bending moment and equivalent torque during static flapping direction loading; ε hb3 , ε hb4 , ε hn5 , ε hn6 are the strain values measured by FBG3, FBG4, FBG5, and FBG6 during static flapping loading, respectively.

[0049] The influence coefficient equation of flapping caused by lagging:

[0050]

[0051] The influence coefficient equation of torsion caused by lagging:

[0052]

[0053] In the formula, M bh , M bn are the equivalent flapping bending moment and equivalent torque during static lagging direction loading; ε bh1 , ε bh2 , ε bn5 , ε bn6 are the strain values measured by FBG1, FBG2, FBG5, and FBG6 during static lagging loading, respectively.

[0054] The influence coefficient equation of flapping caused by torsion:

[0055]

[0056] The influence coefficient equation of lagging caused by torsion:

[0057]

[0058] Wherein, M nh and M nb are the equivalent flapping moment and the equivalent lag moment during the static torsion direction loading respectively; ε nh1 , ε nb2 , ε nb3 , and ε nb4 are the strain values measured by FBG1, FBG2, FBG3, and FBG4 during the static lag loading respectively.

[0059] Step Six: Substitute the influence coefficients obtained in Steps Two, Three, Four, and Five into the moment decoupling equation to obtain the decoupled flapping moment, lag moment, and torque; specifically:

[0060] In the measurement of the dynamic strain of the blade structure, the blade strain composition is as follows:

[0061] ε H = ε h + ε bh + ε nh

[0062] ε B = ε hb + ε b + ε nb

[0063] ε N = ε hn + ε bn + ε n

[0064] Wherein, ε H , ε B , and ε N are the dynamic strain differences of flapping, lag, and torsion measured during the rotation of the blade respectively; ε h is the dynamic strain difference generated by the decoupled flapping moment in the flapping direction; ε b is the dynamic strain difference generated by the decoupled lag moment in the lag direction; ε n is the dynamic strain difference generated by the decoupled torque in the torsion direction; ε hb , and ε hn are the dynamic strain differences generated by the decoupled flapping moment in the lag direction and torsion direction respectively; ε bh , and ε bn are the dynamic strain differences generated by the decoupled lag moment in the flapping direction and torsion direction respectively; ε nh , and ε nb are the dynamic strain differences generated by the decoupled torque in the flapping direction and lag direction respectively;

[0065] Substituting the calculated influence coefficients into the above formula, the decoupling equation of the dynamic load of the blade structure can be obtained:

[0066] ε H = M h K h + M b K bh K h + M n K nh K h

[0067] ε B = M h K hb K b + M b K b + M n K nb K b

[0068] ε N = M h K hn K n + M b K bn K n + M n K n

[0069] In the formula, M h , M b , M n are the dynamic flapping moment, dynamic lag moment, and dynamic torque of the decoupled blade section, respectively.

[0070] Advantages of the present invention:

[0071] The present invention uses fiber Bragg grating sensors to measure the dynamic strain of the blade structure. Compared with the traditional strain gauge measurement method, it has the advantages of high sensitivity; wide frequency band, large measurement range; anti-electromagnetic interference, high voltage resistance, corrosion resistance, good confidentiality, safe and reliable in flammable and explosive environments; light weight, small volume, bendable, easy to change shape, good adaptability; convenient to cooperate with fiber optic telemetry technology to achieve remote measurement and control; capable of real-time measurement, on-line monitoring and automatic control. Secondly, the present invention calculates the influence coefficients and coupling influence coefficients during flapping, lag, and torsion loading under static loading conditions, realizing the decoupling of the dynamic loads of the blade structure in flapping, lag, and torsion and eliminating the influence of temperature on the measurement of bending moment loads. Description of the drawings

[0072] Figure 1 is the layout diagram of the fiber Bragg grating sensors of the blade structure in the flapping direction;

[0073] Figure 2 It is the layout diagram of the flap direction of the blade structure fiber grating sensor;

[0074] Figure 3 It is the layout diagram of the torsion direction of the blade structure fiber grating sensor;

[0075] Figure 4 It is the comparison diagram of the steady-state bending moment after decoupling in the flapping direction and the steady-state bending moment without decoupling;

[0076] Figure 5 It is the comparison diagram of the steady-state bending moment after decoupling in the flap direction and the steady-state bending moment without decoupling;

[0077] Figure 6 It is the comparison diagram of the steady-state bending moment after decoupling in the torsion direction and the steady-state bending moment without decoupling; Specific implementation method

[0078] This application is a bending moment decoupling method in the dynamic load measurement of a blade structure based on a fiber grating sensor, including the following steps:

[0079] Step 1: Layout of fiber grating sensors; specifically:

[0080] On each blade section, the layout of fiber grating sensors is divided into "flapping layout", "flap layout", and "torsion layout". Among them, the flapping layout is to arrange a fiber grating sensor FBG1 and FBG2 along the blade radius at the two intersection points of the "flapping bending neutral axis" and the blade section to be measured, that is, at 1 / 4 chord length from the leading edge of the blade; the flap layout is to arrange the fiber grating sensor FBG3 along the radius at the intersection point of the leading edge of the blade and the section to be measured, and arrange FBG4 at 5 mm from the trailing edge of the blade and the section to be measured; the torsion layout is to arrange FBG5 and FBG6 along the direction of ±45° to the blade radius at 1 / 4 chord length from the leading edge on the upper surface of the blade

[0081] Step 2: Collect the strain information of the fiber grating sensors FBG1-FBG6 under the action of hierarchical loading in the flapping direction, and calculate the flapping moment calibration parameter Δε h , and calibrate the flapping moment of the blade; specifically:

[0082] Keep the chord line of the airfoil of the blade section to be calibrated horizontal, fix the blade root on the blade root fixing fixture, and apply a flapping direction load m h , 2m h , 3m h , 4m h at the loading section, and record the strain information of each fiber grating sensor in each loading state.

[0083] Fiber grating sensors are vulnerable to temperature effects. The strains measured by FBG1 and FBG2 are caused by the sectional flapping moment M hand temperature generation, respectively:

[0084] ε1 = ε h1 + ε t

[0085] ε2 = ε h2 + ε t (1)

[0086] In the formula, ε1 and ε2 are the values measured by the fiber Bragg grating sensors FBG1 and FBG2; ε h1 , ε h2 are the strains in the flapping direction; ε t is the strain generated by the fiber Bragg grating sensor affected by temperature. The strain difference generated by FBG1 and FBG2 in the flapping direction is:

[0087] Δε h = ε h2 - ε h1 (2) The calibration coefficient in the flapping direction is:

[0088]

[0089] Repeat the flapping direction step - loading experiment several times, and calculate the average value h of the calibration coefficient K to obtain the relationship equation between the blade flapping moment and the flapping strain:

[0090]

[0091] Step 3: Collect the strain information of the fiber Bragg grating sensors FBG1 - FBG6 under the action of step - loading in the pitching direction, and calculate the pitching moment calibration parameter Δε b , and calibrate the blade pitching moment; specifically:

[0092] The chord line of the airfoil section of the blade structure to be calibrated is perpendicular to the ground. Fix the blade root on the blade root fixing fixture, and apply pitching direction loads m b , 2m b , 3m b , 4m b at the loading section, and record the strain information of each fiber Bragg grating sensor in each loading state.

[0093] The fiber Bragg grating sensor is vulnerable to temperature influence. The strains measured by FBG3 and FBG4 are generated by the pitching moment M b of the section and temperature, respectively:

[0094] ε3 = ε b1 + ε t

[0095] ε4 = εb2 +ε t (5)

[0096] Where ε3 and ε4 are the values measured by fiber Bragg grating sensors FBG3 and FBG4; ε b1 , ε b2 are the strains in the flapping direction; ε t is the strain generated by the fiber Bragg grating sensor due to temperature influence. The strain difference generated by FBG3 and FBG4 in the pitching direction is:

[0097] Δε b = ε b2 - ε b1 (6) The calibration coefficient in the pitching direction is:

[0098]

[0099] Repeat the pitching direction stepwise loading experiment several times, and calculate the average value b of the calibration coefficient K to obtain the relationship equation between the pitching moment and pitching strain of the blade:

[0100]

[0101] Step 4: Collect the strain information of fiber Bragg grating sensors FBG1 - FBG6 under the action of torsional direction stepwise loading, and calculate the torque calibration parameter Δε n , and calibrate the torsional moment of the blade; specifically:

[0102] The airfoil chord line of the blade structure to be calibrated is perpendicular to the ground. Fix the blade root on the blade root fixing fixture, and apply torsional direction loads m n , 2m n , 3m n , 4m n at the loading section, and record the strain information of each fiber Bragg grating sensor in each loading state.

[0103] Fiber Bragg grating sensors are vulnerable to temperature influence. The strains measured by FBG5 and FBG6 are generated by the sectional torque M n and temperature, and are respectively:

[0104] ε5 = ε n1 + ε r

[0105] ε6 = ε n2 + ε t (9)

[0106] Where ε5 and ε6 are the values measured by fiber Bragg grating sensors FBG5 and FBG6; ε n1 , εn2 Strain in the torsional direction; ε t is the strain generated by the fiber Bragg grating sensor due to temperature influence. The strain difference generated by FBG5 and FBG6 in the torsional direction is:

[0107] Δε n = ε n2 - ε n1 (10) The calibration coefficient in the torsional direction is:

[0108]

[0109] Repeat the torsional direction grading loading experiment several times, and calculate the average value of the calibration coefficient K n each time under the grading loading to obtain the relationship equation between the blade torque and the torsional strain:

[0110]

[0111] Step Five: Calculate the flapping, pitching, and torsional coupling coefficients according to the flapping, pitching, and torsional coupling strain values measured in Steps Two, Three, and Four; specifically:

[0112] The influence coefficient equation of pitching caused by flapping:

[0113]

[0114] The influence coefficient equation of torsion caused by flapping:

[0115]

[0116] In the formula, M hb , M hn are the equivalent pitching bending moment and equivalent torque during the static flapping direction loading respectively; ε hb3 , ε hb4 , ε hn5 , ε hn6 are the strain values measured by FBG3, FBG4, FBG5, and FBG6 during the static flapping loading respectively.

[0117] The influence coefficient equation of flapping caused by pitching:

[0118]

[0119] The influence coefficient equation of torsion caused by pitching:

[0120]

[0121] In the formula, M bh , M bnThe equivalent flapping moment and equivalent torque during static flapping direction loading, respectively; ε bh1 and ε bh2 and ε bn5 and ε bn6 are the strain values measured by FBG1, FBG2, FBG5, and FBG6 during static flapping loading, respectively.

[0122] Coefficient equation for the influence of torsion on flapping:

[0123]

[0124] Coefficient equation for the influence of torsion on flapping:

[0125]

[0126] In the formula, M nh and M nb are the equivalent flapping moment and equivalent flapping moment during static torsion direction loading, respectively; ε nh1 and ε nh2 and ε nb3 and ε nb4 are the strain values measured by FBG1, FBG2, FBG3, and FBG4 during static flapping loading, respectively.

[0127] Step 6: Substitute the influence coefficients obtained in Steps 2, 3, 4, and 5 into the bending moment decoupling equation to obtain the decoupled flapping moment, flapping moment, and torque; specifically:

[0128] In the dynamic strain measurement of the blade structure, the blade strain composition is as follows:

[0129] ε H = ε h + ε bh + ε nh

[0130] ε B = ε hb + ε b + ε nb

[0131] ε N = ε hn + ε bn + ε n (19)

[0132] In the formula, ε H , ε B , and ε N are the dynamic strain differences of flapping, flapping, and torsion measured during blade rotation, respectively; ε h is the dynamic strain difference generated by the decoupled flapping moment in the flapping direction;b is the dynamic strain difference generated by the decoupled flapping moment in the flapping direction; ε n is the dynamic strain difference generated by the decoupled torque in the torsional direction; ε hb and ε hn are respectively the dynamic strain differences generated by the decoupled lead-lag moment in the flapping direction and the torsional direction; ε bh and ε bn are respectively the dynamic strain differences generated by the decoupled flapping moment in the lead-lag direction and the torsional direction; ε nh and ε nb are respectively the dynamic strain differences generated by the decoupled torque in the flapping direction and the lead-lag direction;

[0133] Substituting the calculated influence coefficients into Equation (19), the decoupling equations for the dynamic loads of the blade structure can be obtained:

[0134] ε H = M h K n + M b K bh K h + M n K nh K h

[0135] ε B = M h K hb K b + M b K b + M n K nb K b

[0136] ε N = M h K hn K n + M b K b n n K n + M n K n (20)

[0137] Wherein, M h , M b , and M n are respectively the dynamic flapping moment, the dynamic lead-lag moment, and the dynamic torque of the decoupled blade section.

[0138] To verify the feasibility and effectiveness of the proposed method, fiber Bragg grating sensors were pasted on the blades of a certain type of helicopter according to the above layout. Influence coefficients were obtained through ground calibration experiments, and blade strains were measured through rotor blowing experiments. The uncoupled steady-state bending moment and the steady-state bending moment after decoupling calculated by the proposed method were calculated respectively, and the results were compared.

[0139] Figures 4 - 6 It is a comparison diagram of the uncoupled steady-state bending moment and the steady-state bending moment after decoupling by the decoupling method proposed in the present invention. It can be seen from the figure that the decoupling method proposed in the present invention realizes the decoupling of the flap, lag, and torsion of the dynamic loads of the blade structure, and the calculated dynamic bending moment is more accurate than that in the uncoupled case.

Claims

1. A method for decoupling bending moments in rotor load identification based on fiber Bragg grating sensors, characterized in that, The layout structure of the fiber Bragg grating sensors on the blade is as follows: On each blade section, the layout of the fiber Bragg grating sensors is divided into flap layout, lead-lag layout, and torsion layout; Among them, for the flap layout, at the two intersection points of the flap bending neutral axis and the blade section to be measured, that is, at 1 / 4 chord length from the leading edge of the blade, one fiber Bragg grating sensor FBG1 and FBG2 are arranged along the radial direction of the blade respectively; for the lead-lag layout, a fiber Bragg grating sensor FBG3 is arranged along the radial direction at the intersection point of the leading edge of the blade and the section to be measured, and FBG4 is arranged at 5 mm from the intersection point of the trailing edge of the blade and the section to be measured; for the torsion layout, FBG5 and FBG6 are arranged along the directions forming ±45° with the radial direction of the blade at 1 / 4 chord length from the leading edge of the blade on the upper surface of the blade; The method includes the following steps: Step 1: Layout of the fiber Bragg grating sensor network for the blade structure; Step 2: Under the action of hierarchical loading in the flapping direction, collect the strain information of each fiber Bragg grating sensor respectively, and calculate the calibration parameter Δε of the flapping moment to calibrate the flapping moment of the blade. h , and calibrate the flapping moment of the blade; Step 3: Under the action of step-by-step loading in the flapping direction, collect the strain information of each fiber Bragg grating sensor, and calculate the calibration parameter Δε of the flapping moment b , and calibrate the flapping moment of the blade Step 4: Under the action of graded loading in the torsional direction, collect the strain information of each fiber Bragg grating sensor, and calculate the torque calibration parameter Δε n , and calibrate the torsional torque of the blade; Step 5: Calculate the flap, lead-lag, and torsion coupling coefficients according to the flap, lead-lag, and torsion coupling strain values measured in Steps 2, 3, and 4; Step 6: Substitute the influence coefficients obtained in Steps 2, 3, 4, and 5 into the bending moment decoupling equation to calculate the decoupled flap bending moment, lead-lag bending moment, and torque; The specific content of Step 2 is as follows: Keep the airfoil chord line of the calibration profile of the blade structure horizontal, fix the blade root on the blade root fixing fixture, and apply a flapping direction load m to the blade structure at the loading profile h , 2m h , 3m h , 4m h , and record the strain information of the fiber Bragg grating sensors of each profile under each loading state respectively; Fiber Bragg grating sensors are vulnerable to temperature effects. The strains measured by FBG1 and FBG2 are caused by the sectional flapping moment M h and temperature, respectively, as follows: ε1 = ε h1 + ε t ε2 = ε h2 + ε t where ε1 and ε2 are the values measured by fiber Bragg grating sensors FBG1 and FBG2; ε h1 , ε h2 are the strains in the flapping direction; ε t is the strain generated by the fiber Bragg grating sensor due to temperature influence; the strain difference generated by FBG1 and FBG2 in the flapping direction is: Not h = ε h2 - ε h1 The calibration coefficient in the flap direction is: Repeat the waving direction grading load experiment several times and calculate the calibration coefficient K under each grading load h The average value of That is, the relationship equation between the blade flapping moment and the flapping strain is obtained: Step 3 specifically includes: the chord line of the airfoil of the calibration profile of the blade structure is perpendicular to the ground, the blade root is fixed on the blade root fixing fixture, and a flapping direction load m b , 2m b , 3m b , 4m b is applied to the blade structure at the loading profile, and the strain information of the fiber Bragg grating sensors at each profile under each loading state is recorded; The strains measured by FBG3 and FBG4 are caused by the sectional flap bending moment M b and temperature, respectively, as follows: ε3 = ε b1 + ε t ε4 = ε b2 + ε t where ε3 and ε4 are the values measured by fiber Bragg grating sensors FBG3 and FBG4; ε b1 , ε b2 are the strains in the flapping direction; ε t is the strain generated by the fiber Bragg grating sensor due to temperature influence; the strain difference generated by FBG3 and FBG4 in the pitching direction is: Not b = ε b2 - ε b1 The calibration coefficient in the lead-lag direction is: Repeat the flapping direction step-loading experiment several times and calculate the calibration coefficient K for each step loading b of the average value to obtain the relationship equation between the blade flapping moment and the flapping strain: The specific content of Step 4 is as follows: The chord line of the airfoil at the calibration section of the blade structure is perpendicular to the ground. Fix the blade root on the blade root fixing fixture, and apply torsional loads m n , 2m n , 3m n , 4m n at the loading section, and record the strain information of the fiber Bragg grating sensors at each section under each loading state; The strains measured by FBG5 and FBG6 are caused by the sectional torque M n and temperature, respectively, as follows: E5 = ε n1 + ε t E6 = ε n2 + ε t Where ε5 and ε6 are the values measured by fiber Bragg grating sensors FBG5 and FBG6; ε n1 , ε n2 are the strains in the torsional direction; ε t is the strain generated by the fiber Bragg grating sensor due to temperature influence; the strain difference generated by FBG5 and FBG6 in the torsional direction is: Not n = ε n2 -ε n1 The calibration coefficient in the torsion direction is: Repeat the torsional direction grading loading experiment several times and calculate the calibration coefficient K under each grading load n of the average value to obtain the relationship equation between the blade torque and the torsional strain: The specific content of Step 5 is as follows: The influence coefficient equation of the lead-lag caused by the flap: The influence coefficient equation of the torsion caused by the flap: Where, M hb and M hn are the equivalent flapping moment and equivalent torque during static flapping direction loading respectively; ε hb3 and ε hb4 and ε hn5 and ε hn6 are the strain values measured by FBG3, FBG4, FBG5, and FBG6 during static flapping loading respectively; The influence coefficient equation of the flap caused by the lead-lag: The influence coefficient equation of the torsion caused by the lead-lag: where M bh and M bn are the equivalent flapping moment and equivalent torque during static flapping direction loading respectively; ε bh1 and ε bh2 and ε bn5 and ε bn6 are the strain values measured by FBG1, FBG2, FBG5, and FBG6 during static flapping loading respectively; The influence coefficient equation of the flap caused by the torsion: The influence coefficient equation of the lead-lag caused by the torsion: Where, M nh and M nb are the equivalent flapping moment and the equivalent drag moment during the static torsion direction loading respectively; ε nh1 , ε nh2 , ε nb3 and ε nb4 are the strain values measured by FBG1, FBG2, FBG3 and FBG4 during the static drag loading respectively; The specific content of Step 6 is as follows: In the dynamic strain measurement of the blade structure, the blade strain composition is as follows ε H = ε h + ε bh + ε nh ε B = ε hb + ε b + ε nb ε N = ε hn + ε bn + ε n where ε H , ε B , and ε N are the measured differences in flapping, lagging, and torsional dynamic strains during the rotation of the blade, respectively; ε h is the dynamic strain difference generated by the decoupled flapping moment in the flapping direction; ε b is the dynamic strain difference generated by the decoupled flapping moment in the flapping direction; ε n is the dynamic strain difference generated by the decoupled torque in the torsional direction; ε hb and ε hn are the dynamic strain differences generated by the decoupled flapping moment in the flapping direction and the torsion direction respectively; ε bh and ε bn are the dynamic strain differences generated by the decoupled flapping moment in the flapping direction and the torsional direction, respectively; ε nh and ε nb are the dynamic strain differences generated by the decoupled torque in the flapping direction and the lead-lag direction, respectively; Substitute the calculated influence coefficients into the above formula to obtain the dynamic load decoupling equation of the blade structure: ε H = M h K h + M b K bh K h + M n K nh K h ε B = M h K hb K b + M b K b + M n K nb K b ε N = M h K hn K n + M b K bn K n + M n K n Where, M h , M b , M n are respectively the dynamic flap moment, the dynamic lag moment, and the dynamic torque of the decoupled blade section.

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