Method for predicting fatigue life of rotor blade

Abstract

The invention discloses a method for predicting the fatigue life of a rotor blade. The method specifically comprises the following steps: step 1, carrying out a fatigue life test and a fatigue performance degradation test on a material of the rotor blade; 2, establishing a structural S-N curvilinear equation of the rotor blade according to the data obtained in the step 1; 3, determining the fatigue load and the boundary condition of the rotor blade according to the load condition of the rotor blade during forward flight, and constructing a finite element model of the rotor blade according to the fatigue load and the boundary condition of the rotor blade, so as to obtain the three-dimensional stress distribution state and the fatigue dangerous section of the rotor blade; 4, correcting the stress of the fatigue dangerous section; and 5, establishing a fatigue life prediction model of the rotor blade based on the structure S-N curvilinear equation and the stress corrected in the step 4. The method is simple and practical, the required model parameters are few, and the calculation precision is high.

Description

Technical Field

[0001] The invention belongs to the technical field of helicopters, and in particular relates to a method for predicting the fatigue life of a rotor blade. Background Art

[0002] Carbon nanotube reinforced composite materials are a new type of three-phase composite materials with light weight, high strength and good fatigue durability. They have been initially applied to aviation composite structures. As the main load-bearing components of helicopters, rotor blades are subjected to large forward flight alternating loads, and their fatigue performance is related to the flight safety of the entire helicopter. At present, the fatigue life prediction of carbon nanotube reinforced composite rotor blades can only be carried out through fatigue tests. The test method is costly and inefficient, and is not convenient for the design and use of rotor blades. Summary of the invention

[0003] Purpose of the invention: In order to solve the problems existing in the above-mentioned prior art, the present invention provides a method for predicting the fatigue life of a rotor blade.

[0004] Technical solution: The present invention provides a method for predicting the fatigue life of a rotor blade, which specifically comprises the following steps:

[0005] Step 1: Perform fatigue life test and fatigue performance degradation test on the material of the rotor blade to obtain fatigue stress-life data, residual stiffness data and residual strength data, and establish fatigue SN curve equation based on the obtained data, where S represents fatigue alternating load and N represents fatigue life;

[0006] Step 2: Establish the structural SN curve equation of the rotor blade based on the data obtained in step 1;

[0007] Step 3: According to the load conditions of the rotor blades during forward flight, the fatigue load and boundary conditions of the rotor blades are determined, and a finite element model of the rotor blades is constructed according to the fatigue load and boundary conditions of the rotor blades, so as to obtain the three-dimensional stress distribution state and fatigue critical section of the rotor blades;

[0008] Step 4: Correct the stress of the fatigue-critical section;

[0009] Step 5: Establish a fatigue life prediction model for the rotor blade based on the structural SN curve equation and the stress corrected in step 4.

[0010] Furthermore, the structural SN curve equation in step 2 includes an average SN curve equation and a calculated safety SN curve;

[0011] Step 2.1: First, construct the average SN curve equation according to the following formula:

[0012]

[0013] Where A = 1000 α , α is the shape parameter of fatigue SN curve, S ∞m is the average fatigue limit, S 4m For N = 10 4 Corresponding fatigue alternating load, S m is the low cycle intercept of fatigue SN curve, k m It is the slope of the low cycle section of the fatigue SN curve;

[0014] Step 2.2: Based on the average SN curve equation and fatigue strength reduction factor J p , establish the calculation safety SN curve equation:

[0015]

[0016] Among them, S 4p For N = 10 4 The corresponding calculation safety fatigue alternating load is:

[0017] Furthermore, the fatigue loads in step 3 include swinging bending moment, shimmy bending moment and centrifugal force.

[0018] Furthermore, the boundary condition in step 3 is that the blade root end face is fixedly supported.

[0019] Furthermore, the step 4 is specifically as follows:

[0020] Step 4.1: Maximum normal stress σ along the blade length in the fatigue critical section x,max and the minimum normal stress σ x,min The expression is as follows:

[0021]

[0022] in, is the stress caused by centrifugal force in the dangerous section, is the stress caused by the swinging bending moment in the dangerous section, is the normal stress caused by the shimmying bending moment in the dangerous section;

[0023] Step 4.2: Calculate the average stress S according to the following formula m and alternating stress S a :

[0024]

[0025] Step 4.4: Use Goodman mean stress correction theory to correct the stress of the fatigue critical section and obtain the equivalent mean stress S m,eq and equivalent alternating stress S a,eq :

[0026]

[0027] Among them, σ u is the ultimate stress.

[0028] Furthermore, the expression of the fatigue life prediction model in step 5 is as follows:

[0029]

[0030] Among them, α is the shape parameter of fatigue SN curve, S ∞m is the average fatigue limit, J p is the fatigue strength reduction factor, N1 is the allowable number of cycles of the blade under fatigue load, n is the number of fatigue load cycles corresponding to the blade rotating for one hour, and L is the predicted life of the blade.

[0031] An electronic device / system for a fatigue life prediction method for a rotor blade comprises a processor and a memory, wherein the memory stores execution instructions of the processor, and the processor is configured to execute the execution instructions to implement the fatigue life prediction method for the rotor blade.

[0032] A computer-readable storage medium is used to store a program, and the program is executed to implement the fatigue life prediction method of the rotor blade.

[0033] Beneficial effects: The method of the present invention is simple and practical, requires few model parameters, has high calculation accuracy, can determine the fatigue critical section of carbon nanotube reinforced composite rotor blades and predict fatigue life, and has important academic value and engineering significance. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 is a flow chart of the present invention;

[0035] Figure 2 It is the structural SN curve diagram of the present invention;

[0036] Figure 3 It is the finite element model diagram of the present invention;

[0037] Figure 4 It is a three-dimensional stress distribution diagram of the rotor blade of the present invention. DETAILED DESCRIPTION

[0038] The accompanying drawings, which constitute a part of the present invention, are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0039] It should also be noted that the various specific technical features described in the above specific embodiments can be combined in any suitable manner without contradiction. In order to avoid unnecessary repetition, the present invention will not further describe various possible combinations.

[0040] like Figure 1 As shown, the present invention provides a method for predicting the fatigue life of a rotor blade. The rotor blade in this embodiment adopts a carbon nanotube reinforced composite material. The method specifically comprises the following steps:

[0041] S1. Fatigue life test and fatigue performance degradation test are carried out on carbon nanotube reinforced composite materials to obtain fatigue stress-life data, residual stiffness data and residual strength data.

[0042] S2. Establishing a structural SN curve equation of a carbon nanotube reinforced composite material rotor blade according to fatigue test data of the carbon nanotube reinforced composite material.

[0043] The structural SN curve of the carbon nanotube reinforced composite rotor blade of this embodiment is as follows: Figure 2 As shown, it includes the average curve equation and the safety curve equation.

[0044] According to the fatigue test results of carbon nanotube reinforced composite materials, the average SN curve equation of carbon nanotube reinforced composite rotor blades is established. The expression of the average SN curve equation is:

[0045]

[0046] The fatigue SN curve equation is established based on the obtained data, where S represents the fatigue alternating load and N represents the fatigue life; where A = 1000 α , α is the shape parameter of fatigue SN curve, S ∞m is the average fatigue limit, S 4m For N = 10 4 Corresponding fatigue alternating load, S m is the low cycle intercept of fatigue SN curve, k m is the slope of the low cycle segment of the fatigue SN curve; the fatigue SN curve is the curve established in S1 based on the data obtained.

[0047] According to the average SN curve equation and fatigue strength reduction factor J of carbon nanotube reinforced composite rotor blades p , the calculation safety SN curve equation of carbon nanotube reinforced composite rotor blades is established, and the expression of the calculation safety SN curve equation is:

[0048]

[0049] Among them, S4p Fatigue life N = 10 4 The corresponding calculation safety fatigue alternating load is:

[0050] S3. According to the load conditions of the carbon nanotube reinforced composite rotor blades during forward flight, the fatigue load and boundary conditions of the carbon nanotube reinforced composite rotor blades are determined, a fatigue finite element model of the carbon nanotube reinforced composite rotor blades is established, and the three-dimensional stress distribution state and fatigue critical section of the blades are obtained.

[0051] Among them, the fatigue finite element model of carbon nanotube reinforced composite rotor blades is as follows Figure 3 As shown, according to the load conditions of the carbon nanotube reinforced composite rotor blade during forward flight, the fatigue load and boundary conditions of the carbon nanotube reinforced composite rotor blade are determined, the characterizing load of the fatigue load is the flapping bending moment, the other main loads are the centrifugal force and the swing bending moment, and the boundary condition is the blade root end face fixation.

[0052] According to fatigue load and boundary conditions, fatigue finite element model of carbon nanotube reinforced composite rotor blade is established, and the three-dimensional stress distribution state and fatigue dangerous section of carbon nanotube reinforced composite rotor blade are obtained. The maximum positive stress of fatigue dangerous section along the blade span is formed by the superposition of positive stresses generated by flapping moment, centrifugal force and swing moment, and the minimum positive stress is formed by the superposition of positive stresses generated by centrifugal force and swing moment. The expressions of maximum positive stress and minimum positive stress are as follows:

[0053]

[0054] Among them, σ x,max is the maximum normal stress of the dangerous section, σ x,min is the minimum normal stress of the dangerous section, is the stress caused by centrifugal force in the dangerous section, is the stress caused by the swinging bending moment in the dangerous section, is the normal stress caused by the swing bending moment in the dangerous section.

[0055] According to the maximum normal stress and the minimum normal stress, the average stress and the alternating stress are obtained. The expressions of the average stress and the alternating stress are:

[0056]

[0057] Among them, S m is the mean stress, S a is alternating stress.

[0058] S4. The Goodman mean stress correction theory is used to correct the stress of the fatigue-critical section, and the structural SN curve equation is used to establish a fatigue life prediction model for carbon nanotube reinforced composite rotor blades to predict the fatigue life of carbon nanotube reinforced composite rotor blades.

[0059] According to the mean stress and alternating stress, the Goodman mean stress correction theory is used to obtain the equivalent mean stress and equivalent alternating stress with a stress ratio of R = 0.1. The expressions of the equivalent mean stress and equivalent alternating stress are:

[0060]

[0061] Among them, S m,eq is the equivalent mean stress, S a,eq is the equivalent alternating stress, σ u is the ultimate stress.

[0062] According to the equivalent mean stress and equivalent alternating stress, the fatigue life prediction model of carbon nanotube reinforced composite rotor blades is established by using the calculation safety SN curve equation. The expression of the fatigue life prediction model is:

[0063]

[0064] Among them, N1 is the allowable number of cycles of the blade under fatigue load, n is the number of fatigue load cycles corresponding to one hour of blade rotation, and L is the predicted life of the blade.

[0065] Figure 4 It can be seen that the maximum Mises stress of the carbon nanotube reinforced composite rotor blade is 245.55 MPa, which appears at the flexible beam installation opening at the blade root. The allowable number of cycles of the carbon nanotube reinforced composite rotor blade is 8.75×10 9 When the blade speed is 1000RPM, the fatigue life prediction result of the blade is 1.167×10 5 Hour.

[0066] It should be understood that, although the various steps of the fatigue life prediction method of carbon nanotube reinforced composite rotor blades in this article are displayed in sequence, these steps are not necessarily performed in sequence. Unless clearly stated in this article, there is no strict order restriction on the execution of these steps, and these steps can be performed in other orders. Moreover, at least a part of the steps may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily performed at the same time, but can be performed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be performed in turn or alternating with other steps or at least a part of the sub-steps or stages of other steps.

[0067] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0068] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the attached claims.

Claims

1. A method for predicting fatigue life of a rotor blade, characterized in that: The specific steps include: Step 1: Perform fatigue life test and fatigue performance degradation test on the material of the rotor blade to obtain fatigue stress-life data, residual stiffness data and residual strength data, and establish fatigue SN curve equation based on the obtained data, where S represents fatigue alternating load and N represents fatigue life; Step 2: Establish the structural SN curve equation of the rotor blade based on the data obtained in step 1; Step 3: According to the load conditions of the rotor blades during forward flight, the fatigue load and boundary conditions of the rotor blades are determined, and a finite element model of the rotor blades is constructed according to the fatigue load and boundary conditions of the rotor blades, so as to obtain the three-dimensional stress distribution state and fatigue critical section of the rotor blades; Step 4: Correct the stress of the fatigue-critical section; Step 5: Establish a fatigue life prediction model for the rotor blade based on the structural SN curve equation and the stress corrected in step 4.

2. A method for predicting fatigue life of a rotor blade according to claim 1, characterized in that: The structural SN curve equation in step 2 includes an average SN curve equation and a calculated safety SN curve; Step 2.1: First, construct the average SN curve equation according to the following formula: Where A = 1000 α , α is the shape parameter of fatigue SN curve, S ∞m is the average fatigue limit, S 4m For N = 10 4 Corresponding fatigue alternating load, S m is the low cycle intercept of fatigue SN curve, k m It is the slope of the low cycle section of the fatigue SN curve; Step 2.2: Based on the average SN curve equation and fatigue strength reduction factor J p , establish the calculation safety SN curve equation: Among them, S 4p For N = 10 4 The corresponding calculation safety fatigue alternating load is:

3. The method for predicting fatigue life of a rotor blade according to claim 1, characterized in that: The fatigue loads in step 3 are swinging bending moment, shimmy bending moment and centrifugal force.

4. The method for predicting fatigue life of a rotor blade according to claim 1, characterized in that: The boundary condition in step 3 is that the blade root end face is fixed.

5. The method for predicting fatigue life of a rotor blade according to claim 1, characterized in that: The step 4 is specifically as follows: Step 4.1: Maximum normal stress σ along the blade length in the fatigue critical section x,max and the minimum normal stress σ x,min The expression is as follows: in, is the stress caused by centrifugal force in the dangerous section, is the stress caused by swinging bending moment in the dangerous section, is the normal stress caused by the shimmying bending moment in the dangerous section; Step 4.2: Calculate the average stress S according to the following formula m and alternating stress S a : Step 4.4: Use Goodman mean stress correction theory to correct the stress of the fatigue critical section and obtain the equivalent mean stress S m,eq and equivalent alternating stress S a,eq : Among them, σ u is the ultimate stress.

6. The method for predicting fatigue life of a rotor blade according to claim 1, characterized in that: The expression of the fatigue life prediction model in step 5 is as follows: Among them, α is the shape parameter of fatigue SN curve, S ∞m is the average fatigue limit, J p is the fatigue strength reduction factor, N1 is the allowable number of cycles of the blade under fatigue load, n is the number of fatigue load cycles corresponding to the blade rotating for one hour, and L is the predicted life of the blade.

7. An electronic device / system for a method for predicting fatigue life of a rotor blade, characterized in that: It comprises a processor and a memory, wherein the memory stores execution instructions of the processor, and the processor is configured to execute the execution instructions to implement the fatigue life prediction method of the rotor blade according to any one of claims 1-6.

8. A computer-readable storage medium for storing a program, characterized in that: Execute the program to implement the fatigue life prediction method of the rotor blade described in any one of claims 1-6.

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