Compressor blade vibration fatigue failure probability assessment method

Abstract

The invention aims to provide a compressor blade vibration fatigue failure probability evaluation method. The method comprises the following steps: constructing a probability Goodman curve of a blade material; obtaining the vibration stress distribution of the blade at the dangerous rotating speed; determining a vibration fatigue dangerous part of the blade, and obtaining the steady-state stress of the vibration fatigue dangerous part; and calculating the vibration fatigue failure probability of the dangerous part of the blade according to the steady-state stress and the vibration stress amplitude of the vibration fatigue dangerous part of the blade based on the blade material probability Goldman curve. The evaluation method can solve the problems that an existing blade vibration fatigue failure probability evaluation method does not conform to the design thought of high-cycle fatigue infinite life of the blade, the test amount is large, and engineering feasibility is lacked.

Description

Technical Field

[0001] The invention relates to the field of gas turbine engines, and in particular to a method for evaluating the vibration fatigue failure probability of compressor blades. Background Art

[0002] Compressor blades are important parts of aircraft engines, and their failure probability is crucial to the reliability level of aircraft engines. Vibration fatigue (high cycle fatigue) is the main failure mode of compressor blades. Usually, in the high cycle fatigue design of aircraft engine compressor blades, a deterministic life design method is adopted, and the Goodman diagram is used to design the blade high cycle fatigue for infinite life, and a certain frequency margin and vibration stress margin are given. However, due to the uncertainty of different degrees in the geometric dimensions, material properties and loads of compressor blades, the vibration fatigue failure of blades has probabilistic characteristics. Even if a certain frequency margin and vibration stress margin are left in the high cycle fatigue design, the vibration fatigue failure of blades cannot be completely avoided. Therefore, based on the probability and statistics theory, quantitatively evaluating the vibration fatigue failure probability of compressor blades has important engineering significance.

[0003] Existing blade vibration fatigue probabilistic life assessment methods include: considering the uncertainty of blade high-cycle fatigue life by randomizing size parameters, material performance parameters, and load parameters; obtaining the material PSN fatigue life curve based on blade material tests; using Monte Carlo sampling technology, or response surface method, or combined with a proxy model to calculate the stress and fatigue life of blades with specific dimensions, material properties, and loads; finally, calculating the relationship between blade vibration fatigue life and failure probability.

[0004] However, the inventors found that the existing blade vibration fatigue failure probability assessment method still has problems such as not conforming to the design concept of high-cycle fatigue infinite life of the blade, large test volume, and lack of engineering feasibility. Summary of the invention

[0005] The purpose of the present invention is to provide a compressor blade vibration fatigue failure probability assessment method, which can solve the problems of existing blade vibration fatigue failure probability assessment methods that do not conform to the blade high cycle fatigue infinite life design concept, large test volume, and lack of engineering feasibility.

[0006] A method for evaluating the probability of compressor blade vibration fatigue failure to achieve the above-mentioned purpose comprises the following steps:

[0007] Construct probabilistic Goodman curves for blade materials;

[0008] Obtain the vibration stress distribution of blades at dangerous speeds;

[0009] Determine the vibration fatigue risk position of the blade, and obtain the steady-state stress of the vibration fatigue risk position;

[0010] Based on the blade material probability Goodman curve and in accordance with the steady-state stress and vibration stress amplitude of the vibration fatigue hazardous part of the blade, the vibration fatigue failure probability of the blade hazardous part is calculated.

[0011] In one or more embodiments, the probabilistic Goodman curve is established by the following steps:

[0012] Construct the probability density function of the tensile strength limit of the blade material;

[0013] Construct the probability density function of the tensile fatigue strength of blade materials;

[0014] A probability Goodman curve of the blade material is constructed according to the probability density function of the tensile strength limit of the blade material and the probability density function of the tensile fatigue strength.

[0015] In one or more embodiments, constructing a probability density function of the tensile strength limit of the blade material includes:

[0016] Obtain the dispersion data of the tensile strength limit of the blade material, and construct the probability density function f of the tensile strength limit of the blade material through the dispersion data of the tensile strength limit of the blade material b (S b ).

[0017] In one or more embodiments, constructing a probability density function of the tensile fatigue strength of a blade material includes:

[0018] Obtain the tensile fatigue strength of the blade material, assuming that the tensile fatigue strength of the blade material S e and tensile strength limit S b They are related to each other and satisfy the following relationship:

[0019] S e =kS b ;

[0020] Where k is a constant related to material properties, and the obtained blade material tensile fatigue strength S e Mean value and tensile strength limit S b The ratio between the means is determined;

[0021] According to the tensile fatigue strength of the blade material and the distribution characteristics of the tensile strength limit of the blade material, the probability density function f of the tensile fatigue strength of the blade material is constructed. e (S e ),as follows:

[0022]

[0023] In one or more embodiments, the probabilistic Goodman curve is a cluster of countless Goodman curves corresponding to different failure probabilities, and the failure probability is 0% to 100%;

[0024] Among them, the Goodman curve with a failure probability of N% (0≤N≤100) is a line connecting the tensile strength with a reliability of N% in the probability density function of the tensile strength limit of the blade material and the tensile fatigue strength with a reliability of N% in the probability density function of the tensile fatigue strength of the blade material.

[0025] In one or more embodiments, the blade vibration stress distribution at a critical speed is obtained by the following steps:

[0026] Preliminarily determine the dangerous rotation speed of the blades;

[0027] Conduct blade vibration stress test within the initially determined dangerous speed range to obtain the blade's dangerous speed;

[0028] Finite element analysis is performed on the vibration mode of the blade at the critical speed to obtain the vibration stress distribution of the blade at the critical speed.

[0029] In one or more embodiments, the preliminary determination of the dangerous rotational speed of the blade further includes: establishing a finite element analysis model of the blade, drawing a Campbell diagram of the blade, finding the dangerous vibration order and frequency multiple of the blade within the normal operating speed range of the engine, and preliminarily determining the dangerous rotational speed of the blade.

[0030] In one or more embodiments, the blade vibration stress test comprises the following steps:

[0031] Through test runs on different engine benches, several strain gauges are pasted on each test blade and connected to the dynamic strain signal acquisition and data analysis device through signal acquisition leads to collect dangerous speed and vibration strain data of the same type of blades in different engines and at different positions.

[0032] In one or more embodiments, the dangerous rotation speed of the blade is obtained by the following steps:

[0033] Slowly accelerate and decelerate within the engine's normal operating speed range, and based on the dangerous speed preliminarily determined based on the Campbell diagram of the blade, monitor the engine's vibration condition in real time through the acceleration signal acquisition and data analysis device, and find the engine speed corresponding to the maximum vibration stress. This speed is the dangerous speed of the blade.

[0034] In one or more embodiments, if there are multiple vibration peaks within the normal operating speed range of the engine, the dangerous speed and vibration strain data of the blades at different vibration peaks are recorded respectively.

[0035] In one or more embodiments, obtaining the vibration stress distribution of the blade at the dangerous speed comprises the following steps:

[0036] Finite element analysis is performed on the vibration mode of the compressor blade at the dangerous speed. According to the blade vibration mode analysis results, the vibration stress distribution of the blade at the dangerous speed is reversely calculated using the strain test data of each measuring point of the blade at the dangerous speed.

[0037] In one or more embodiments, the steady-state stress of the vibration fatigue risk position is obtained by the following method:

[0038] The static strength analysis of the blade is carried out by using the finite element simulation method, and the steady-state stress distribution of the blade at the dangerous speed is calculated;

[0039] Comprehensively analyze the steady-state stress distribution and vibration stress amplitude distribution of the blade to determine the vibration fatigue risk position and dangerous speed of the blade;

[0040] The steady-state stress corresponding to the vibration fatigue risk area is obtained through the calculated steady-state stress distribution data.

[0041] In one or more embodiments, the steady-state stress at any node i of the blade at any dangerous speed is x i , the vibration stress amplitude is y i , then when When it is the maximum value, the location of the node is the dangerous part of the blade.

[0042] In one or more embodiments, the steady-state stress distribution of a small number of blades with different masses at dangerous locations is calculated first, and the steady-state stress of other blades at dangerous locations is calculated by interpolation.

[0043] In one or more embodiments, the vibration fatigue risk position and the risky speed of the blade are determined and the temperature of the position is recorded. Based on the blade material probability Goodman curve at the corresponding temperature, the steady-state stress x of any blade risk position is calculated. a and vibration stress amplitude y a The blade vibration fatigue failure probability p is calculated by the following formula: j :

[0044]

[0045] in, f b (S b ) is the tensile strength distribution of the material at the temperature of the dangerous part of the blade.

[0046] The vibration fatigue failure probability assessment method for compressor blades can achieve the following:

[0047] (1) The probability distribution characteristics of the material's tensile fatigue strength are determined based on the probability distribution characteristics of the material's tensile strength limit, which greatly reduces the amount of tests required to construct the material probability Goodman curve; (2) The blade material density variable is used to reflect the blade weight difference caused by the dispersion of geometric dimensions, which avoids the difficulty of parameterizing the blade geometric characteristics and reduces the difficulty of analyzing the uncertainty of centrifugal load caused by individual differences in blades; (3) The dispersion data of the blade vibration strain is obtained through the blade installation vibration test, which avoids the difficulty of obtaining the blade excitation load distribution and dispersion data, and has good engineering feasibility; (4) An algorithm for the probability of blade vibration fatigue failure is established, and the two-dimensional stress-strength interference model is converted into a one-dimensional stress-strength interference model, which greatly reduces the computational complexity.

[0048] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present application. Moreover, the same reference numerals are used throughout the drawings to represent the same components. In the drawings:

[0050] Figure 1 A schematic diagram of a flow chart according to some embodiments of the compressor blade vibration fatigue failure probability assessment method is shown;

[0051] Figure 2 A schematic diagram of a probabilistic Goodman curve according to some embodiments of the present application is shown. DETAILED DESCRIPTION

[0052] The following embodiments of the technical solution of the present application are described in detail in conjunction with the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solution of the present application, and are therefore only used as examples, and cannot be used to limit the scope of protection of the present application.

[0053] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by technicians in the technical field to which this application belongs; the terms used herein are only for the purpose of describing specific embodiments and are not intended to limit this application; the terms "including" and "having" in the specification and claims of this application and the above-mentioned figure descriptions and any variations thereof are intended to cover non-exclusive inclusions.

[0054] The existing compressor blade vibration fatigue failure probability assessment methods often have the following shortcomings:

[0055] (1) The existing methods still follow the analytical thinking of low-cycle fatigue probability life of the structure, mainly evaluating the blade failure probability corresponding to the specified life or the blade life corresponding to the specified reliability requirement, which is inconsistent with the design concept of high-cycle fatigue infinite life of the blade;

[0056] (2) The existing methods require the PSN fatigue life curve of the blade material as input, which requires a large number of material fatigue tests;

[0057] (3) The existing methods obtain the vibration stress and its distribution of the blade through simulation analysis, which requires the distribution of the excitation load and dispersion data as input conditions. However, it is more difficult to obtain these data in engineering than to directly obtain the vibration stress and its distribution of the blade;

[0058] (4) In order to take into account geometric dispersion, existing methods have oversimplified the blade model (such as simplifying it to a rectangular parallelepiped), which makes it difficult to apply in engineering.

[0059] In order to solve the above defects in the prior art, according to some embodiments of the present application, a method for evaluating the probability of vibration fatigue failure of a compressor blade is provided, such as Figure 1 A schematic flow chart of some embodiments of the compressor blade vibration fatigue failure probability assessment method is shown.

[0060] The vibration fatigue failure probability assessment method for compressor blades includes the following steps:

[0061] S1: Construct the probability Goodman curve of blade material;

[0062] S2: Obtain the vibration stress distribution of the blade at dangerous speed;

[0063] S3: determining the vibration fatigue risk position of the blade, and obtaining the steady-state stress of the vibration fatigue risk position;

[0064] S4: Based on the probability Goodman curve of blade material, the probability of vibration fatigue failure of dangerous parts of blade is calculated according to the steady-state stress and vibration stress amplitude of dangerous parts of blade.

[0065] In some specific embodiments of the present evaluation method, the probability Goodman curve in step S1 is established by the following steps:

[0066] Construct the probability density function of the tensile strength limit of the blade material;

[0067] Construct the probability density function of the tensile fatigue strength of blade materials;

[0068] According to the probability density function of the tensile strength limit and the probability density function of the tensile fatigue strength of the blade material, the probability Goodman curve of the blade material is constructed.

[0069] Furthermore, in some specific embodiments, step S1 specifically includes:

[0070] Obtain the dispersion data of the tensile strength limit of the blade material, and construct the probability density function f of the tensile strength limit of the blade material through the dispersion data of the tensile strength limit of the blade material b (S b ). In some specific embodiments, the dispersion data of the tensile strength limit of the blade material is obtained by, but not limited to, a blade material tensile strength test, a material manual, a material database, etc. In some specific embodiments, a probability density function f of the tensile strength limit of the blade material is constructed. b (S b ) is, for example, a normal distribution or a Weibull distribution.

[0071] Obtain the tensile fatigue strength of the blade material, assuming that the tensile fatigue strength of the blade material S e and tensile strength limit S b Interrelated, satisfying S e =kS b Where k is a constant related to material properties, obtained from the tensile fatigue strength S of the blade material e and tensile strength limit S b The ratio between the means is determined.

[0072] According to the tensile fatigue strength of the blade material and referring to the distribution characteristics of the tensile strength limit of the blade material, the probability density function of the tensile fatigue strength of the blade material is constructed as follows:

[0073] In some specific embodiments, the tensile fatigue strength of the blade material is obtained through methods including but not limited to high cycle tensile fatigue testing of the blade material, querying a material manual, a material database, and the like.

[0074] In some specific embodiments of the present evaluation method, the probabilistic Goodman curve is a cluster of countless Goodman curves corresponding to different failure probabilities, where the failure probability is 0% to 100%, wherein the Goodman curve with a failure probability of N% (0≤N≤100) is a line connecting the tensile strength with a reliability of N% in the probability density function of the tensile strength limit of the blade material and the tensile fatigue strength with a reliability of N% in the probability density function of the tensile fatigue strength of the blade material.

[0075] like Figure 2A schematic diagram of a probability Goodman curve according to some embodiments of the present application is shown, in which the distribution curve on the X-axis is the tensile strength limit S b Distribution, the distribution curve on the Y axis is the tensile fatigue strength S e Distribution, the median Goodman curve 101 is the line connecting the median point of the tensile strength limit on the x-axis and the median point of the tensile fatigue strength on the y-axis, and the 95% reliability Goodman curve 102 is the line connecting the tensile strength limit point with a reliability of 95% on the x-axis and the tensile fatigue strength point with a reliability of 95% on the y-axis. When the stress coordinates (steady-state stress, vibration stress amplitude) of the dangerous part of the blade are at the lower left of the median Goodman curve, the probability of vibration fatigue failure of the blade is less than 50%; when the stress coordinates (steady-state stress, vibration stress amplitude) of the dangerous part of the blade are at the upper right of the median Goodman curve, the probability of vibration fatigue failure of the blade is greater than 50%; when the stress coordinates (steady-state stress, vibration stress amplitude) of the dangerous part of the blade are on the median Goodman curve, the probability of vibration fatigue failure of the blade is equal to 50%. Similarly, when the stress coordinates (steady-state stress, vibration stress amplitude) of the dangerous part of the blade are on the 95% reliability Goodman curve, the probability of vibration fatigue failure of the blade is equal to 5%.

[0076] In some specific embodiments of the present evaluation method, in step S2, the blade vibration stress distribution at the dangerous speed is obtained by the following steps:

[0077] Through test runs on different engine benches, compressor blade vibration stress tests were carried out. The blade weight, blade speed when the vibration was most intense, and strain data of each measuring point were recorded. Combined with the blade vibration shape analysis results, the blade vibration stress distribution at dangerous speeds was calculated.

[0078] Specifically, the blade vibration stress distribution at dangerous speed is obtained through the following steps:

[0079] Establish a finite element analysis model for the blades and preliminarily determine the dangerous speed of the blades. Specifically, the establishment of the finite element analysis model for the blades does not take into account the dispersion of the blade geometry and material properties. The resonance frequency of the compressor blades under various operating conditions is analyzed, and the Campell diagram of the blades is drawn. The dangerous vibration order and frequency doubling of the blades are found within the common operating speed range of the engine, and the dangerous speed of the blades is preliminarily determined, thereby providing guidance for the blade vibration stress test. Among them, the blade geometry is the nominal size, and the material properties are the median or mean.

[0080] The blade vibration stress test is performed within the preliminarily determined dangerous speed range to obtain the dangerous speed of the blade. In some specific embodiments, the blade vibration stress test is carried out by testing the compressor blade vibration stress through different engine bench tests. Before the blades are installed, the test blades are numbered, and the weight of each test blade is accurately measured and recorded. Several strain gauges are pasted on each test blade, and connected to a dynamic strain signal acquisition and data analysis device (dynamic strain gauge) through signal acquisition leads. The pasting position, blade number and signal channel of the strain gauge corresponding to each lead are recorded, and the dangerous speed and vibration strain data of the same type of blades at different positions in different engines are collected. Acceleration sensors are pasted on some blades and connected to the acceleration signal acquisition and data analysis device through signal acquisition leads. During the engine bench test, the engine is slowly accelerated and decelerated within the normal operating speed range of the engine. According to the dangerous speed preliminarily determined based on the Campbell diagram of the blade, the vibration condition of the engine is monitored in real time through the acceleration signal acquisition and data analysis device. In the speed band near the peak value of the vibration acceleration signal, the dynamic strain signal of the blade is collected. Through data processing, the vibration strain (amplitude)-time curve of different blade positions is obtained, and the engine speed corresponding to the maximum vibration stress is found. This speed is the dangerous speed of the blade. Due to the differences between individual blades and engines and uncertain factors such as environment and operation, there are differences in the dangerous speed and vibration stress of the same type of blades on different engines or at different positions of the same engine. Therefore, it is necessary to collect the dangerous speed and vibration strain data of the same type of blades at different engines and different positions through multiple engine bench tests. For the different vibration strain data of the blade measured by multiple bench tests of the same engine, the vibration strain data with the largest vibration strain amplitude is used as the vibration strain data of the blade. If there are multiple vibration peaks in the commonly used operating speed range of the engine, the dangerous speed and vibration strain data of the blade at different vibration peaks should be recorded separately.

[0081] The calculation of blade vibration stress amplitude distribution includes finite element analysis of the vibration mode of the blade at the dangerous speed to obtain the vibration stress distribution of the blade at the dangerous speed.

[0082] Specifically, the vibration mode of the compressor blade at the dangerous speed is analyzed by finite element analysis. The difference in blade weight is simulated by changing the blade material density. According to the results of the blade vibration mode analysis, the strain test data of each measuring point of the blade at the dangerous speed is used to reversely calculate the vibration stress distribution of the blade at the dangerous speed. If the dangerous part of the blade has been predicted, it is only necessary to calculate the vibration stress amplitude of the dangerous part of the blade at the dangerous speed.

[0083] In some specific embodiments of the present evaluation method, in step S3, the blade vibration fatigue risk position is obtained by the following steps:

[0084] The static strength analysis of the blades is carried out by finite element simulation method, and the steady-state stress distribution of the blades at dangerous speeds is calculated. Specifically, by changing the material density of the blades, the difference in blade weight is simulated, and the steady-state stress distribution of a small number of blades with different masses at dangerous speeds is calculated. If there are multiple vibration peaks within the commonly used operating speed range of the engine, the steady-state stress distribution of the blades at different dangerous speeds should be calculated separately.

[0085] The steady-state stress distribution and vibration stress amplitude distribution of the blade are combined to determine the vibration fatigue dangerous parts and dangerous speeds of the blade, and the temperature of the parts is recorded at the same time. For example, suppose the steady-state stress at any node i of the blade at any dangerous speed is x i , the vibration stress amplitude is y i , then when When it is the maximum value, the location of the node is the dangerous part of the blade, and the speed is the vibration fatigue dangerous speed. The steady-state stress corresponding to the vibration fatigue dangerous part is obtained by calculating the steady-state stress distribution data. Among them, k is a constant related to the material properties, and the obtained blade material tensile fatigue strength S e and tensile strength limit S b The ratio between the means is determined.

[0086] In some specific embodiments, based on the steady-state stress distribution and dangerous parts of the blades obtained by finite element simulation calculations on a small number of blades, the steady-state stresses of dangerous parts of other blades (with different weights and dangerous speeds) are calculated by interpolation. Since the amount of calculation required to conduct strength analysis on a large number of blades with different weights and dangerous speeds one by one is large, and considering that the weights and dangerous speeds of different blades usually vary within a small range, the steady-state stresses of dangerous parts of other blades can be obtained by interpolation calculation based on the steady-state stress distribution and dangerous parts of the blades obtained by finite element simulation calculations on a small number of samples, so as to simplify the calculation process.

[0087] In some specific embodiments, step S4 includes:

[0088] Based on the probability Goodman curve of blade material at the corresponding temperature, according to the steady-state stress x of any dangerous part of the blade a and vibration stress amplitude y a , calculate the blade vibration fatigue failure probability p j .

[0089]

[0090] in, f b (S b ) is the tensile strength distribution of the material at the temperature of the dangerous part of the blade.

[0091] Evaluate the probability of vibration fatigue failure of this type of blade. If the stress combinations of dangerous parts of n blades at dangerous speeds are obtained through multiple engine vibration stress tests and finite element simulation, the probability of vibration fatigue failure of this type of blade is:

[0092]

[0093] For details, please refer to Figure 2 , assuming that the stress combination of a dangerous part of a blade is a(x a ,y a ), the steady-state stress is x a , the vibration stress amplitude is y a , the coordinates on the two-dimensional plane are (x a ,y a ). The stress a(x a ,y a ) is projected onto the Sm axis parallel to the Goodman curve, and the projection is marked as z a ,but

[0094]

[0095] Suppose any intensity combination A(X A , Y A ), the intensity A(X A , Y A ) Project the probability Goodman curve through point A onto the Sm axis, and mark it as Z A ,but

[0096]

[0097] Since X and Y are related variables, Y = kX, the probability distribution characteristics of Z are the same as those of X, that is,

[0098] f Z (Z) = f b (S b )

[0099] where f b (S b ) is the tensile strength distribution of the material at the temperature of the dangerous part of the blade.

[0100] At this time, if Z A -z a ≤0, the blade fails due to vibration fatigue; if Z A -z a >0, the leaf survives.

[0101] Let M = Z A -z a, the vibration fatigue failure probability p of the blade j for

[0102]

[0103] If the stress combinations of dangerous parts of n blades at dangerous speeds are obtained through multiple engine vibration stress tests and finite element simulations, the vibration fatigue failure probability of this type of blade is

[0104]

[0105] The vibration fatigue failure probability assessment method for compressor blades can achieve the following:

[0106] (1) The probability distribution characteristics of the material's tensile fatigue strength are determined based on the probability distribution characteristics of the material's tensile strength limit, which greatly reduces the amount of testing required to construct the material's probability Goodman curve;

[0107] (2) The blade material density variable is used to reflect the blade weight difference caused by the dispersion of geometric dimensions, which avoids the difficulty of parameterizing the blade geometric characteristics and reduces the difficulty of analyzing the uncertainty of centrifugal load caused by individual differences of blades;

[0108] (3) The dispersion data of blade vibration strain is obtained through the blade installation vibration test, which avoids the difficulty of obtaining the distribution and dispersion data of blade excitation load and has good engineering feasibility.

[0109] (4) An algorithm for blade vibration fatigue failure probability was established, and the two-dimensional stress-strength interference model was converted into a one-dimensional stress-strength interference model, which greatly reduced the computational complexity;

[0110] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0111] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them; although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein by equivalents; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present application, and they should all be included in the scope of the claims and specification of the present application. In particular, as long as there is no structural conflict, the various technical features mentioned in the various embodiments can be combined in any way. The present application is not limited to the specific embodiments disclosed herein, but includes all technical solutions that fall within the scope of the claims.

Claims

1. A method for evaluating the probability of compressor blade vibration fatigue failure, characterized in that: The steps include: Construct probabilistic Goodman curves for blade materials; Obtain the vibration stress distribution of blades at dangerous speeds; Determine the vibration fatigue risk position of the blade, and obtain the steady-state stress of the vibration fatigue risk position; Based on the blade material probability Goodman curve and in accordance with the steady-state stress and vibration stress amplitude of the vibration fatigue hazardous part of the blade, the vibration fatigue failure probability of the blade hazardous part is calculated.

2. The compressor blade vibration fatigue failure probability assessment method according to claim 1, characterized in that: The probabilistic Goodman curve is established by the following steps: Construct the probability density function of the tensile strength limit of the blade material; Construct the probability density function of the tensile fatigue strength of blade materials; A probability Goodman curve of the blade material is constructed according to the probability density function of the tensile strength limit of the blade material and the probability density function of the tensile fatigue strength.

3. The compressor blade vibration fatigue failure probability assessment method according to claim 2, characterized in that: The probability density function of the tensile strength limit of the blade material is constructed by: Obtain the dispersion data of the tensile strength limit of the blade material, and construct the probability density function f of the tensile strength limit of the blade material through the dispersion data of the tensile strength limit of the blade material b (S b ).

4. The compressor blade vibration fatigue failure probability assessment method according to claim 3, characterized in that: The probability density function of the tensile fatigue strength of the blade material is constructed by: Obtain the tensile fatigue strength of the blade material, assuming that the tensile fatigue strength of the blade material S e and tensile strength limit S b They are related to each other and satisfy the following relationship: S e =kS b ; Where k is a constant related to material properties, and the obtained blade material tensile fatigue strength S e Mean value and tensile strength limit S b The ratio between the means is determined; According to the tensile fatigue strength of the blade material and the distribution characteristics of the tensile strength limit of the blade material, the probability density function f of the tensile fatigue strength of the blade material is constructed. e (S e ),as follows:

5. The compressor blade vibration fatigue failure probability assessment method according to claim 2, characterized in that: The probabilistic Goodman curve is a cluster of countless Goodman curves corresponding to different failure probabilities, and the failure probability is 0% to 100%; Among them, the Goodman curve with a failure probability of N% (0≤N≤100) is a line connecting the tensile strength with a reliability of N% in the probability density function of the tensile strength limit of the blade material and the tensile fatigue strength with a reliability of N% in the probability density function of the tensile fatigue strength of the blade material.

6. The compressor blade vibration fatigue failure probability assessment method according to claim 1, characterized in that: The blade vibration stress distribution at dangerous speed is obtained through the following steps: Preliminarily determine the dangerous rotation speed of the blades; Conduct blade vibration stress test within the initially determined dangerous speed range to obtain the blade's dangerous speed; Finite element analysis is performed on the vibration mode of the blade at the critical speed to obtain the vibration stress distribution of the blade at the critical speed.

7. The compressor blade vibration fatigue failure probability assessment method according to claim 6, characterized in that: The preliminary determination of the dangerous rotation speed of the blade further includes: establishing a finite element analysis model of the blade, drawing a Campbell diagram of the blade, finding the dangerous vibration order and frequency multiple of the blade within the normal operating speed range of the engine, and preliminary determining the dangerous rotation speed of the blade.

8. The compressor blade vibration fatigue failure probability assessment method according to claim 6, characterized in that: The blade vibration stress test comprises the following steps: Through test runs on different engine benches, several strain gauges are pasted on each test blade and connected to the dynamic strain signal acquisition and data analysis device through signal acquisition leads to collect dangerous speed and vibration strain data of the same type of blades in different engines and at different positions.

9. The compressor blade vibration fatigue failure probability assessment method according to claim 6, characterized in that: The dangerous rotation speed of the blade is obtained by the following steps: Slowly accelerate and decelerate within the engine's normal operating speed range, and based on the dangerous speed preliminarily determined based on the Campbell diagram of the blade, monitor the engine's vibration condition in real time through the acceleration signal acquisition and data analysis device, and find the engine speed corresponding to the maximum vibration stress. This speed is the dangerous speed of the blade.

10. The compressor blade vibration fatigue failure probability assessment method according to claim 9, characterized in that: If there are multiple vibration peaks within the normal operating speed range of the engine, the dangerous speed and vibration strain data of the blades at different vibration peaks are recorded respectively.

11. The compressor blade vibration fatigue failure probability assessment method according to claim 6, characterized in that: Obtaining the vibration stress distribution of the blade at the dangerous speed includes the following steps: Finite element analysis is performed on the vibration mode of the compressor blade at the dangerous speed. According to the blade vibration mode analysis results, the vibration stress distribution of the blade at the dangerous speed is reversely calculated using the strain test data of each measuring point of the blade at the dangerous speed.

12. The compressor blade vibration fatigue failure probability assessment method according to claim 6, characterized in that: The steady-state stress of the vibration fatigue risk position is obtained by the following method: The static strength analysis of the blade is carried out by using the finite element simulation method, and the steady-state stress distribution of the blade at the dangerous speed is calculated; Comprehensively analyze the steady-state stress distribution and vibration stress amplitude distribution of the blade to determine the vibration fatigue risk position and dangerous speed of the blade; The steady-state stress corresponding to the vibration fatigue risk area is obtained through the calculated steady-state stress distribution data.

13. The compressor blade vibration fatigue failure probability assessment method according to claim 12, characterized in that: Assume that the steady-state stress at any node i of the blade at any dangerous speed is x i , the vibration stress amplitude is y i , then when When it is the maximum value, the location of the node is the dangerous part of the blade.

14. The compressor blade vibration fatigue failure probability assessment method according to claim 12, characterized in that: First, the steady-state stress distribution of a small number of blades with different masses at dangerous locations is calculated, and then the steady-state stress of other blades at dangerous locations is calculated by interpolation.

15. The compressor blade vibration fatigue failure probability assessment method according to claim 14, characterized in that: While determining the vibration fatigue dangerous part of the blade and the dangerous speed, record the temperature of the part, and based on the blade material probability Goodman curve at the corresponding temperature, according to the steady-state stress x of any dangerous part of the blade a and vibration stress amplitude y a The blade vibration fatigue failure probability p is calculated by the following formula: j : in, f b (S b ) is the tensile strength distribution of the material at the temperature of the dangerous part of the blade.

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