Method for constructing cavitation erosion resistance evaluation model of material

Abstract

The invention discloses a material cavitation erosion resistance evaluation model construction method, which comprises the following steps: S1, preparing a material sample, and recording the initial mass m0 of the material sample; s2, the sample is placed in cavitation erosion equipment, test parameters are set, and a cavitation erosion test is carried out; s3, taking out the sample within preset time intervals t1, t2, t3,..., tn, and cleaning and drying the sample; measuring the sample mass mi at each time point ti by using a precision balance; recording the mass data of each time point, and calculating the weight loss delta mi = m0-mi; after the test is finished, recording the final mass mf of the sample; the total weight loss delta mtotal is calculated according to the formula: delta mtotal = m0-mf; s4, for each time point ti, calculating a cumulative weight loss percentage Ci, and directly regarding the cumulative weight loss percentage Ci as a failure probability F (ti); s5, fitting the test data (ti, F (ti)), and determining a shape parameter beta and a scale parameter eta of Weibull distribution; and S6, analyzing parameters of the evaluation model to complete quantitative evaluation of the cavitation erosion resistance of the material. The method can quantify the failure mode and the characteristic life of the material and accurately predict the failure probability of the material.

Description

Technical Field

[0001] The present invention relates to the technical field of quantitative evaluation of the cavitation resistance performance of materials, and particularly to a method for constructing an evaluation model for the cavitation resistance performance of materials. Background Art

[0002] Cavitation is the dynamic impact damage to the material surface caused by the collapse of cavitation bubbles in the fluid, which widely exists in key equipment such as hydraulic systems, water turbine blades, and propellers. Research shows that cavitation not only causes material mass loss and structural failure, but also leads to equipment vibration, noise, and safety hazards. For example, the surface of water turbine blades is prone to form honeycomb-like defects under long-term cavitation in a wet steam environment, significantly reducing the equipment efficiency and shortening the service life. Therefore, accurately evaluating the cavitation resistance performance of materials is crucial for equipment material selection, optimization design, and extension of the service cycle.

[0003] The prior art cannot quantify the failure mode and characteristic life of materials; nor can it accurately predict the failure probability and life distribution of materials; even less can it reveal the failure mechanism of materials to provide a more reliable basis for material design and engineering applications. Summary of the Invention

[0004] Aiming at the deficiencies of the above prior art, the technical problem to be solved by this patent application is how to provide a more scientific and accurate method for constructing an evaluation model for the cavitation resistance performance of materials by introducing the Weibull distribution.

[0005] To solve the above technical problems, the present invention adopts the following technical solutions:

[0006] A method for constructing an evaluation model for the cavitation resistance performance of materials, comprising the following steps:

[0007] S1: Prepare material samples of standard size and record their initial mass m0;

[0008] S2: Place the samples in a cavitation device, set the test parameters, and conduct a cavitation test;

[0009] S3: At predetermined time intervals t1, t2, t3,..., t n within, take out the samples and clean and dry them; measure the mass m of the samples at each time point t i ; record the mass data at each time point and calculate the weight loss Δm i = m0 - m i ; after the test, record the final mass m of the samples i ; calculate the total weight loss Δm f = m0 - m total ; f ;

[0010] S4: For each time point ti , calculate the cumulative weight loss percentage C i , and directly regard the cumulative weight loss percentage C i as the failure probability F(t i );

[0011] S5: Fit the test data (t i , F(t i )) to determine the shape parameter β and scale parameter η of the Weibull distribution;

[0012] S6: Complete the quantitative evaluation of the cavitation erosion resistance performance of the material by analyzing the evaluation model parameters.

[0013] Preferably, in S4, the cumulative weight loss percentage C i , and its calculation formula is:

[0014]

[0015] Where: Δm i is the weight loss at time point t i ; Δm total is the total weight loss.

[0016] Preferably, in S4, the failure probability F(t i ), and its definition is:

[0017] In the cavitation erosion test, failure is defined as the material reaching a certain weight loss threshold; the failure probability F(t i ) represents the possibility of the material failing before time t i .

[0018] Preferably, in S5, the Weibull distribution model is:

[0019]

[0020] Preferably, S6 includes but is not limited to the following steps and methods:

[0021] S601: Quantify the failure mode of the material: If β < 1, it means that the material is prone to failure in the early stage; if β ≈ 1, it means that the material fails randomly; if β > 1, it means that the material is more likely to fail in the later stage;

[0022] S602: Quantify the characteristic life of the material: The larger η is, the better the cavitation erosion resistance performance of the material.

[0023] Preferably, the time point t i has the unit unified as "hour", and the mass measurement unit is unified as "milligram".

[0024] In summary, the method for constructing the cavitation erosion resistance performance evaluation model of this material has the following beneficial effects:

[0025] 1. It can quantify the failure mode and characteristic life of the material;

[0026] 2. It can accurately predict the failure probability of the material at different time points;

[0027] 3. It can reveal the failure mechanism of the material and predict its life distribution;

[0028] 4. It can distinguish the differences in cavitation erosion resistance performance of different materials;

[0029] 5. It is applicable to different types of materials (such as metals, ceramics, and composite materials) and different cavitation erosion conditions. Description of the Drawings

[0030] Figure 1 It is a flowchart of a method for constructing a cavitation erosion resistance performance evaluation model of a material according to the present invention. Detailed Embodiment

[0031] The present invention will be further described in detail below with reference to the drawings. In the description of the present invention, it should be understood that the orientation or positional relationship indicated by the orientation words such as "upper, lower" and "top, bottom" is usually based on the orientation or positional relationship shown in the drawings, and is only for the convenience of describing the present invention and simplifying the description. Without contrary description, these orientation words do not indicate and imply that the device or element referred to must have a specific orientation or be constructed and operated in a specific orientation, so they cannot be understood as limiting the protection scope of the present invention; the orientation words "inner, outer" refer to the inside and outside relative to the contour of each component itself.

[0032] As Figure 1 shown, a method for constructing a cavitation erosion resistance performance evaluation model of a material includes the following steps:

[0033] S1: Prepare material samples with standard dimensions, and record their initial mass m0, ensuring that the surface treatment of the samples is consistent to eliminate the influence of surface roughness on the test results;

[0034] S2: Place the samples in a cavitation erosion device, set the test parameters (such as cavitation intensity, temperature, time, etc.), and conduct a cavitation erosion test;

[0035] S3: At predetermined time intervals t1, t2, t3,..., t n within, take out the samples and clean and dry them; use a precision balance to measure the mass m i of the samples at each time point t i ; record the mass data at each time point, and calculate the weight loss Δm i = m0 - m i; After the test, record the final mass m of the sample f ; Calculate the total weight loss Δm total = m0 - m f ;

[0036] S4: For each time point t i , calculate the cumulative weight loss percentage C i , and directly regard the cumulative weight loss percentage C i as the failure probability F(t i );

[0037] The cumulative weight loss percentage C i , and its calculation formula is:

[0038]

[0039] where: Δm i is the weight loss at time point t i ; Δm total is the total weight loss.

[0040] The failure probability F(t i ), and its definition is:

[0041] In the cavitation erosion test, failure can be defined as the material reaching a certain weight loss threshold (such as 50% of the total weight loss). The failure probability F(t i ) represents the possibility of the material failing before time t i .

[0042] The test data is shown in Table 1. The total weight loss Δm total = 50 mg. The cumulative weight loss percentage c i and the failure probability F(t i ) at each time point are shown in Table 1.

[0043] <![CDATA[Time t i (hours)]]> <![CDATA[Weight loss Δm i (mg)]]> <![CDATA[Cumulative weight loss percentage C i (%)]]> <![CDATA[Failure probability F(t i )]]> 1 5 10 0.10 2 10 20 0.20 3 15 30 0.30 4 20 40 0.40 5 25 50 0.50

[0044] S5: Fit the test data (t i , F(t i )) to determine the shape parameter β and scale parameter η of the Weibull distribution;

[0045] The Weibull distribution, its model is:

[0046]

[0047] Fit the test data (t i , F(t i )) using the least squares method or maximum likelihood estimation method to determine the shape parameter β and scale parameter η of the Weibull distribution.

[0048] S6: Complete the quantitative evaluation of the cavitation erosion resistance of the material by analyzing the evaluation model parameters.

[0049] S601: Quantify the failure mode of the material. If β < 1, it indicates that the material is prone to failure in the early stage (early failure mode); if β ≈ 1, it indicates that the material fails randomly (random failure mode); if β > 1, it indicates that the material is more likely to fail in the later stage (wear failure mode);

[0050] S602: Quantify the characteristic life of the material. The larger η is, the better the cavitation erosion resistance of the material;

[0051] S603: More accurately predict the failure probability and life of the material through the Weibull distribution parameters β and η.

[0052] For example:

[0053] Weibull distribution parameters of Material A: β = 1.2, η = 50 hours.

[0054] Weibull distribution parameters of Material B: β = 0.8, η = 40 hours.

[0055] Prior art: The total weight loss of Material A and Material B is similar, and the average weight loss rate is also similar. The prior art cannot distinguish the difference in cavitation erosion resistance between the two materials.

[0056] Technology of this article: For Material A, β > 1, indicating that it is more likely to fail in the later stage (wear failure mode); for Material B, β < 1, indicating that it is more likely to fail in the early stage (early failure mode); the η value of Material A is larger, indicating that its characteristic life is longer and its cavitation erosion resistance is better than that of Material B.

[0057] Conclusion: The technology of this article can reveal the difference in failure modes between Material A and Material B, which the prior art cannot do. The method based on the Weibull distribution can more accurately evaluate the cavitation erosion resistance of materials.

[0058] Finally, it should be noted that those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these changes and modifications.

Claims

1. A method for constructing a material anti-cavitation performance evaluation model, characterized in that: The following steps are involved: S1: Prepare a material sample of standard size and record its initial mass m0; S2: placing the sample in the cavitation equipment, setting the test parameters, and conducting the cavitation test; S3: At predetermined time intervals t1, t2, t3, ..., t n Within 2 hours, take out the sample and wash and dry it; use a precision balance to measure the time t at each time point. i The sample mass m i ; Record the mass data at each time point and calculate the weight loss Δm i =m0-m i ; After the test, record the final mass m of the sample f ; Calculate the total weight loss Δm total =m0-m f ; S4: For each time point t i , calculate the cumulative weight loss percentage C i , and the cumulative weight loss percentage C i Directly regarded as the failure probability F(t i ); S5: Test data (t i , F(t i )) is fitted to determine the shape parameter β and scale parameter η of the Weibull distribution; S6: Complete the quantitative evaluation of the material's anti-cavitation performance by analyzing the evaluation model parameters.

2. The method for constructing a material anti-cavitation performance evaluation model according to claim 1, characterized in that: In S4, the cumulative weight loss percentage C i , and its calculation formula is: Where: Δm i is the time point t i Weight loss; Δm total is the total weight loss.

3. The method for constructing a material anti-cavitation performance evaluation model according to claim 1, characterized in that: In S4, the failure probability F(t i ), which is defined as: In cavitation tests, failure is defined as the material reaching a certain weight loss threshold; the failure probability F(t i ) indicates that at time t i The possibility of previous material failure.

4. The method for constructing a material anti-cavitation performance evaluation model according to claim 1, characterized in that: In S5, the Weibull distribution model is:

5. The method for constructing a material anti-cavitation performance evaluation model according to claim 1, characterized in that: S6 includes but is not limited to the following steps and methods: S601: Quantify the failure mode of the material: if β<1, it means that the material is prone to failure in the early stage; if β≈1, it means that the material failure is random; if β>1, it means that the material is more likely to fail in the later stage; S602: Quantifying material characteristic life: The larger the η is, the better the material's anti-cavitation performance is.

6. The method for constructing a material anti-cavitation performance evaluation model according to claim 1, characterized in that: The time point t i The unit is unified as "hour" and the mass measurement unit is unified as "milligram".

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