Structural strength performance evaluation method based on multistage virtual-real fusion

Abstract

The invention discloses a structural strength performance evaluation method based on multistage virtual-real fusion. The method comprises the following steps: acquiring digital simulation data, displacement measurement data, load measurement data and strain measurement data; based on the displacement measurement data, the load measurement data and the digital simulation data, establishing a displacement field twinborn evaluation model; establishing a strain field twinborn evaluation model based on the load measurement data, the strain measurement data and the digital simulation data; based on the displacement field twinborn evaluation model and the strain field twinborn evaluation model, obtaining a strain-displacement synchronous twinborn evaluation model; establishing an early warning analysis and evaluation model based on a strain-displacement synchronous twinborn evaluation model; according to the real-time strain and the real-time displacement, a load early-warning threshold value is analyzed and determined in real time in combination with an early-warning analysis and evaluation model. The problems that in the existing strength test process, the states of various parameters such as strain and displacement of the tested piece cannot be evaluated in real time, and real-time early warning analysis cannot be carried out when the test process is abnormal are solved.

Description

Technical Field

[0001] The present invention belongs to the technical field of load-bearing structure strength testing, and in particular relates to a structural strength performance evaluation method based on multi-level virtual-real fusion. Background Art

[0002] The strength test of load-bearing structures is an important mechanical environmental test in many industrial fields such as aviation, aerospace, military, vehicles, ships, and buildings to test the load-bearing capacity of structural products, verify the strength / rigidity of structures, evaluate the reliability of structures under various mechanical conditions, and evaluate their service quality. The test process usually requires a certain magnitude of mechanical load loading on the product according to the product application conditions to simulate its load-bearing state, and simultaneously measure various parameters such as stress, strain, and displacement of the loaded product to obtain the performance of various parameter data during the load-bearing process of the tested piece. The changes in various performance parameters of the structure under mechanical load directly determine the service reliability of the structure. Since the existing strength test detection data evaluation method mainly relies on the analysis of the order of magnitude, trend and other parameters of the measured data after the test, abnormal data results can often only be found after the test, and it is impossible to evaluate the status of each area of ​​the tested piece in real time. In addition, since the existing measurement method mainly relies on sensor array acquisition, data in some areas of the test piece cannot be effectively collected, the global coverage of the test parameters is limited, and abnormal states in some blind areas of the test process cannot be timely warned, and there is a problem of incomplete performance evaluation of the tested piece. Summary of the invention

[0003] The technology of the present invention solves the problem: Overcoming the shortcomings of the prior art, providing a structural strength performance evaluation method based on multi-level virtual-real fusion, aiming to solve the problem that the strain and displacement parameters of the tested piece cannot be evaluated in real time during the existing strength test, and the abnormality of the test process cannot be analyzed in real time.

[0004] In order to solve the above technical problems, the present invention discloses a structural strength performance evaluation method based on multi-level virtual-real fusion, comprising: According to the digital model and load conditions of the tested piece, digital simulation analysis is performed to obtain digital simulation data of the test piece; Acquire real physical measurement data during the strength test of the tested piece; wherein the real physical measurement data includes: displacement measurement data, load measurement data and strain measurement data; Based on the displacement measurement data and load measurement data, the digital simulation data is synchronously corrected to establish a displacement field twin evaluation model; Based on the load measurement data and strain measurement data, the digital simulation data is synchronously corrected to establish a strain field twin evaluation model; The displacement field twin assessment model is coupled with the strain field twin assessment model to obtain the strain-displacement synchronous twin assessment model. According to the strain warning threshold and displacement warning threshold preset in the test, combined with the strain-displacement synchronous twin assessment model, an early warning analysis and evaluation model is established; According to the real-time strain and real-time displacement, combined with the early warning analysis and evaluation model, the load early warning threshold is analyzed and determined in real time.

[0005] In the above-mentioned structural strength performance evaluation method based on multi-level virtual-real fusion, digital simulation analysis is performed according to the digital model and load conditions of the test piece to obtain digital simulation data of the test piece, including: Establish a three-dimensional digital model of the test piece; According to the three-dimensional digital model of the test piece and the boundary requirements of the test load conditions, a digital simulation model of the test piece is established; Based on the digital simulation model, digital simulation analysis is performed to obtain digital simulation data of the test piece.

[0006] In the above-mentioned structural strength performance evaluation method based on multi-level virtual-real fusion, the digital simulation data includes: displacement simulation data Y 0 and strain simulation data S 0 .

[0007] In the above-mentioned structural strength performance evaluation method based on multi-level virtual-real fusion,

[0008] Among them, F represents the digital simulation load condition force value, K represents the functional relationship between displacement and load condition force value, J represents the functional relationship between strain and load condition force value, G represents the structural stiffness, and E represents the elastic modulus of the material.

[0009] In the above-mentioned structural strength performance evaluation method based on multi-level virtual-real fusion, real physical measurement data is obtained during the strength test of the test piece, including: According to the test requirements, build a strength test system and install the displacement measurement system, load measurement system and strain measurement system; Based on the strength test system, the strength test is carried out on the tested piece, and the displacement measurement data Y is obtained by measuring the displacement measurement system, load measurement system and strain measurement system during the strength test. z , load measurement data F z and strain measurement data S z .

[0010] In the above-mentioned structural strength performance evaluation method based on multi-level virtual-real fusion, Y z =L(F z ), S z =M(F z ) Where L represents F z With Y z Functional relationship, M represents F z With S z The functional relationship of .

[0011] In the above-mentioned structural strength performance evaluation method based on multi-level virtual-real fusion, the digital simulation data is synchronously corrected based on the displacement measurement data and the load measurement data to establish a displacement field twin evaluation model, including: Determine the actual position P of each displacement measurement sensor in the displacement measurement system; According to the load measurement data F z and the actual position P of each displacement measurement sensor, and the corresponding F is obtained from the digital simulation data query z , P displacement simulation data Y 0 ; Use displacement measurement data Y z Displacement simulation data Y 0 Perform synchronous correction, and determine the displacement parameter correction function Δy according to the deviation of the corresponding load condition force value when each displacement measurement data is equal to the corresponding displacement simulation data: Y 0 =K(F z ), Δy=

[0012] in, s Indicates the weight of the measurement results of each displacement measuring point, and n indicates the number of measuring points; The displacement parameter correction function Δy is used as the correction value to correct and update the digital simulation model in real time to ensure that the displacement simulation data is consistent with the displacement measurement data, and the displacement field twin evaluation model Y is obtained. 1 : Y 1 ∈∑[K(Y z -Y 0 )+Δy]×α Where α represents the twin assessment displacement correction coefficient.

[0013] In the above-mentioned structural strength performance evaluation method based on multi-level virtual-real fusion, the digital simulation data is synchronously corrected based on the load measurement data and the strain measurement data to establish a strain field twin evaluation model, including: Determine the actual position Q of each strain measurement sensor in the strain measurement system; According to the load measurement data F z and the actual position Q of each strain measurement sensor, and the corresponding F is obtained from the digital simulation data. z , Q strain simulation data S 0 ; Using strain measurement data S z Corresponding strain simulation data S 0 Perform synchronous correction, and determine the strain parameter correction function Δs according to the deviation of the corresponding load condition force value when each strain measurement data is equal to the corresponding strain simulation data: S 0 =J(F z ), Δs=

[0014] in, c Indicates the weight of the measurement results of each strain measuring point; The strain parameter correction function Δs is used as the correction value to perform real-time correction and update of the digital simulation model to ensure that the strain simulation data is consistent with the strain measurement data, and the strain field twin evaluation model S is obtained. 1 : S 1 ∈∑[J(S z -S 0 )+Δs]×β Where β represents the twin assessment strain correction factor.

[0015] In the above-mentioned structural strength performance evaluation method based on multi-level virtual-real fusion, the displacement field twin evaluation model is coupled with the strain field twin evaluation model to obtain a strain-displacement synchronous twin evaluation model, including: According to the displacement field twin assessment model, the displacement trend of each area of ​​the tested piece is analyzed in real time to identify and determine the key area A; wherein the key area A refers to: the area of ​​maximum displacement data, and / or the area where the displacement and load condition force value change nonlinearly; Obtain the strain analysis data S corresponding to the key area A in the strain field twin assessment model A ; The strain analysis data S A As the input of the displacement field twin assessment model, the displacement field twin assessment model is modified and updated to obtain the strain-displacement synchronous twin assessment model YS 2 : YS 2 ∈[∑(∑(S A -pY 1 )×T)-Y z ]×δ Among them, p represents the mapping function of strain and displacement determined by digital simulation, T represents the correlation coefficient between the strain change gradient and the displacement change gradient, and δ represents the strain-displacement correction coefficient.

[0016] In the above-mentioned structural strength performance evaluation method based on multi-level virtual-real fusion, The identification and determination basis of key area A is as follows: MAX Y1 ||ΔY 1 / ΔF≠C Among them, ΔY 1 represents the displacement change, ΔF represents the load condition force change, and C represents a constant;

[0017] Among them, (x i ,y i ,z i ) represents the coordinates of the feature points within the typical feature radius near the key area A, S Ai It means (x i ,y i ,z i ) position.

[0018] The present invention has the following advantages: (1) The present invention discloses a structural strength performance evaluation method based on multi-level virtual-real fusion. Through multi-level twin evaluation, it can effectively and dynamically associate various measured data of the test process with digital simulation data in real time, realize synchronous evaluation and analysis, improve the accuracy of performance evaluation of the tested piece during the strength test, and solve the problem that the strain and displacement parameters of the tested piece cannot be evaluated in real time during the existing strength test, and the abnormality of the test process cannot be analyzed in real time.

[0019] (2) The present invention discloses a structural strength performance evaluation method based on multi-level virtual-real fusion, which associates the strain-load and displacement-load measured data with the digital simulation data, thereby realizing the preliminary correction of the digital simulation model; further, through the key area identification, the displacement field twin evaluation model is coupled with the strain field twin evaluation model to establish a strain-displacement synchronous twin evaluation model, refine the evaluation model, and achieve high consistency between the measured results and the digital simulation results.

[0020] (3) The present invention discloses a structural strength performance evaluation method based on multi-level virtual-real fusion. According to the strain warning threshold and displacement warning threshold preset in the test, combined with the strain-displacement synchronous twin evaluation model, a warning analysis and evaluation model is established. Based on the warning analysis and evaluation model, dynamic warning evaluation of the test process is realized, which solves the problem that the traditional fixed warning threshold cannot adapt to the dynamic changes of the test piece during the test process in real time.

[0021] (4) The present invention discloses a structural strength performance evaluation method based on multi-level virtual-real fusion, which is suitable for real-time high-precision twin evaluation of structural strength performance during strength tests of load-bearing structures such as large cabins, spacecraft payload platforms, load-bearing structures, and pressure vessels. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 It is a flow chart of a method for evaluating structural strength performance based on multi-level virtual-real fusion in an embodiment of the present invention. DETAILED DESCRIPTION

[0023] In order to make the objectives, technical solutions and advantages of the present invention more clear, the embodiments disclosed in the present invention will be further described in detail below with reference to the accompanying drawings.

[0024] Reference Figure 1 In this embodiment, the structural strength performance evaluation method based on multi-level virtual-real fusion includes: Step 1: Perform digital simulation analysis based on the digital model and load conditions of the test piece to obtain digital simulation data of the test piece.

[0025] In this embodiment, the digital simulation data of the test piece can be obtained by: Establish a three-dimensional digital model of the test piece.

[0026] According to the three-dimensional digital model of the test piece and the boundary requirements of the test load conditions, a digital simulation model of the test piece is established.

[0027] Based on the digital simulation model, digital simulation analysis is performed to obtain digital simulation data of the test piece. The digital simulation data includes but is not limited to: displacement simulation data Y 0 and strain simulation data S 0 :

[0028] Among them, F represents the force value of the digital simulation load condition; K represents the functional relationship between displacement and load condition force value; J represents the functional relationship between strain and load condition force value; G represents structural stiffness, which is related to the material properties and structural configuration of the test piece; E represents the elastic modulus of the material.

[0029] Step 2: Obtain the real physical measurement data during the strength test of the test piece.

[0030] In this embodiment, the real physical measurement data includes but is not limited to: displacement measurement data, load measurement data and strain measurement data.

[0031] The actual physical measurement data during the strength test of the test piece can be obtained in the following ways: According to the test requirements, a strength test system is built, and a displacement measurement system, a load measurement system and a strain measurement system are installed; based on the strength test system, a strength test is performed on the test piece, and during the strength test, the displacement measurement data Y is obtained by measuring the displacement measurement system, the load measurement system and the strain measurement system. z , load measurement data Fz and strain measurement data S z : Y z =L(F z ), S z =M(F z ) Where L represents F z With Y z Functional relationship, M represents F z With S z The functional relationship of .

[0032] Step 3: Synchronously correct the digital simulation data based on the displacement measurement data and load measurement data to establish a displacement field twin evaluation model.

[0033] In this embodiment, the displacement field twin evaluation model can be established in the following manner: Determine the actual position P of each displacement measurement sensor in the displacement measurement system.

[0034] According to the load measurement data F z and the actual position P of each displacement measurement sensor, and the corresponding F is obtained from the digital simulation data query z , P displacement simulation data Y 0 .

[0035] Use displacement measurement data Y z Displacement simulation data Y 0 Perform synchronous correction, and determine the displacement parameter correction function Δy according to the deviation of the corresponding load condition force value when each displacement measurement data is equal to the corresponding displacement simulation data: Y 0 =K(F z ), Δy=

[0036] in, s It represents the weight of the measurement results of each displacement measuring point, which is related to the structural configuration, material properties and displacement data of the tested object; n represents the number of measuring points.

[0037] The displacement parameter correction function Δy is used as the correction value to correct and update the digital simulation model in real time to ensure that the displacement simulation data is consistent with the displacement measurement data, and the displacement field twin evaluation model Y is obtained. 1 : Y 1 ∈∑[K(Y z -Y 0 )+Δy]×α Among them, α represents the twin assessment displacement correction coefficient, which is related to the change gradient of the displacement and local force value at the corresponding measurement position.

[0038] Step 4: Synchronously correct the digital simulation data based on the load measurement data and strain measurement data to establish a strain field twin evaluation model.

[0039] In this embodiment, the strain field twin evaluation model can be established in the following manner: Determine the actual position Q of each strain measurement sensor in the strain measurement system.

[0040] According to the load measurement data F z and the actual position Q of each strain measurement sensor, and the corresponding F is obtained from the digital simulation data. z , Q strain simulation data S 0 .

[0041] Using strain measurement data S z Corresponding strain simulation data S 0 Perform synchronous correction, and determine the strain parameter correction function Δs according to the deviation of the corresponding load condition force value when each strain measurement data is equal to the corresponding strain simulation data: S 0 =J(F z ), Δs=

[0042] in, c It represents the weight of the measurement results of each strain measuring point, which is related to the structural residual stress distribution, material properties and the size of the strain data corresponding to the measuring point.

[0043] The strain parameter correction function Δs is used as the correction value to perform real-time correction and update of the digital simulation model to ensure that the strain simulation data is consistent with the strain measurement data, and the strain field twin evaluation model S is obtained. 1 : S 1 ∈∑[J(S z -S 0 )+Δs]×β Among them, β represents the twin assessment strain correction coefficient, which is related to the change gradient of the strain and local force value at the corresponding measurement position.

[0044] Step 5: Couple the displacement field twin assessment model with the strain field twin assessment model to obtain a strain-displacement synchronous twin assessment model.

[0045] In this embodiment, the displacement field twin assessment model is coupled with the strain field twin assessment model, and the key area A with abnormal displacement change is identified according to the mapping analysis results of the displacement field twin assessment model. The twin models are further corrected synchronously through the strain field twin assessment model, thereby achieving a zero-deviation and accurate prediction of the actual state of the test and the twin analysis results, improving the evaluation accuracy, and forming a strain-displacement synchronous twin assessment model. The specific implementation method is as follows: According to the displacement field twin evaluation model, the displacement trend of each area of ​​the tested piece is analyzed in real time to identify and determine the key area A. Among them, the key area A refers to: the maximum displacement data area, and / or the area where the displacement and load condition force value change nonlinearly; the identification and determination basis of the key area A is as follows: MAX Y 1 ||ΔY 1 / ΔF≠C Among them, ΔY 1 represents the displacement change, ΔF represents the load condition force change, and C represents a constant.

[0046] Obtain the strain analysis data S corresponding to the key area A in the strain field twin assessment model A :

[0047] Among them, (x i ,y i ,z i ) represents the coordinates of the characteristic points within the typical characteristic radius (usually 3% of the geometric size of the test piece or 10 times the size of the strain measurement sensor) near the critical area A, S Ai It means (x i ,y i ,z i ) position.

[0048] The strain analysis data S A As the input of the displacement field twin evaluation model (i.e., directly referencing S in the digital simulation process of the key area A) A , further refine the digital simulation model of the key area A), modify and update the displacement field twin evaluation model, and obtain the strain-displacement synchronous twin evaluation model YS 2 : YS 2 ∈[∑(∑(S A -pY 1 )×T)-Y z ]×δ Where p represents the mapping function of strain and displacement determined by digital simulation, T represents the correlation coefficient between the strain change gradient and the displacement change gradient; δ represents the strain-displacement correction coefficient, which is related to the distribution of strain and displacement measurement data of the test piece and the configuration and material of the test piece.

[0049] Step 6: Based on the strain warning threshold and displacement warning threshold preset in the experiment, combined with the strain-displacement synchronous twin assessment model, establish a warning analysis and evaluation model.

[0050] Step 7: Analyze and determine the load warning threshold in real time based on the real-time strain and real-time displacement in combination with the early warning analysis and evaluation model.

[0051] Although the present invention has been disclosed as above in the form of a preferred embodiment, it is not intended to limit the present invention. Any person skilled in the art may make possible changes and modifications to the technical solution of the present invention by using the methods and technical contents disclosed above without departing from the spirit and scope of the present invention. Therefore, any simple modifications, equivalent changes and modifications made to the above embodiments based on the technical essence of the present invention without departing from the content of the technical solution of the present invention shall fall within the protection scope of the technical solution of the present invention.

[0052] The contents not described in detail in the specification of the present invention belong to the common knowledge of the professionals in this field.

Claims

1. A structural strength performance evaluation method based on multi-level virtual-real fusion, characterized in that: include: According to the digital model and load conditions of the tested piece, digital simulation analysis is performed to obtain digital simulation data of the test piece; Acquire real physical measurement data during the strength test of the tested piece; wherein the real physical measurement data includes: displacement measurement data, load measurement data and strain measurement data; Based on the displacement measurement data and load measurement data, the digital simulation data is synchronously corrected to establish a displacement field twin evaluation model; Based on the load measurement data and strain measurement data, the digital simulation data is synchronously corrected to establish a strain field twin evaluation model; The displacement field twin assessment model is coupled with the strain field twin assessment model to obtain the strain-displacement synchronous twin assessment model. According to the strain warning threshold and displacement warning threshold preset in the test, combined with the strain-displacement synchronous twin assessment model, an early warning analysis and evaluation model is established; According to the real-time strain and real-time displacement, combined with the early warning analysis and evaluation model, the load early warning threshold is analyzed and determined in real time.

2. The structural strength performance evaluation method based on multi-level virtual-real fusion according to claim 1 is characterized in that: According to the digital model and load conditions of the test piece, digital simulation analysis is performed to obtain the digital simulation data of the test piece, including: Establish a three-dimensional digital model of the test piece; According to the three-dimensional digital model of the test piece and the boundary requirements of the test load conditions, a digital simulation model of the test piece is established; Based on the digital simulation model, digital simulation analysis is performed to obtain digital simulation data of the test piece.

3. The structural strength performance evaluation method based on multi-level virtual-real fusion according to claim 2 is characterized in that: The digital simulation data includes displacement simulation data Y0 and strain simulation data S0.

4. The structural strength performance evaluation method based on multi-level virtual-real fusion according to claim 3 is characterized in that: Among them, F represents the digital simulation load condition force value, K represents the functional relationship between displacement and load condition force value, J represents the functional relationship between strain and load condition force value, G represents the structural stiffness, and E represents the elastic modulus of the material.

5. The structural strength performance evaluation method based on multi-level virtual-real fusion according to claim 4 is characterized in that: Obtain real physical measurement data during the strength test of the test piece, including: According to the test requirements, build a strength test system and install the displacement measurement system, load measurement system and strain measurement system; Based on the strength test system, the strength test is carried out on the tested piece, and the displacement measurement data Y is obtained by measuring the displacement measurement system, load measurement system and strain measurement system during the strength test. z , load measurement data F z and strain measurement data S z .

6. The structural strength performance evaluation method based on multi-level virtual-real fusion according to claim 5 is characterized in that: Y z =L(F z ),S z =M(F z ) Where L represents F z With Y z Functional relationship, M represents F z With S z The functional relationship of .

7. The structural strength performance evaluation method based on multi-level virtual-real fusion according to claim 6 is characterized in that: Based on the displacement measurement data and load measurement data, the digital simulation data is synchronously corrected to establish a displacement field twin evaluation model, including: Determine the actual position P of each displacement measurement sensor in the displacement measurement system; According to the load measurement data F z and the actual position P of each displacement measurement sensor, and the corresponding F is obtained from the digital simulation data query z , P's displacement simulation data Y0; Use displacement measurement data Y z The displacement simulation data Y0 is corrected synchronously, and the displacement parameter correction function Δy is determined according to the deviation of the corresponding load condition force value when each displacement measurement data is equal to the corresponding displacement simulation data: Y0=K(F z ),Δy= in, σ Indicates the weight of the measurement results of each displacement measuring point, and n indicates the number of measuring points; The displacement parameter correction function Δy is used as the correction value to correct and update the digital simulation model in real time to ensure that the displacement simulation data is consistent with the displacement measurement data, and the displacement field twin evaluation model Y1 is obtained: Y1∈∑[K(Y z -Y0)+Δy]×α Where α represents the twin assessment displacement correction coefficient.

8. The structural strength performance evaluation method based on multi-level virtual-real fusion according to claim 7 is characterized in that: Based on the load measurement data and strain measurement data, the digital simulation data is synchronously corrected to establish a strain field twin evaluation model, including: Determine the actual position Q of each strain measurement sensor in the strain measurement system; According to the load measurement data F z and the actual position Q of each strain measurement sensor, and the corresponding F is obtained from the digital simulation data. z , Q's strain simulation data S0; Using strain measurement data S z The strain simulation data S0 is corrected synchronously, and the strain parameter correction function Δs is determined according to the deviation of the corresponding load condition force value when each strain measurement data is equal to the corresponding strain simulation data: S0=J(F z ),Δs= in, γ Indicates the weight of the measurement results of each strain measuring point; The strain parameter correction function Δs is used as the correction value to correct and update the digital simulation model in real time to ensure that the strain simulation data is consistent with the strain measurement data, and the strain field twin evaluation model S1 is obtained: S1∈∑[J(S z -S0)+Δs]×β Where β represents the twin assessment strain correction factor.

9. The structural strength performance evaluation method based on multi-level virtual-real fusion according to claim 8 is characterized in that: The displacement field twin assessment model is coupled with the strain field twin assessment model to obtain the strain-displacement synchronous twin assessment model, which includes: According to the displacement field twin assessment model, the displacement trend of each area of ​​the tested piece is analyzed in real time to identify and determine the key area A; wherein the key area A refers to: the area of ​​maximum displacement data, and / or the area where the displacement and load condition force value change nonlinearly; Obtain the strain analysis data S corresponding to the key area A in the strain field twin assessment model A ; The strain analysis data S A As the input of the displacement field twin assessment model, the displacement field twin assessment model is corrected and updated to obtain the strain-displacement synchronous twin assessment model YS2: YS2∈[∑(∑(S A -pY1)×T)-Y z ]×δ Among them, p represents the mapping function of strain and displacement determined by digital simulation, T represents the correlation coefficient between the strain change gradient and the displacement change gradient, and δ represents the strain-displacement correction coefficient.

10. The structural strength performance evaluation method based on multi-level virtual-real fusion according to claim 8 is characterized in that: The identification and determination basis of key area A is as follows: MAX Y1||ΔY1 / ΔF≠C Among them, ΔY1 represents the displacement change, ΔF represents the load condition force change, and C represents a constant; Among them, (x i ,y i ,z i ) represents the coordinates of the feature points within the typical feature radius near the key area A, S Ai It means (x i ,y i ,z i ) position.

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