CN111581737B - Finite element simulation-based structural member reliability assessment method and system - Google Patents

Finite element simulation-based structural member reliability assessment method and system Download PDF

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CN111581737B
CN111581737B CN202010259555.3A CN202010259555A CN111581737B CN 111581737 B CN111581737 B CN 111581737B CN 202010259555 A CN202010259555 A CN 202010259555A CN 111581737 B CN111581737 B CN 111581737B
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田富君
张红旗
陈兴玉
周红桥
郭磊
周金文
陈亮希
魏一雄
张燕龙
苏建军
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Abstract

The invention discloses a method and a system for evaluating the reliability of a structural member based on finite element simulation, which belong to the technical field of product reliability simulation tests and comprise the following steps: s1: constructing a structural part model; s2: determining simulation environment parameters; s3: carrying out finite element simulation; s4: determining fault data characteristics of the structural member; s5: constructing a reliability analysis model; s6: evaluating the reliability of the structural part; s7: determining the reliability under a given threshold; s8: and judging whether the analysis result meets the expectation. In step S1, the digital prototype model refers to a two-dimensional or three-dimensional digital prototype model. In step S2, the preliminary determination of the environmental parameters and the loading conditions of the simulation process includes determining the distribution type to which the environmental parameters comply, determining specific parameter values, and determining the loading conditions. The invention can expose the design defect of the structural member as soon as possible, reduce the reliability test time of the structural member, improve the reliability evaluation efficiency, shorten the product development period and reduce the development cost.

Description

Finite element simulation-based structural member reliability assessment method and system
Technical Field
The invention relates to the technical field of product reliability simulation tests, in particular to a structural member reliability evaluation method based on finite element simulation.
Background
With the continuous progress of science and technology, engineering equipment such as wind turbines, numerical control machines, engineering machinery and the like gradually develops to flexibility, precision and intelligence. Once a fault or deterioration of health status occurs in such a complex equipment system, huge economic loss or even catastrophic consequences are often brought to users or related enterprises.
Thus, in the face of increasingly demanding customer requirements and market competition, developers are investing more and more effort and cost to improve product reliability while meeting product functional/performance design. However, highly reliable products cannot be obtained by the air, which is determined by the design stage and guaranteed by the manufacturing technique and scientific management. The traditional product design is based on manual work and adopts safety factors to determine a design scheme, potential defects are difficult to find and improve in the design stage, and the problem is almost solved by means of 'after-the-fact verification'. The data show that: a design deficiency, exposed and resolved by post-testing or user feedback, requiring at least 10 times more cost; meanwhile, long-time test verification is needed to draw a conclusion, the test efficiency is low, the development period of a product is long, and the problems need to be solved urgently, so that a structural part reliability evaluation method and system based on finite element simulation are provided.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: how to expose the design defects of the product as soon as possible, reduce the time of the reliability test of the product, improve the efficiency of the reliability test, shorten the development period, reduce the development cost and provide a structural member reliability evaluation method based on finite element simulation.
The invention solves the technical problems through the following technical scheme, and comprises the following steps:
s1: building a structural part model
Constructing a digital prototype model of the structural part;
s2: determining simulation environment parameters
Preliminarily determining environmental parameters and load conditions of the simulation process;
s3: performing finite element simulation
Inputting a digital prototype model of the structural part and the determined simulation environment parameters, and performing finite element simulation;
s4: determining fault data characteristics of a structural component
Determining the potential failure position of the structural member, failure modules, failure threshold values thereof and other failure data characteristics according to the environmental parameters borne by the structural member and by combining the failure mode, the influence and hazard analysis report and the finite element analysis data of the structural member;
s5: building reliability analysis model
Selecting a distribution function model according to finite element simulation data of the potential fault part (the failure module in the step S4) and a failure mechanism of the potential fault part, estimating parameters of the distribution function such as position parameters, scale parameters and proportion parameters according to the data sample and the distribution model, and determining a reliability analysis model of the structural part based on the distribution function;
s6: assessing structural member reliability
Evaluating the reliability of the structural member by using the reliability and fault probability density functions, and defining the reliability of the structural member as follows:
R(S)＝P{S≥s}
wherein S is a failure threshold value of a certain physical quantity of the system, S is an actual value of the physical quantity in the simulation process, S is more than or equal to 0, and S is more than or equal to 0; r (S) ≥ 0, R (0) =0,
Figure BDA0002438787790000021
given a failure threshold S, the reliability of the system can be represented by the probability that the actual value S is less than or equal to S;
s7: determining reliability at a given threshold
For a given failure threshold S, the N discrete sample (or cell) reliabilities may be calculated by the following equation:
Figure BDA0002438787790000022
Figure BDA0002438787790000023
Figure BDA0002438787790000024
wherein s is i Is the actual value of the physical quantity in the simulation of the ith sample (or cell), I (S, S) i ) For the indicator function of the ith sample (or cell), which indicates whether the sample (or cell) meets the threshold requirement, determining the reliability size by counting the number of samples (or cells) meeting the threshold requirement;
s8: judging whether the analysis result meets the expectation
Comparing the calculated reliability with the expected reliability, and outputting a digital prototype model if the expected reliability is reached; if the expected reliability is not reached, the structural part needs to be redesigned, the reliability is improved, and then the steps S3 to S8 are repeated until the expected reliability is reached.
Further, in the step S1, the digital prototype model refers to a two-dimensional or three-dimensional digital prototype model.
Further, in step S2, the environmental parameters and the loading conditions of the simulation process are preliminarily determined, specifically including the distribution type, the distribution function location parameter, the proportion parameter, the scale parameter, and the loading threshold value to which the environmental parameters comply.
Further, in the reliability engineering, the distribution types to which the environmental parameters are subjected include exponential distribution, weibull distribution, normal logarithmic distribution, and the like, and the determining the load conditions includes determining the environmental load and the workload.
Further, in step S4, fault data characteristics of the structural component, such as a range, an extreme point, a mean value, a variance, a kurtosis, and the like of each fault data are determined.
Further, in the step S5, a manner of estimating the parameter of the distribution function is any one of a moment estimation method, a maximum likelihood estimation method, a least square method, and the like.
Further, in step S6, the reliability refers to the probability that the structure or the system will complete its specified function in a specified time and under specified conditions, and the definition domain is [0,1]; after a system or a structural member is just used or completely repaired, the reliability of the system or the structural member is 1, the system or the structural member can completely and normally work, the reliability gradually decreases along with the increase of time until the reliability is 0, and the system or the structural member fails or breaks down; the fault probability density function is the probability of a fault occurring in the remaining samples in the next unit time at any time.
Furthermore, in step S8, the method for completing the structural part design again and improving the reliability thereof is any one of a digital prototype redesign method, an environmental parameter redetermination method, and the like.
The invention also provides a structural member reliability evaluation system based on finite element simulation, which comprises the following steps:
the digital prototype model construction module is used for constructing a digital prototype model of the structural part;
the environment parameter setting module is used for preliminarily determining environment parameters and load conditions of the simulation process;
the finite element simulation module is used for carrying out finite element simulation by utilizing the digital prototype model of the input structural part and the determined simulation environment parameters;
the fault data characteristic determination module is used for determining a potential failure position, a failure module and a failure threshold value of the structural member according to the environmental parameters borne by the structural member by combining the fault mode, the influence and hazard analysis report and the finite element analysis data of the structural member;
the reliability analysis model building module is used for selecting a distribution function model according to finite element simulation data of the potential fault part and the failure mechanism of the potential fault part, estimating parameters of the distribution function according to the data sample and the distribution model, and further determining a reliability analysis model of the structural part;
the reliability evaluation module is used for evaluating the reliability of the structural component by using the reliability and the fault probability density function;
the reliability calculation module is used for calculating the reliability of the structural member by combining a fault probability density function f (S) with a given failure threshold value S in combination with the reliability analysis model;
the analysis result comparison module is used for comparing the reliability obtained by calculation with the expected reliability and executing the established steps according to the comparison result;
the central processing module is used for sending instructions to other modules to complete related actions;
the digital prototype model building module, the environment parameter setting module, the finite element simulation module, the fault data characteristic determining module, the reliability analysis model building module, the reliability evaluation module, the reliability calculation module and the analysis result comparison module are all electrically connected with the central processing module.
Compared with the prior art, the invention has the following advantages: the structural member reliability assessment method based on finite element simulation can expose structural member design defects as soon as possible, reduce structural member reliability test time, improve reliability assessment efficiency, shorten product development period, reduce development cost, and is worthy of popularization and use.
Drawings
FIG. 1 is a schematic general flow chart of a simulation test method for reliability of a structural member according to a second embodiment of the present invention
FIG. 2 is a schematic diagram of a finite element simulation according to a second embodiment of the present invention;
FIG. 3 is a simulated cloud based on stress-strain after finite element simulation in the second embodiment of the present invention;
FIG. 4 is a simulated cloud based on displacement deformation after being simulated by finite elements in the second embodiment of the present invention;
FIG. 5 is a distribution diagram based on the total displacement according to the second embodiment of the present invention;
fig. 6 is a diagram illustrating a reliability function curve based on the total displacement according to a second embodiment of the present invention.
Detailed Description
The following examples are given for the detailed implementation and specific operation of the present invention, but the scope of the present invention is not limited to the following examples.
Example one
The embodiment provides a technical scheme: a structural member reliability assessment method based on finite element simulation comprises the following steps:
s1: building structural member model
And constructing a digital prototype model of the structural member.
S2: determining simulation environment parameters
And preliminarily determining environmental parameters and load conditions of the simulation process.
S3: performing finite element simulation
Inputting the digital prototype model of the structural part and the determined simulation environment parameters, and performing finite element simulation.
S4: determining fault data characteristics of a structural member
And determining the potential failure position, the failure module, the failure threshold value and other failure data characteristics of the structural member according to the environmental parameters borne by the structural member and by combining the failure mode, the influence and hazard analysis report and the finite element analysis data of the structural member.
S5: building reliability analysis model
Selecting a distribution function model according to finite element simulation data of the potential fault part (namely the failure module in the step S4) and a failure mechanism of the potential fault part, estimating parameters (position parameters, proportion parameters and scale parameters) of the distribution function according to the data sample and the distribution model, and determining a reliability analysis model of the structural part based on the distribution function.
It should be noted that the failure mechanism of this embodiment is that a certain part may deform when subjected to a load, and when the load is large enough, the deformation will reach the maximum allowable limit value, and at this time, it may be determined that it is about to fail; furthermore, residual stresses occur in the parts under load, and engineering considerations dictate that they fail when they exceed the yield limit.
S6: assessing structural member reliability
And evaluating the reliability of the structural member by using the reliability and the fault probability density function, and defining the reliability of the structural member as follows:
R(S)＝P{S≥s}
wherein S is a failure threshold value of a certain physical quantity of the system, S is an actual value of the physical quantity in the simulation process, S is more than or equal to 0, and S is more than or equal to 0; r (S) ≥ 0, R (0) =0,
Figure BDA0002438787790000051
given a failure threshold S, the reliability of the system can be characterized by the magnitude of the probability that the actual value S is less than or equal to S.
S7: determining reliability at a given threshold
For a given failure threshold S, the N discrete sample (or cell) reliabilities may be calculated by the following equation:
Figure BDA0002438787790000052
Figure BDA0002438787790000054
Figure BDA0002438787790000053
wherein s is i Is the actual value of the physical quantity in the simulation of the ith sample (or cell), I (S, S) i ) For the indicator function of the ith sample (or cell), which indicates whether the sample (or cell) meets the threshold requirement, the reliability size is determined by the number of statistical samples (or cells) that meet the threshold requirement.
S8: judging whether the analysis result is in accordance with the expectation
Comparing the calculated reliability with an expected reliability, and outputting a digital prototype model if the expected reliability is reached; and if the expected reliability is not reached, redesigning the structural part and improving the reliability, and then repeating the steps S3 to S8 until the expected reliability is reached.
In step S1, the digital prototype model refers to a two-dimensional or three-dimensional digital prototype model.
In step S2, the environmental parameters or the loading conditions of the simulation process are preliminarily determined, which specifically include the distribution type, the distribution function location parameter, the proportion parameter, the scale parameter, and the loading threshold value to which the environmental parameters comply.
In reliability engineering, the distribution types to which the environmental parameters are subjected comprise exponential distribution, weibull distribution, normal logarithmic distribution and the like, and the determination of the load conditions comprises the determination of environmental loads and working loads.
In step S4, fault data characteristics of the structural component, such as a range, an extreme point, a mean value, a variance, a kurtosis, and the like of each fault data are determined.
In step S5, the method of estimating the parameters of the distribution function is any one of a moment estimation method, a maximum likelihood estimation method, a least square method, and the like.
In step S6, the reliability refers to the probability that the structure or system will complete its specified function in a specified time and under specified conditions, and is defined as [0,1]; after a system or a structural member is just used or completely repaired, the reliability of the system or the structural member is 1, the system or the structural member can completely and normally work, the reliability gradually decreases along with the increase of time until the reliability is 0, and the system or the structural member fails or breaks down; the failure probability density function is the probability of failure occurring in the remaining samples in the next unit time at any time.
In step S8, the method for completing the structural part design again and improving the reliability thereof is any one of a digital prototype redesign method, an environmental parameter redetermination method, and the like. The digital prototype redesign method is a product prototype redesign method, and the environment parameter redetermining method needs to re-assume the use environment so as to determine new environment parameters.
The embodiment further provides a structural member reliability evaluation system based on finite element simulation, which includes:
the digital prototype model construction module is used for constructing a digital prototype model of the structural part;
the environment parameter setting module is used for preliminarily determining environment parameters and load conditions of the simulation process;
the finite element simulation module is used for carrying out finite element simulation by utilizing the digital prototype model of the input structural part and the determined simulation environment parameters;
the fault data characteristic determination module is used for determining a potential failure position, a failure module and a failure threshold value of the structural member according to the environmental parameters borne by the structural member by combining the fault mode, the influence and hazard analysis report and the finite element analysis data of the structural member;
the reliability analysis model building module is used for selecting a distribution function model according to finite element simulation data of the potential fault part and the failure mechanism of the potential fault part, estimating parameters of the distribution function according to the data sample and the distribution model, and further determining a reliability analysis model of the structural part;
the reliability evaluation module is used for evaluating the reliability of the structural member by utilizing the reliability and the fault probability density function;
the reliability calculation module is used for calculating the reliability of the structural member by combining a fault probability density function f (S) with a given failure threshold value S in combination with the reliability analysis model;
the analysis result comparison module is used for comparing the reliability obtained by calculation with the expected reliability and executing the established steps according to the comparison result;
the central processing module is used for sending instructions to other modules to complete related actions;
the digital prototype model building module, the environment parameter setting module, the finite element simulation module, the fault data characteristic determining module, the reliability analysis model building module, the reliability evaluation module, the reliability calculation module and the analysis result comparison module are all electrically connected with the central processing module.
Example two
As shown in fig. 1, the present embodiment provides a structural member reliability analysis method based on finite element simulation, where the structural member reliability simulation test includes the following steps:
1) And constructing a digital prototype model of the structural part, wherein the digital prototype model refers to a two-dimensional or three-dimensional digital prototype model, and the structural part adopts a certain radar structural part in the embodiment.
2) And preliminarily determining simulated environment parameters and the like, and generating random environment parameters by adopting normal distribution aiming at the simulation of a certain radar structural member in the gravity acceleration environment, wherein the normal distribution parameters are shown in a table 1.
Table 1 environment parameter setting table in the present embodiment
Figure BDA0002438787790000071
3) Inputting a digital prototype model, environmental parameters and the like, starting finite element simulation, as shown in figure 2, wherein the simulation software is ABAQUS, and the specific simulation implementation flow is shown in figure 2.
4) Analyzing the simulation data of the structural part and determining the fault data characteristics of the structural part
The output finite element simulation is based on simulated cloud pictures of stress strain and displacement deformation, as shown in fig. 3 and 4. And determining the potential failure position, the failure module, the failure threshold value and the like of the structural member according to the environmental parameters borne by the structural member by combining the failure mode, the influence and hazard analysis report and the finite element analysis data of the structural member. The fault data characteristic determination method is based on a data analysis technology and is used for determining the range, distribution and the like of fault data; the total displacement is taken as an example, as shown in fig. 5.
5) Determining finite element simulation data of the structural part for reliability analysis, and constructing a reliability analysis model
Selecting a suitably distributed function model; exponential distribution, weibull distribution, normal logarithmic distribution and the like are commonly distributed in reliability engineering;
estimating parameters of the distribution function according to the data samples and the distribution model; the precision of parameter estimation depends on the integrity of sample data and the adopted algorithm, and commonly used estimation algorithms include a moment estimation method, a maximum likelihood estimation method, a least square method and the like.
6) And evaluating reliability of structural member
Determining a reliability function and drawing an image based on the distribution model and the parameter estimation result; fig. 6 is a reliability image based on the total displacement amount, which has a close relationship with the reliability of the component.
7) Determining the reliability under the possible threshold value by combining a reliability analysis model
In this embodiment, when the threshold value of the total displacement amount is 1.0X 10-4mm, the reliability of the component is 98.21%, which meets the expected requirement.
To sum up, the structural member reliability evaluation method based on finite element simulation of the two groups of embodiments can expose structural member design defects as soon as possible, reduce structural member reliability test time, improve reliability evaluation efficiency, shorten product development period, reduce development cost, and is worth being popularized and used.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of the feature. In the description of the present invention, "a plurality" means at least two, e.g., two, three, etc., unless explicitly specified otherwise.
In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention, and that variations, modifications, substitutions and alterations can be made to the above embodiments by those of ordinary skill in the art within the scope of the present invention.

Claims (9)

1. A structural member reliability evaluation method based on finite element simulation is characterized by comprising the following steps:
s1: building structural member model
Constructing a digital prototype model of the structural member;
s2: determining simulation environment parameters
Preliminarily determining environmental parameters and load conditions of the simulation process;
s3: performing finite element simulation
Inputting a digital prototype model of the structural part and the determined simulation environment parameters, and performing finite element simulation;
s4: determining fault data characteristics of a structural member
Determining a potential failure position, a failure module and a failure threshold value of the structural member according to the environmental parameters borne by the structural member by combining the failure mode, the influence and hazard analysis report and the finite element analysis data of the structural member;
s5: building reliability analysis model
Selecting a distribution function model according to the finite element simulation data of the failure module and the failure mechanism of the failure module in the step S4, estimating parameters of the distribution function according to the data sample and the distribution model, and determining a reliability analysis model of the structural member based on the distribution function;
s6: assessing structural member reliability
Evaluating the reliability of the structural member by using the reliability and fault probability density functions, and defining the reliability of the structural member as follows:
R(S)＝P{S≥s}
wherein S is a failure threshold value of a certain physical quantity of the system, S is an actual value of the physical quantity in the simulation process, S is more than or equal to 0, and S is more than or equal to 0;R(S)≥0，R(0)＝0，
Figure FDA0002438787780000011
given a failure threshold S, the reliability of the system can be represented by the probability that the actual value S is less than or equal to S;
s7: determining reliability at a given threshold
For a given failure threshold S, the N discrete sample reliabilities are calculated by the following equation:
Figure FDA0002438787780000012
Figure FDA0002438787780000013
Figure FDA0002438787780000014
wherein s is i Is the actual value of the physical quantity in the simulation of the ith sample, I (S, S) i ) The reliability is determined by the number of statistical samples meeting the threshold requirement for an indicator function of the ith sample, wherein the indicator function is used for indicating whether the sample meets the threshold requirement;
s8: judging whether the analysis result meets the expectation
Comparing the calculated reliability with the expected reliability, and outputting a digital prototype model if the expected reliability is reached; and if the expected reliability is not reached, redesigning the structural part and improving the reliability, and then repeating the steps S3 to S8 until the expected reliability is reached.
2. The finite element simulation-based structural member reliability evaluation method according to claim 1, wherein: in step S1, the digital prototype model refers to a two-dimensional or three-dimensional digital prototype model.
3. The finite element simulation-based structural member reliability evaluation method according to claim 1, wherein: in the step S2, the environmental parameters and the loading conditions of the simulation process are preliminarily determined, and specifically include distribution types, distribution function position parameters, proportion parameters, scale parameters and loading thresholds to which the environmental parameters comply.
4. The finite element simulation-based structural member reliability evaluation method according to claim 3, wherein: in reliability engineering, the distribution types to which the environmental parameters are subjected include exponential distribution, weibull distribution, normal distribution and normal logarithmic distribution, and the determining the load conditions includes determining the environmental load and the working load.
5. The finite element simulation-based structural member reliability evaluation method according to claim 1, wherein: in step S4, the fault data characteristics of the structural component are determined, including the range, the extreme point, the mean, the variance, and the kurtosis of each fault data.
6. The finite element simulation-based structural member reliability evaluation method according to claim 1, wherein: in step S5, the method of estimating the parameter of the distribution function is any one of a moment estimation method, a maximum likelihood estimation method, and a least square method.
7. The finite element simulation-based structural member reliability evaluation method according to claim 1, wherein: in step S6, the reliability refers to the probability that the structure or system will complete its specified function in a specified time and under specified conditions, and is defined as [0,1]; after a system or a structural member is just used or completely repaired, the reliability of the system or the structural member is 1, the system or the structural member can completely and normally work, the reliability gradually decreases along with the increase of time until the reliability is 0, and the system or the structural member fails or breaks down; the fault probability density function is the probability of a fault occurring in the remaining samples in the next unit time at any time.
8. The finite element simulation-based structural member reliability evaluation method according to claim 1, wherein: in step S8, the method for completing the structural part design again and improving the reliability thereof is a digital prototype redesign method or an environmental parameter redetermination method.
9. A structural member reliability evaluation system based on finite element simulation is characterized in that: the structural member reliability evaluation method according to any one of claims 1 to 8, which evaluates reliability of a structural member, comprising:
the digital prototype model building module is used for building a digital prototype model of the structural part;
the environment parameter setting module is used for preliminarily determining environment parameters and load conditions of the simulation process;
the finite element simulation module is used for carrying out finite element simulation by utilizing the digital prototype model of the input structural part and the determined simulation environment parameters;
the fault data characteristic determination module is used for determining a potential failure position, a failure module and a failure threshold value of the structural member according to the environmental parameters borne by the structural member by combining the fault mode, the influence and hazard analysis report and the finite element analysis data of the structural member;
the reliability analysis model building module is used for selecting a distribution function model according to the finite element simulation data of the failure module and the failure mechanism of the failure module, estimating the parameters of the distribution function according to the data sample and the distribution model, and further determining the reliability analysis model of the structural member;
the reliability evaluation module is used for evaluating the reliability of the structural member by utilizing the reliability and the fault probability density function;
the reliability calculation module is used for combining the reliability analysis model and calculating the reliability of the structural member by combining a fault probability density function f (S) with a given failure threshold value S;
the analysis result comparison module is used for comparing the calculated reliability with the expected reliability and executing the established steps according to the comparison result;
the central processing module is used for sending instructions to other modules to complete related actions;
the digital prototype model building module, the environment parameter setting module, the finite element simulation module, the fault data characteristic determining module, the reliability analysis model building module, the reliability evaluation module, the reliability calculation module and the analysis result comparison module are all electrically connected with the central processing module.
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