CN107506552A - Analysis method for reliability and system based on sensitivity test - Google Patents
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Abstract
The disclosure provides a kind of analysis method for reliability and system based on sensitivity test, and this method includes：Multiple input variables are determined according to the position of a mechanism part in preset model, and sensitivity test is carried out to the input variable；The sensitivity index that output of each input variable to the preset model responds is determined, and target input variable is determined according to the sensitivity index；Fail-safe analysis is carried out to the position of the mechanism part in the preset model based on the target input variable.The disclosure by sensitivity test, can reduce the dimension of input variable and improve fail-safe analysis efficiency.
Description
Technical Field
The present disclosure relates to the field of structural optimization design technologies, and in particular, to a reliability analysis method based on a sensitivity test and a reliability analysis system based on a sensitivity test.
Background
The aviation hydraulic circuit generally operates in a random vibration environment due to fuselage vibrations caused by engine vibrations and wing flutters, which is one of the main causes of sudden rupture of the aviation hydraulic circuit. To reduce the probability of rupture and improve the safety of an aircraft hydraulic line, it is generally necessary to provide a series of support restraining members on its system to reduce vibration of the line system. Therefore, the quality of the supporting position directly affects the safety of the hydraulic pipeline system.
The general aviation hydraulic pipeline system needs more supports to ensure enough stability due to the longer span. Therefore, optimization of the aviation hydraulic line is a multivariable high-dimensional optimization problem. However, in general, optimization is slow for large-scale optimization problems involving more variables. Furthermore, the general engineering problem requires that numerical analysis software, such as finite element ANSYS, be called to solve. For complex structures such as an aviation hydraulic pipeline system, a finite element analysis is a time-consuming process, and the optimization process needs to call finite element software repeatedly in a large quantity for calculation, so the optimization process is a very time-consuming process. In addition, when the optimization problem of the hydraulic pipeline is solved in the related art, the shape of the pipeline system cannot be affected by the change of the design variables of the local sensitivity test and the global sensitivity test, and the distribution function is unknown, so that the method is difficult to be applied to the aviation hydraulic pipeline system.
In order to solve the problem of high-dimensional optimization which cannot be overcome by the traditional optimization method, the reliability analysis method of the aviation hydraulic pipeline based on the sensitivity test is provided.
It is to be noted that the information disclosed in the above background section is only for enhancement of understanding of the background of the present disclosure, and thus may include information that does not constitute prior art known to those of ordinary skill in the art.
Disclosure of Invention
It is an object of the present disclosure to provide a reliability analysis method and system based on sensitivity testing, thereby overcoming, at least to some extent, one or more of the problems due to the limitations and disadvantages of the related art.
Additional features and advantages of the disclosure will be set forth in the detailed description which follows, or in part will be obvious from the description, or may be learned by practice of the disclosure.
According to an aspect of the present disclosure, there is provided a reliability analysis method based on a sensitivity test, including:
determining a plurality of input variables according to the position of a mechanism part in a preset model, and carrying out sensitivity test on the input variables;
determining sensitivity indexes of the output response of the input variables to the preset model, and determining target input variables according to the sensitivity indexes;
and performing reliability analysis on the position of the mechanism component in the preset model based on the target input variable.
In an exemplary embodiment of the present disclosure, the method further comprises:
establishing an optimization model and performing iterative optimization on the output response according to the optimized position of the mechanism component and the optimization model to determine a target output response;
in an exemplary embodiment of the disclosure, the expression of the optimization model is:
Smax(X*)＝Min Smax(X)
Subject to Dmax-D*＜0
R*-R＜0
(j＝2～7,10～16,18,19,22～25)；
wherein S ismaxTo output a response, X*For the optimum value of the input variable, X is the input variable, XjIs the jth variable, D is the displacement response, D*For the displacement response threshold, R is the reliability, R*In order to be the threshold value of the reliability,andrespectively representing the amount by which the jth variable can be decreased and increased at a given value.
In an exemplary embodiment of the present disclosure, determining a sensitivity index of each of the input variables to an output response of the preset model includes:
and determining the influence degree of the input variable on the output response of the preset model from the aspects of the median and the deviation respectively.
In an exemplary embodiment of the present disclosure, determining a degree of influence of the input variable on the output response of the preset model includes:
representing each input variable as an interval input variable according to each input variable and the increment and decrement of each input variable at a first preset value;
and determining a corresponding interval target function according to the interval input variable, and acquiring a sensitivity index corresponding to the median and the deviation according to the median and the deviation of the output response.
In an exemplary embodiment of the present disclosure, determining the target input variable according to the sensitivity index includes:
and determining the input variables with the sensitivity indexes larger than a second preset value as the target input variables, and rejecting the input variables with the sensitivity indexes smaller than the second preset value.
In an exemplary embodiment of the present disclosure, the preset model includes a model of an aero-hydraulic line, and the mechanism component includes a support constraint component in the aero-hydraulic line.
In an exemplary embodiment of the disclosure, the input variables include one or more of each of the support restraint position coordinates.
In an exemplary embodiment of the disclosure, the output response includes a maximum stress response of the aero-hydraulic circuit.
According to an aspect of the present disclosure, there is provided a reliability analysis system based on a sensitivity test, including:
the sensitivity testing module is used for determining a plurality of input variables according to the position of a mechanism part in a preset model and carrying out sensitivity testing on the input variables;
the target input variable determining module is used for determining sensitivity indexes of output responses of the input variables to the preset model and determining target input variables according to the sensitivity indexes;
and the reliability analysis module is used for carrying out reliability analysis on the position of the mechanism component in the preset model based on the target input variable.
According to the reliability analysis method and system provided by the exemplary embodiment of the disclosure, the positions of the mechanism components are optimized based on the sensitivity test, on one hand, the input variables with small influence on the output response can be screened and ignored through the sensitivity indexes determined in the sensitivity test, so that the dimension reduction of the input variables in the reliability optimization analysis process is realized, the optimization process is simplified, and the optimization speed and the optimization efficiency are improved; on the other hand, the accurate optimization of mechanism parts can be realized through a small amount of input variables, and the accuracy of reliability analysis is improved.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and together with the description, serve to explain the principles of the disclosure. It is to be understood that the drawings in the following description are merely exemplary of the disclosure, and that other drawings may be derived from those drawings by one of ordinary skill in the art without the exercise of inventive faculty.
Fig. 1 schematically illustrates a flow chart of a reliability analysis method based on sensitivity testing in an exemplary embodiment of the present disclosure.
FIG. 2 schematically illustrates a schematic diagram of an aviation hydraulic piping system in an exemplary embodiment of the present disclosure.
Fig. 3 schematically illustrates a position diagram of a supporting and restraining member in an exemplary embodiment of the present disclosure.
Fig. 4 schematically illustrates a median sensitivity index diagram in an exemplary embodiment of the present disclosure.
Fig. 5 schematically illustrates a deviation sensitivity index diagram in an exemplary embodiment of the present disclosure.
Fig. 6 schematically illustrates an optimization process of the maximum stress response in an exemplary embodiment of the disclosure.
Fig. 7 schematically illustrates a block diagram of a reliability analysis system based on sensitivity testing in an exemplary embodiment of the present disclosure.
Detailed Description
Example embodiments will now be described more fully with reference to the accompanying drawings. Example embodiments may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of example embodiments to those skilled in the art. The same reference numerals denote the same or similar parts in the drawings, and thus, a repetitive description thereof will be omitted.
Furthermore, the described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to give a thorough understanding of embodiments of the disclosure. One skilled in the relevant art will recognize, however, that the embodiments of the disclosure can be practiced without one or more of the specific details, or with other methods, components, materials, devices, steps, and so forth. In other instances, well-known structures, methods, devices, implementations, materials, or operations are not shown or described in detail to avoid obscuring aspects of the disclosure.
For ease of description, spatial relationship terms such as "below …," "below …," "lower," "above …," "upper," and the like may be used herein to describe one element or feature's relationship to another element or feature (or other elements or features) as illustrated. It will be understood that the spatially relative terms are intended to encompass different orientations of the device in use or operation in addition to the orientation depicted in the figures.
Furthermore, the block diagrams shown in the figures are only functional entities and do not necessarily correspond to physically separate entities. That is, these functional entities may be implemented in the form of software, or in one or more software-hardened modules, or in different networks and/or processor devices and/or microcontroller devices. The drawings are merely schematic illustrations of the present disclosure and are not necessarily drawn to scale. The thicknesses and shapes of the layers in the drawings are not to be construed as true scale, but merely as a matter of convenience for illustrating the disclosure. The same reference numerals in the drawings denote the same or similar parts, and thus their repetitive description will be omitted.
The present exemplary embodiment provides a reliability analysis method based on a sensitivity test, which may be applied to an aviation hydraulic pipeline system as shown in fig. 2, and referring to fig. 1, the reliability analysis method may include:
s110, determining a plurality of input variables according to the position of a mechanism part in a preset model, and carrying out sensitivity test on the input variables;
s120, determining sensitivity indexes of the input variables for output response of the preset model, and determining target input variables according to the sensitivity indexes;
and S130, carrying out reliability analysis on the position of the mechanism component in the preset model based on the target input variable.
According to the reliability analysis method provided by the exemplary embodiment of the disclosure, the positions of the mechanism components are optimized based on the sensitivity test, the input variables with small influence on the output response are screened and ignored through the sensitivity indexes determined in the sensitivity test, and the dimension reduction of the input variables in the reliability optimization analysis process is realized, so that the optimization speed and the optimization efficiency are improved.
Next, each step of the reliability analysis method in the present exemplary embodiment is explained in detail with reference to fig. 2 to 6.
In step S110, a plurality of input variables are determined according to the position of a mechanism component in the preset model, and the input variables are subjected to a sensitivity test.
In the present exemplary embodiment, numerical analysis software may be invoked to solve, for example, finite element ANSYS. The preset model can be a model of the aviation hydraulic pipeline in a finite element, and the mechanism component can comprise a supporting and restraining component which plays an important role in the aviation hydraulic pipeline system in the aviation hydraulic pipeline. Due to the long span of the aeronautical hydraulic line system, a greater number of supporting and constraining components are required to guarantee sufficient stability.
The aircraft hydraulic circuit shown in fig. 2 comprises a connecting hydraulic pump 201, and oil outlets 202 and 203. The model of the aviation hydraulic pipeline in the finite element, the positions of the supporting and constraining components and the corresponding node numbers of the supporting and constraining components are shown in fig. 3. Because the input variables can be determined according to the positions of the supporting and restraining components, the input variables can be determined, and therefore the optimization problem of the aviation hydraulic pipeline is converted into a high-dimensional optimization problem related to the multiple input variables. The input variables may be a set of uniform or non-uniform random input variables, which may be determined according to actual engineering requirements.
It is to be noted that the input variables may comprise one or more of the position coordinates of each of the supporting and constraining members, for example, the input variables may comprise only the X-coordinates of the positions of the supporting and constraining members; it may also include both the X and Y coordinates, or both the X and Z coordinates, of the position of one of said supporting and constraining members; and may also include a combination of X, Y and Z coordinates for the location of the supporting constraining member.
Based on the position coordinates of the supporting and restraining component in the aviation hydraulic pipeline in the practical engineering shown in the table 1, wherein the numerical value of the upper mark is an input variable, the preset model is subjected to sensitivity test, and the sensitivity test can comprise a local sensitivity test and a global sensitivity test.
TABLE 1 support restraint position coordinates
| Numbering | 14 | 17 | 20 | 23 | 26 | 30 | 33 |
| X | -5091* | -7122 | -10233 | -13854 | -16205 | -19806 | -23177 |
| Y | -160 | -154 | -146 | -104 | -135 | -148 | -148 |
| Z | -227 | -233 | -223 | -192 | -207 | -188 | -188 |
| Numbering | 36 | 39 | 40 | 42 | 45 | 51 | 54 |
| X | -25638 | -27759 | -291910 | -351311 | -363412 | -420914 | -452115 |
| Y | -111 | -111 | -148 | -148 | -148 | -40 | -35 |
| Z | -155 | -155 | -188 | -188 | -6913 | 168 | 180 |
| Numbering | 59 | 62 | 65 | 69 | 72 | 75 | 82 |
| X | -488816 | -503617 | -514819 | -541520 | -574522 | -660224 | -203326 |
| Y | -35 | 12318 | 247 | 34421 | 38723 | 40525 | -16427 |
| Z | -189 | 214 | 171 | 195 | 201 | 274 | 14028 |
Since the local sensitivity test quantifies the degree of influence of an input variable on the output response of the pre-set model, typically in the form of the derivative of the maximum stress response on its distribution parameters. Global sensitivity in the optimization problem of the hydraulic pipeline, the distribution function of the input variable is unknown, and the change of the input variable cannot influence the shape of the pipeline system, so that the local sensitivity test and the global sensitivity test are difficult to be applied to the engineering problem.
The reliability analysis method based on the non-probability global sensitivity test provided by the exemplary embodiment can be applied to any mechanical system or other systems to obtain the influence degree of the input variable on the output response of the mechanical system.
In step S120, a sensitivity index of each input variable in response to the output of the preset model is determined, and a target input variable is determined according to the sensitivity index.
In the present exemplary embodiment, the target input variable refers to an input variable that has a large influence on the maximum stress response of the aviation hydraulic line, and the output response refers to the maximum stress response of the aviation hydraulic line. Specifically, an optimization model may be established, and a sensitivity index of each input variable to the maximum stress response of the preset model may be sequentially calculated based on the increasable amount and the reducible amount of each input variable determined by the plurality of support constraint components shown in table 2. Next, an index meeting a preset condition may be selected from the sensitivity indexes corresponding to each input variable, and the input variable corresponding to the sensitivity index may be determined as the target input variable.
Based on the optimization result of the positions of a plurality of supporting constraint components in the aviation hydraulic pipeline system, an optimization model shown as a formula (1) can be established, wherein the optimization model takes the maximum stress response minimum as an objective function, and takes the displacement response, the reliability and the variable intervals of input variables as constraint conditions:
Smax(X*)＝Min Smax(X)
Subject to Dmax-D*＜0
R*-R＜0
(j＝1～28) (1)
wherein S ismaxFor maximum stress response, X*For the optimum value of the input variable, X is the input variable, XjIs the jth variable, D is the displacement response, D*For the displacement response threshold, R is the reliability, R*In order to be the threshold value of the reliability,andrespectively representing the amount by which the jth variable can be decreased and increased at a given value.
TABLE 2 reducible and increasable amounts of input variables
| Numbering | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 |
| Δ– | 33 | 25 | 83 | 45 | 46 | 100 | 148 | 78 | 83 | 80 | 280 | 20 | 20 | 50 |
| Δ+ | 107 | 165 | 107 | 205 | 34 | 50 | 42 | 112 | 57 | 10 | 123 | 40 | 40 | 53 |
| Numbering | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 |
| Δ– | 53 | 26 | 19 | 49 | 46 | 177 | 10 | 101 | 3 | 42 | 6 | 44 | 18 | 40 |
| Δ+ | 37 | 84 | 11 | 41 | 24 | 13 | 5 | 89 | 7 | 92 | 8 | 46 | 12 | 50 |
Based on this, in the present exemplary embodiment, determining the sensitivity index of each of the input variables to the output response of the preset model may include:
and determining the influence degree of the input variable on the output response of the preset model from the aspects of the median and the deviation respectively.
In the exemplary embodiment, in order to accurately determine the degree of influence of each input variable on the maximum stress response of the aviation hydraulic line, computational multidimensional verification can be performed from the perspective of the median and the deviation, respectively.
Specifically, determining the degree of influence of the input variable on the output response of the preset model may include:
representing each input variable as an interval input variable according to each input variable and the increment and decrement of each input variable at a first preset value;
and determining a corresponding interval target function according to the interval input variable, and acquiring a sensitivity index corresponding to the median and the deviation according to the median and the deviation of the output response.
In the exemplary embodiment, the input variables are illustrated as 28, and the number of the input variables may also be determined according to actual engineering requirements. All of the input variables can be expressed in the interval form as shown in equation (2) according to the increasable amount and the decreasable amount of each input variable shown in table 2:
wherein,andrepresenting the lower and upper bounds of the jth input variable. Since the input variable is an interval, the corresponding maximum stress response is also an interval and can be expressed in the form as shown in equation (3):
wherein,andrepresenting the lower and upper bounds of the maximum stress response, respectively, then the median and deviation of the maximum stress response can be derived:
next, equation (4) and equation (5) are combined and the index is calculated according to equation (6):
in this example, the first preset value may be a value of the input variable in the actual project. Input variable when intervalFixed at its real valueCan eliminateThe influence of the uncertainty of (2) on the index η, the corresponding condition index beingWhen in useAt the input of variable XjInterval of (1)When the temperature of the molten steel is changed within the range,it can also be expressed by the interval shown in equation (7):
then, the median and variance corresponding to the condition indexes are respectively shown in formula (8) and formula (9):
based on this, the final non-probabilistic global sensitivity index corresponding to the median and variance is defined as follows:
and determining a non-probability global sensitivity index through the steps, and quantizing the influence degree of uncertainty of the input variable in the range of the input variable on the maximum stress response from the angles of the median and the deviation. Based on this, the target input variable may be determined according to the sensitivity index, and specifically may include:
and determining the input variables with the sensitivity indexes larger than a second preset value as the target input variables, and rejecting the input variables with the sensitivity indexes smaller than the second preset value.
In the present exemplary embodiment, the sensitivity indicators corresponding to all input variables, which are determined by the two angles of the median and the deviation, may be sorted in order from large to small. Through comparison, the sensitivity index larger than the second preset value is screened out, and the input variable corresponding to the sensitivity index is determined as the target input variable. The greater the sensitivity index of an input variable, the greater the degree of influence of the input variable on the maximum stress response. The second preset value here may be determined according to the overall distribution of the sensitivity index. In addition, the preset number of input variables with larger sensitivity indexes can be directly determined as the target input variables, and the preset number can be determined according to the actual engineering requirements of the system.
Referring to the bar graphs of the median sensitivity index and the deviation sensitivity index shown in fig. 4 and 5, the influence degree of each input variable on the maximum stress response can be obtained, and then 10 design variables with indexes of zero or less influence are screened out by comparison, and the numbers of the design variables are respectively 1, 8, 9, 17, 18, 20, 21, 26, 27 and 28. For input variables with smaller sensitivity indexes, the influence on the maximum stress response of the aviation hydraulic pipeline is small or even almost no, so that the influence can be ignored. Therefore, the sensitivity testing method can achieve the purpose of dimension reduction of the input variable in the optimization process by neglecting the input variable which has small influence on the output result, thereby improving the speed of reliability analysis of the aviation hydraulic pipeline system and further improving the optimization efficiency.
In step S130, reliability analysis is performed on the positions of the mechanism components in the preset model based on the target input variables.
In this example embodiment, the positions of the plurality of supporting and constraining components in the aviation hydraulic line system may be optimized according to the target input variables determined in the above steps. After ignoring the input variables that have less influence on the maximum stress response of the aviation hydraulic line, the optimization model in equation (1) may be correspondingly modified to equation (12):
it should be noted that, compared with the optimization model in formula (1), the optimization model shown in formula (12) only includes 18 input variables having a larger influence on the maximum stress response of the aviation hydraulic pipeline system.
The optimization results of the position coordinates of the support constraining member determined according to the formula (12) and the target input variables are shown in table 3.
TABLE 3 optimized position coordinates
| Numbering | 14 | 17 | 20 | 23 | 26 | 30 | 33 |
| X | -509 | -691.4* | -943.9 | -1384.7 | -1650.4 | -1994.9 | -2288.2 |
| Y | -160 | -154 | -146 | -104 | -135 | -148 | -148 |
| Z | -227 | -233 | -223 | -192 | -207 | -188 | -188 |
| Numbering | 36 | 39 | 40 | 42 | 45 | 51 | 54 |
| X | -2563 | -2775 | -2891.1 | -3527.9 | -3648.9 | -4219.2 | -4463.2 |
| Y | -111 | -111 | -148 | -148 | -148 | -40 | -35 |
| Z | -155 | -155 | -188 | -188 | -109 | 168 | 180 |
| Numbering | 59 | 62 | 65 | 69 | 72 | 75 | 82 |
| X | -4969.2 | -5036 | -5175.9 | -5415 | -5909.4 | -6536.4 | -2033 |
| Y | -35 | 123 | 247 | 344 | 385.5 | 417.1 | -164 |
| Z | -189 | 214 | 171 | 195 | 201 | 274 | 140 |
Further, in the present exemplary embodiment, after optimizing the position of the mechanism component, the method may further include:
and establishing an optimization model and performing iterative optimization on the output response according to the optimized position of the mechanism component and the optimization model to determine a target output response.
In the exemplary embodiment, referring to FIG. 6, the reliability analysis method of the non-probabilistic global sensitivity test based on equation (12) can be converged after about 300 iterations, while the conventional optimization method based on equation (1) still cannot be converged after 400 iterations7And the optimal value of the maximum stress response of the aviation hydraulic pipeline obtained by the traditional optimization method is 1.91 × 107And maximum stress response 2.69 × 10 before optimization7In contrast, the optimization method in this example reduces the maximum stress response by about 7.44% more than the conventional optimization method.
Considering the complexity of the optimization of the position of the supporting and constraining component in the aviation hydraulic pipeline, the example firstly provides a non-probability global sensitivity index based on interval uncertainty, and then sensitivity test is carried out on the aviation hydraulic pipeline on the basis and non-important input variables are compared and eliminated. In the traditional optimization method, when the sensitivity index of the aviation hydraulic pipeline is analyzed based on the finite element ANSYS, a large amount of finite element software needs to be called, and the sensitivity testing process is a time-consuming process. However, in the subsequent optimization in this example, the finite element can be directly called, and only the remaining target input variables with large influence on the maximum stress response are considered, so as to achieve the purposes of simplifying the optimization model and reducing the dimension of the input variables
Since the objective function in the optimization model established in the above steps is the minimum value of the maximum stress response, for the aviation hydraulic pipeline system, the optimization speed and the optimization result of the optimization method based on the non-probabilistic global sensitivity test in the present example exceed those of the conventional optimization method which does not involve the sensitivity test. Compared with the traditional optimization method, the reliability analysis method based on the non-probability global sensitivity test in the technical scheme of the disclosure can be found to remarkably reduce the required iteration times, reduce the dimension of input variables in the optimization process and improve the optimization efficiency under the condition of achieving the same calculation precision.
In this example embodiment, there is also provided a reliability analysis system based on a sensitivity test, and referring to fig. 7, the system 700 may include:
the sensitivity testing module 701 can be used for determining a plurality of input variables according to the position of a mechanism part in a preset model and carrying out sensitivity testing on the input variables;
a target input variable determining module 702, configured to determine a sensitivity index of each input variable in response to the output of the preset model, and determine a target input variable according to the sensitivity index;
a reliability analysis module 703, configured to perform reliability analysis on the position of the mechanism component in the preset model based on the target input variable.
The details of each module in the reliability analysis system are already described in detail in the corresponding reliability analysis method, and therefore are not described herein again.
Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This application is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.
It will be understood that the present disclosure is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.
Claims (10)
1. A reliability analysis method based on sensitivity test is characterized by comprising the following steps:
determining a plurality of input variables according to the position of a mechanism part in a preset model, and carrying out sensitivity test on the input variables;
determining sensitivity indexes of the output response of the input variables to the preset model, and determining target input variables according to the sensitivity indexes;
and performing reliability analysis on the position of the mechanism component in the preset model based on the target input variable.
2. The method for reliability analysis based on sensitivity testing according to claim 1, wherein the method further comprises:
and establishing an optimization model and performing iterative optimization on the output response according to the optimized position of the mechanism component and the optimization model to determine a target output response.
3. The method of claim 2, wherein the optimization model is expressed as:
Smax(X*)＝Min Smax(X)
Subject to Dmax-D*＜0
R*-R＜0
<mrow> <msubsup> <mi>X</mi> <mi>j</mi> <mo>*</mo> </msubsup> <mo>-</mo> <msubsup> <mi>&Delta;</mi> <mi>j</mi> <mo>-</mo> </msubsup> <mo>&le;</mo> <msub> <mi>X</mi> <mi>j</mi> </msub> <mo>&le;</mo> <msubsup> <mi>X</mi> <mi>j</mi> <mo>*</mo> </msubsup> <mo>+</mo> <msubsup> <mi>&Delta;</mi> <mi>j</mi> <mo>+</mo> </msubsup> </mrow>
(j＝2～7,10～16,18,19,22～25)；
wherein S ismaxTo output a response, X*For the optimum value of the input variable, X is the input variable, XjIs the jth variable, D is the displacement response, D*For the displacement response threshold, R is the reliability, R*In order to be the threshold value of the reliability,andrespectively representing the amount by which the jth variable can be decreased and increased at a given value.
4. The method of claim 1, wherein determining the sensitivity index of each of the input variables for the output response of the pre-set model comprises:
and determining the influence degree of the input variable on the output response of the preset model from the aspects of the median and the deviation respectively.
5. The sensitivity test-based reliability analysis method according to claim 4, wherein determining the degree of influence of the input variable on the output response of the preset model comprises:
representing each input variable as an interval input variable according to each input variable and the increment and decrement of each input variable at a first preset value;
and determining a corresponding interval target function according to the interval input variable, and acquiring a sensitivity index corresponding to the median and the deviation according to the median and the deviation of the output response.
6. The sensitivity test-based reliability analysis method according to claim 1, wherein determining a target input variable from the sensitivity index comprises:
and determining the input variables with the sensitivity indexes larger than a second preset value as the target input variables, and rejecting the input variables with the sensitivity indexes smaller than the second preset value.
7. The sensitivity test-based reliability analysis method according to any one of claims 1 to 6, wherein the preset model comprises a model of an aero-hydraulic line, and the mechanism component comprises a support constraint component in the aero-hydraulic line.
8. The sensitivity test based reliability analysis method of claim 7 wherein the input variables include one or more of each of the support restraint position coordinates.
9. The sensitivity test based reliability analysis method according to claim 7, wherein the output response comprises a maximum stress response of the aviation hydraulic line.
10. A reliability analysis system based on sensitivity testing, comprising:
the sensitivity testing module is used for determining a plurality of input variables according to the position of a mechanism part in a preset model and carrying out sensitivity testing on the input variables;
the target input variable determining module is used for determining sensitivity indexes of output responses of the input variables to the preset model and determining target input variables according to the sensitivity indexes;
and the reliability analysis module is used for carrying out reliability analysis on the position of the mechanism component in the preset model based on the target input variable.
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