CN110737208B - Semi-physical simulation test task ordering method and system based on resource optimization configuration - Google Patents
Semi-physical simulation test task ordering method and system based on resource optimization configuration Download PDFInfo
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Abstract
The invention provides a semi-physical simulation test task sequencing method based on resource optimization configuration, which comprises the following steps of: step 1: carrying out parametric design on the product state of the test task, and evaluating the product maturity of the test task; step 2: and carrying out parametric design on the workload and the test environment state of the test project, calculating the priority level of the test task by combining the maturity of the product and the proportion of the historical occupied resources of the party to which the test task belongs, and sequencing the test task in sequence according to the priority level. By the method, the total number of scientific research test tasks completed by an enterprise in a certain period can be increased on the premise of ensuring certain fairness, and the effect of promoting the operation efficiency of the enterprise is achieved.
Description
Technical Field
The invention relates to the field of research management and research, in particular to a semi-physical simulation test task ordering method and system based on resource optimization configuration.
Background
In recent years, the number of types of aerospace research is rapidly increased, and multitask and lifting are the reality normality. The efficiency of the test tasks is influenced by multiple factors such as the state of a product, test conditions, test projects and the like, how to scientifically evaluate the occupied resource expectation of the tasks participating in competition test resources and sequence all the test tasks participating in competition on the premise of ensuring certain fairness, so that limited semi-physical simulation resources are utilized to the maximum within a certain time period, and the method becomes an important obstacle for meeting multi-task parallel operation of space enterprises. The number of items of the test tasks is a main factor for determining the test period, but because the aerospace semi-physical simulation test system and the tested product belong to high-end manufacturing products, the preparation work of the test conditions is extremely complicated, and the test difficulty of the products in different states is different. A conventional semi-physical simulation control test platform and a test method thereof, as disclosed in patent document CN109100955A, the test platform includes a laboratory controller i, a computer and mathematical software thereon, and a virtual controlled object obtained by modeling a real controlled object on an industrial field by the mathematical software, wherein a control parameter when the controller i performs simulation control on the virtual controlled object through the computer can be adjusted and optimized repeatedly on the controller i, and the optimized control parameter can be provided to a field controller ii which controls the real controlled object on the industrial field.
However, the traditional semi-physical simulation test task ordering method has the following problems:
1. the total number of scientific research test tasks completed by enterprises in a certain period can not be increased on the premise of certain fairness, and the operation efficiency of the enterprises can not be improved.
2. The product state of the test task party cannot be parameterized and designed, and effective evaluation on the test task party cannot be formed.
Disclosure of Invention
Aiming at the defects in the prior art, the invention aims to provide a semi-physical simulation test task ordering method and system based on resource optimization configuration.
The invention provides a semi-physical simulation test task ordering method based on resource optimization configuration, which comprises the following steps:
step 1: carrying out parametric design on the product state of the test task, and evaluating the product maturity of the test task;
step 2: and carrying out parametric design on the workload of the test project and the test environment state, calculating the priority level of the test task by combining the maturity of the product and the proportion of the historical occupied resource of the party to which the test task belongs, and sequencing the priority level in sequence according to the priority level.
Preferably, the step 1 comprises:
carrying out parameterization processing on four factors of the verification depth of a test task product desktop simulation test, the software modification degree, the development stage and the controlled state of product software;
by X 1 Represents the ratio of the number of lists verified against the changed software code to the total number of changed lists in the desktop simulation test, X 1 In the range of 0. Ltoreq. X 1 ≤1；
By X 2 Representing the ratio of the number of modified lines of the software code to the total number of lines of the software code, X 2 In the range of 0. Ltoreq. X 2 ≤1；
By X 3 A maturity coefficient representing the stage state of the product, the reference value is 1, and X is set when the product is a principle prototype 3 ＝1-α 1 When the product is in the engineering development stage X 3 =1, X when product is in batch state 3 ＝1+α 1 ；α 1 Adjusting the coefficient value range to 0 for maturity<α 1 <0.5；
By X 4 Representing the controlled state of the product software version, X when the product software is in the development library 4 ＝1－α 2 X when the product software is in the controlled library 4 =1, X when product software is in product library 4 ＝1+α 2 ；α 2 Adjusting the value range of the coefficient to be more than 0 and less than alpha for the software state 2 ＜0.5。
Preferably, the step 1 further comprises:
the maturity of the product involved in the test task is expressed by the formula:
M＝X 1 (1-X 2 )X 3 X 4 (1)
wherein M represents the product maturity of the test task.
Preferably, the step 2 includes:
the workload evaluation method of the test project comprises the following steps:
W＝TX 5 (2)
wherein W represents the workload of the test item, X 5 For test complexity, X when the product is subjected to independent loop test 5 ＝1-α 3 And during non-interference test of closed loop X 5 =1, closed loop anti-interference test X 5 ＝1+α 3 ；α 3 The value range of the difficulty adjustment coefficient for the test item is more than 0 and less than alpha 3 ＜0.5；
T is the required test time calculated from the simulated trajectory and product characteristics:
T 1 time for trajectory simulation of this test, T 2 For the power-on time of the sprung device, T 3 Product continuous working time, T 4 The time of power failure and rest is needed, and the damage to the product caused by too long work is prevented;
the evaluation method of the completeness of the test environmental conditions comprises the following steps:
f(x 1 ,x 2 ,…,x n )＝x 1 x 2 …x n (4)
wherein x 1 To x n The completeness of each simulation resource system required to be used in the test task is shown, and x is more than or equal to 0 1 x 2 …x n ≤1。
Preferably, the step 2 further comprises:
the calculation method of the test task priority level R comprises the following steps:
wherein, P represents the condition that the part to which the test task belongs historically occupies the semi-physical simulation resource;
wherein D is i Representing the number of days that the party participating in the ranked test task has recently occupied the test resource.
The invention provides a semi-physical simulation test task sequencing system based on resource optimization configuration, which comprises the following modules:
a module M1: carrying out parametric design on the product state of the test task, and evaluating the product maturity of the test task;
a module M2: and carrying out parametric design on the workload of the test project and the test environment state, calculating the priority level of the test task by combining the maturity of the product and the proportion of the historical occupied resource of the party to which the test task belongs, and sequencing the priority level in sequence according to the priority level.
Preferably, said module M1 comprises:
carrying out parameterization processing on four factors of the verification depth of a test task product desktop simulation test, the software modification degree, the development stage and the controlled state of product software;
by X 1 Represents the ratio of the number of lists verified against the changed software code to the total number of changed lists in the desktop simulation test, X 1 In the range of 0. Ltoreq. X 1 ≤1；
By X 2 Representing the ratio of the number of modified lines of the software code to the total number of lines of the software code, X 2 In the range of 0. Ltoreq. X 2 ≤1；
By X 3 A maturity coefficient representing the stage state of the product, the reference value is 1, and X is set when the product is a principle prototype 3 ＝1-α 1 When the product is in the engineering development stage X 3 =1, X when product is in batch state 3 ＝1+α 1 ；α 1 Adjusting the value range of the coefficient to be 0 for the maturity<α 1 <0.5；
By X 4 Representing the controlled state of the product software version, X when the product software is in the development library 4 ＝1－α 2 X when the product software is in the controlled library 4 =1, X product software is in product library 4 ＝1+α 2 ；α 2 Adjusting the value range of the coefficient to be more than 0 and less than alpha for the software state 2 ＜0.5。
Preferably, the module M1 further comprises:
the maturity of the product involved in the test task is expressed by the formula:
M＝X 1 (1-X 2 )X 3 X 4 (1)
wherein M represents the product maturity of the test task.
Preferably, said module M2 comprises:
the workload evaluation system of the test project comprises:
W＝TX 5 (2)
wherein W represents the workload of the test project, X 5 For test complexity, X when the product is subjected to independent loop test 5 ＝1-α 3 In the case of a closed-loop non-interference test X 5 =1, closed loop anti-interference test X 5 ＝1+α 3 ；α 3 The value range of the difficulty adjustment coefficient for the test item is more than 0 and less than alpha 3 ＜0.5；
T is the required test time calculated from the simulated trajectory and product characteristics:
T 1 time for trajectory simulation of this test, T 2 For the power-on time of the sprung device, T 3 Product continuous working time, T 4 The time of power failure and rest is needed, and the damage to the product caused by too long work is prevented;
the evaluation system for the completeness of the test environmental conditions comprises the following steps:
f(x 1 ,x 2 ,…,x n )＝x 1 x 2 …x n (4)
wherein x 1 To x n The completeness of each simulation resource system required to be used in the test task is shown, and x is more than or equal to 0 1 x 2 …x n ≤1。
Preferably, said module M2 further comprises:
the calculation system of the test task priority level R is as follows:
wherein, P represents the situation that the party to which the test task belongs historically occupies the semi-physical simulation resource;
wherein D is i Representing the number of days that the party participating in the ranked test task recently occupied the test resource.
Compared with the prior art, the invention has the following beneficial effects:
1. by the method, the total number of scientific research test tasks completed by an enterprise in a certain period can be increased on the premise of ensuring certain fairness, and the effect of promoting the operation efficiency of the enterprise is achieved.
2. By the method, the product state of the test task party is parameterized, effective evaluation on the test task party is formed, and the effect of scientifically managing the test system is achieved.
Drawings
Other features, objects and advantages of the invention will become more apparent upon reading of the detailed description of non-limiting embodiments with reference to the following drawings:
fig. 1 is a schematic diagram of a test task product maturity assessment process.
FIG. 2 is a schematic diagram of task prioritization process for semi-physical simulation testing.
Fig. 3 is a table of data of the status of the products under test.
FIG. 4 is a semi-physical simulation time data table.
Detailed Description
The present invention will be described in detail with reference to specific examples. The following examples will assist those skilled in the art in further understanding the invention, but are not intended to limit the invention in any way. It should be noted that it would be obvious to those skilled in the art that various changes and modifications can be made without departing from the spirit of the invention. All falling within the scope of the present invention.
As shown in fig. 1 to fig. 2, the semi-physical simulation test task ordering method based on resource optimization configuration according to the present invention includes the following steps:
step 1: carrying out parametric design on the product state of the test task, and evaluating the product maturity of the test task;
step 2: and carrying out parametric design on the workload and the test environment state of the test project, calculating the priority level of the test task by combining the maturity of the product and the proportion of the historical occupied resources of the party to which the test task belongs, and sequencing the test task in sequence according to the priority level.
Further, the step 1 comprises:
carrying out parameterization processing on four factors of the verification depth of a test task product desktop simulation test, the software modification degree, the development stage and the controlled state of product software;
by X 1 Represents the ratio of the number of lists verified against the changed software code to the total number of changed lists in the desktop simulation test, X 1 In the range of 0. Ltoreq. X 1 ≤1；
By X 2 Indicating the ratio of the number of software code change lines to the total number of software code lines, X 2 In the range of 0. Ltoreq. X 2 ≤1；
By X 3 A maturity coefficient representing the stage state of the product, the reference value is 1, and X is set when the product is a principle prototype 3 ＝1-α 1 When the product is in the engineering development stage X 3 =1, X when product is in batch state 3 ＝1+α 1 ；α 1 Adjusting the value range of the coefficient to be 0 for the maturity<α 1 <0.5；
By X 4 Representing the controlled state of the product software version, X when the product software is in the development library 4 ＝1－α 2 X when the product software is in the controlled library 4 =1, X when product software is in product library 4 ＝1+α 2 ；α 2 As software statesThe value range of the adjustment coefficient is more than 0 and less than alpha 2 ＜0.5。
Further, the step 1 further comprises:
the maturity of the product involved in the test task is expressed by the formula:
M＝X 1 (1-X 2 )X 3 X 4 (1)
wherein M represents the product maturity of the test task.
Further, the step 2 comprises:
the workload evaluation method of the test project comprises the following steps:
W＝TX 5 (2)
wherein W represents the workload of the test item, X 5 For test complexity, X when the product is subjected to independent loop test 5 ＝1-α 3 In the case of a closed-loop non-interference test X 5 =1, closed loop anti-interference test X 5 ＝1+α 3 ；α 3 The value range of the difficulty adjustment coefficient for the test item is more than 0 and less than alpha 3 ＜0.5；
T is the required test time calculated from the simulated trajectory and product characteristics:
T 1 time for trajectory simulation of this test, T 2 For the power-on time of the sprung device, T 3 Product continuous working time, T 4 The power-off rest time is needed, and the damage to the product caused by too long work is prevented;
the evaluation method of the completeness of the test environmental conditions comprises the following steps:
f(x 1 ,x 2 ,…,x n )＝x 1 x 2 …x n (4)
wherein x is 1 To x n The completeness of each simulation resource system required to be used in the test task is shown, and x is more than or equal to 0 1 x 2 …x n ≤1。
Further, the step 2 further comprises:
the calculation method of the test task priority level R comprises the following steps:
wherein, P represents the condition that the part to which the test task belongs historically occupies the semi-physical simulation resource;
wherein D is i Representing the number of days that the party participating in the ranked test task has recently occupied the test resource.
The invention provides a semi-physical simulation test task sequencing system based on resource optimization configuration, which comprises the following modules:
a module M1: carrying out parametric design on the product state of the test task, and evaluating the product maturity of the test task;
a module M2: and carrying out parametric design on the workload and the test environment state of the test project, calculating the priority level of the test task by combining the maturity of the product and the proportion of the historical occupied resources of the party to which the test task belongs, and sequencing the test task in sequence according to the priority level.
Further, the module M1 comprises:
carrying out parameterization processing on four factors of the verification depth of a test task product desktop simulation test, the software modification degree, the development stage and the controlled state of product software;
by X 1 Representing the ratio of the number of manifests verified against the altered software code to the total number of manifests altered in the desktop simulation test, X 1 In the range of 0. Ltoreq. X 1 ≤1；
By X 2 Representing the ratio of the number of modified lines of the software code to the total number of lines of the software code, X 2 In the range of 0. Ltoreq.X 2 ≤1；
By X 3 A maturity coefficient representing the stage state of the product, the reference value is 1, and X is set when the product is a principle prototype 3 ＝1-α 1 When the product is in the engineering development stage X 3 =1, X when product is in batch state 3 ＝1+α 1 ；α 1 Adjusting the coefficient value range to 0 for maturity<α 1 <0.5；
By X 4 Representing the controlled state of the product software version, X when the product software is in the development library 4 ＝1－α 2 X when the product software is in the controlled library 4 =1, X product software is in product library 4 ＝1+α 2 ；α 2 Adjusting the value range of the coefficient to be more than 0 and less than alpha for the software state 2 ＜0.5。
Further, the module M1 further includes:
the maturity of the product involved in the test task is expressed by the formula:
M＝X 1 (1-X 2 )X 3 X 4 (1)
wherein M represents the product maturity of the test task.
Further, the module M2 comprises:
the workload evaluation system of the test project comprises:
W＝TX 5 (2)
wherein W represents the workload of the test item, X 5 For test complexity, X when the product is subjected to independent loop test 5 ＝1-α 3 And during non-interference test of closed loop X 5 =1, closed loop anti-interference test X 5 ＝1+α 3 ；α 3 The value range of the difficulty adjustment coefficient for the test item is more than 0 and less than alpha 3 ＜0.5；
T is the required test time calculated from the simulated trajectory and product characteristics:
T 1 time for trajectory simulation of this test, T 2 For the power-on time of the sprung device, T 3 Product continuous working time, T 4 The time of power failure and rest is needed, and the damage to the product caused by too long work is prevented;
the evaluation system for the completeness of the test environmental conditions comprises the following steps:
f(x 1 ,x 2 ,…,x n )＝x 1 x 2 …x n (4)
wherein x 1 To x n The completeness of each simulation resource system required to be used in the test task is shown, and x is more than or equal to 0 1 x 2 …x n ≤1。
Further, the module M2 further includes:
the calculation system of the test task priority level R comprises the following steps:
wherein, P represents the condition that the part to which the test task belongs historically occupies the semi-physical simulation resource;
wherein D is i Representing the number of days that the party participating in the ranked test task has recently occupied the test resource.
In a preferred embodiment, the method of the technical scheme is used for sequencing the tasks of 3 test task parties applying for the semi-physical simulation resources. The state data of the products to be tested of the 3 task parties are shown in figure 3, and the semi-physical simulation time data are shown in figure 4. The simulation system resources needed in the test task are all in good condition.
As can be seen from fig. 3, the parameterized values of the verification depth and the degree of software modification of the desktop simulation test of the 3 task parties are as follows:
taking the maturity adjustment coefficient alpha 1 =0.3, the development stage parameterization value is
Taking a software state adjustment coefficient alpha 2 =0.2, the controlled state parameterization value of the product software is
The maturity of the products involved in the test task is expressed as follows:
and carrying out parametric design on the workload and the test environment state of the test project. If the resources of the simulation system are in good condition, then
From the time data of FIG. 4, it can be seen that
Calculating the test time:
wherein the content of the first and second substances,
representing an rounding up symbol.
Taking the difficulty adjustment coefficient alpha of the test item 3 =0.3, the test complexity is taken as
The workload of the test project was calculated as follows:
and (4) calculating the priority level of the test tasks by combining the maturity of the product and the proportion of the historical occupied resources of the party to which the test tasks belong, and sequencing the test tasks in sequence according to the priority level.
As can be seen from FIG. 4, the simulation resource occupation time of the 3 test task parties at the early stage is respectively
Calculating the condition that the part to which the test task belongs historically occupies the semi-physical simulation resource:
calculating the priority level of the test task:
thus having R B ＞R A ＞R C The priority of the task party B is the highest, and the priority of the task party C is the lowest.
It is well within the knowledge of a person skilled in the art to implement the system and its various devices, modules, units provided by the present invention in a purely computer readable program code means that the same functionality can be implemented by logically programming method steps in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers and the like. Therefore, the system and various devices, modules and units thereof provided by the present invention can be regarded as a hardware component, and the devices, modules and units included therein for implementing various functions can also be regarded as structures within the hardware component; means, modules, units for performing the various functions may also be regarded as structures within both software modules and hardware components for performing the method.
The foregoing description of specific embodiments of the present invention has been presented. It is to be understood that the present invention is not limited to the specific embodiments described above, and that various changes or modifications may be made by one skilled in the art within the scope of the appended claims without departing from the spirit of the invention. The embodiments and features of the embodiments of the present application may be combined with each other arbitrarily without conflict.
Claims (2)
1. A semi-physical simulation test task ordering method based on resource optimization configuration is characterized by comprising the following steps:
step 1: carrying out parametric design on the product state of the test task, and evaluating the product maturity of the test task;
and 2, step: carrying out parametric design on the workload and the test environment state of the test project, calculating the priority level of the test task by combining the maturity of the product and the proportion of the historical occupied resources of the party to which the test task belongs, and then sequentially sequencing according to the priority level;
the step 1 comprises the following steps:
carrying out parameterization processing on four factors of the verification depth of a test task product desktop simulation test, the software modification degree, the development stage and the controlled state of product software;
by X 1 Representing the number of manifests and the verification of the changed software code in the desktop simulation testProportion of total number of changed lists, X 1 In the range of 0. Ltoreq.X 1 ≤1；
By X 2 Indicating the ratio of the number of software code change lines to the total number of software code lines, X 2 In the range of 0. Ltoreq.X 2 ≤1；
By X 3 A maturity coefficient representing the stage state of the product, the reference value is 1, and X is set when the product is a principle prototype 3 ＝1-α 1 When the product is in the engineering development stage X 3 =1, X when product is in batch state 3 ＝1+α 1 ；α 1 Adjusting the coefficient value range to 0 for maturity<α 1 <0.5；
By X 4 Representing the controlled state of the product software version, X when the product software is in the development library 4 ＝1－α 2 X when the product software is in the controlled library 4 =1, X when product software is in product library 4 ＝1+α 2 ；α 2 Adjusting the value range of the coefficient to be more than 0 and less than alpha for the software state 2 ＜0.5；
The step 1 further comprises:
the maturity of the product involved in the test task is expressed by the formula:
M＝X 1 (1-X 2 )X 3 X 4 (1)
wherein M represents the product maturity of the test task;
the step 2 comprises the following steps:
the workload evaluation method of the test project comprises the following steps:
W＝TX 5 (2)
wherein W represents the workload of the test project, X 5 For test complexity, X when the product is subjected to independent loop test 5 ＝1-α 3 In the case of a closed-loop non-interference test X 5 =1, closed loop anti-interference test X 5 ＝1+α 3 ；α 3 The value range of the difficulty adjustment coefficient for the test item is more than 0 and less than alpha 3 ＜0.5；
T is the required test time calculated from the simulated trajectory and product characteristics:
T 1 time for trajectory simulation of this test, T 2 For the power-on time of the sprung device, T 3 Product continuous working time, T 4 The time of power failure and rest is needed, and the damage to the product caused by too long work is prevented;
the evaluation method of the completeness of the test environmental conditions comprises the following steps:
f(x 1 ,x 2 ,…,x n )＝x 1 x 2 …x n (4)
wherein x 1 To x n The completeness of each simulation resource system required in the test task is shown, and x is more than or equal to 0 1 x 2 …x n ≤1；
The step 2 further comprises:
the calculation method of the test task priority level R comprises the following steps:
wherein, P represents the situation that the party to which the test task belongs historically occupies the semi-physical simulation resource;
wherein D is i Representing the number of days that the party participating in the ranked test task recently occupied the test resource.
2. A semi-physical simulation test task sequencing system based on resource optimization configuration is characterized by comprising the following modules:
a module M1: carrying out parametric design on the product state of the test task, and evaluating the product maturity of the test task, wherein the method comprises the following steps:
carrying out parameterization processing on four factors of the verification depth of a test task product desktop simulation test, the software modification degree, the development stage and the controlled state of product software;
by X 1 Representing the ratio of the number of manifests verified against the altered software code to the total number of manifests altered in the desktop simulation test, X 1 In the range of 0. Ltoreq. X 1 ≤1；
By X 2 Representing the ratio of the number of modified lines of the software code to the total number of lines of the software code, X 2 In the range of 0. Ltoreq.X 2 ≤1；
By X 3 A maturity coefficient representing the stage state of the product, the reference value is 1, and X is set when the product is a principle prototype 3 ＝1-α 1 When the product is in the engineering development stage X 3 =1, X when product is in batch state 3 ＝1+α 1 ；α 1 Adjusting the coefficient value range to 0 for maturity<α 1 <0.5；
By X 4 Representing the controlled state of the product software version, X when the product software is in the development library 4 ＝1－α 2 X when the product software is in the controlled library 4 =1, X when product software is in product library 4 ＝1+α 2 ；α 2 Adjusting the value range of the coefficient to be more than 0 and less than alpha for the software state 2 ＜0.5；
The maturity of the product involved in the test task is expressed by the formula:
M＝X 1 (1-X 2 )X 3 X 4 (1)
wherein M represents the product maturity of the test mission;
a module M2: carrying out parametric design on the workload and the test environment state of the test project, and calculating the priority level of the test task by combining the maturity of the product and the proportion of the historical occupied resources of the party to which the test task belongs, wherein the method comprises the following steps:
the workload evaluation system of the test project comprises the following steps:
W＝TX 5 (2)
wherein W represents the workload of the test item, X 5 For test complexity, X when the product is subjected to independent loop test 5 ＝1-α 3 In the case of a closed-loop non-interference test X 5 =1, closed loop anti-interference test X 5 ＝1+α 3 ；α 3 The value range of the difficulty adjustment coefficient for the test item is more than 0 and less than alpha 3 ＜0.5；
T is the required test time calculated from the simulated trajectory and product characteristics:
T 1 time for trajectory simulation of this test, T 2 For the power-on time of the sprung device, T 3 Product continuous working time, T 4 The time of power failure and rest is needed, and the damage to the product caused by too long work is prevented;
the evaluation system for the completeness of the test environmental conditions comprises the following steps:
f(x 1 ,x 2 ,…,x n )＝x 1 x 2 …x n (4)
wherein x 1 To x n The completeness of each simulation resource system required in the test task is shown, and x is more than or equal to 0 1 x 2 …x n ≤1；
The calculation system of the test task priority level R comprises the following steps:
wherein, P represents the condition that the part to which the test task belongs historically occupies the semi-physical simulation resource;
wherein D is i Representing the number of days for which the parties participating in the sequencing test task recently occupy the test resources;
and sequencing the data according to the priority level.
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| CN108388755A (en) * | 2018-03-30 | 2018-08-10 | 哈尔滨理工大学 | A kind of simulating experimental for flame retardant cable combustion test |
| CN109289201A (en) * | 2018-11-07 | 2019-02-01 | 成都夏飞科技有限公司 | Mission Objective dissemination system based on big data |
| CN109919487A (en) * | 2019-03-07 | 2019-06-21 | 大连大学 | The calculation method of entry priority under multifactor impact |
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