CN113127968B - Evaluation method based on carrier rocket - Google Patents

Evaluation method based on carrier rocket Download PDF

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CN113127968B
CN113127968B CN202110269261.3A CN202110269261A CN113127968B CN 113127968 B CN113127968 B CN 113127968B CN 202110269261 A CN202110269261 A CN 202110269261A CN 113127968 B CN113127968 B CN 113127968B
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颜晓明
姚迪
谢立
金益辉
汪曦
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Shanghai Aerospace System Engineering Institute
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Abstract

The invention relates to an evaluation method based on a carrier rocket, belonging to the technical field of rocket total test; selecting key parameters influencing product characteristics and task success and failure by using an FMECA or FTA method; step two, constructing a standard evaluation function; step three, collecting test data of key parameters; step four, carrying out primary elimination and secondary elimination treatment on the test data in sequence; obtaining screened test data; constructing a probability density function; step six, calculating a consistency evaluation value of the experimental data; evaluating the test data of the carrier rocket according to the consistency evaluation value; the invention provides a method for quantitatively evaluating the consistency of test data, and provides a quick analysis tool for test and analysis personnel so as to solve the technical problem that no applicable method or tool is available at present for evaluating the consistency of the test data.

Description

Evaluation method based on carrier rocket
Technical Field
The invention belongs to the technical field of rocket total test and relates to an evaluation method based on a carrier rocket.
Background
At present, the rocket total test has wider and higher range and higher requirement, whether the test result can be consistent with the design target or not is becoming a more and more concerned problem of the test, and is also one of the core problems restricting the test application. The method for analyzing and evaluating the consistency of the test result data is applied to rocket total measurement and flight remote measurement, is beneficial to improving the confidence coefficient of the test data, and provides support for design and process improvement.
The evaluation of the total test data of the rocket is mainly carried out in a manual mode, the evaluation is mainly based on whether the test data exceeds the designed index range or not, the effectiveness of the evaluation conclusion depends on the professional knowledge and practical experience of an executive, the evaluation cannot be automatically and intelligently executed, and the evaluation is difficult to popularize.
Some designers are exploring successful data envelope analysis, a successful data envelope range is constructed by using historical successful data, test data and the successful data envelope range are compared during evaluation, and whether a test result is in the successful data envelope range is judged. The current attempts are usually based on simple statistical methods, and only qualitative conclusions can be obtained, but quantitative evaluation results cannot be obtained.
At present, an effective consistency evaluation method for total test data of the rocket is lacked, accurate quantitative evaluation for the test data cannot be carried out, and certain adverse effect is brought to the application of the test data.
Disclosure of Invention
The technical problem solved by the invention is as follows: the method overcomes the defects of the prior art, provides an evaluation method based on a carrier rocket, provides a method for quantitatively evaluating the consistency of test data, and provides a quick analysis tool for test and analysis personnel so as to solve the technical problem that the consistency of the test data is evaluated by lacking an applicable method and tool at present.
The technical scheme of the invention is as follows:
the evaluation method based on the carrier rocket comprises the following steps:
selecting key parameters influencing product characteristics and task success and failure by using an FMECA or FTA method;
step two, constructing a standard evaluation function P (x);
step three, collecting test data of key parameters;
step four, carrying out primary elimination and secondary elimination treatment on the test data in sequence; obtaining screened test data;
constructing a probability density function F (x);
step six, calculating a consistency evaluation value I of the experimental data;
and seventhly, evaluating the test data of the carrier rocket according to the consistency evaluation value I.
In the evaluation method based on the carrier rocket, in the first step, the key parameters include first-stage oxygen tank pressure, first-stage combustion tank pressure, second-stage oxygen tank pressure, second-stage combustion tank pressure, third-stage oxygen tank pressure and third-stage combustion tank pressure.
In the above evaluation method based on a launch vehicle, in the second step, the standard evaluation function p (x) is:
Figure BDA0002973522860000021
in the formula, x is a key parameter;
k1is a first coefficient of the first,
Figure BDA0002973522860000022
b1is a first constant which is a function of,
Figure BDA0002973522860000023
k2is a second coefficient of the first coefficient,
Figure BDA0002973522860000024
b2is a second constant which is a function of,
Figure BDA0002973522860000025
in the above evaluation method based on a launch vehicle, in the fourth step, the primary elimination refers to performing outlier detection on the test data and eliminating an abnormal value which generates interference.
In the above evaluation method by a launch vehicle, in the fourth step, the second elimination refers to substituting the test data as x into a calculation formula of a standard evaluation function p (x), and eliminating the test data when p (x) is 0.
In the above evaluation method based on a launch vehicle, in the fifth step, the probability density function f (x) is constructed by:
step one, calculating the mean value u of the screened test data:
Figure BDA0002973522860000031
in the formula, n is the number of test data;
i is the number of the test data;
step two, calculating the standard deviation sigma of the screened test data:
Figure BDA0002973522860000032
step three, calculating a probability density function F (x):
Figure BDA0002973522860000033
in the above evaluation method based on a launch vehicle, in the sixth step, the consistency evaluation value I is calculated by:
Figure BDA0002973522860000034
in the above evaluation method based on a launch vehicle, in the seventh step, the method for evaluating the test data of the launch vehicle is as follows:
when I is more than or equal to 0.9, the evaluation test data is excellent;
when I is more than or equal to 0.75 and less than 0.9, the evaluation test data is better;
when I is more than or equal to 0.6 and less than 0.75, evaluating the test data as qualified;
when I is less than 0.6, the test data is evaluated as fail.
Compared with the prior art, the invention has the beneficial effects that:
(1) the invention provides a method for quantitatively evaluating the consistency of test data, accurately describes the consistency degree of the test data and design requirements, better reflects the confidence of the test data and quantifies the evaluation result;
(2) when the consistency evaluation of test data is carried out, the design theoretical standard value and the control limit requirement are fully considered, and the evaluation model has strong pertinence;
(3) the invention fully utilizes the data processing and visual display capabilities of the rocket test big data platform, realizes the automatic data consistency evaluation, provides a quick and practical analysis tool for analysts, provides powerful technical support for intuitively and efficiently analyzing test data, is seamlessly integrated with the rocket test big data platform, and realizes the automatic analysis evaluation.
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FIG. 1 is a flow chart of a launch vehicle evaluation of the present invention;
FIG. 2 is a schematic diagram of the system framework of the present invention.
Detailed Description
The invention is further illustrated by the following examples.
The invention provides an evaluation method based on a carrier rocket, provides a quantitative evaluation method for test data consistency by combining the characteristics of a total test of the rocket, and provides a quick analysis tool for a test and an analyst so as to solve the technical problem that the test data consistency is evaluated by lacking an applicable method and tool at present.
The evaluation method based on the carrier rocket, as shown in fig. 1, comprises the following steps:
selecting key parameters influencing product characteristics and task success and failure by using an FMECA or FTA method; the key parameters comprise first-level oxygen tank pressure, first-level combustion tank pressure, second-level oxygen tank pressure, second-level combustion tank pressure, third-level oxygen tank pressure and third-level combustion tank pressure. And selecting key parameters influencing the product characteristics and the success or failure of the task. A sampling interval is set based on data characteristics, test data with the same model and the same technical state are selected from rocket test big data, and partial parameters need to be sampled and evaluated in a segmented mode.
Determining a theoretical standard value and control upper and lower bounds of a parameter index according to the provided technical requirements, and constructing a standard evaluation function P (x); the standard evaluation function p (x) is:
Figure BDA0002973522860000051
in the formula, x is a key parameter;
k1is a first coefficient of the first,
Figure BDA0002973522860000052
b1is a first constant which is a function of the first,
Figure BDA0002973522860000053
k2is a second coefficient of the first coefficient,
Figure BDA0002973522860000054
b2is a second constant which is a function of,
Figure BDA0002973522860000055
step three, collecting test data of key parameters; and reading test data to be evaluated from the rocket test big data platform according to the analysis parameters and the sampling interval determined in the step one. Before the analysis and evaluation of the test data, necessary cleaning conversion is required, including missing value processing, abnormal value processing, format conversion, value domain mapping and the like.
Step four, carrying out primary elimination and secondary elimination treatment on the test data in sequence; obtaining screened test data; the primary elimination refers to the wild value detection of the test data and the elimination of the abnormal value which generates the interference. The secondary elimination refers to the elimination of test data when p (x) is 0 by substituting the test data as x into a calculation formula of a standard evaluation function p (x).
The evaluation method aims at data conforming to normal distribution, the data is firstly subjected to normality test before evaluation, and when the data obeys the normal distribution, the subsequent processing step is carried out; when the data do not obey normal distribution, other probability density functions can be selected for analysis and evaluation according to the distribution characteristics of the data. The normality test may be carried out according to the test method described in GB/T4882 "statistical processing and interpretation of data" clause 8.
The field value generated by accidental deviation of the test conditions and the test method has a great influence on consistency evaluation, so that the field value of the test data is detected based on a rationality detection method, and abnormal values which may generate interference are eliminated. The wild value is screened and removed by selecting the methods provided in clauses 6, 7 and 8 according to GB/T4883 < statistical processing of data > and judgment and processing of normal sample outliers </i > and actual conditions.
Constructing a probability density function F (x); the construction method of the probability density function F (x) comprises the following steps:
step one, calculating the mean value u of the screened test data:
Figure BDA0002973522860000061
in the formula, n is the number of test data;
i is the number of the test data;
step two, calculating the standard deviation sigma of the screened test data:
Figure BDA0002973522860000062
step three, calculating a probability density function F (x), wherein the probability density function F (x) accords with the data of normal distribution with the mean value u and the standard deviation sigma, and is as follows:
Figure BDA0002973522860000063
integrating the probability density function and the standard evaluation function within the control limit, and calculating a consistency evaluation value I of the experimental data;
Figure BDA0002973522860000064
as a quantitative evaluation index of test data consistency, the closer the value of I is to 1, the better the data consistency is.
Through a tool provided by a big data platform, the final result and the intermediate result of the consistency analysis can be displayed on a human-computer interface in a graphical mode, so that an interpretation analyst can observe the evaluation process in a visual mode, and the value of the data is exerted to the maximum extent.
And seventhly, evaluating the test data of the carrier rocket according to the consistency evaluation value I. The method for evaluating the test data of the carrier rocket comprises the following steps:
when I is more than or equal to 0.9, the evaluation test data is excellent;
when I is more than or equal to 0.75 and less than 0.9, the evaluation test data is better;
when I is more than or equal to 0.6 and less than 0.75, evaluating the test data as qualified;
when I is less than 0.6, the test data is evaluated as fail.
Based on the results of the consistency evaluation, the test results were analyzed and confirmed, and based on the analysis results, corresponding countermeasures were taken as shown in table 1. And carrying out related improvement work aiming at the potential hazards and problems in the aspects of design, process and the like.
TABLE 1
Figure BDA0002973522860000071
Implementation of the test data consistency evaluation tool:
the invention firstly uses java language to carry out programming simulation, and then carries out programming realization based on a rocket total measurement big data platform, and a system framework is shown in figure 2.
Firstly, test data are all stored in a rocket test big data platform, and besides the test data collected in the ground total test and flight remote measurement processes, the test data also store and manage relevant basic resource information of model products, technical states, test sites and the like.
And secondly, the data layer completes the basic processing and management functions of the data.
1. Data access: finishing the storage and reading of data according to a preset standard;
2. data processing: performing basic conversion processing such as format conversion, value domain mapping, deficiency processing, wild value elimination and the like on data;
3. data management: and the man-machine interaction interface provides the hierarchical classification management of the test data and the management functions of the test result data and the metadata thereof.
4. Managing parameter indexes: the characteristic parameters of the product are configured and managed, and indexes for data analysis based on the parameters are managed, including statistical indexes (mean, standard deviation, and the like), interpretation indexes (trajectory, thrust, and the like), and the like.
And thirdly, the calculation layer is used for executing calculation in a specific analysis process.
1. Statistical analysis: automatically calculating statistical indexes of the specified data set, such as maximum and minimum values, mean values, extreme values, standard deviations and the like;
2. an algorithm model: providing a basic algorithm model for data analysis dependence, wherein the basic algorithm model comprises a statistical algorithm, a correlation analysis algorithm, a classification algorithm, a special algorithm and the like;
3. and (4) normal test: completing calculation related to the normality test of the data, including normality test, outlier rejection and the like;
4. memory calculation: perform some computations in the analysis process, and scheduling and management of computing resources. For example, the system provides various integral calculation methods such as a rectangle method, a trapezoid method, a Simpson method and the like, and the application layer can be selected according to specific needs.
And fourthly, the application layer completes data processing and calculation required by the test data analysis service, and the relevant application functions of the test data consistency analysis are mainly relevant in the text.
1. Data sampling: screening data according to the model, the technical state and the like, selecting test data in a segmented mode according to set characteristic parameters, and generating a data set to be evaluated;
2. evaluation after the fact: analyzing and evaluating test result data provided in a data packet form after the test is finished;
3. and (3) real-time evaluation: analyzing and evaluating the test data acquired in real time in the test process, and realizing real-time interpretation and real-time evaluation of the test data;
4. visual display: and carrying out visual graphic display on the final result and the intermediate result of the evaluation, so that an analyst can visually observe and analyze the test data.
The invention is based on probability statistics theory, takes test data as a group of random variables obeying probability distribution, and identifies the consistency degree of the test measured value of the parameter and the design target through the integral value of the probability density function calculated between parameter design control limits. The method comprises the steps of selecting appropriate analysis parameters according to business needs, constructing a standard evaluation function through control indexes, collecting test data in the test process or after the test is completed, constructing a probability density function according to data characteristics, and then comprehensively performing consistency evaluation, wherein the evaluation data processing and analysis and calculation are completed based on a rocket test big data platform, so that the automation of the evaluation process and the visualization of results are realized.
Although the present invention has been described with reference to the preferred embodiments, it is not intended to limit the present invention, and those skilled in the art can make variations and modifications of the present invention without departing from the spirit and scope of the present invention by using the methods and technical contents disclosed above.

Claims (5)

1. The evaluation method based on the carrier rocket is characterized by comprising the following steps: the method comprises the following steps:
selecting key parameters influencing product characteristics and task success and failure by using an FMECA or FTA method; the key parameters comprise a primary oxygen box pressure, a primary combustion box pressure, a secondary oxygen box pressure, a secondary combustion box pressure, a tertiary oxygen box pressure and a tertiary combustion box pressure;
step two, constructing a standard evaluation function P (x); the standard evaluation function p (x) is:
Figure FDA0003573181350000011
in the formula, x is a key parameter;
k1is a first coefficient of the first,
Figure FDA0003573181350000012
b1is a first constant which is a function of the first,
Figure FDA0003573181350000013
k2is a second coefficient of the first coefficient,
Figure FDA0003573181350000014
b2is a second constant which is a function of,
Figure FDA0003573181350000015
step three, collecting test data of key parameters;
step four, carrying out primary elimination and secondary elimination treatment on the test data in sequence; obtaining screened test data;
constructing a probability density function F (x);
step six, calculating a consistency evaluation value I of the experimental data; the consistency evaluation value I is calculated by the following method:
Figure FDA0003573181350000016
and seventhly, evaluating the test data of the carrier rocket according to the consistency evaluation value I.
2. A launch vehicle-based evaluation method according to claim 1, characterized in that: in the fourth step, the primary elimination refers to performing outlier detection on the test data and eliminating abnormal values which generate interference.
3. A launch vehicle-based evaluation method according to claim 2, characterized in that: in the fourth step, the secondary elimination refers to substituting the test data as x into the calculation formula of the standard evaluation function p (x), and eliminating the test data when p (x) is 0.
4. A launch vehicle-based evaluation method according to claim 3, characterized in that: in the fifth step, the construction method of the probability density function f (x) comprises the following steps:
step one, calculating the mean value u of the screened test data:
Figure FDA0003573181350000021
in the formula, n is the number of test data;
i is the number of the test data;
step two, calculating the standard deviation sigma of the screened test data:
Figure FDA0003573181350000022
step three, calculating a probability density function F (x):
Figure FDA0003573181350000023
5. a launch vehicle-based evaluation method according to claim 4, characterized in that: in the seventh step, the method for evaluating the test data of the carrier rocket comprises the following steps:
when I is more than or equal to 0.9, the evaluation test data is excellent;
when I is more than or equal to 0.75 and less than 0.9, the evaluation test data is better;
when I is more than or equal to 0.6 and less than 0.75, evaluating the test data as qualified;
when I is less than 0.6, the test data is evaluated as fail.
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