CN106991126A - A kind of computational methods and system of composite B a reference values - Google Patents
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Abstract
The present invention relates to a kind of computational methods and system of composite B a reference values, this method includes：Retrieve and choose composite property data in database；Composite property data are detected, if there is exceptional value in composite property data, exceptional value is modified；If the composite property data more than two for being as good as constant value come from same parent, the composite property data more than two for being as good as constant value are non-structural type data, and B a reference values are calculated using the mode for handling non-structural type data；The system includes acquisition module, detection module, judge module and computing module.The links such as data inputting, the outlier processing in the calculation process of composite B a reference values are improved by the present invention, user's operation is more convenient.
Description
Technical Field
The invention relates to the field of calculation of a composite material B reference value, in particular to a method and a system for calculating the composite material B reference value.
Background
The allowable indexes for evaluating the static performance of the composite material generally adopt a B reference value, and the B reference value is defined as: a limit value for the mechanical properties, the value of the 90% group of values for the properties being not less than the value at a 95% confidence level. The U.S. military manual MIL-HDBK-17-1F teaches a method for calculating the B reference value, after which FAA proposes the latest B reference value calculation method based on previous methods based on long-term usage experience. In China, the aviation industry standard HB 7618-2009 expression criteria for mechanical property data of polymer-based composite materials are compiled by combining the results of the above foreign research.
At present, the automatic calculation of the B reference value of the composite material is generally realized by programming of Matlab and other programs, the method requires user data to be input from a machine where the Matlab computing environment is located, the problems of data format and the like cannot be well solved, a user needs to manually detect the error of the input data in advance, and the efficiency is low. In addition, for Web platforms and distributed computing environments, the Matlab program for local computing is also not able to interface efficiently.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: for the measurement of the B reference value of the composite material, a user needs to manually detect the error of input data in advance, so that the efficiency is low; in order to solve the problems, the invention provides a method and a system for calculating a composite material B reference value.
The technical scheme for solving the technical problems is as follows: a method of calculating a composite B reference value, the method comprising the steps of:
step 1: retrieving and selecting composite material performance data in a database;
step 2: detecting the performance data of the composite material, and if an abnormal value exists in the performance data of the composite material, correcting the abnormal value;
and step 3: and if more than two groups of composite material performance data without abnormal values come from the same matrix, the more than two groups of composite material performance data without abnormal values are non-structural data, and the B reference value is calculated by utilizing a mode of processing the non-structural data.
The invention has the beneficial effects that: aiming at the situation of composite material data in a specific field, links such as data entry, abnormal value processing and the like in the calculation process of the composite material B reference value given in the American military manual are improved, so that the method is more convenient for users to operate.
On the basis of the technical scheme, the invention can be further improved as follows.
Further, the step 2 comprises: and (3) detecting the abnormal value by adopting a maximum normalized residual error detection method, finding out the abnormal reason of the abnormal value detected by the maximum normalized residual error detection method by combining visual inspection, and correcting the abnormal value according to the abnormal reason until all the abnormal values are corrected.
Further, the composite material performance data comprises a manufacturer name, a material type, a material specification, a performance test type, a performance parameter, a test start date and a test end date.
Further, the step 3 comprises:
step 3.1: judging whether more than two groups of composite material performance data without abnormal values are from the same matrix, if so, calculating a B reference value by utilizing a mode of processing non-structural data, executing the step 3.2, otherwise, calculating the B reference value by utilizing a mode of processing structural data, and executing the step 3.3;
step 3.2: whether the performance data of the composite material accord with Weibull distribution or not is checked, if the performance data of the composite material accord with the Weibull distribution, the performance data of the non-structural composite material is calculated by adopting a Weibull method, and a B reference value is obtained;
step 3.3: and judging whether the variances among all groups of composite material performance data are equal through Leven inspection, if so, calculating the structural composite material performance data by adopting an analysis of variance method to obtain a B reference value, otherwise, failing to calculate the output B reference value, and finishing the calculation.
Further, the step 3.2 further comprises: if the composite material performance data do not accord with Weibull distribution, performing normal distribution test on the composite material performance data, if the composite material performance data meet the normal distribution, calculating the non-structural composite material performance data by adopting a normal distribution method to obtain a B reference value, if not, performing lognormal distribution test on the composite material performance data, if the composite material performance data meet the lognormal distribution, calculating the non-structural composite material performance data by adopting a lognormal distribution method to obtain a B reference value, and if not, calculating the non-structural composite material performance data by adopting a non-parametric method to obtain a B reference value.
Further, said step 3.1 comprises the steps of:
step 3.1.1: assuming that different sets of composite property data are independent random samples from the same matrix;
step 3.1.2: calculating Anderson-Darling statistic ADK and critical value ADC of K groups of samples, wherein K is more than or equal to 2;
step 3.1.3: if ADK is less than ADC, the hypothesis in the step 3.1.1 is received, the performance data of each group of composite materials are combined, a B reference value is calculated by utilizing a mode of processing non-structural data, and the step 3.2 is executed; if ADK is greater than or equal to ADC, the performance data of each group of composite materials can be judged to come from different matrixes, and step 3.3 is executed.
The other technical scheme provided by the invention is as follows: a system for calculating a B reference value of a composite material comprises an acquisition module, a detection module, a judgment module and a calculation module;
the acquisition module is used for retrieving and selecting the composite material performance data in the database;
the detection module is used for detecting the composite material performance data, and if an abnormal value exists in the composite material performance data, the abnormal value is corrected.
The judging module is used for judging whether more than two groups of abnormal-value-free composite material performance data are non-structural data if the more than two groups of abnormal-value-free composite material performance data are from the same parent body;
and the calculating module is used for calculating the B reference value by utilizing a mode of processing the non-structural data.
Further, the composite material performance data comprises manufacturer name, material type, material specification, performance test type, performance parameter, test start date and test end date
Further, the detection module is further configured to perform abnormal value detection by using a maximum normalized residual error detection method, find out an abnormal cause of the abnormal value detected by the maximum normalized residual error detection method, and correct the abnormal value according to the abnormal cause until all the abnormal values are corrected.
Further, the system further comprises an output module, wherein the output module is used for outputting the calculation result of the B reference value.
Drawings
Fig. 1 is a schematic flow chart of a method for calculating a reference value of B in a composite material according to the present invention.
Detailed Description
The principles and features of this invention are described below in conjunction with the following drawings, which are set forth by way of illustration only and are not intended to limit the scope of the invention.
As shown in fig. 1, a method for calculating a reference value of a composite material B according to an embodiment of the present invention includes the following steps:
step 1: retrieving and selecting composite material performance data in a database;
step 2: detecting the performance data of the composite material, and if an abnormal value exists in the performance data of the composite material, correcting the abnormal value;
and step 3: and if more than two groups of composite material performance data without abnormal values come from the same matrix, the more than two groups of composite material performance data without abnormal values are non-structural data, and the B reference value is calculated by utilizing a mode of processing the non-structural data.
Wherein, step 2 includes: and (3) detecting the abnormal value by adopting a maximum normalized residual error detection method, finding out the abnormal reason of the abnormal value detected by the maximum normalized residual error detection method by combining visual inspection, and correcting the abnormal value according to the abnormal reason until all the abnormal values are corrected.
The detection of data outliers was calculated using the maximum normalized residual test (MNR) according to the method given in the MIL-HDBK-17 specification, based on the following assumptions: observations that are not anomalous data can be viewed as a random sample from some normal parent.
The statistical test can only detect one abnormal datum at a time, and for small samples, such as a group containing 5 to 6 data, the method may identify most of the data as abnormal, especially when two or more of them are equal. Therefore, the inspection of the abnormal data should be combined with the visual inspection, and if the abnormal data detected by the MNR method is not found, the original data is required to be retained.
For a given sample x1,x2,......,xnThe MNR statistic is:
for a threshold value CV with a sample capacity n and a significant level α:
and comparing the MNR statistic with the CV, and if the MNR is larger than the CV, determining that the corresponding value is an abnormal value. The invention displays all the selected data in a table form on an abnormal value detection page, and particularly marks the cell where the abnormal value data is positioned with red so as to facilitate the user to carry out abnormal value correction next.
The abnormal value correction is completed by manual inspection and manual correction of a user, a function of temporarily correcting any data is provided on an abnormal value correction page, the correction cannot be stored in a database, and only the calculation use of a single B reference value is met, so that the integrity of original test data is effectively reserved on the basis of ensuring the smooth calculation of the single B reference value.
Every time the user modifies the data, the invention automatically executes the abnormal value detection algorithm again, and uses the newly obtained data rerun program MNR to detect the abnormal value of the whole data again. When the user finds out the reasons of all abnormal data and modifies or deletes all the abnormal data, the abnormal data can not be detected, and the abnormal value detection and modification link is finished.
The composite material performance data comprises manufacturer name, material type, material specification, performance test type, performance parameter, test starting date and test ending date.
Wherein, the method also comprises: and outputting the calculation result of the B reference value.
Wherein, step 3 includes:
step 3.1: judging whether more than two groups of composite material performance data without abnormal values are from the same matrix, if so, calculating a B reference value by utilizing a mode of processing non-structural data, executing the step 3.2, otherwise, calculating the B reference value by utilizing a mode of processing structural data, and executing the step 3.3;
step 3.2: whether the performance data of the composite material accord with Weibull distribution or not is checked, if the performance data of the composite material accord with the Weibull distribution, the performance data of the non-structural composite material is calculated by adopting a Weibull method, and a B reference value is obtained;
weibull distribution test and calculation of B reference value under the distribution:
theory indicates that Weibull distribution is suitable for simulating brittle materials; the 'beam chain' strength model of the two-dimensional and three-dimensional unidirectional composite material shows that the Weibull distribution is suitable for the strength distribution of the composite material; therefore, the Weibull distribution test was preferentially performed.
For a set of data x1,x2,......,xnThe shape parameters α and scale parameters β of the Weibull distribution first need to be estimated by the following system of equations:
calculate the Anderson-Darling statistic:
wherein
Calculating the observed significance level OSL:
OSL＝1/{1+exp[-0.10+1.24ln(AD*)+4.48AD*]}；
wherein
If OSL is less than or equal to 0.05, it can be concluded (5% risk of misjudgment) that the parent does not conform to Weibull distribution; otherwise, the assumption that the parent conforms to the two-parameter Weibull distribution holds.
The B baseline values at Weibull distribution are:
whereinV is obtained by looking up a table.
Step 3.3: and judging whether the variances among all groups of composite material performance data are equal through Leven inspection, if so, calculating the structural composite material performance data by adopting an analysis of variance method to obtain a B reference value, otherwise, failing to calculate the output B reference value, and finishing the calculation.
The Leven test:
for k (k is more than or equal to 3) groups of data, each data is marked as XijWherein i is the group number i ═ 1, 2, … …, k; j is the number of observations in a group of j-1, 2, … …,
each data within the group is transformed:
wherein,n in the ith groupiMedian of values
Calculating the F value:
if the F value is equal to or less than the 1- α quantile (α ═ 0.05) of the F distribution with a numerator degree of freedom k-1 and a denominator degree of freedom n-k, the B value is calculated by the ANOVA method after the test of the equal variance.
One-way analysis of variance ANOVA method and calculation of B reference value:
calculating aggregate statistics including the batch mean, the total mean, the inter-batch mean squared MSB and the intra-batch mean squared MSE, thereby obtaining a parent standard deviation S as:
calculating a tolerance coefficient T:
b baseline under analysis of variance:
wherein, step 3.2 still includes: if the composite material performance data do not accord with Weibull distribution, performing normal distribution test on the composite material performance data, if the composite material performance data meet the normal distribution, calculating the non-structural composite material performance data by adopting a normal distribution method to obtain a B reference value, if not, performing lognormal distribution test on the composite material performance data, if the composite material performance data meet the lognormal distribution, calculating the non-structural composite material performance data by adopting a lognormal distribution method to obtain a B reference value, and if not, calculating the non-structural composite material performance data by adopting a non-parametric method to obtain a B reference value.
Normal distribution test and calculation of B reference value under the distribution:
for a set of data x1,x2,......,xnArranged incrementally as x(1),x(2),......,x( n)
Calculate the Anderson-Darling statistic AD:
whereinF0Is a standard normal distribution function.
Observation of significance level OSL: OSL 1/{1+ exp [ -0.48+0.781ln (AD)*)+4.58AD*]}；
Wherein, AD*＝(1+4/n-25/n2)AD。
If OSL is less than or equal to 0.05, it can be concluded (5% risk of misjudgment) that the parent does not fit normal distribution; otherwise, the assumption that the mother fits a normal distribution holds.
The B reference value under normal distribution is:
wherein k isBThe single-side tolerance coefficient can be known by looking up a table;
and (3) carrying out logarithmic normal distribution test and calculating a B reference value under the distribution:
for a set of data x1,x2,......,xnThe natural logarithm is calculated to obtain a new group of numbers y(1),y(2),......,y(n)Performing normal distribution test on the new array, and if the new array conforms to the normal distribution, determining that the new array is normalGroup B reference value:
the B reference value of the original array under the lognormal distribution is as follows: b isL＝eB。
Non-parametric method and calculation of B reference value under the method:
for a set of data x(1),x(2),......,x(n)First, the value of the sample size n is determined. When n is greater than 28, the rB value is determined by the table lookup, and the rB-th minimum observed value, namely x (rB), is the B reference value. When n is less than 29, using Hanson-Koopmans method, assuming that the observed value is a random sample from a logarithmically concave parent of the cumulative distribution function, then the B reference value is
Where the r and k values depend on the n value, a look-up table can be derived.
Wherein, step 3.1 comprises the following steps:
step 3.1.1: assuming that different sets of composite property data are independent random samples from the same matrix;
step 3.1.2: calculating Anderson-Darling statistic ADK and critical value ADC of K groups of samples, wherein K is more than or equal to 2;
step 3.1.3: if ADK is less than ADC, the hypothesis in the step 3.1.1 is received, the performance data of each group of composite materials are combined, a B reference value is calculated by utilizing a mode of processing non-structural data, and the step 3.2 is executed; if ADK is greater than or equal to ADC, the performance data of each group of composite materials can be judged to come from different matrixes, and step 3.3 is executed.
The K sample Anderson-Darling test is based on the following assumptions: the test data of different batches are mutually independent random samples from the same population.
For k (k is more than or equal to 2) groups of data, each data is marked as XijWherein i is the group number i ═ 1, 2, … …, k; j is the observation number j ═ 1, 2, … …, ni in a certain group. When performing the k-sample Anderson-Darling test, the k groups of data are first combined, and the total number of the combined data is n, which is n1+ n2+ … … + nk. The merged data are arranged from small to large and are marked as Z(1),Z(2),......，Z(L)If the data is the same, then L is not more than n, n is 1+ n2+ … … + nk.
Calculating k sample Anderson-Darling statistic:
wherein h isjEqual to Z in the merged sample(j)Number of values, Hj＝Z(j)The number of less than the value in the combined sample plus Z in the combined sample(j)Half the number of values, FijI in group i less than Z(j)The number of values plus Z in the group being equal to(j)Half the number of values.
Critical value ADC:
if ADK is larger than or equal to ADC, judging that each group of data comes from different matrixes (with 5% misjudgment risk), and calculating the B value according to structural data; if ADK < ADC, the hypothesis from the same parent is received, each group of data is combined, and B value calculation is carried out according to non-structural data.
The embodiment of the invention also provides a system for calculating the B reference value of the composite material, which comprises an acquisition module, a detection module, a judgment module and a calculation module;
the acquisition module is used for retrieving and selecting the composite material performance data in the database;
the detection module is used for detecting the composite material performance data, and if an abnormal value exists in the composite material performance data, the abnormal value is corrected.
The judging module is used for judging whether more than two groups of abnormal value-free composite material performance data are non-structural data if the more than two groups of abnormal value-free composite material performance data are from the same matrix;
and the calculating module is used for calculating the B reference value by utilizing a mode of processing the non-structural data.
The composite material performance data comprises manufacturer name, material type, material specification, performance test type, performance parameter, test starting date and test ending date.
The detection module is further used for detecting the abnormal values by adopting a maximum normalized residual error detection method, finding out abnormal reasons of the abnormal values detected by the maximum normalized residual error detection method, and correcting the abnormal values according to the abnormal reasons until all the abnormal values are corrected.
The system further comprises an output module, and the output module is used for outputting the calculation result of the B reference value.
Net platform has been adopted to this system and has been developed, uses C # programming language to realize.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
Claims (10)
1. A method for calculating a B reference value of a composite material, which is characterized by comprising the following steps:
step 1: retrieving and selecting composite material performance data in a database;
step 2: detecting the performance data of the composite material, and if an abnormal value exists in the performance data of the composite material, correcting the abnormal value;
and step 3: and if more than two groups of composite material performance data without abnormal values come from the same matrix, the more than two groups of composite material performance data without abnormal values are non-structural data, and the B reference value is calculated by utilizing a mode of processing the non-structural data.
2. The method for calculating the reference value of the composite material B according to claim 1, wherein the step 2 comprises the following steps: and (3) detecting the abnormal value by adopting a maximum normalized residual error detection method, finding out the abnormal reason of the abnormal value detected by the maximum normalized residual error detection method by combining visual inspection, and correcting the abnormal value according to the abnormal reason until all the abnormal values are corrected.
3. The method for calculating the reference value of the composite material B as claimed in claim 1 or 2, wherein the composite material performance data comprises manufacturer name, material type, material specification, performance test type, performance parameter, test start date and test end date.
4. The method for calculating the reference value of B of the composite material according to claim 3, wherein the step 3 comprises the following steps:
step 3.1: judging whether more than two groups of composite material performance data without abnormal values are from the same matrix, if so, calculating a B reference value by utilizing a mode of processing non-structural data, executing the step 3.2, otherwise, calculating the B reference value by utilizing a mode of processing structural data, and executing the step 3.3;
step 3.2: whether the performance data of the composite material accord with Weibull distribution or not is checked, if the performance data of the composite material accord with the Weibull distribution, the performance data of the non-structural composite material is calculated by adopting a Weibull method, and a B reference value is obtained;
step 3.3: and judging whether the variances among all groups of composite material performance data are equal through Leven inspection, if so, calculating the structural composite material performance data by adopting an analysis of variance method to obtain a B reference value, otherwise, failing to calculate the output B reference value, and finishing the calculation.
5. The method for calculating the reference value of B of the composite material according to claim 4, wherein the step 3.2 further comprises the following steps: if the composite material performance data do not accord with Weibull distribution, performing normal distribution test on the composite material performance data, if the composite material performance data meet the normal distribution, calculating the non-structural composite material performance data by adopting a normal distribution method to obtain a B reference value, if not, performing lognormal distribution test on the composite material performance data, if the composite material performance data meet the lognormal distribution, calculating the non-structural composite material performance data by adopting a lognormal distribution method to obtain a B reference value, and if not, calculating the non-structural composite material performance data by adopting a non-parametric method to obtain a B reference value.
6. The method for calculating the reference value of B of the composite material according to claim 4 or 5, wherein the step 3.1 comprises the following steps:
step 3.1.1: assuming that different sets of composite property data are independent random samples from the same matrix;
step 3.1.2: calculating Anderson-Darling statistic ADK and critical value ADC of K groups of samples, wherein K is more than or equal to 2;
step 3.1.3: if ADK is less than ADC, the hypothesis in the step 3.1.1 is received, the performance data of each group of composite materials are combined, a B reference value is calculated by utilizing a mode of processing non-structural data, and the step 3.2 is executed; if ADK is greater than or equal to ADC, the performance data of each group of composite materials can be judged to come from different matrixes, and step 3.3 is executed.
7. The system for calculating the B reference value of the composite material is characterized by comprising an acquisition module, a detection module, a judgment module and a calculation module;
the acquisition module is used for retrieving and selecting the composite material performance data in the database;
the detection module is used for detecting the performance data of the composite material, and if an abnormal value exists in the performance data of the composite material, the abnormal value is corrected;
the judging module is used for judging whether more than two groups of abnormal-value-free composite material performance data are non-structural data if the more than two groups of abnormal-value-free composite material performance data are from the same parent body;
and the calculating module is used for calculating the B reference value by utilizing a mode of processing the non-structural data.
8. The system for calculating the B reference value of the composite material as claimed in claim 7, wherein the composite material performance data comprises manufacturer name, material type, material specification, performance test type, performance parameter, test start date and test end date.
9. The system for calculating the reference value of the composite material B as claimed in claim 8, wherein the detection module is further configured to perform the abnormal value detection by using a maximum normalized residual error detection method, find out the abnormal cause of the abnormal value detected by the maximum normalized residual error detection method, and correct the abnormal value according to the abnormal cause until all the abnormal values are corrected.
10. The system for calculating the B reference value of the composite material according to any one of claims 7 to 9, wherein the system further comprises an output module, and the output module is used for outputting the calculation result of the B reference value.
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| CN112464484A (en) * | 2020-12-04 | 2021-03-09 | 上海波客实业有限公司 | Statistical analysis method of composite material |
| CN112560265A (en) * | 2020-12-15 | 2021-03-26 | 北京动力机械研究所 | Method and device for calculating B reference value of composite material |
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Application publication date: 20170728 |