CN115077618A - Quality detection method and system for nuclear-grade alloy steel elbow - Google Patents
Quality detection method and system for nuclear-grade alloy steel elbow Download PDFInfo
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Abstract
The invention provides a quality detection method and a system for a nuclear-grade alloy steel elbow, and relates to the technical field of alloy detection, wherein the method comprises the following steps: determining a use parameter threshold value based on the nuclear-grade alloy steel elbow application environment information; obtaining multi-dimensional parameter information of the nuclear-grade alloy steel elbow, classifying the multi-dimensional parameter information based on scene use characteristic requirements, constructing a parameter classification data set, and determining a use characteristic classification weight analysis result by using an analytic hierarchy process; and determining a use parameter calculation result based on the use characteristic classification weight analysis result and the parameter classification data set, and determining whether the nuclear-grade alloy steel elbow is qualified or not according to the use parameter calculation result and the use parameter threshold. The technical problems that in the prior art, quality detection of the nuclear-grade alloy steel elbow depends on manual detection, the detection process is complicated and time-consuming, and the detection result has subjective errors are solved. The technical effect that whether the nuclear-grade alloy steel elbow meets the use requirement of an application scene or not can be accurately obtained according to the detection result is achieved.
Description
Technical Field
The invention relates to the technical field of alloy detection, in particular to a quality detection method and system for a nuclear-grade alloy steel elbow.
Background
Elbows are connecting elements used to change the direction of a pipe in a piping system. In order to meet the requirement of changing the angles of different pipeline directions, the elbow is cast and produced according to the bending angle. In the use process of the pipeline, the flow speed change of fluid and gas transported in the pipeline generates impact action on the elbow when the fluid and the gas flow through the elbow part due to the change of the flow direction, corrosive fluid and gas can also generate corrosion damage on the elbow, and the alloy is widely applied to the elbow production due to good corrosion resistance and impact deformation resistance.
In order to avoid pipeline leakage caused by the erosion damage of impact force and corrosive substances in the use process of the alloy steel elbow, the production specification requirements are carried out according to the use scene during the production and quality inspection of the alloy steel elbow, and the qualified quality inspection is correspondingly carried out. Compared with the steering elbow of civil industrial pipelines and urban water drainage pipelines, the steering alloy steel elbow for nuclear power production has stricter quality inspection requirements.
The quality detection of the nuclear-grade alloy steel elbow depends on manual detection, the detection process is complicated and time-consuming, and the detection result has subjective errors, so that the accuracy of the detection result of the nuclear-grade alloy steel elbow is low, and the service life and the safety of a spliced pipeline are affected.
Disclosure of Invention
The application provides a quality detection method and system for a nuclear-grade alloy steel elbow, which are used for solving the technical problems that in the prior art, quality detection of the nuclear-grade alloy steel elbow depends on manual detection, the detection process is complicated and time-consuming, and the detection result has subjective errors, so that the accuracy of the detection result of the nuclear-grade alloy steel elbow is low, and the service life and the safety of a spliced pipeline are influenced.
In view of the above problems, the present application provides a quality detection method and system for a nuclear grade alloy steel elbow.
In a first aspect of the application, a quality detection method for a nuclear-grade alloy steel elbow is provided, and the method comprises the following steps: obtaining application environment information of the nuclear-grade alloy steel elbow, carrying out environment use characteristic analysis based on the application environment information, and determining a scene use characteristic requirement; determining a usage parameter threshold based on the scene usage characteristic requirement; carrying out multi-dimensional parameter detection on the nuclear-grade alloy steel elbow to obtain multi-dimensional parameter information, wherein the multi-dimensional parameter information comprises appearance parameter information, size parameter information and performance parameter information; classifying the appearance parameter information, the size parameter information and the performance parameter information based on the scene use characteristic requirements to construct a parameter classification data set; carrying out weight analysis on all parameters in the parameter classification data set by using an analytic hierarchy process to determine a characteristic classification weight analysis result; performing parameter operation based on the use characteristic classification weight analysis result and the parameter classification data set, and determining a use parameter calculation result; and judging whether the use parameter calculation result meets the use parameter threshold value, wherein the quality detection result is qualified when the use parameter calculation result meets the use parameter threshold value, and the quality detection result is unqualified when the use parameter calculation result does not meet the use parameter threshold value.
In a second aspect of the present application, a quality inspection system for a nuclear grade alloy steel elbow is provided, the system comprising: the scene characteristic generation module is used for obtaining application environment information of the nuclear-grade alloy steel elbow, analyzing environment use characteristics based on the application environment information and determining the scene use characteristic requirement; a usage parameter determination module for determining a usage parameter threshold based on the scene usage characteristic requirement; the parameter information acquisition module is used for carrying out multi-dimensional parameter detection on the nuclear-grade alloy steel elbow to acquire multi-dimensional parameter information, wherein the multi-dimensional parameter information comprises appearance parameter information, size parameter information and performance parameter information; the parameter classification execution module is used for classifying the appearance parameter information, the size parameter information and the performance parameter information based on the scene use characteristic requirements to construct a parameter classification data set; the weight analysis assignment module is used for carrying out weight analysis on all parameters in the parameter classification data set by utilizing an analytic hierarchy process and determining a result of using the feature classification weight analysis; the using parameter calculating module is used for performing parameter operation on the basis of the using characteristic classification weight analysis result and the parameter classification data set and determining a using parameter calculating result; and the quality detection judging module is used for judging whether the use parameter calculation result meets the use parameter threshold value, if so, the quality detection result is qualified, and if not, the quality detection result is unqualified.
One or more technical solutions provided in the present application have at least the following technical effects or advantages:
the method provided by the embodiment of the application comprises the steps of obtaining application environment information of the nuclear-grade alloy steel elbow, carrying out environment use characteristic analysis based on the application environment information, and determining a scene use characteristic requirement; determining a usage parameter threshold based on the scene usage characteristic requirement; and a comparison reference is provided for subsequently judging whether the nuclear-grade alloy steel elbow meets the use requirement of an application scene. Carrying out multi-dimensional parameter detection on the nuclear-grade alloy steel elbow to obtain multi-dimensional parameter information, obtaining composition information related to physical and chemical performance characteristics of the nuclear-grade alloy steel elbow, classifying the appearance parameter information, the size parameter information and the performance parameter information based on the scene use characteristic requirements, and constructing a parameter classification data set; performing weight analysis on all parameters in the parameter classification data set by using an analytic hierarchy process to determine a used feature classification weight analysis result, and performing parameter operation on the parameter classification data set based on the used feature classification weight analysis result to determine a used parameter calculation result; and determining the multidimensional parameters of the nuclear-grade alloy steel elbow and the correlation between the multidimensional parameters and the application characteristics of the nuclear-grade alloy steel elbow, and providing a data basis for subsequently judging whether the nuclear-grade alloy steel elbow meets the application scene requirements. And judging the numerical value relationship between the use parameter calculation result and the use parameter threshold value, and judging whether the quality detection of the nuclear-grade alloy steel elbow is qualified or not, so that the technical effect of accurately knowing whether the nuclear-grade alloy steel elbow meets the use requirement of an application scene according to the detection result is achieved.
Drawings
FIG. 1 is a schematic flow chart of a quality detection method for a nuclear-grade alloy steel elbow provided by the present application;
FIG. 2 is a schematic flow chart illustrating the determination of a threshold value of a use parameter in the quality detection method for a nuclear-grade alloy steel elbow provided by the present application;
FIG. 3 is a schematic flow chart illustrating the consistency test result obtained by the quality testing method for the nuclear-grade alloy steel elbow provided by the present application;
fig. 4 is a schematic structural diagram of a quality detection system for a nuclear-grade alloy steel elbow provided by the present application.
Description of reference numerals: the system comprises a scene characteristic generation module 11, a use parameter determination module 12, a parameter information obtaining module 13, a parameter classification execution module 14, a weight analysis assignment module 15, a use parameter calculation module 16 and a quality detection judgment module 17.
Detailed Description
The application provides a quality detection method and system for a nuclear-grade alloy steel elbow, which are used for solving the technical problems that in the prior art, quality detection of the nuclear-grade alloy steel elbow depends on manual detection, the detection process is complicated and time-consuming, and the detection result has subjective errors, so that the accuracy of the detection result of the nuclear-grade alloy steel elbow is low, and the service life and the safety of a spliced pipeline are influenced.
In view of the above technical problems, the technical solution provided by the present application has the following general idea:
determining a use parameter threshold value of the nuclear-grade alloy steel elbow as a qualified product based on application environment information, determining multi-dimensional parameter information of the nuclear-grade alloy steel elbow through a measuring device and factory information, classifying the multi-dimensional parameter information based on scene use characteristic requirements, constructing a parameter classification data set, and determining a use characteristic classification weight analysis result by using an analytic hierarchy process; and determining a use parameter calculation result based on the use characteristic classification weight analysis result and the parameter classification data set, and determining whether the nuclear-grade alloy steel elbow is qualified or not according to the use parameter calculation result and the use parameter threshold. The technical effect that whether the nuclear-grade alloy steel elbow meets the use requirement of an application scene or not can be accurately obtained according to the detection result is achieved.
Example one
As shown in fig. 1, the present application provides a quality inspection method for a nuclear-grade alloy steel elbow, the method comprising:
s100: obtaining application environment information of the nuclear-grade alloy steel elbow, carrying out environment use characteristic analysis based on the application environment information, and determining a scene use characteristic requirement;
specifically, it should be understood that the nuclear power production flow includes a heat transfer system and a cooling system, which are used for realizing heat exchange in the nuclear power production process. A plurality of coolant conveying straight pipe section pipelines and heat exchange straight pipe section pipelines are arranged in the loop heat transmission system and the shutdown cooling system, and the straight pipe section pipelines are in steering connection through nuclear-grade alloy steel elbows.
The application environment information is a working system to which a pipeline loop formed by connecting a nuclear-grade alloy steel elbow and a straight pipe section belongs in a nuclear power production flow. Illustratively, when the nuclear-grade alloy steel elbow is applied to a cooling system, the application environment of the nuclear-grade alloy steel elbow is a cooling system environment, and the application environment information is that the nuclear-grade alloy steel elbow is in a high-salt high-corrosivity high-impact-pressure environment.
The use scene characteristic requirements are the chemical properties of the fluid which flows through the management system and the physical properties generated when the fluid flows, and the requirements on the physical and chemical properties of the pipeline and the elbow which form the application scene when the pipeline and the elbow are not deformed and damaged. For example, the application scenario usage characteristic requirements may include, but are not limited to, fluid flow rate threshold requirements, fluid corrosivity requirements to be endured by a nuclear grade alloy steel elbow in the circuit.
In this embodiment, the application environment information is preferably a nuclear power component system pipeline, such as a seawater cooling system pipeline of a nuclear power plant, in which fluid in the nuclear power system pipeline has high corrosivity, high fluid flow rate, and high system requirements for a component pipeline, a connecting element, and a pump.
And after obtaining the application environment information of the nuclear-grade alloy steel elbow, performing characteristic analysis on the flow velocity and the chemical property of the fluid flowing through the application environment according to the application environment information, and determining the scene use characteristic requirement.
S200: determining a usage parameter threshold based on the scene usage characteristic requirement;
further, as shown in fig. 2, based on the scene usage characteristic requirement, determining a usage parameter threshold, step S200 of the method provided by the present application further includes:
s210: extracting historical scene use record data based on the scene use characteristic requirement to obtain a historical scene record set;
s220: extracting chemical and physical parameters of the historical scene record set to obtain scene characteristic parameter characteristics, wherein the scene characteristic parameter characteristics comprise structural shape influence characteristics and chemical reaction influence characteristics;
s230: extracting fault record information according to the historical scene record set, analyzing fault parameters based on the fault record information, and determining fault parameter characteristics;
s240: and determining the use parameter threshold according to the structural shape influence characteristic, the chemical reaction influence characteristic and the fault parameter characteristic.
Specifically, the use parameter threshold is a parameter threshold of the nuclear-grade alloy steel elbow in the application environment, which is not cracked or corroded and damaged due to factors such as fluid flow velocity impact, fluid corrosion, fluid temperature change and the like in the application environment, and for example, the use parameter threshold may be composed of multiple pieces of use parameter threshold information, including but not limited to a temperature resistance threshold, a corrosion resistance threshold and a shock pressure resistance threshold.
Generating a retrieval instruction based on the scene use characteristic requirement, obtaining historical scene use record data corresponding to the scene use characteristic requirement in historical scene use data, and obtaining a historical scene record set, wherein the historical scene record set comprises impact pressure parameters of fluid flowing through the application scene at the position where the direction of the fluid pipeline changes under different working conditions, steering elbows at the steering positions, chemical erosion parameters of the whole pipeline system and temperature parameters.
And extracting chemical and physical parameters from the historical scene record set to obtain scene characteristic parameter characteristics, wherein the scene characteristic parameter characteristics comprise structural shape influence characteristics and chemical reaction influence characteristics on the elbow under different chemical and physical parameter combinations.
Traversing the historical scene record set to obtain fault record information extraction, obtaining chemical information (pH value) of fluid in the pipeline with corresponding relation when a plurality of groups of pipelines with elbow damage stop pendulum based on the fault record information, analyzing fault parameters and determining fault parameter characteristics, wherein the chemical information comprises impact pressure of the fluid on the elbow at the elbow, the inner diameter of the elbow, the bending angle and the material information of the elbow; and determining the use parameter threshold according to the structural shape influence characteristic, the chemical reaction influence characteristic and the fault parameter characteristic.
For example, the usage parameter threshold may be a corrosion resistance parameter threshold: the nuclear-grade alloy steel elbow normally works at the temperature of 270 ℃ and the pH value of the fluid is higher than PH 2; impact resistance parameter threshold: the pressure generated by the flow velocity of the fluid is below 2.7Mpa, and the nuclear-grade alloy steel elbow normally works.
According to the method, the structural form and the fluid physicochemical property of the elbow at the historical fault position under the same use scene are obtained by combining the historical scene use data records, the structural form and the physicochemical property requirements which the nuclear-grade alloy steel elbow should have without working condition faults under the application scene are obtained, the reference standard for subsequently detecting whether the current nuclear-grade alloy steel elbow is qualified or not is provided, and the technical effect of avoiding the qualified and misjudged detection based on artificial subjective experience detection is achieved.
S300: carrying out multi-dimensional parameter detection on the nuclear-grade alloy steel elbow to obtain multi-dimensional parameter information, wherein the multi-dimensional parameter information comprises appearance parameter information, size parameter information and performance parameter information;
particularly, it should be understood that the nuclear power main pipeline is driven by the main pump to convey reactor coolant to form forced thermal circulation between a reactor and an evaporator, and under a rated working condition, the appearance, the size and the performance of the nuclear grade alloy steel elbow are beneficial to reducing impact pressure generated when fluid flows through the elbow, delaying the erosion action of the fluid on an anti-erosion coating or an alloy material of the elbow and reducing the influence degree of temperature difference change on the deformation of the elbow.
In this embodiment, multidimensional parameter detection is performed on the nuclear-grade alloy steel elbow to obtain multidimensional parameter information. The appearance parameter information is the elbow bending angle parameter and the elbow length parameter of the nuclear-grade alloy steel elbow obtained through an ultrasonic image acquisition technology, the size parameter information is the elbow thickness data of the nuclear-grade alloy steel elbow and the inner diameter and outer diameter data of the elbow section obtained through a distance measuring device or an electronic measuring device, and the performance parameters are the alloy steel elbow metal composition, the surface coating thickness, the coating corrosion resistance and other parameters obtained based on the factory instructions of the nuclear-grade alloy steel elbow.
S400: classifying the appearance parameter information, the size parameter information and the performance parameter information based on the scene use characteristic requirements to construct a parameter classification data set;
further, based on the scene usage characteristic requirement, classifying the appearance parameter information, the size parameter information, and the performance parameter information, and constructing a parameter classification dataset, where the method provided in this application further includes step S400:
s410: carrying out use parameter clustering on the scene use characteristic requirements to obtain a scene use characteristic clustering result;
s420: determining scene clustering characteristics based on the scene usage characteristic clustering results;
s430: extracting the appearance parameter information, the size parameter information and the performance parameter information based on the scene clustering characteristics, and marking the appearance parameter information, the size parameter information and the performance parameter information according to the scene clustering characteristics according to the characteristic extraction result;
s440: and classifying according to the clustering characteristics of the mark identification parameter information to construct the parameter classification data set.
Specifically, as can be seen from step S100, the usage scenario characteristic requirements are the chemical properties of the fluid flowing through the management system and the physical properties of the fluid flowing through the management system, and the physical and chemical properties of the pipeline and the elbow forming the application scenario are required when the pipeline and the elbow are not deformed and damaged.
Determining the functional types of the nuclear-grade alloy steel elbows required to be exerted under the requirements of the scene use characteristics, performing cluster analysis on the scene use characteristics, and determining that the nuclear-grade alloy steel elbows maintain the original working performance and the properties of corrosion resistance, pit impact resistance, chemical reaction resistance and the like which the working parameters should have under the requirements of the scene use characteristics, wherein the properties of the nuclear-grade alloy steel elbows are the scene use characteristic clustering results obtained by using parameter distances.
The scene clustering characteristics are determined based on the scene use characteristic clustering result, and the method is used for analyzing the relevance between the properties of corrosion resistance, pit impact resistance, physical deformation resistance and the like of the nuclear-grade alloy steel elbow and the appearance parameter information, the size parameter information and the performance parameter information of the nuclear-grade alloy steel elbow.
Performing characteristic analysis on the appearance parameter information, wherein the appearance parameters are related to the flow velocity of fluid flowing through the nuclear-grade alloy steel elbow, namely the corrosion resistance and the pressure resistance of the nuclear-grade alloy steel elbow; carrying out characteristic analysis on the dimensional parameter information, wherein the dimensional parameter information is related to the flow velocity and the pressure intensity of fluid flowing through the nuclear-grade alloy steel elbow, namely the dimensional parameter information is related to the corrosion resistance, the pressure resistance and the chemical reaction resistance of the nuclear-grade alloy steel elbow; and performing characteristic analysis on the performance parameter information, wherein the performance parameters essentially determine whether the elbow is corroded, deformed or damaged due to the influence of the temperature, the pH value and the flow speed of the fluid when the elbow flows through the nuclear-grade alloy steel elbow, namely the performance parameters are related to the corrosion resistance, the pressure resistance and the deformation resistance of the nuclear-grade alloy steel elbow.
Illustratively, the nuclear-grade alloy steel elbow has corrosion resistance, the flow speed of fluid flowing through the nuclear-grade alloy steel elbow part is high, the contact time with the elbow part is short, and the elbow metal or the coating has the corrosion resistance, so that appearance parameter information and performance parameter information are marked according to the corrosion resistance of the nuclear-grade alloy steel elbow.
Extracting the appearance parameter information, the size parameter information and the performance parameter information based on the scene clustering characteristics, and marking the appearance parameter information, the size parameter information and the performance parameter information according to the scene clustering characteristics according to the characteristic extraction result; and classifying according to the clustering characteristics of the mark identification parameter information to construct the parameter classification data set. The parameter classification data set takes performances as a division standard, and each performance comprises one or more items of parameter information.
According to the embodiment, the parameter information enabling the nuclear-grade alloy steel elbow to have the corresponding difference function is determined by analyzing the difference of the requirements of different application scenes on the functional characteristics of the nuclear-grade alloy steel elbow, and the technical effect of accurately obtaining the correlation between the appearance, the size and the performance parameters and the functional characteristics of the nuclear-grade alloy steel elbow when the nuclear-grade alloy steel elbow has the corresponding functions under the requirements of different application scenes is achieved.
S500: carrying out weight analysis on all parameters in the parameter classification data set by using an analytic hierarchy process to determine a characteristic classification weight analysis result;
further, an analytic hierarchy process is used to perform weight analysis on all parameters in the parameter classification data set, and a result of using the feature classification weight analysis is determined, where the method provided in this application further includes step S500:
s510: respectively constructing a hierarchical structure model of each classified data set according to the parameter classified data sets, wherein the hierarchical structure model comprises a target layer, an index layer and a weight distribution scheme layer, the target layer is a scene clustering feature, and the index layer is a parameter classified data set corresponding to the scene clustering feature;
s520: constructing a pair comparison matrix of each layer for each factor of the previous layer based on a pair comparison method and a 1-9 scale setting method;
s530: carrying out consistency check on the paired comparison matrixes to obtain a consistency check result;
s540: when the consistency check result meets the requirement, performing matrix weight operation according to the paired comparison matrixes to determine single-layer index weight;
s550: and performing probability operation on the target layer based on the single-layer index weight to obtain the use characteristic classification weight analysis result.
The analytic hierarchy process is a decision-making process which decomposes elements related to decision-making into levels of targets, criteria, schemes and the like and performs qualitative and quantitative analysis on the basis. Specifically, in this embodiment, the analytic hierarchy process decomposes elements related to whether the nuclear-grade alloy steel elbow in the application scene is qualified or not into the target layer, the index layer, and the weight distribution scheme layer, and the target layer, the index layer, and the weight distribution scheme layer form the hierarchical structure model. The target layer is a scene clustering feature, and the index layer is a parameter classification data set corresponding to the scene clustering feature.
The paired comparison method is to compare indexes in the index set in a pairwise comparison mode. The 1-9 scale setting method is a numerical scale of importance degrees of two factors compared according to a pairwise comparison method, and the influence degree difference of the two factors participating in pairwise comparison on the factor of the previous layer is larger along with the increase of the numerical scale.
Illustratively, a scale of 1 indicates that two factors have the same degree of importance compared to each other, a scale of 9 indicates that two factors are compared and that one factor is extremely important compared to the other, and if the scale of A factor compared to B factor is 3, then it represents that B and A are compared to 1/3.
In this embodiment, a pair comparison matrix of each layer for each factor of the previous layer is constructed based on a pair comparison method and a 1-9 scale setting method, and illustratively, when the scene clustering feature of the target layer is pit corrosivity, the parameter classification data set corresponding to the scene clustering feature may include appearance parameter information, size parameter information, and performance parameter information. Obtaining values of the appearance parameter information, the size parameter information and the performance parameter information by adopting a pairwise comparison method and combining a 1-9 scale setting method, constructing an importance degree judgment matrix, calculating the relative weight of the compared elements to the criterion by the judgment matrix, and carrying out consistency check to obtain a consistency check result; when the consistency check result meets the requirement, performing matrix weight operation according to the paired comparison matrixes to determine single-layer index weight; and performing probability operation on the target layer based on the single-layer index weight to obtain the use characteristic classification weight analysis result.
In the embodiment, by using an analytic hierarchy process to perform weight analysis on all parameters in the parameter classification data set and determine the result of using the feature classification weight analysis, the technical effect of providing a data basis for subsequently obtaining the result of using parameter calculation by combining the parameter classification data set to judge whether the nuclear-grade alloy steel elbow meets the performance requirement of the current application scene is achieved.
S600: performing parameter operation based on the use characteristic classification weight analysis result and the parameter classification data set, and determining a use parameter calculation result;
s700: and judging whether the use parameter calculation result meets the use parameter threshold value, wherein the quality detection result is qualified when the use parameter calculation result meets the use parameter threshold value, and the quality detection result is unqualified when the use parameter calculation result does not meet the use parameter threshold value.
Specifically, in this embodiment, the usage parameter calculation result is each usage parameter of the nuclear-grade alloy steel elbow to be detected, which is obtained based on actual calculation, and may be a specific numerical value, or may be a data set composed of a plurality of usage parameters. Performing parameter operation based on the use characteristic classification weight analysis result and the parameter classification data set, determining a use parameter calculation result, comparing the use parameter calculation result with the use parameter threshold determined in step S200, if the use parameter calculation result falls within the use parameter threshold range, it indicates that the nuclear grade alloy steel elbow to be detected can be stably used in a preset application scene without occurrence of accidents of corrosion deformation and the like, which reduce the use safety of a loop, otherwise, if the use parameter calculation result does not fall within the use parameter threshold range, it indicates that the nuclear grade alloy steel elbow to be detected does not meet the use requirements of the preset application scene, and the quality detection result is unqualified.
The method provided by the embodiment comprises the steps of obtaining application environment information of the nuclear-grade alloy steel elbow, carrying out environment use characteristic analysis based on the application environment information, and determining a scene use characteristic requirement; determining a usage parameter threshold based on the scene usage characteristic requirement; and a comparison reference is provided for subsequently judging whether the nuclear-grade alloy steel elbow meets the use requirement of an application scene. Carrying out multi-dimensional parameter detection on the nuclear-grade alloy steel elbow to obtain multi-dimensional parameter information, obtaining composition information related to physical and chemical performance characteristics of the nuclear-grade alloy steel elbow, classifying the appearance parameter information, the size parameter information and the performance parameter information based on the scene use characteristic requirements, and constructing a parameter classification data set; performing weight analysis on all parameters in the parameter classification data set by using an analytic hierarchy process to determine a used feature classification weight analysis result, and performing parameter operation on the parameter classification data set based on the used feature classification weight analysis result to determine a used parameter calculation result; and determining the multidimensional parameters of the nuclear-grade alloy steel elbow and the correlation between the multidimensional parameters and the application characteristics of the nuclear-grade alloy steel elbow, and providing a data basis for subsequently judging whether the nuclear-grade alloy steel elbow meets the application scene requirements. And judging the numerical value relationship between the use parameter calculation result and the use parameter threshold value, and judging whether the quality detection of the nuclear-grade alloy steel elbow is qualified or not, so that the technical effect of accurately knowing whether the nuclear-grade alloy steel elbow meets the use requirement of an application scene according to the detection result is achieved.
Further, as shown in fig. 3, a consistency check is performed on the pair of comparison matrices to obtain a consistency check result, and step S530 of the method provided by the present application further includes:
s531: calculating a maximum eigenvalue and an eigenvector corresponding to the maximum eigenvalue for each pair comparison matrix;
s532: calculating a consistency index based on the maximum feature value;
s533: continuously matching from a preset table based on the consistency index, determining an average random consistency index, and obtaining a consistency ratio according to the average random consistency index and the consistency index;
s534: and when the consistency ratio meets a preset requirement, the consistency test result is that the consistency test is met.
It should be understood that the target layer is a plurality of scene clustering features, and therefore, a pair comparison method and a 1-9 scale setting method are performed on the scene classification parameter set of each scene clustering feature to construct a pair comparison matrix of the scene classification parameters corresponding to the scene clustering layer. Calculating a maximum eigenvalue and an eigenvector corresponding to the maximum eigenvalue for each pair of comparison matrices; and calculating a consistency index based on the maximum characteristic value.
The predetermined table is a standard R for finding out the consistency of the proposed paired comparison matrix A from related data 1 ，R 1 Called the average random consistency index, is only related to the matrix order n. Exemplary when n ═ 1, R 1 Corresponds to 0; when n is 2, R 1 The correspondence is 0; when n is 2, R 1 Corresponds to 0; when n is 3, R 1 Corresponds to 0.58; when n is 4, R 1 Corresponds to 0.90; when n is 5, R 1 Corresponding to 1.12; when n is 6, R 1 Corresponds to 1.24; when n is 7, R 1 Corresponds to 1.32; when n is 8, R 1 Corresponds to 1.41; when n is 9, R 1 Corresponding to 1.45.
And continuously matching from a preset table based on the consistency index, determining an average random consistency index, obtaining a consistency ratio according to the average random consistency index and the consistency index, and when the consistency ratio meets a preset requirement, obtaining a consistency test result that the consistency test is met.
In the embodiment, consistency check is performed on each scene clustering characteristic before weight calculation, so that the situation that the weight calculation result deviates from the actual weight value due to the fact that the judgment matrix constructed in the embodiment is greatly different from the consistency matrix and the weight calculation is performed on the basis of the non-consistency matrix is avoided.
Further, step S540 of the method provided by the present application further includes:
s541: judging whether the paired comparison matrixes are consistent matrixes or not, wherein the consistent matrixes are matrixes with multiple relations among rows and columns;
s542: when the paired comparison matrix is the uniform matrix, performing mean calculation by using any column vector;
s543: and determining the single-layer index weight according to the column vector mean value.
Further, performing probability operation on the target layer based on the single-layer index weight to obtain the result of using the feature classification weight analysis, where step S550 of the method provided by the present application further includes:
s551: determining a first weight vector of the index layer to the target layer;
s552: obtaining a second weight vector of the weight distribution scheme layer to the index layer;
s553: and obtaining the use feature classification weight analysis result according to the product of the first weight vector and the second weight vector.
Specifically, the method for determining whether the pair comparison matrix is a consistent matrix is to observe whether each row in the determination matrix corresponding to each constructed scene clustering feature satisfies a multiple relationship, and when the multiple relationship exists between the rows of the determination matrix, it is stated that the determination matrix is a consistent matrix. And based on the consistent arrays of the clustering features of all scenes, carrying out mean value calculation by utilizing any column vector, and taking the mean value calculation result as single-layer index weight.
The weight vector is a new column vector obtained by multiplying the judgment matrix according to rows, each vector of the new vector is opened to the power of n, and geometric mean normalization is carried out on the vectors to generate the weight vector. Determining a first weight vector of the index layer to the target layer, and obtaining a second weight vector of the weight distribution scheme layer to the index layer; and obtaining the use feature classification weight analysis result according to the product of the first weight vector and the second weight vector.
In the embodiment, a characteristic value method is adopted, and when the consistency of the matrix is judged to be acceptable, normalization processing is performed based on the maximum characteristic value of the judgment matrix and the corresponding characteristic vector to obtain the use characteristic weight analysis result, so that the technical effect of providing a data base for subsequently obtaining the use parameter calculation result by combining the parameter classification data set to judge whether the nuclear-grade alloy steel elbow meets the performance requirement of the current application scene is achieved.
Example two
Based on the same inventive concept as the quality detection method for the nuclear-grade alloy steel elbow in the previous embodiment, as shown in fig. 4, the present application provides a quality detection system for the nuclear-grade alloy steel elbow, wherein the system includes:
the scene characteristic generation module 11 is used for obtaining application environment information of the nuclear-grade alloy steel elbow, performing environment use characteristic analysis based on the application environment information, and determining a scene use characteristic requirement;
a usage parameter determination module 12, configured to determine a usage parameter threshold based on the scene usage characteristic requirement;
the parameter information obtaining module 13 is configured to perform multidimensional parameter detection on the nuclear-grade alloy steel elbow to obtain multidimensional parameter information, where the multidimensional parameter information includes appearance parameter information, size parameter information, and performance parameter information;
a parameter classification execution module 14, configured to classify the appearance parameter information, the size parameter information, and the performance parameter information based on the scene usage characteristic requirement, and construct a parameter classification dataset;
the weight analysis assignment module 15 is used for performing weight analysis on all the parameters in the parameter classification data set by using an analytic hierarchy process to determine a feature classification weight analysis result;
a usage parameter calculation module 16, configured to perform parameter calculation based on the usage feature classification weight analysis result and the parameter classification data set, and determine a usage parameter calculation result;
and the quality detection judging module 17 is configured to judge whether the usage parameter calculation result meets the usage parameter threshold, where the quality detection result is qualified when the usage parameter calculation result meets the usage parameter threshold, and the quality detection result is unqualified when the usage parameter calculation result does not meet the usage parameter threshold.
Further, the usage parameter determining module 12 further includes:
the historical data acquisition unit is used for extracting historical scene use record data based on the scene use characteristic requirements to obtain a historical scene record set;
the characteristic parameter acquisition unit is used for extracting chemical and physical parameters of the historical scene record set to obtain scene characteristic parameter characteristics, wherein the scene characteristic parameter characteristics comprise structural shape influence characteristics and chemical reaction influence characteristics;
the fault parameter analysis unit is used for extracting fault record information according to the historical scene record set, analyzing fault parameters based on the fault record information and determining fault parameter characteristics;
and the use parameter determining unit is used for determining the use parameter threshold according to the structural shape influence characteristic, the chemical reaction influence characteristic and the fault parameter characteristic.
Further, the parameter classification executing module 14 further includes:
a clustering result obtaining unit, configured to perform usage parameter clustering on the scene usage characteristic requirements to obtain a scene usage characteristic clustering result;
a clustering feature obtaining unit configured to determine a scene clustering feature based on the scene usage feature clustering result;
the characteristic mark execution unit is used for extracting the characteristics of the appearance parameter information, the size parameter information and the performance parameter information based on the scene clustering characteristics and marking the appearance parameter information, the size parameter information and the performance parameter information according to the scene clustering characteristics according to the characteristic extraction result;
and the clustering characteristic classification unit is used for classifying according to the clustering characteristics of the mark identification parameter information to construct the parameter classification data set.
Further, the weight analysis assigning module 15 further includes:
the model construction execution unit is used for respectively constructing a hierarchical structure model of each classified data set according to the parameter classified data sets, and the hierarchical structure model comprises a target layer, an index layer and a weight distribution scheme layer, wherein the target layer is a scene clustering feature, and the index layer is a parameter classified data set corresponding to the scene clustering feature;
the comparison matrix construction unit is used for constructing a pair comparison matrix of each layer for each factor of the previous layer based on a pair comparison method and a 1-9 scale setting method;
the comparison matrix checking unit is used for carrying out consistency check on the paired comparison matrixes to obtain a consistency check result;
the weight calculation execution unit is used for performing matrix weight operation according to the paired comparison matrixes when the consistency check result meets the requirement, and determining the weight of the single-layer index;
and the analysis result obtaining unit is used for carrying out probability operation on the target layer based on the single-layer index weight to obtain the analysis result of the using feature classification weight.
Further, the comparison matrix checking unit further includes:
the eigenvector calculating unit is used for calculating the maximum eigenvalue and the eigenvector corresponding to the maximum eigenvalue for each paired comparison matrix;
a consistency index obtaining unit for calculating a consistency index based on the maximum feature value;
the consistency ratio obtaining unit is used for continuously matching from a preset table based on the consistency indexes, determining an average random consistency index and obtaining a consistency ratio according to the average random consistency index and the consistency index;
and the checking result obtaining unit is used for judging that the consistency checking result meets the consistency check when the consistency ratio meets a preset requirement.
Further, the calculation execution unit further includes:
the consistent array judging unit is used for judging whether the paired comparison matrixes are consistent arrays or not, wherein the consistent arrays are matrix rows and columns which have a multiple relation;
the mean value calculation unit is used for performing mean value calculation by utilizing any column vector when the paired comparison matrix is the uniform matrix;
and the weight calculation unit is used for determining the single-layer index weight according to the column vector mean value.
Further, the analysis result obtaining unit further includes:
a weight vector determination unit, configured to determine a first weight vector of the index layer to the target layer;
a weight vector obtaining unit, configured to obtain a second weight vector of the weight distribution scheme layer to the index layer;
a weight analysis result obtaining unit, configured to obtain the usage feature classification weight analysis result according to a product of the first weight vector and the second weight vector.
Based on the above embodiments of the present invention, those skilled in the art should make any improvements and modifications to the present invention without departing from the principle of the present invention, and therefore, the present invention should fall into the protection scope of the present invention.
Claims (8)
1. A quality detection method for a nuclear-grade alloy steel elbow is characterized by comprising the following steps:
obtaining application environment information of the nuclear-grade alloy steel elbow, carrying out environment use characteristic analysis based on the application environment information, and determining a scene use characteristic requirement;
determining a usage parameter threshold based on the scene usage characteristic requirement;
carrying out multi-dimensional parameter detection on the nuclear-grade alloy steel elbow to obtain multi-dimensional parameter information, wherein the multi-dimensional parameter information comprises appearance parameter information, size parameter information and performance parameter information;
classifying the appearance parameter information, the size parameter information and the performance parameter information based on the scene use characteristic requirements to construct a parameter classification data set;
carrying out weight analysis on all parameters in the parameter classification data set by using an analytic hierarchy process to determine a characteristic classification weight analysis result;
performing parameter operation based on the use characteristic classification weight analysis result and the parameter classification data set, and determining a use parameter calculation result;
and judging whether the use parameter calculation result meets the use parameter threshold value, wherein the quality detection result is qualified when the use parameter calculation result meets the use parameter threshold value, and the quality detection result is unqualified when the use parameter calculation result does not meet the use parameter threshold value.
2. The method of claim 1, wherein determining a usage parameter threshold based on the scene usage characteristic requirement comprises:
extracting historical scene use record data based on the scene use characteristic requirement to obtain a historical scene record set;
extracting chemical and physical parameters of the historical scene record set to obtain scene characteristic parameter characteristics, wherein the scene characteristic parameter characteristics comprise structural shape influence characteristics and chemical reaction influence characteristics;
extracting fault record information according to the historical scene record set, analyzing fault parameters based on the fault record information, and determining fault parameter characteristics;
and determining the use parameter threshold according to the structural shape influence characteristic, the chemical reaction influence characteristic and the fault parameter characteristic.
3. The method of claim 1, wherein classifying the appearance parameter information, the size parameter information, the performance parameter information based on the scene usage characteristic requirements, constructing a parametric classification dataset, comprises:
carrying out use parameter clustering on the scene use characteristic requirements to obtain a scene use characteristic clustering result;
determining scene clustering characteristics based on the scene usage characteristic clustering results;
extracting the appearance parameter information, the size parameter information and the performance parameter information based on the scene clustering characteristics, and marking the appearance parameter information, the size parameter information and the performance parameter information according to the scene clustering characteristics according to the characteristic extraction result;
and classifying according to the clustering characteristics of the mark identification parameter information to construct the parameter classification data set.
4. The method of claim 3, wherein performing a weight analysis on all parameters in the parameter classification dataset using an analytic hierarchy process to determine using feature classification weight analysis results comprises:
respectively constructing a hierarchical structure model of each classified data set according to the parameter classified data sets, wherein the hierarchical structure model comprises a target layer, an index layer and a weight distribution scheme layer, the target layer is a scene clustering feature, and the index layer is a parameter classified data set corresponding to the scene clustering feature;
constructing a pair comparison matrix of each layer for each factor of the previous layer based on a pair comparison method and a 1-9 scale setting method;
carrying out consistency check on the paired comparison matrixes to obtain a consistency check result;
when the consistency test result meets the requirement, performing matrix weight operation according to the paired comparison matrixes to determine single-layer index weight;
and performing probability operation on the target layer based on the single-layer index weight to obtain the use characteristic classification weight analysis result.
5. The method of claim 4, wherein performing a consistency check on the pair of comparison matrices to obtain a consistency check result comprises:
calculating a maximum eigenvalue and an eigenvector corresponding to the maximum eigenvalue for each pair of comparison matrices;
calculating a consistency index based on the maximum feature value;
continuously matching from a preset table based on the consistency index, determining an average random consistency index, and obtaining a consistency ratio according to the average random consistency index and the consistency index;
and when the consistency ratio meets a preset requirement, the consistency test result is that the consistency test is met.
6. The method of claim 5, wherein the method further comprises:
judging whether the paired comparison matrixes are consistent matrixes or not, wherein the consistent matrixes are matrixes with multiple relations among rows and columns;
when the paired comparison matrix is the uniform matrix, performing mean calculation by using any column vector;
and determining the single-layer index weight according to the column vector mean value.
7. The method of claim 4, wherein performing a probabilistic operation on a target layer based on the single-layer index weight to obtain the result of using the feature classification weight analysis comprises:
determining a first weight vector of the index layer to the target layer;
obtaining a second weight vector of the weight distribution scheme layer to the index layer;
and obtaining the use feature classification weight analysis result according to the product of the first weight vector and the second weight vector.
8. A quality detection system for a nuclear grade alloy steel elbow, the system comprising:
the system comprises a scene characteristic generation module, a data acquisition module and a data processing module, wherein the scene characteristic generation module is used for acquiring application environment information of the nuclear-grade alloy steel elbow, analyzing environment use characteristics based on the application environment information and determining a scene use characteristic requirement;
a usage parameter determination module for determining a usage parameter threshold based on the scene usage characteristic requirement;
the parameter information acquisition module is used for carrying out multi-dimensional parameter detection on the nuclear-grade alloy steel elbow to acquire multi-dimensional parameter information, wherein the multi-dimensional parameter information comprises appearance parameter information, size parameter information and performance parameter information;
the parameter classification execution module is used for classifying the appearance parameter information, the size parameter information and the performance parameter information based on the scene use characteristic requirements to construct a parameter classification data set;
the weight analysis assignment module is used for carrying out weight analysis on all parameters in the parameter classification data set by utilizing an analytic hierarchy process and determining a result of using the feature classification weight analysis;
the using parameter calculating module is used for performing parameter operation on the basis of the using characteristic classification weight analysis result and the parameter classification data set and determining a using parameter calculating result;
and the quality detection judging module is used for judging whether the use parameter calculation result meets the use parameter threshold value, if so, the quality detection result is qualified, and if not, the quality detection result is unqualified.
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