CN115049319B - Quality evaluation method and system for steel forging forming - Google Patents
Quality evaluation method and system for steel forging forming Download PDFInfo
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- 238000005242 forging Methods 0.000 title claims abstract description 371
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Abstract
The invention provides a quality evaluation method and a system for steel forging forming, which relate to the technical field of data processing, and the method comprises the following steps: determining a target steel material; obtaining a first defect index information set; forging the target steel; after the forging processing is finished, a second defect index information set is obtained; acquiring a quality index information set; constructing a steel forging quality evaluation model, which comprises a forging defect improvement evaluation branch, a forging quality evaluation branch and a calculation branch; obtaining a forging defect improvement evaluation result and a forging quality evaluation result; and inputting the data into the calculation branches, and performing weighted calculation to obtain a final evaluation result. The technical problem that the evaluation result of the steel forging forming quality has certain deviation due to the fact that the evaluation of the steel forging forming quality is concentrated on the related parameter indexes of the forging performance is solved, and the technical effects that the related index parameters are improved by combining the forging defects, the steel forging forming quality is comprehensively evaluated in an all-round mode, and the reliability of the evaluation result of the steel forging forming is improved are achieved.
Description
Technical Field
The invention relates to the technical field of data processing, in particular to a quality evaluation method and system for steel forging forming.
Background
The steel forges the blank and is forging and pressing the shaping course of working, if the blank surface is coarse, there is nick, crazing line or thick impurity, can make the steel after the forging process produce stress concentration or fracture, carry out accurate aassessment to the forging quality, can reduce the probability that the unqualified steel of forging process flows into market, at present stage, through stress verification test, steel surface image information acquisition analysis processing aassessment forging quality, but inevitable, the steel that obtains forges the shaping aassessment result the precision is limited.
In the prior art, the technical problem that the evaluation result of the forging forming quality of the steel has certain deviation because the evaluation of the forging forming quality of the steel is focused on the related parameter indexes of the forging defects exists.
Disclosure of Invention
The application provides a quality evaluation method and system for steel forging forming, and the technical problem that the evaluation of the steel forging forming quality is concentrated on the related parameter indexes of the forging performance, so that the evaluation result of the steel forging forming quality has certain deviation is solved, the technical effects of improving the related index parameters by combining forging defects, comprehensively evaluating the steel forging forming quality in all aspects and improving the reliability of the steel forging forming evaluation result are achieved.
In view of the above problems, the present application provides a method and a system for evaluating the quality of steel forging.
In a first aspect, the present application provides a method for evaluating the quality of a steel forging formation, wherein the method includes: determining a target steel material, wherein the target steel material is a steel material to be subjected to forging forming and quality evaluation; acquiring index parameter information of a plurality of defect indexes when target steel is not forged to obtain a first defect index information set; forging the target steel by adopting a preset forging process; after the forging processing is finished, acquiring index parameter information of a plurality of defect indexes of the target steel to obtain a second defect index information set; acquiring index parameter information of a plurality of quality indexes obtained after the target steel is forged and processed, and acquiring a quality index information set; constructing a steel forging quality evaluation model, wherein the steel forging quality evaluation model comprises a forging defect improvement evaluation branch, a forging quality evaluation branch and a calculation branch; inputting the first defect index information set, the second defect index information set and the quality index information set into a forging defect improvement evaluation branch and a forging quality evaluation branch in the steel forging quality evaluation model respectively to obtain a forging defect improvement evaluation result and a forging quality evaluation result respectively; and inputting the forging defect improvement evaluation result and the forging quality evaluation result into the calculation branch, and performing weighted calculation to obtain a final evaluation result.
In a second aspect, the present application provides a quality evaluation system for steel forging forming, wherein the system includes: the steel material determination unit is used for determining a target steel material, wherein the target steel material is a steel material to be subjected to forging forming and quality evaluation; the first defect index acquisition unit is used for acquiring index parameter information of a plurality of defect indexes when target steel is not forged to obtain a first defect index information set; the forging processing unit is used for forging and processing the target steel by adopting a preset forging process; the second defect index acquisition unit is used for acquiring index parameter information of a plurality of defect indexes of the target steel after the forging processing is finished, and acquiring a second defect index information set; the quality index acquisition unit is used for acquiring index parameter information of a plurality of quality indexes obtained after the target steel is forged and processed, and acquiring a quality index information set; the model construction unit is used for constructing a steel forging quality evaluation model, wherein the steel forging quality evaluation model comprises a forging defect improvement evaluation branch, a forging quality evaluation branch and a calculation branch; an evaluation result obtaining unit, configured to input the first defect index information set, the second defect index information set, and the quality index information set into a forging defect improvement evaluation branch and a forging quality evaluation branch in the steel forging quality evaluation model, respectively, and obtain a forging defect improvement evaluation result and a forging quality evaluation result, respectively; and the weighting calculation unit is used for inputting the forging defect improvement evaluation result and the forging quality evaluation result into the calculation branch to perform weighting calculation so as to obtain a final evaluation result.
One or more technical solutions provided in the present application have at least the following technical effects or advantages:
because the determined target steel is adopted; obtaining a first defect index information set; forging the target steel by adopting a preset forging process; after the forging processing is finished, a second defect index information set is obtained; acquiring a quality index information set; constructing a steel forging quality evaluation model; inputting the first defect index information set, the second defect index information set and the quality index information set into a forging defect improvement evaluation branch and a forging quality evaluation branch in a steel forging quality evaluation model respectively to obtain a forging defect improvement evaluation result and a forging quality evaluation result respectively; and inputting the forging defect improvement evaluation result and the forging quality evaluation result into a calculation branch, and performing weighted calculation to obtain a final evaluation result. The embodiment of the application achieves the technical effects of improving related index parameters by combining forging defects, comprehensively evaluating the quality of steel forging forming in all aspects and improving the reliability of the steel forging forming evaluation result.
Drawings
FIG. 1 is a schematic flow chart illustrating a method for evaluating the quality of a steel forging;
FIG. 2 is a schematic flow chart of a quality index information set obtained by the quality evaluation method for steel forging forming according to the present application;
FIG. 3 is a schematic diagram of a process for obtaining a steel forging quality evaluation model according to the quality evaluation method for steel forging forming of the present application;
FIG. 4 is a schematic structural diagram of a system for evaluating the quality of a steel forging operation according to the present invention.
Description of reference numerals: the device comprises a steel material determining unit 11, a first defect index obtaining unit 12, a forging unit 13, a second defect index obtaining unit 14, a quality index obtaining unit 15, a model building unit 16, an evaluation result obtaining unit 17 and a weighting calculating unit 18.
Detailed Description
The technical problem that the evaluation of the quality of the steel forging forming is concentrated on the related parameter indexes of the forging defects to cause certain deviation of the evaluation result of the quality of the steel forging forming is solved, the improvement of the related index parameters by combining the forging defects is achieved, the quality of the steel forging forming is comprehensively evaluated in all aspects, and the technical effect of improving the reliability of the evaluation result of the steel forging forming is improved.
Example one
As shown in fig. 1, the present application provides a quality evaluation method for steel forging forming, wherein the method comprises:
s100: determining a target steel material, wherein the target steel material is a steel material to be subjected to forging forming and quality evaluation;
specifically, the target steel material is a steel ingot which is not forged yet, the target steel material is a steel material to be forged and formed and subjected to quality evaluation, the volume, the quality and other relevant indexes of the target steel material are not specifically limited, and generally, in order to ensure the stability of the result, the volume of the target steel material is set to be less than or equal to 10m 3 The quality of the target steel is determined by combining the carbon content of the target steel and performing comparison, rho Low carbon steel = 7.85g/cm 3 ，ρ Medium carbon steel = 7.82g/cm 3 ，ρ High carbon steel = 7.81g/cm 3 And the quality of the target steel is limited through operation and comparison, the target steel is determined, and the stability of the quality evaluation result of the target steel is guaranteed to a certain extent.
S200: acquiring index parameter information of a plurality of defect indexes when target steel is not forged to obtain a first defect index information set;
further, the acquiring and obtaining of the index parameter information of the plurality of defect indexes when the target steel is not forged includes step S200;
s210: acquiring and obtaining first loosening information of the target steel when the target steel is not forged;
s220: acquiring first air hole information of the target steel when the target steel is not forged;
s230: acquiring and obtaining first secondary shrinkage information of the target steel when the target steel is not forged;
s240: and taking the first porosity information, the first pore information and the first secondary shrinkage cavity information as the first defect index information set.
Specifically, index parameter information of a plurality of defect indexes of target steel without forging is detected, acquired and obtained through a portable X-ray tube, an analog ultrasonic flaw detector and other detection devices, wherein the plurality of defect indexes can be loose defect indexes, pore defect indexes, secondary shrinkage defect indexes and the like, the index parameter information corresponds to a detection result of the detection device to obtain a first defect index information set, and the first defect index information set comprises the plurality of defect indexes and the index parameter information of the plurality of defect indexes and provides data support for subsequent data analysis.
Specifically, the method comprises the steps of detecting the target steel which is not forged through a detection device such as a digital eddy current flaw detector, a portable X-ray tube and an analog ultrasonic flaw detector, acquiring target steel detection information, wherein the target steel detection information comprises but is not limited to longitudinal crack information, transverse defect information (such as a lapel), shrinkage cavity (commonly seen at a riser end of a steel ingot) information and air hole defect information, retrieving and extracting the target steel detection information through a loosening defect index, and acquiring first loosening information when the target steel is not forged; performing information retrieval and extraction on the target steel detection information through a gas hole defect index to obtain first gas hole information when the target steel is not forged; performing information retrieval and extraction on the target steel detection information through a secondary shrinkage defect index to obtain first secondary shrinkage information when the target steel is not forged; the index parameter information of the plurality of defect indexes comprises the first loosening information, the first air hole information and the first secondary shrinkage information, and the first loosening information, the first air hole information, the first secondary shrinkage information, the corresponding loosening defect index, the air hole defect index and the secondary shrinkage defect index are used as the first defect index information set, so that the integrity of the defect index information of the steel to be forged and formed is ensured.
S300: forging the target steel by adopting a preset forging process;
s400: after the forging processing is finished, acquiring index parameter information of a plurality of defect indexes of the target steel to obtain a second defect index information set;
specifically, the preset forging process comprises a series of forging process flows, the target steel is forged through the preset forging process, the forging process flow of the target steel is any forging process flow, the target steel is forged and collected in sections before and after the steel is forged and formed, the relevant parameter indexes of the overall steel forging and forming quality are obtained for collection, after the forging process is completed, index parameter information of a plurality of defect indexes of the target steel is collected and obtained through detection devices such as a digital eddy current flaw detector, a portable X-ray tube and an analog ultrasonic flaw detector in combination with a loosening defect index, a gas hole defect index and a secondary shrinkage defect index, the index parameter information of the plurality of defect indexes further comprises second loosening information, second gas hole information and second secondary shrinkage information, the second loosening information, the second secondary shrinkage information and corresponding loosening defect index, gas hole defect index and secondary shrinkage defect index serve as a second defect index information set, and data guarantee is provided for subsequent data analysis. And the second defect index information set corresponds to the defect index information in the first defect index information set one by one, and the second defect index information set corresponds to the defect index information sets of the plurality of defect indexes before and after the forging processing of the target steel material.
Wherein, in the process of forging and processing, the steel can improve the loosening defect, the air hole defect and the secondary shrinkage defect through forging. Therefore, the quality evaluation of the steel forging forming is carried out based on the improvement condition of the defect index and the parameters of other steel forging quality indexes, and the method and the device are more comprehensive and accurate.
S500: acquiring index parameter information of a plurality of quality indexes obtained after the target steel is forged and processed, and acquiring a quality index information set;
further, as shown in fig. 2, the acquiring and obtaining index parameter information of a plurality of quality indexes after the forging process of the target steel material is completed includes:
s510: acquiring and obtaining internal crack information of the target steel after forging processing is completed;
s520: acquiring and obtaining as-cast coarse grain information after the target steel is forged and processed;
s530: acquiring and obtaining surface segregation information after the target steel is forged and processed;
s540: acquiring and obtaining inclusion information after the target steel is forged and processed;
s550: and taking the internal crack information, the as-cast coarse crystal information, the surface segregation information and the inclusion information as the quality index information set.
Specifically, after the target steel is detected and processed by a detection device such as a digital eddy current flaw detector, a portable X-ray tube, an analog ultrasonic flaw detector and the like, index parameter information of a plurality of quality indexes after the target steel is forged and processed is acquired, the plurality of quality indexes comprise an internal crack quality index, an as-cast coarse grain quality index, a surface segregation quality index and an inclusion quality index, the index parameter information of the plurality of quality indexes comprises internal crack information, as-cast coarse grain information, surface segregation information and inclusion information (including nonmetallic inclusions and metallic inclusions), the formation reasons of the index parameter information of the plurality of quality indexes are complex and inconsistent, the formation reasons are not taken as the key points of quality evaluation, and the internal crack information, as-cast coarse grain information, surface segregation information and inclusion information, the internal crack quality index, as-cast coarse grain quality index, surface segregation quality index and inclusion quality index are taken as the quality index information set, so as to provide data guarantee for subsequent data analysis.
S600: constructing a steel forging quality evaluation model, wherein the steel forging quality evaluation model comprises a forging defect improvement evaluation branch, a forging quality evaluation branch and a calculation branch;
further, as shown in fig. 3, the step S600 of constructing a steel forging quality evaluation model includes:
s610: constructing the forging defect improvement evaluation branch;
s620: constructing the forging quality evaluation branch;
s630: constructing the calculation branch, wherein the calculation branch comprises a preset calculation rule;
s640: and connecting the calculation branch with the forging defect improvement evaluation branch and the forging quality evaluation branch to obtain the steel forging quality evaluation model.
Specifically, the steel forging quality evaluation model comprises a forging defect improvement evaluation branch, a forging quality evaluation branch and a calculation branch, wherein the forging defect improvement evaluation branch and the forging quality evaluation branch are arranged and constructed in parallel, and the forging defect improvement evaluation branch and the forging quality evaluation branch are respectively connected with the calculation branch to provide a model basis for data analysis.
Specifically, the forging defect improvement evaluation branch and the forging quality evaluation branch both use a BP neural network as a model basis to construct the forging defect improvement evaluation branch, wherein the forging defect improvement evaluation branch uses associated sample information of a first defect index information set and a second defect index information set as training information; constructing the forging quality evaluation branch, wherein the forging quality evaluation branch takes associated sample information of a quality index information set as training information; constructing the calculation branch, wherein the calculation branch comprises preset calculation rules, the preset calculation rules are that weight distribution is carried out on the output result of the forging defect improvement evaluation branch and the output result of the forging quality evaluation branch according to different weight distribution methods, and the average value of a plurality of weight distribution results is calculated, and the weight distribution methods can comprise objective weighting methods such as a coefficient of variation method and the like, and can also comprise subjective weighting methods such as an analytic hierarchy process and the like; the forging defect improvement evaluation branch and the forging quality evaluation branch are arranged in parallel, the forging defect improvement evaluation branch and the forging quality evaluation branch are respectively connected with the calculation branch and are connected with the calculation branch, the forging defect improvement evaluation branch and the forging quality evaluation branch, a steel forging quality evaluation model is obtained, the layout of the model is optimized, and technical support is provided for the stability of the steel forging quality evaluation model.
Further, constructing the forging defect improvement evaluating branch, wherein the step S610 includes:
s611: obtaining a plurality of sample steel products according to the target steel product;
s612: acquiring a first defect index information set and a second defect index information set of the plurality of sample steel materials before forging processing and after forging processing to obtain a plurality of sample first defect index information sets and a plurality of sample second defect index information sets;
s613: calculating and obtaining a plurality of forging defect improvement scores of the plurality of sample steel products according to the plurality of sample first defect index information sets and the plurality of sample second defect index information sets;
s614: dividing and identifying the plurality of sample first defect index information sets, the plurality of sample second defect index information sets and the plurality of forging defect improvement scores to obtain a first training sample set, a first verification sample set and a first test sample set;
s615: constructing the forging defect improvement evaluation branch based on a BP neural network;
s616: and performing supervision training, verification and testing on the forging defect improvement evaluation branch by adopting the first training sample set, the first verification sample set and the first testing sample set, and if the accuracy of the forging defect improvement evaluation branch meets the preset requirement, obtaining the forging defect improvement evaluation branch.
Specifically, the plurality of sample steel materials, namely steel materials with the same specification, components and grade as the target steel material, are obtained according to the specification, components and grade of the target steel material; the method comprises the steps that a digital eddy current flaw detector, a portable X-ray tube, an analog ultrasonic flaw detector and other detection devices are used for monitoring and acquiring a first defect index information set and a second defect index information set before forging processing and after forging processing of a plurality of sample steel materials respectively, wherein the marking information corresponding to the first defect index information set and the second defect index information set of the same sample steel material is consistent, the first defect index information set and the second defect index information set of the plurality of sample steel materials before forging processing and after forging processing are obtained, the first defect index information set and the second defect index information set of the plurality of sample steel materials before forging processing and after forging processing are indicated before the previous forging processing, the forging processing operation is the previous historical processing operation, namely before the historical forging processing operation, the ' after forging processing ' before the previous forging processing and after forging processing is limited, namely after the historical forging processing operation, the ' after forging processing ' before forging processing ' is limited to be completed in the historical forging processing operation, and the first defect index information set and the second defect index information set of the plurality of sample steel materials are obtained; based on an expert system, establishing a forging defect scoring expert system by taking relevant standards such as GB 50017-2003 steel structure design Specification, GB/T12363-2021 forge piece function Classification and the like as a knowledge base, respectively and sequentially inputting the first defect index information sets of the plurality of samples and the second defect index information sets of the plurality of samples into the forging defect scoring expert system to obtain forging defect scores of the plurality of samples before and after forging processing, subtracting the forging defect scores of the plurality of samples before forging processing from the forging defect scores of the plurality of samples after forging processing, and calculating to obtain a plurality of forging defect improvement scores of the plurality of sample steel products; dividing and identifying the plurality of sample first defect index information sets, the plurality of sample second defect index information sets and the plurality of forging defect improvement scores by combining the marking information with the sample numbers of the plurality of sample steel materials to obtain a first training sample set, a first verification sample set and a first test sample set, wherein the first training sample set, the first verification sample set and the first test sample set respectively comprise the plurality of sample first defect index information sets, the plurality of sample second defect index information sets and the plurality of forging defect improvement scores; on the basis of a BP neural network, sequentially inputting elements in the first training sample set, wherein the elements are a first defect index information set and a second defect index information set of any sample steel of the multiple sample steel, performing supervised training by taking a corresponding forging defect improvement score in the multiple forging defect improvement scores as mark supervision information, verifying and testing a trained model through the first verification sample set and the first test sample set, wherein the verification is that the elements in the first verification sample set are input into the model after training, obtaining an output result, determining an index difference between the output result and the corresponding forging defect improvement score, and the preset requirement is an index difference threshold value which meets the requirement that the output result is accurate and does not meet the requirement that the output result is inaccurate, and the ratio of the accurate number of the output result to the verification number is the verification accuracy, and the test accuracy is consistent with the technical means for obtaining the verification accuracy, and obtaining the forging defect improvement evaluation branch if the verification and the test accuracy of the forging defect improvement evaluation branch both meet the preset requirement.
Further, the forging quality evaluation branch is constructed, and step S620 includes:
s621: acquiring index parameter information of a plurality of quality indexes of the plurality of sample steel products subjected to forging processing in the past to obtain a plurality of sample quality index information sets;
s622: acquiring forging quality inspection results of the plurality of sample steel products to obtain a sample forging quality evaluation result set;
s623: dividing and identifying the multiple sample quality index information sets and the sample forging quality evaluation result set to obtain a second training sample set, a second verification sample set and a second test sample set;
s624: constructing the forging quality evaluation branch based on a BP neural network;
s625: and performing supervision training, verification and testing on the forging quality evaluation branch by adopting the second training sample set, the second verification sample set and the second testing sample set, and obtaining the forging quality evaluation branch if the accuracy of the forging defect improvement evaluation branch meets a preset requirement.
Specifically, the plurality of sample quality index information sets are quality index information sets of steel materials with the same specification, composition, grade and grade as a target steel material, the collection mode of index parameter information of a plurality of quality indexes of the plurality of sample steel materials after previous forging processing is consistent with the quality index information sets, the forging processing operation of the plurality of sample steel materials is the previous historical processing operation, the forging quality inspection results include but are not limited to fluorescent inspection results, magnetic powder inspection results, dye penetrant inspection detection results and low-power inspection results, the forging quality inspection results of the plurality of sample steel materials are collected and called according to the historical quality inspection results of the plurality of sample steel materials, and a sample forging quality evaluation result set is obtained by taking the forging quality inspection results of the plurality of sample steel materials as elements; dividing and identifying the plurality of sample quality index information sets and the sample forging quality evaluation result set by combining the sample numbers to obtain a second training sample set, a second verification sample set and a second test sample set; and based on a BP neural network, performing supervised training, verification and testing on the forging quality evaluation branch by adopting the second training sample set, the second verification sample set and the second test sample set, if the accuracy of the forging defect improvement evaluation branch meets the preset requirement, obtaining the forging quality evaluation branch, constructing the forging quality evaluation branch, and ensuring the reliability of the forging quality evaluation branch, wherein the technical means for constructing the forging quality evaluation branch and the technical means for constructing the forging defect improvement evaluation branch have consistency, and repeated description is not needed here.
S700: inputting the first defect index information set, the second defect index information set and the quality index information set into a forging defect improvement evaluation branch and a forging quality evaluation branch in the steel forging quality evaluation model respectively to obtain a forging defect improvement evaluation result and a forging quality evaluation result respectively;
s800: and inputting the forging defect improvement evaluation result and the forging quality evaluation result into the calculation branch, and performing weighted calculation to obtain a final evaluation result.
Specifically, the first defect index information set and the second defect index information set are input into a forging defect improvement evaluation branch in the steel forging quality evaluation model, and the forging defect improvement evaluation branch outputs a forging defect improvement evaluation result; inputting the quality index information set into a forging quality evaluation branch in the steel forging quality evaluation model, wherein the forging quality evaluation branch outputs a forging quality evaluation result; and synchronously inputting the forging defect improvement evaluation result and the forging quality evaluation result into the calculation branch in parallel to perform weighted calculation to obtain a final evaluation result, wherein the final evaluation result is used for evaluating the forging forming quality of the target steel, and technical support is provided for comprehensively evaluating the forging forming quality of the steel in all aspects.
Further, the forging defect improvement evaluation result and the forging quality evaluation result are input into the calculation branch for weighted calculation, and step S800 includes:
s810: inputting the forging defect improvement evaluation result and the forging quality evaluation result into the calculation branch;
s820: performing weighted summation calculation on the forging defect improvement evaluation result and the forging quality evaluation result according to the preset calculation rule, wherein the preset calculation rule comprises a preset weight distribution result;
s830: and calculating to obtain the final evaluation result.
Specifically, the forging defect improvement evaluation result and the forging quality evaluation result are synchronously and parallelly input into the calculation branch, the weighted summation calculation is to determine a first weight index and a second weight index corresponding to the forging defect improvement evaluation result and the forging quality evaluation result respectively through the preset calculation rule, the first weight index is used for carrying out weighted calculation on the forging defect improvement evaluation result, the second weight index is used for carrying out weighted calculation on the forging quality evaluation result, the two results corresponding to the weighted calculation are added to obtain the final evaluation result, the preset calculation rule is to carry out weight distribution on the forging defect improvement evaluation result and the forging quality evaluation result according to different weight distribution methods, the average value of a plurality of weight distribution results is calculated to obtain a preset weight distribution result, the preset weight distribution result comprises the first weight index and the second weight index, the verification limitation is shown, the second weight index corresponding to the forging quality evaluation result is larger, namely the weight of the second weight index is limited to be larger than the weight of the first weight index, and the forming support technology evaluation result is provided for ensuring the generality of the final evaluation result and improving the forging quality of the steel product.
In summary, the quality evaluation method and system for steel forging and forming provided by the present application have the following technical effects:
the method comprises the steps of determining a target steel, acquiring index parameter information of a plurality of defect indexes of the target steel when the target steel is not forged, acquiring a first defect index information set, forging the target steel, acquiring a second defect index information set after the forging is finished, acquiring a quality index information set, constructing a steel forging quality evaluation model, inputting the first defect index information set, the second defect index information set and the quality index information set into a forging defect improvement evaluation branch and a forging quality evaluation branch in the steel forging quality evaluation model respectively, acquiring a forging defect improvement evaluation result and a forging quality evaluation result respectively, inputting the forging defect improvement evaluation result and the forging quality evaluation result into a calculation branch, and performing weighted calculation to obtain a final evaluation result.
The method comprises the steps of obtaining first loosening information of target steel; acquiring first air hole information of target steel; acquiring first secondary shrinkage information of target steel; and taking the first porosity information, the first pore information and the first secondary shrinkage information as a first defect index information set. The integrity of the defect index information of the steel to be forged and formed is ensured.
Due to the adoption of a construction forging defect improvement evaluation branch; constructing a forging quality evaluation branch; constructing a calculation branch; and connecting the calculation branch with the forging defect improvement evaluation branch and the forging quality evaluation branch to obtain a steel forging quality evaluation model. Optimizing the layout of the model and providing technical support for the stability of the steel forging quality evaluation model.
Example two
Based on the same inventive concept as the quality evaluation method for steel forging forming in the previous embodiment, as shown in fig. 4, the present application provides a quality evaluation system for steel forging forming, wherein the system comprises:
a steel material determination unit 11, wherein the steel material determination unit 11 is configured to determine a target steel material, and the target steel material is a steel material to be subjected to forging forming and quality evaluation;
the first defect index obtaining unit 12, where the first defect index obtaining unit 12 is configured to acquire and obtain index parameter information of a plurality of defect indexes when a target steel is not forged, and obtain a first defect index information set;
the forging processing unit 13 is used for forging and processing the target steel by adopting a preset forging process;
a second defect index obtaining unit 14, where the second defect index obtaining unit 14 is configured to, after the forging process is completed, acquire index parameter information of a plurality of defect indexes of the target steel, and obtain a second defect index information set;
the quality index acquiring unit 15 is configured to acquire index parameter information of a plurality of quality indexes obtained after the forging processing of the target steel is completed, and acquire a quality index information set;
a model construction unit 16, wherein the model construction unit 16 is used for constructing a steel forging quality evaluation model, and the steel forging quality evaluation model comprises a forging defect improvement evaluation branch, a forging quality evaluation branch and a calculation branch;
an evaluation result obtaining unit 17, where the evaluation result obtaining unit 17 is configured to input the first defect index information set, the second defect index information set, and the quality index information set into a forging defect improvement evaluation branch and a forging quality evaluation branch in the steel forging quality evaluation model, respectively, and obtain a forging defect improvement evaluation result and a forging quality evaluation result, respectively;
and the weighting calculation unit 18 is used for inputting the forging defect improvement evaluation result and the forging quality evaluation result into the calculation branch for weighting calculation to obtain a final evaluation result.
Further, the system comprises:
the loosening information acquisition unit is used for acquiring and acquiring first loosening information of the target steel when the target steel is not forged;
the air hole information acquisition unit is used for acquiring and acquiring first air hole information of the target steel when the target steel is not forged;
the secondary shrinkage information acquisition unit is used for acquiring and acquiring first secondary shrinkage information of the target steel when the target steel is not forged;
a first defect index information determination unit configured to use the first porosity information, the first pore information, and the first secondary shrinkage information as the first defect index information set.
Further, the system comprises:
the internal crack information acquisition unit is used for acquiring and acquiring internal crack information of the target steel after forging;
the as-cast coarse grain information acquisition unit is used for acquiring and acquiring as-cast coarse grain information after the target steel is forged and processed;
the surface segregation information acquisition unit is used for acquiring and obtaining surface segregation information after the forging processing of the target steel;
the inclusion information acquisition unit is used for acquiring and acquiring inclusion information after the forging processing of the target steel is finished;
a quality index information determination unit configured to set the internal crack information, the as-cast coarse grain information, the surface segregation information, and the inclusion information as the quality index information set.
Further, the system comprises:
an improvement evaluation branch construction unit for constructing the forging defect improvement evaluation branch;
a quality evaluation branch construction unit for constructing the forging quality evaluation branch;
the calculation branch construction unit is used for constructing the calculation branch, wherein the calculation branch comprises a preset calculation rule;
and the quality evaluation model determining unit is used for connecting the calculating branch, the forging defect improvement evaluating branch and the forging quality evaluating branch to obtain the steel forging quality evaluation model.
Further, the system comprises:
the sample steel obtaining unit is used for obtaining a plurality of sample steels according to the target steels;
the system comprises a sample defect index information obtaining unit, a first defect index information acquiring unit and a second defect index information acquiring unit, wherein the sample defect index information obtaining unit is used for acquiring and acquiring a first defect index information set and a second defect index information set of a plurality of sample steel products before forging processing and after forging processing so as to obtain a plurality of sample first defect index information sets and a plurality of sample second defect index information sets;
a defect improvement score calculation unit, configured to calculate and obtain a plurality of forging defect improvement scores of the plurality of sample steel materials according to the plurality of sample first defect index information sets and the plurality of sample second defect index information sets;
a training sample set obtaining unit, configured to divide and identify the plurality of sample first defect index information sets, the plurality of sample second defect index information sets, and the plurality of forged defect improvement scores, to obtain a first training sample set, a first verification sample set, and a first test sample set;
a defect improvement evaluation branch construction unit for constructing the forged defect improvement evaluation branch based on a BP neural network;
and the defect improvement evaluation branch obtaining unit is used for performing supervised training, verification and testing on the forging defect improvement evaluation branch by adopting the first training sample set, the first verification sample set and the first test sample set, and obtaining the forging defect improvement evaluation branch if the accuracy of the forging defect improvement evaluation branch meets a preset requirement.
Further, the system comprises:
the device comprises a sample quality index information obtaining unit, a data processing unit and a data processing unit, wherein the sample quality index information obtaining unit is used for acquiring index parameter information of a plurality of quality indexes of a plurality of sample steel products subjected to forging processing in the past and obtaining a plurality of sample quality index information sets;
the sample quality evaluation result obtaining unit is used for acquiring forging quality inspection results of the plurality of sample steel products and obtaining a sample forging quality evaluation result set;
the identification dividing unit is used for dividing and identifying the plurality of sample quality index information sets and the sample forging quality evaluation result set to obtain a second training sample set, a second verification sample set and a second test sample set;
a quality evaluation branch construction unit for constructing the forging quality evaluation branch based on a BP neural network;
and the model training accuracy judgment unit is used for performing supervision training, verification and testing on the forging quality evaluation branch by adopting the second training sample set, the second verification sample set and the second test sample set, and obtaining the forging quality evaluation branch if the accuracy of the forging defect improvement evaluation branch meets a preset requirement.
Further, the system comprises:
an evaluation result input unit for inputting the forging defect improvement evaluation result and the forging quality evaluation result into the calculation branch;
the weighted sum calculation unit is used for carrying out weighted sum calculation on the forging defect improvement evaluation result and the forging quality evaluation result according to the preset calculation rule, wherein the preset calculation rule comprises a preset weight distribution result;
and the final evaluation result obtaining unit is used for calculating and obtaining the final evaluation result.
The specification and drawings are merely exemplary of the application and various modifications and combinations can be made thereto without departing from the spirit and scope of the application. Such modifications and variations of the present application are within the scope of the claims of the present application and their equivalents, and the present application is intended to include such modifications and variations.
Claims (8)
1. A quality evaluation method for steel forging forming is characterized by comprising the following steps:
determining a target steel material, wherein the target steel material is a steel material to be subjected to forging forming and quality evaluation;
acquiring index parameter information of a plurality of defect indexes when target steel is not forged to obtain a first defect index information set;
forging the target steel by adopting a preset forging process;
after the forging processing is finished, acquiring index parameter information of a plurality of defect indexes of the target steel to obtain a second defect index information set;
acquiring index parameter information of a plurality of quality indexes obtained after the target steel is forged and processed, and acquiring a quality index information set;
constructing a steel forging quality evaluation model, wherein the steel forging quality evaluation model comprises a forging defect improvement evaluation branch, a forging quality evaluation branch and a calculation branch;
inputting the first defect index information set, the second defect index information set and the quality index information set into a forging defect improvement evaluation branch and a forging quality evaluation branch in the steel forging quality evaluation model respectively to obtain a forging defect improvement evaluation result and a forging quality evaluation result respectively;
and inputting the forging defect improvement evaluation result and the forging quality evaluation result into the calculation branch, and performing weighted calculation to obtain a final evaluation result.
2. The method according to claim 1, wherein the acquiring index parameter information of a plurality of defect indexes of the target steel without forging comprises:
acquiring and obtaining first loosening information of the target steel when the target steel is not forged;
acquiring and obtaining first air hole information of the target steel when the target steel is not forged;
acquiring and obtaining first secondary shrinkage information of the target steel when the target steel is not forged;
and taking the first porosity information, the first pore information and the first secondary shrinkage information as the first defect index information set.
3. The method according to claim 1, wherein the acquiring of the index parameter information of the plurality of quality indexes after the forging processing of the target steel material comprises:
acquiring and obtaining internal crack information of the target steel after forging processing is completed;
acquiring and obtaining as-cast coarse grain information after the target steel is forged and processed;
acquiring and obtaining surface segregation information after the target steel is forged and processed;
acquiring and obtaining inclusion information after the target steel is forged and processed;
and taking the internal crack information, the as-cast coarse crystal information, the surface segregation information and the inclusion information as the quality index information set.
4. The method according to claim 1, wherein the constructing a steel forging quality evaluation model includes:
constructing the forging defect improvement evaluation branch;
constructing the forging quality evaluation branch;
constructing the calculation branch, wherein the calculation branch comprises a preset calculation rule;
and connecting the calculation branch with the forging defect improvement evaluation branch and the forging quality evaluation branch to obtain the steel forging quality evaluation model.
5. The method of claim 4, wherein constructing the forging defect improvement evaluation branch comprises:
obtaining a plurality of sample steel products according to the target steel product;
acquiring a first defect index information set and a second defect index information set of the plurality of sample steel materials before and after the previous forging processing to obtain a plurality of sample first defect index information sets and a plurality of sample second defect index information sets;
calculating and obtaining a plurality of forging defect improvement scores of the plurality of sample steel products according to the plurality of sample first defect index information sets and the plurality of sample second defect index information sets;
dividing and identifying the plurality of sample first defect index information sets, the plurality of sample second defect index information sets and the plurality of forging defect improvement scores to obtain a first training sample set, a first verification sample set and a first test sample set;
constructing the forging defect improvement evaluation branch based on a BP neural network;
and performing supervision training, verification and testing on the forging defect improvement evaluation branch by adopting the first training sample set, the first verification sample set and the first testing sample set, and if the accuracy of the forging defect improvement evaluation branch meets the preset requirement, obtaining the forging defect improvement evaluation branch.
6. The method of claim 5, wherein constructing the forging quality assessment branch comprises:
acquiring index parameter information of a plurality of quality indexes of the plurality of sample steel products subjected to forging processing in the past to obtain a plurality of sample quality index information sets;
acquiring forging quality inspection results of the plurality of sample steel products to obtain a sample forging quality evaluation result set;
dividing and identifying the multiple sample quality index information sets and the sample forging quality evaluation result set to obtain a second training sample set, a second verification sample set and a second test sample set;
constructing the forging quality evaluation branch based on a BP neural network;
and performing supervision training, verification and testing on the forging quality evaluation branch by adopting the second training sample set, the second verification sample set and the second test sample set, and obtaining the forging quality evaluation branch if the accuracy of the forging defect improvement evaluation branch meets the preset requirement.
7. The method of claim 4, wherein inputting the forging defect improvement evaluation result and the forging quality evaluation result into the calculation branch for weighted calculation comprises:
inputting the forging defect improvement evaluation result and the forging quality evaluation result into the calculation branch;
performing weighted summation calculation on the forging defect improvement evaluation result and the forging quality evaluation result according to the preset calculation rule, wherein the preset calculation rule comprises a preset weight distribution result;
and calculating to obtain the final evaluation result.
8. A quality evaluation system for steel forging forming, comprising:
the steel material determination unit is used for determining a target steel material, wherein the target steel material is a steel material to be subjected to forging forming and quality evaluation;
the first defect index acquisition unit is used for acquiring index parameter information of a plurality of defect indexes when target steel is not forged to obtain a first defect index information set;
the forging processing unit is used for forging and processing the target steel by adopting a preset forging process;
the second defect index acquisition unit is used for acquiring index parameter information of a plurality of defect indexes of the target steel after the forging processing is finished, and acquiring a second defect index information set;
the quality index acquisition unit is used for acquiring index parameter information of a plurality of quality indexes obtained after the target steel is forged and processed, and acquiring a quality index information set;
the model construction unit is used for constructing a steel forging quality evaluation model, wherein the steel forging quality evaluation model comprises a forging defect improvement evaluation branch, a forging quality evaluation branch and a calculation branch;
an evaluation result obtaining unit, configured to input the first defect index information set, the second defect index information set, and the quality index information set into a forging defect improvement evaluation branch and a forging quality evaluation branch in the steel forging quality evaluation model, respectively, and obtain a forging defect improvement evaluation result and a forging quality evaluation result, respectively;
and the weighting calculation unit is used for inputting the forging defect improvement evaluation result and the forging quality evaluation result into the calculation branch, and performing weighting calculation to obtain a final evaluation result.
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