CN117910886B - Intelligent analysis method and system for smelting effect applied to titanium alloy smelting - Google Patents
Intelligent analysis method and system for smelting effect applied to titanium alloy smelting Download PDFInfo
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- 238000003723 Smelting Methods 0.000 title claims abstract description 1084
- 229910001069 Ti alloy Inorganic materials 0.000 title claims abstract description 316
- 230000000694 effects Effects 0.000 title claims abstract description 134
- 238000004458 analytical method Methods 0.000 title claims abstract description 56
- 238000001514 detection method Methods 0.000 claims abstract description 168
- 238000000034 method Methods 0.000 claims abstract description 143
- 238000012545 processing Methods 0.000 claims abstract description 113
- 238000005070 sampling Methods 0.000 claims abstract description 67
- 238000013441 quality evaluation Methods 0.000 claims abstract description 50
- 238000011156 evaluation Methods 0.000 claims abstract description 24
- 230000000379 polymerizing effect Effects 0.000 claims abstract description 8
- 238000004519 manufacturing process Methods 0.000 claims description 239
- 239000002994 raw material Substances 0.000 claims description 92
- 230000008569 process Effects 0.000 claims description 68
- 238000012544 monitoring process Methods 0.000 claims description 47
- 238000012360 testing method Methods 0.000 claims description 30
- 229910045601 alloy Inorganic materials 0.000 claims description 26
- 239000000956 alloy Substances 0.000 claims description 26
- 238000004364 calculation method Methods 0.000 claims description 26
- 238000005516 engineering process Methods 0.000 claims description 26
- 230000003749 cleanliness Effects 0.000 claims description 14
- 238000009826 distribution Methods 0.000 claims description 13
- 230000004931 aggregating effect Effects 0.000 claims description 11
- 238000002425 crystallisation Methods 0.000 claims description 11
- 230000008025 crystallization Effects 0.000 claims description 11
- 239000012535 impurity Substances 0.000 claims description 11
- 238000013508 migration Methods 0.000 claims description 11
- 230000005012 migration Effects 0.000 claims description 11
- 230000006978 adaptation Effects 0.000 claims description 10
- 238000007689 inspection Methods 0.000 claims description 8
- 238000006116 polymerization reaction Methods 0.000 claims description 7
- 239000011148 porous material Substances 0.000 claims description 7
- 239000002245 particle Substances 0.000 claims description 6
- 238000012937 correction Methods 0.000 claims description 5
- 239000000126 substance Substances 0.000 claims description 5
- 238000003860 storage Methods 0.000 description 7
- 230000007704 transition Effects 0.000 description 6
- 230000002776 aggregation Effects 0.000 description 2
- 238000004220 aggregation Methods 0.000 description 2
- 230000015556 catabolic process Effects 0.000 description 2
- 238000006731 degradation reaction Methods 0.000 description 2
- 230000002452 interceptive effect Effects 0.000 description 2
- 238000002844 melting Methods 0.000 description 2
- 230000008018 melting Effects 0.000 description 2
- 230000003287 optical effect Effects 0.000 description 2
- 238000010998 test method Methods 0.000 description 2
- RTAQQCXQSZGOHL-UHFFFAOYSA-N Titanium Chemical compound [Ti] RTAQQCXQSZGOHL-UHFFFAOYSA-N 0.000 description 1
- 238000001816 cooling Methods 0.000 description 1
- 238000005260 corrosion Methods 0.000 description 1
- 230000007797 corrosion Effects 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 238000010438 heat treatment Methods 0.000 description 1
- 229910052751 metal Inorganic materials 0.000 description 1
- 239000007769 metal material Substances 0.000 description 1
- 238000004321 preservation Methods 0.000 description 1
- 239000010936 titanium Substances 0.000 description 1
- 229910052719 titanium Inorganic materials 0.000 description 1
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Abstract
The embodiment of the application provides an intelligent analysis method and an intelligent analysis system for smelting effects applied to titanium alloy smelting. The method comprises the following steps: obtaining element information and attribute characteristic information of category titanium alloy batch smelting, obtaining a sample group of multiple smelting batches corresponding to product sampling, detecting each product sample in the sample group to obtain detection result data, processing the detection result data of each sample to obtain a product sample smelting effect index, extracting element characteristic data of each batch according to smelting element information and processing to obtain an interference coefficient, correcting and polymerizing the smelting effect index of each batch of product sample to obtain smelting quality evaluation data, and evaluating the smelting quality of all batches of titanium alloy through comparison results with a threshold value; therefore, effect detection and full-batch smelting quality effect evaluation are carried out on the titanium alloy smelting batch product samples based on big data, a smelting quality evaluation result of the titanium alloy smelting product is obtained, and the effect evaluation of titanium alloy smelting is realized.
Description
Technical Field
The application relates to the technical field of titanium alloy smelting, in particular to an intelligent analysis method and an intelligent analysis system for smelting effects applied to titanium alloy smelting.
Background
The titanium alloy is a high-strength, low-density and corrosion-resistant metal material composed of titanium and other metal elements, is widely applied to the fields of aviation, aerospace, chemical industry and the like, titanium alloy smelting is a key for preparing high-quality titanium alloy products, and comprises pretreatment, heating, heat preservation, cooling and other steps.
In view of the above problems, an effective technical solution is currently needed.
Disclosure of Invention
The embodiment of the application aims to provide an intelligent analysis method and an intelligent analysis system for smelting effects under titanium alloy smelting, which can be used for carrying out effect detection and whole-batch smelting quality effect evaluation on titanium alloy smelting batch product samples through big data to obtain a smelting quality evaluation result of titanium alloy smelting products and realize effect evaluation on titanium alloy smelting.
The embodiment of the application also provides an intelligent analysis method of the smelting effect applied to the smelting of the titanium alloy, which comprises the following steps:
obtaining smelting element information of a batch of titanium alloy smelting products of a smelting preset type of titanium alloy and smelting attribute characteristic information of titanium alloy smelting processing;
Sampling products of titanium alloy products of a plurality of smelting production batches according to the smelting attribute characteristic information according to a corresponding sampling method, obtaining smelting batch sample groups of each smelting production batch, and aggregating each sampling sample group into a smelting batch sample set;
Carrying out sample test detection on each smelting product sample in the smelting batch sample group, and extracting sample detection result data of the smelting product test samples;
Processing corresponding sample detection result data of each smelting product sample in the smelting batch sample group of each smelting production batch to obtain a product sample smelting achievement index;
Extracting smelting production element characteristic data of each smelting production batch according to the smelting element information, and processing to obtain smelting production effect interference coefficients of each smelting production batch;
Correcting and polymerizing the smelting achievement indexes of the product samples of the corresponding smelting production batches according to the smelting production achievement interference coefficients of the smelting production batches to obtain smelting quality evaluation data of the smelting batch sample set;
And carrying out threshold comparison according to the smelting quality evaluation data and a preset smelting quality detection threshold corresponding to the smelting attribute characteristic information, and evaluating the smelting quality of the titanium alloy smelting products of the smelting production batches according to threshold comparison results.
Optionally, in the method for intelligently analyzing a smelting effect applied to titanium alloy smelting according to the embodiment of the present application, the obtaining smelting element information of a batch of titanium alloy smelting products for smelting a preset type of titanium alloy and smelting attribute feature information of titanium alloy smelting processing includes:
obtaining a batch of titanium alloy smelting products of a preset type of titanium alloy obtained by smelting in a preset time period, and extracting smelting element information of the titanium alloy smelting products, wherein the smelting element information comprises titanium alloy raw material information, smelting equipment processing information and smelting process information;
Inquiring through a preset titanium alloy smelting database according to the titanium alloy raw material information and smelting process information to obtain smelting attribute characteristic information of smelting processing of a titanium alloy smelting product;
The smelting attribute characteristic information comprises smelting method modes, alloy components and smelting process attribute types.
Optionally, in the method for intelligently analyzing a smelting effect applied to smelting a titanium alloy according to the embodiment of the present application, product sampling is performed on titanium alloy products of a plurality of smelting production batches according to the smelting attribute feature information according to a corresponding sampling method, a smelting batch sample group of each smelting production batch is obtained, and each sampling sample group is aggregated into a smelting batch sample set, including:
Obtaining a corresponding titanium alloy product sampling method and a titanium alloy product inspection method through a preset titanium alloy smelting database according to the smelting method mode, alloy components and smelting process attribute types corresponding to the titanium alloy smelting product;
Respectively sampling titanium alloy smelting products of a plurality of smelting production batches according to the titanium alloy product sampling method to obtain smelting batch sample groups corresponding to each smelting production batch;
The smelting batch sample set includes a plurality of smelting product samples;
corresponding smelting batch sample sets of the plurality of smelting production batches are aggregated into a smelting batch sample set.
Optionally, in the method for intelligently analyzing a smelting effect applied to smelting a titanium alloy according to the embodiment of the present application, the sample test detection is performed on each smelting product sample in the smelting batch sample group, and sample detection result data of the smelting product test sample is extracted, including:
sample detection is carried out on each smelting product sample in the smelting batch sample group according to the titanium alloy product detection method;
extracting sample detection result data of a smelting product test sample, wherein the sample detection result data comprises sample physicochemical detection data, sample metallographic analysis detection data and sample mechanical property detection data;
the sample physical and chemical detection data comprise oxide content data, impurity particle data and air hole shrinkage density distribution data, the sample metallographic analysis detection data comprise grain size data, grain boundary migration data and crystallization non-uniformity data, and the sample mechanical property detection data comprise strength data, toughness data and hardness data.
Optionally, in the method for intelligently analyzing a smelting effect applied to titanium alloy smelting according to the embodiment of the present application, the processing the sample detection result data corresponding to each smelting product sample in the smelting batch sample group of each smelting production batch to obtain a product sample smelting achievement index includes:
Processing corresponding sample physicochemical detection data, sample metallographic analysis detection data and sample mechanical property detection data of each smelting product sample in the smelting batch sample group of each smelting production batch through a preset alloy smelting detection model to obtain a product sample smelting achievement index of the smelting batch sample group;
The calculation formula of the smelting achievement index of the product sample is as follows:
；
Wherein, Smelting achievement index for product sample,/>、/>、/>Oxide content data, impurity granularity data and pore shrinkage density distribution data of an ith smelting product sample are respectively obtained by using the method of,/>、/>、/>Grain size data, grain boundary migration data, and crystallization unevenness data of the ith molten product sample,/>, respectively、/>、/>Respectively the intensity data, the toughness data and the hardness data of the ith smelting product sample, wherein n is the number of smelting product samples in a smelting batch sample group,/>、/>、/>、/>、/>Is a preset characteristic coefficient.
Optionally, in the method for intelligently analyzing a smelting effect applied to smelting a titanium alloy according to the embodiment of the present application, extracting feature data of smelting production elements of each smelting production batch according to the smelting element information, and processing to obtain a smelting production effect interference coefficient of each smelting production batch includes:
Extracting smelting production element characteristic data corresponding to smelting production batches according to the smelting element information of each batch of titanium alloy smelting products, wherein the smelting production element characteristic data comprises titanium alloy raw material characteristic data, smelting equipment processing characteristic data and smelting processing technology monitoring data;
the titanium alloy raw material characteristic data comprises raw material proportion data and raw material granularity data, the smelting equipment processing characteristic data comprises smelting equipment reliability data and smelting cavity cleanliness data, and the smelting processing technology monitoring data comprises temperature control reliability monitoring data, smelting atmosphere adaptation degree data and overtemperature and superpressure amplitude frequency monitoring data;
Respectively processing according to the titanium alloy raw material characteristic data, the smelting equipment processing characteristic data and the smelting processing technology monitoring data to respectively obtain a raw material texture compensation coefficient, an equipment performance compensation coefficient and a technology steady-state compensation coefficient;
processing according to the raw material texture compensation coefficient, the equipment performance compensation coefficient and the process steady-state compensation coefficient to obtain smelting production effect interference coefficients of each smelting production batch;
the calculation formulas of the texture compensation coefficient, the equipment performance compensation coefficient and the process steady-state compensation coefficient of the raw materials are respectively as follows:
；
；
；
Wherein, Compensation coefficient for raw material texture,/>Compensation coefficient for device Performance,/>For the process steady state compensation coefficient,/>、/>Respectively raw material proportion data and raw material granularity data,/>、/>Respectively smelting equipment reliability data and smelting cavity cleanliness data,/>、/>、/>Respectively temperature control reliability monitoring data, smelting atmosphere adaptation degree data and overtemperature and overpressure amplitude-frequency monitoring data,/>、/>、/>、/>Is a preset characteristic coefficient;
the calculation formula of the smelting production effect interference coefficient is as follows:
；
Wherein, For smelting production effect interference coefficient,/>、/>、/>Respectively a raw material texture compensation coefficient, an equipment performance compensation coefficient and a process steady state compensation coefficient,/>Is a preset characteristic coefficient.
Optionally, in the method for intelligently analyzing a smelting effect applied to titanium alloy smelting according to the embodiment of the present application, the correcting and polymerizing the smelting achievement index of the product sample corresponding to each smelting production batch according to the smelting production achievement interference coefficient of each smelting production batch to obtain smelting quality evaluation data of the smelting batch sample set includes:
Carrying out correction polymerization treatment through a preset alloy smelting quality evaluation model according to the smelting production effect interference coefficient corresponding to each smelting production batch and the smelting effect index corresponding to the product sample, so as to obtain smelting quality evaluation data of the smelting batch sample set;
the calculation formula of the smelting quality evaluation data is as follows:
；
Wherein, For the evaluation of smelting quality and efficacy data,/>Smelting achievement index for the product sample of the jth smelting production lot,/>For the smelting production effect interference coefficient of the jth smelting production batch, m is the number of smelting production batches contained in the smelting batch sample set,/>And the preset characteristic coefficient corresponding to the smelting batch sample group of the jth smelting production batch is set.
In a second aspect, the embodiment of the application also provides a smelting effect intelligent analysis system applied to titanium alloy smelting, which comprises: the intelligent analysis device comprises a memory and a processor, wherein the memory comprises a program applied to the intelligent analysis method of the smelting effect under the titanium alloy smelting, and the program applied to the intelligent analysis method of the smelting effect under the titanium alloy smelting realizes the following steps when being executed by the processor:
obtaining smelting element information of a batch of titanium alloy smelting products of a smelting preset type of titanium alloy and smelting attribute characteristic information of titanium alloy smelting processing;
Sampling products of titanium alloy products of a plurality of smelting production batches according to the smelting attribute characteristic information according to a corresponding sampling method, obtaining smelting batch sample groups of each smelting production batch, and aggregating each sampling sample group into a smelting batch sample set;
Carrying out sample test detection on each smelting product sample in the smelting batch sample group, and extracting sample detection result data of the smelting product test samples;
Processing corresponding sample detection result data of each smelting product sample in the smelting batch sample group of each smelting production batch to obtain a product sample smelting achievement index;
Extracting smelting production element characteristic data of each smelting production batch according to the smelting element information, and processing to obtain smelting production effect interference coefficients of each smelting production batch;
Correcting and polymerizing the smelting achievement indexes of the product samples of the corresponding smelting production batches according to the smelting production achievement interference coefficients of the smelting production batches to obtain smelting quality evaluation data of the smelting batch sample set;
And carrying out threshold comparison according to the smelting quality evaluation data and a preset smelting quality detection threshold corresponding to the smelting attribute characteristic information, and evaluating the smelting quality of the titanium alloy smelting products of the smelting production batches according to threshold comparison results.
Optionally, in the intelligent analysis system for a smelting effect applied to titanium alloy smelting according to the embodiment of the present application, the obtaining smelting element information of a batch of titanium alloy smelting products for smelting a preset type of titanium alloy and smelting attribute feature information of titanium alloy smelting processing includes:
obtaining a batch of titanium alloy smelting products of a preset type of titanium alloy obtained by smelting in a preset time period, and extracting smelting element information of the titanium alloy smelting products, wherein the smelting element information comprises titanium alloy raw material information, smelting equipment processing information and smelting process information;
Inquiring through a preset titanium alloy smelting database according to the titanium alloy raw material information and smelting process information to obtain smelting attribute characteristic information of smelting processing of a titanium alloy smelting product;
The smelting attribute characteristic information comprises smelting method modes, alloy components and smelting process attribute types.
Optionally, in the intelligent analysis system for a smelting effect under titanium alloy smelting according to the embodiment of the present application, the product sampling is performed on titanium alloy products of a plurality of smelting production batches according to the smelting attribute feature information according to a corresponding sampling method, a smelting batch sample group of each smelting production batch is obtained, and each sampling sample group is aggregated into a smelting batch sample set, including:
Obtaining a corresponding titanium alloy product sampling method and a titanium alloy product inspection method through a preset titanium alloy smelting database according to the smelting method mode, alloy components and smelting process attribute types corresponding to the titanium alloy smelting product;
Respectively sampling titanium alloy smelting products of a plurality of smelting production batches according to the titanium alloy product sampling method to obtain smelting batch sample groups corresponding to each smelting production batch;
The smelting batch sample set includes a plurality of smelting product samples;
corresponding smelting batch sample sets of the plurality of smelting production batches are aggregated into a smelting batch sample set.
As can be seen from the above, the smelting effect intelligent analysis method and system applied to titanium alloy smelting provided by the embodiment of the application obtain the element information and attribute characteristic information of category titanium alloy batch smelting, obtain a sample group of multiple smelting batches corresponding to product sampling, detect each product sample in the sample group to obtain detection result data, process the detection result data of each sample to obtain a product sample smelting effect index, extract the element characteristic data of each batch according to the smelting element information and process to obtain an interference coefficient, correct and polymerize the smelting effect index of each batch of product samples to obtain smelting quality evaluation data, and evaluate the smelting quality of all batches of titanium alloy through the comparison result with a threshold; therefore, effect detection and full-batch smelting quality effect evaluation are carried out on the titanium alloy smelting batch product samples based on big data, a smelting quality evaluation result of the titanium alloy smelting product is obtained, and the effect evaluation of titanium alloy smelting is realized.
Additional features and advantages of the application will be set forth in the description which follows, and in part will be apparent from the description, or may be learned by practice of the embodiments of the application. The objectives and other advantages of the application may be realized and attained by the structure particularly pointed out in the written description and drawings.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the embodiments of the present application will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and should not be considered as limiting the scope, and other related drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a smelting effect intelligent analysis method applied to titanium alloy smelting, provided by an embodiment of the application;
Fig. 2 is a flowchart of obtaining smelting element information and smelting attribute feature information of a smelting effect intelligent analysis method applied to titanium alloy smelting provided by an embodiment of the application;
FIG. 3 is a flowchart of obtaining a smelting batch sample set of each smelting production batch by the intelligent analysis method for smelting effect under titanium alloy smelting provided by the embodiment of the application;
fig. 4 is a flowchart of sample detection result data of a test sample of a smelting product extracted by the intelligent analysis method of smelting effect applied to titanium alloy smelting, which is provided by the embodiment of the application.
Detailed Description
The following description of the embodiments of the present application will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present application, but not all embodiments. The components of the embodiments of the present application generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the application, as presented in the figures, is not intended to limit the scope of the application, as claimed, but is merely representative of selected embodiments of the application. All other embodiments, which can be made by a person skilled in the art without making any inventive effort, are intended to be within the scope of the present application.
It should be noted that like reference numerals and letters refer to like items in the following figures, and thus once an item is defined in one figure, no further definition or explanation thereof is necessary in the following figures. Meanwhile, in the description of the present application, the terms "first", "second", and the like are used only to distinguish the description, and are not to be construed as indicating or implying relative importance.
Referring to fig. 1, fig. 1 is a flowchart of a method for intelligent analysis of smelting effects applied to titanium alloy smelting in some embodiments of the application. The intelligent analysis method for the smelting effect applied to the smelting of the titanium alloy is used in terminal equipment, such as a computer, a mobile phone terminal and the like. The intelligent analysis method for the smelting effect applied to titanium alloy smelting comprises the following steps:
s11, obtaining smelting element information of a batch of titanium alloy smelting products of a smelting preset type of titanium alloy and smelting attribute characteristic information of titanium alloy smelting processing;
S12, sampling products of titanium alloy products of a plurality of smelting production batches according to the smelting attribute characteristic information according to a corresponding sampling method, obtaining smelting batch sample groups of each smelting production batch, and aggregating each sampling sample group into a smelting batch sample set;
s13, carrying out sample test detection on each smelting product sample in the smelting batch sample group, and extracting sample detection result data of the smelting product test samples;
S14, processing corresponding sample detection result data of each smelting product sample in the smelting batch sample group of each smelting production batch to obtain a product sample smelting achievement index;
S15, extracting smelting production element characteristic data of each smelting production batch according to the smelting element information, and processing to obtain smelting production effect interference coefficients of each smelting production batch;
s16, correcting and polymerizing the smelting achievement indexes of the product samples corresponding to the smelting production batches according to the smelting production achievement interference coefficients of the smelting production batches to obtain smelting quality evaluation data of the smelting batch sample sets;
S17, carrying out threshold comparison according to the smelting quality evaluation data and a preset smelting quality detection threshold corresponding to the smelting attribute characteristic information, and evaluating smelting quality of the titanium alloy smelting products of the smelting production batches according to threshold comparison results.
Wherein, in order to effectively evaluate the quality of titanium alloy products obtained by smelting, a plurality of batches of titanium alloy products of the category obtained by smelting are sampled according to a certain sampling and detecting method, and the samples are detected to obtain the detection results of each batch of samples, the detection results of each batch of detection samples are evaluated, and the smelting quality effect evaluation results of the batch of titanium alloy product samples are obtained by combining with the compensation interference elements of raw materials, equipment and processes related to smelting, the smelting effect quality of titanium alloy is detected according to the quality effect evaluation results, the technology of carrying out effect detection and full batch smelting quality effect evaluation on titanium alloy smelting batch products through big data is realized, in particular, the smelting element information of the smelting preset category titanium alloy products and the attribute characteristic information of processing and smelting are obtained through a preset titanium alloy smelting database, obtaining corresponding sampling methods according to attribute characteristic information, sampling products of each batch to obtain a sample group and a sample set of smelting batches, performing test detection on product samples in each sample group to obtain detection result data of each batch of sample groups, processing the detection result data of each batch of samples to obtain smelting effect indexes of the product samples to obtain smelting effect detection result data of each batch of sample groups, processing the obtained smelting element characteristic data of each batch to obtain smelting effect interference coefficients for compensating and interfering smelting titanium alloy effects for elements taking smelting production into consideration, correcting and aggregating the smelting effect indexes of the corresponding batches according to the interference coefficients to obtain smelting effect evaluation data of smelting batch sample sets of all batches of products to be evaluated, and finally, carrying out threshold comparison according to the quality evaluation data and a corresponding preset smelting quality detection threshold value, and evaluating the smelting quality of all batches of titanium alloy smelting products in the time period according to the threshold value comparison result, wherein if the smelting quality evaluation data is greater than or equal to the preset smelting quality detection threshold value, the smelting quality of all batches of titanium alloy smelting products is qualified, otherwise, if the smelting quality evaluation data is less than the preset smelting quality detection threshold value, the quality is not passed.
Referring to fig. 2, fig. 2 is a flowchart of obtaining smelting element information and smelting attribute feature information according to a smelting effect intelligent analysis method applied to titanium alloy smelting in some embodiments of the present application. According to the embodiment of the application, the smelting element information of the batch of titanium alloy smelting products for smelting the preset category of titanium alloy and the smelting attribute characteristic information of the titanium alloy smelting process are obtained, and specifically:
S21, obtaining a batch of titanium alloy smelting products of a preset type of titanium alloy obtained by smelting in a preset time period, and extracting smelting element information of the titanium alloy smelting products, wherein the smelting element information comprises titanium alloy raw material information, smelting equipment processing information and smelting process information;
S22, inquiring through a preset titanium alloy smelting database according to the titanium alloy raw material information and the smelting process information to obtain smelting attribute characteristic information of smelting processing of a titanium alloy smelting product;
S23, the smelting attribute characteristic information comprises a smelting method mode, alloy components and smelting process attribute types.
The method comprises the steps of obtaining the smelting attribute characteristics of the titanium alloy product to be evaluated, extracting smelting element information of the products of the plurality of batches of titanium alloy in a preset period, wherein the smelting element is a core element of the titanium alloy smelting process, is extracted through a preset smelting element information of a titanium alloy smelting database according to the preset smelting element which is correspondingly arranged in the processing process of the titanium alloy product, and comprises information of the titanium alloy raw material, smelting equipment processing and the smelting process, namely raw material, equipment and process information of the titanium alloy smelting process, and is obtained through a preset titanium alloy smelting database query according to the titanium alloy raw material and the smelting process information, and the preset titanium alloy smelting attribute characteristic information is obtained through a preset titanium alloy smelting database query according to the titanium alloy raw material and the smelting process information, and is a third-party attribute information and a third-party attribute information database, wherein the smelting attribute information comprises the attribute information of the titanium alloy is stored in the third-party attribute information database.
Referring to fig. 3, fig. 3 is a flowchart of a smelting batch sample set for obtaining each smelting production batch according to a smelting effect intelligent analysis method applied to titanium alloy smelting in some embodiments of the present application. According to the embodiment of the application, the product sampling is carried out on the titanium alloy products of a plurality of smelting production batches according to the smelting attribute characteristic information according to a corresponding sampling method, smelting batch sample groups of each smelting production batch are obtained, and the sampling sample groups are aggregated into a smelting batch sample set, specifically:
S31, acquiring a corresponding titanium alloy product sampling method and a titanium alloy product inspection method through a preset titanium alloy smelting database according to the smelting method mode, alloy components and smelting process attribute types corresponding to the titanium alloy smelting product;
s32, respectively sampling titanium alloy smelting products of a plurality of smelting production batches according to the titanium alloy product sampling method to obtain smelting batch sample groups corresponding to the smelting production batches;
S33, the smelting batch sample group comprises a plurality of smelting product samples;
S34, corresponding smelting batch sample groups of the smelting production batches are aggregated into a smelting batch sample set.
The method comprises the steps of acquiring a corresponding sampling method and a corresponding detection method according to attribute characteristic information of titanium alloy smelting products through a preset titanium alloy smelting database, performing control query acquisition according to the attribute characteristics of titanium alloy smelting, respectively sampling multiple batches of the titanium alloy products to obtain multiple samples of each batch corresponding to a sample group, aggregating the sample groups of all batches into a smelting batch sample set of the titanium alloy smelting products processed and produced in a preset time period, and further obtaining sample detection results of the titanium alloy smelting products of each batch through detection of the sample groups.
Referring to fig. 4, fig. 4 is a flowchart of sample detection result data of a test sample of a melted product extracted by the intelligent analysis method of melting effect applied to titanium alloy melting according to some embodiments of the present application. According to the embodiment of the application, the sample test is performed on each smelting product sample in the smelting batch sample group, and sample test result data of the smelting product test sample is extracted, specifically:
S41, carrying out sample detection on each smelting product sample in the smelting batch sample group according to the titanium alloy product detection method;
S42, extracting sample detection result data of a smelting product test sample, wherein the sample detection result data comprises sample physicochemical detection data, sample metallographic analysis detection data and sample mechanical property detection data;
s43, sample physical and chemical detection data comprise oxide content data, impurity particle data and air hole shrinkage density distribution data, sample metallographic analysis detection data comprise grain size data, grain boundary migration data and crystallization non-uniformity data, and sample mechanical property detection data comprise strength data, toughness data and hardness data.
The detection module is used for detecting samples of each batch of sample groups according to an obtained titanium alloy product detection test method, and is used for detecting physicochemical detection, metallographic analysis detection and mechanical property detection, and obtaining corresponding detection data, wherein the sample physicochemical detection data comprise oxide content detection data of the titanium alloy product samples, particle data of impurities and density distribution data of shrinkage porosity of finished product cross-section pores, the sample metallographic analysis detection data comprise grain size data of the titanium alloy product samples, migration data of grain boundaries and data of non-uniformity of crystallization, and the sample mechanical property detection data comprise strength detection data, toughness detection data and hardness detection data of the titanium alloy product samples.
According to an embodiment of the present invention, the processing of the sample detection result data corresponding to each smelting product sample in the smelting batch sample group of each smelting production batch to obtain a product sample smelting achievement index specifically includes:
Processing corresponding sample physicochemical detection data, sample metallographic analysis detection data and sample mechanical property detection data of each smelting product sample in the smelting batch sample group of each smelting production batch through a preset alloy smelting detection model to obtain a product sample smelting achievement index of the smelting batch sample group;
The calculation formula of the smelting achievement index of the product sample is as follows:
；
Wherein, Smelting achievement index for product sample,/>、/>、/>Oxide content data, impurity granularity data and pore shrinkage density distribution data of an ith smelting product sample are respectively obtained by using the method of,/>、/>、/>Grain size data, grain boundary migration data, and crystallization unevenness data of the ith molten product sample,/>, respectively、/>、/>Respectively the intensity data, the toughness data and the hardness data of the ith smelting product sample, wherein n is the number of smelting product samples in a smelting batch sample group,/>、/>、/>、/>、/>Is a preset characteristic coefficient (the characteristic coefficient is obtained through searching a preset titanium alloy smelting database).
The method comprises the steps of calculating sample physicochemical detection data, sample metallographic analysis detection data and sample mechanical property detection data of samples of smelting products in sample groups of each smelting production batch through a calculation formula of a preset alloy smelting detection model to obtain smelting achievement indexes of the sample products of the batch, and reflecting smelting achievement of the sample groups of each batch.
According to the embodiment of the invention, the feature data of the smelting production elements of each smelting production batch are extracted according to the smelting element information, and the smelting production effect interference coefficients of each smelting production batch are obtained through processing, specifically:
Extracting smelting production element characteristic data corresponding to smelting production batches according to the smelting element information of each batch of titanium alloy smelting products, wherein the smelting production element characteristic data comprises titanium alloy raw material characteristic data, smelting equipment processing characteristic data and smelting processing technology monitoring data;
the titanium alloy raw material characteristic data comprises raw material proportion data and raw material granularity data, the smelting equipment processing characteristic data comprises smelting equipment reliability data and smelting cavity cleanliness data, and the smelting processing technology monitoring data comprises temperature control reliability monitoring data, smelting atmosphere adaptation degree data and overtemperature and superpressure amplitude frequency monitoring data;
Respectively processing according to the titanium alloy raw material characteristic data, the smelting equipment processing characteristic data and the smelting processing technology monitoring data to respectively obtain a raw material texture compensation coefficient, an equipment performance compensation coefficient and a technology steady-state compensation coefficient;
processing according to the raw material texture compensation coefficient, the equipment performance compensation coefficient and the process steady-state compensation coefficient to obtain smelting production effect interference coefficients of each smelting production batch;
the calculation formulas of the texture compensation coefficient, the equipment performance compensation coefficient and the process steady-state compensation coefficient of the raw materials are respectively as follows:
；
；
；
Wherein, Compensation coefficient for raw material texture,/>Compensation coefficient for device Performance,/>For the process steady state compensation coefficient,/>、/>Respectively raw material proportion data and raw material granularity data,/>、/>Respectively smelting equipment reliability data and smelting cavity cleanliness data,/>、/>、/>Respectively temperature control reliability monitoring data, smelting atmosphere adaptation degree data and overtemperature and overpressure amplitude-frequency monitoring data,/>、/>、/>、/>The characteristic coefficient is preset (the characteristic coefficient is obtained by inquiring a preset titanium alloy smelting database);
the calculation formula of the smelting production effect interference coefficient is as follows:
；
Wherein, For smelting production effect interference coefficient,/>、/>、/>Respectively a raw material texture compensation coefficient, an equipment performance compensation coefficient and a process steady state compensation coefficient,/>Is a preset characteristic coefficient (the characteristic coefficient is obtained through searching a preset titanium alloy smelting database).
Wherein, because the production elements of titanium alloy smelting comprise raw materials, equipment and processes, each element has an influence and interference effect on the quality of titanium alloy smelting products, in order to obtain effective consideration and compensation of the production elements on the effect of smelting titanium alloy, the production element characteristics of each batch of titanium alloy smelting are processed to obtain the effect interference coefficient of each batch of smelting production, wherein, the extracted smelting production element characteristic data of the smelting production batch comprise titanium alloy raw material characteristic data, smelting equipment processing characteristic data and smelting processing technology monitoring data, the smelting production element characteristic data is characteristic data which is contained in the smelting element information and is related to the titanium alloy smelting, wherein, the characteristic data comprises raw material proportion data and raw material granularity data, the proportion and granularity influence on the smelting strength, plasticity and hardness, the smelting equipment processing characteristic data comprises smelting equipment reliability data and smelting cavity cleanliness data, the reliability of the smelting equipment is obtained by monitoring through presetting a titanium alloy smelting database platform, the smelting cavity cleanliness influence on the purity and metallographic distribution of the titanium alloy, the processing technology data comprises temperature control reliability, the temperature monitoring data and super-amplitude monitoring data and the super-amplitude monitoring data have a proper influence on the quality of the titanium alloy smelting, the quality is suitable for the quality of the titanium alloy, the quality is controlled, the quality is suitable for avoiding the phase transition, the quality is suitable for the quality of the transition, the quality is reduced, the quality is suitable for the quality is controlled, and the quality is reduced, the quality is suitable for the quality of the transition is reduced, and the quality is easy to be reduced, monitoring the over-temperature and over-pressure amplitude frequency in smelting to avoid titanium alloy quality degradation caused by temperature and pressure discomfort, respectively calculating to obtain a raw material texture compensation coefficient, an equipment performance compensation coefficient and a process steady-state compensation coefficient according to the data, and then processing and calculating to obtain smelting production effect interference coefficients of corresponding batches.
According to the embodiment of the invention, the smelting efficiency index of the product sample corresponding to each smelting production batch is corrected and polymerized according to the smelting production efficiency interference coefficient of each smelting production batch to obtain smelting quality efficiency evaluation data of the smelting batch sample set, specifically:
Carrying out correction polymerization treatment through a preset alloy smelting quality evaluation model according to the smelting production effect interference coefficient corresponding to each smelting production batch and the smelting effect index corresponding to the product sample, so as to obtain smelting quality evaluation data of the smelting batch sample set;
the calculation formula of the smelting quality evaluation data is as follows:
；
Wherein, For the evaluation of smelting quality and efficacy data,/>Smelting achievement index for the product sample of the jth smelting production lot,/>For the smelting production effect interference coefficient of the jth smelting production batch, m is the number of smelting production batches contained in the smelting batch sample set,/>And (3) corresponding preset characteristic coefficients for a smelting batch sample group of the jth smelting production batch (the characteristic coefficients are obtained through query of a preset titanium alloy smelting database).
And finally, in order to obtain quality evaluation and inspection of all production product batches in a preset time period, correcting and performing aggregation calculation on smelting effect indexes of corresponding batches according to smelting production effect interference coefficients of products in each batch through a calculation formula of a preset alloy smelting quality evaluation model, so as to obtain smelting quality evaluation data of smelting batch sample sets of all product batches, namely, total smelting quality evaluation results of the titanium alloy products smelted and processed in the preset time period.
The invention also discloses a smelting effect intelligent analysis system applied to titanium alloy smelting, which comprises: the intelligent analysis method for the smelting effect under the titanium alloy smelting comprises a memory and a processor, wherein the memory comprises an intelligent analysis method program for the smelting effect under the titanium alloy smelting, and the intelligent analysis method program for the smelting effect under the titanium alloy smelting realizes the following steps when being executed by the processor:
obtaining smelting element information of a batch of titanium alloy smelting products of a smelting preset type of titanium alloy and smelting attribute characteristic information of titanium alloy smelting processing;
Sampling products of titanium alloy products of a plurality of smelting production batches according to the smelting attribute characteristic information according to a corresponding sampling method, obtaining smelting batch sample groups of each smelting production batch, and aggregating each sampling sample group into a smelting batch sample set;
Carrying out sample test detection on each smelting product sample in the smelting batch sample group, and extracting sample detection result data of the smelting product test samples;
Processing corresponding sample detection result data of each smelting product sample in the smelting batch sample group of each smelting production batch to obtain a product sample smelting achievement index;
Extracting smelting production element characteristic data of each smelting production batch according to the smelting element information, and processing to obtain smelting production effect interference coefficients of each smelting production batch;
Correcting and polymerizing the smelting achievement indexes of the product samples of the corresponding smelting production batches according to the smelting production achievement interference coefficients of the smelting production batches to obtain smelting quality evaluation data of the smelting batch sample set;
And carrying out threshold comparison according to the smelting quality evaluation data and a preset smelting quality detection threshold corresponding to the smelting attribute characteristic information, and evaluating the smelting quality of the titanium alloy smelting products of the smelting production batches according to threshold comparison results.
Wherein, in order to effectively evaluate the quality of titanium alloy products obtained by smelting, a plurality of batches of titanium alloy products of the category obtained by smelting are sampled according to a certain sampling and detecting method, and the samples are detected to obtain the detection results of each batch of samples, the detection results of each batch of detection samples are evaluated, and the smelting quality effect evaluation results of the batch of titanium alloy product samples are obtained by combining with the compensation interference elements of raw materials, equipment and processes related to smelting, the smelting effect quality of titanium alloy is detected according to the quality effect evaluation results, the technology of carrying out effect detection and full batch smelting quality effect evaluation on titanium alloy smelting batch products through big data is realized, in particular, the smelting element information of the smelting preset category titanium alloy products and the attribute characteristic information of processing and smelting are obtained through a preset titanium alloy smelting database, obtaining corresponding sampling methods according to attribute characteristic information, sampling products of each batch to obtain a sample group and a sample set of smelting batches, performing test detection on product samples in each sample group to obtain detection result data of each batch of sample groups, processing the detection result data of each batch of samples to obtain smelting effect indexes of the product samples to obtain smelting effect detection result data of each batch of sample groups, processing the obtained smelting element characteristic data of each batch to obtain smelting effect interference coefficients for compensating and interfering smelting titanium alloy effects for elements taking smelting production into consideration, correcting and aggregating the smelting effect indexes of the corresponding batches according to the interference coefficients to obtain smelting effect evaluation data of smelting batch sample sets of all batches of products to be evaluated, and finally, carrying out threshold comparison according to the quality evaluation data and a corresponding preset smelting quality detection threshold value, and evaluating the smelting quality of all batches of titanium alloy smelting products in the time period according to the threshold value comparison result, wherein if the smelting quality evaluation data is greater than or equal to the preset smelting quality detection threshold value, the smelting quality of all batches of titanium alloy smelting products is qualified, otherwise, if the smelting quality evaluation data is less than the preset smelting quality detection threshold value, the quality is not passed.
According to the embodiment of the invention, the smelting element information of the batch of titanium alloy smelting products for smelting the preset category of titanium alloy and the smelting attribute characteristic information of the titanium alloy smelting process are obtained, and specifically:
obtaining a batch of titanium alloy smelting products of a preset type of titanium alloy obtained by smelting in a preset time period, and extracting smelting element information of the titanium alloy smelting products, wherein the smelting element information comprises titanium alloy raw material information, smelting equipment processing information and smelting process information;
Inquiring through a preset titanium alloy smelting database according to the titanium alloy raw material information and smelting process information to obtain smelting attribute characteristic information of smelting processing of a titanium alloy smelting product;
The smelting attribute characteristic information comprises smelting method modes, alloy components and smelting process attribute types.
The method comprises the steps of obtaining the smelting attribute characteristics of the titanium alloy product to be evaluated, extracting smelting element information of the products of the plurality of batches of titanium alloy in a preset period, wherein the smelting element is a core element of the titanium alloy smelting process, is extracted through a preset smelting element information of a titanium alloy smelting database according to the preset smelting element which is correspondingly arranged in the processing process of the titanium alloy product, and comprises information of the titanium alloy raw material, smelting equipment processing and the smelting process, namely raw material, equipment and process information of the titanium alloy smelting process, and is obtained through a preset titanium alloy smelting database query according to the titanium alloy raw material and the smelting process information, and the preset titanium alloy smelting attribute characteristic information is obtained through a preset titanium alloy smelting database query according to the titanium alloy raw material and the smelting process information, and is a third-party attribute information and a third-party attribute information database, wherein the smelting attribute information comprises the attribute information of the titanium alloy is stored in the third-party attribute information database.
According to the embodiment of the invention, the product sampling is carried out on the titanium alloy products of a plurality of smelting production batches according to the smelting attribute characteristic information according to a corresponding sampling method, smelting batch sample groups of each smelting production batch are obtained, and the sampling sample groups are aggregated into a smelting batch sample set, specifically:
Obtaining a corresponding titanium alloy product sampling method and a titanium alloy product inspection method through a preset titanium alloy smelting database according to the smelting method mode, alloy components and smelting process attribute types corresponding to the titanium alloy smelting product;
Respectively sampling titanium alloy smelting products of a plurality of smelting production batches according to the titanium alloy product sampling method to obtain smelting batch sample groups corresponding to each smelting production batch;
The smelting batch sample set includes a plurality of smelting product samples;
corresponding smelting batch sample sets of the plurality of smelting production batches are aggregated into a smelting batch sample set.
The method comprises the steps of acquiring a corresponding sampling method and a corresponding detection method according to attribute characteristic information of titanium alloy smelting products through a preset titanium alloy smelting database, performing control query acquisition according to the attribute characteristics of titanium alloy smelting, respectively sampling multiple batches of the titanium alloy products to obtain multiple samples of each batch corresponding to a sample group, aggregating the sample groups of all batches into a smelting batch sample set of the titanium alloy smelting products processed and produced in a preset time period, and further obtaining sample detection results of the titanium alloy smelting products of each batch through detection of the sample groups.
According to the embodiment of the invention, the sample test is performed on each smelting product sample in the smelting batch sample group, and sample test result data of the smelting product test sample is extracted, specifically:
sample detection is carried out on each smelting product sample in the smelting batch sample group according to the titanium alloy product detection method;
extracting sample detection result data of a smelting product test sample, wherein the sample detection result data comprises sample physicochemical detection data, sample metallographic analysis detection data and sample mechanical property detection data;
the sample physical and chemical detection data comprise oxide content data, impurity particle data and air hole shrinkage density distribution data, the sample metallographic analysis detection data comprise grain size data, grain boundary migration data and crystallization non-uniformity data, and the sample mechanical property detection data comprise strength data, toughness data and hardness data.
The detection module is used for detecting samples of each batch of sample groups according to an obtained titanium alloy product detection test method, and is used for detecting physicochemical detection, metallographic analysis detection and mechanical property detection, and obtaining corresponding detection data, wherein the sample physicochemical detection data comprise oxide content detection data of the titanium alloy product samples, particle data of impurities and density distribution data of shrinkage porosity of finished product cross-section pores, the sample metallographic analysis detection data comprise grain size data of the titanium alloy product samples, migration data of grain boundaries and data of non-uniformity of crystallization, and the sample mechanical property detection data comprise strength detection data, toughness detection data and hardness detection data of the titanium alloy product samples.
According to an embodiment of the present invention, the processing of the sample detection result data corresponding to each smelting product sample in the smelting batch sample group of each smelting production batch to obtain a product sample smelting achievement index specifically includes:
Processing corresponding sample physicochemical detection data, sample metallographic analysis detection data and sample mechanical property detection data of each smelting product sample in the smelting batch sample group of each smelting production batch through a preset alloy smelting detection model to obtain a product sample smelting achievement index of the smelting batch sample group;
The calculation formula of the smelting achievement index of the product sample is as follows:
；
Wherein, Smelting achievement index for product sample,/>、/>、/>Oxide content data, impurity granularity data and pore shrinkage density distribution data of an ith smelting product sample are respectively obtained by using the method of,/>、/>、/>Grain size data, grain boundary migration data, and crystallization unevenness data of the ith molten product sample,/>, respectively、/>、/>Respectively the intensity data, the toughness data and the hardness data of the ith smelting product sample, wherein n is the number of smelting product samples in a smelting batch sample group,/>、/>、/>、/>、/>Is a preset characteristic coefficient (the characteristic coefficient is obtained through searching a preset titanium alloy smelting database).
The method comprises the steps of calculating sample physicochemical detection data, sample metallographic analysis detection data and sample mechanical property detection data of samples of smelting products in sample groups of each smelting production batch through a calculation formula of a preset alloy smelting detection model to obtain smelting achievement indexes of the sample products of the batch, and reflecting smelting achievement of the sample groups of each batch.
According to the embodiment of the invention, the feature data of the smelting production elements of each smelting production batch are extracted according to the smelting element information, and the smelting production effect interference coefficients of each smelting production batch are obtained through processing, specifically:
Extracting smelting production element characteristic data corresponding to smelting production batches according to the smelting element information of each batch of titanium alloy smelting products, wherein the smelting production element characteristic data comprises titanium alloy raw material characteristic data, smelting equipment processing characteristic data and smelting processing technology monitoring data;
the titanium alloy raw material characteristic data comprises raw material proportion data and raw material granularity data, the smelting equipment processing characteristic data comprises smelting equipment reliability data and smelting cavity cleanliness data, and the smelting processing technology monitoring data comprises temperature control reliability monitoring data, smelting atmosphere adaptation degree data and overtemperature and superpressure amplitude frequency monitoring data;
Respectively processing according to the titanium alloy raw material characteristic data, the smelting equipment processing characteristic data and the smelting processing technology monitoring data to respectively obtain a raw material texture compensation coefficient, an equipment performance compensation coefficient and a technology steady-state compensation coefficient;
processing according to the raw material texture compensation coefficient, the equipment performance compensation coefficient and the process steady-state compensation coefficient to obtain smelting production effect interference coefficients of each smelting production batch;
the calculation formulas of the texture compensation coefficient, the equipment performance compensation coefficient and the process steady-state compensation coefficient of the raw materials are respectively as follows:
；
；/>
；
Wherein, Compensation coefficient for raw material texture,/>Compensation coefficient for device Performance,/>For the process steady state compensation coefficient,/>、/>Respectively raw material proportion data and raw material granularity data,/>、/>Respectively smelting equipment reliability data and smelting cavity cleanliness data,/>、/>、/>Respectively temperature control reliability monitoring data, smelting atmosphere adaptation degree data and overtemperature and overpressure amplitude-frequency monitoring data,/>、/>、/>、/>The characteristic coefficient is preset (the characteristic coefficient is obtained by inquiring a preset titanium alloy smelting database);
the calculation formula of the smelting production effect interference coefficient is as follows:
；
Wherein, For smelting production effect interference coefficient,/> Respectively a raw material texture compensation coefficient, an equipment performance compensation coefficient and a process steady state compensation coefficient,/>Is a preset characteristic coefficient (the characteristic coefficient is obtained through searching a preset titanium alloy smelting database).
Wherein, because the production elements of titanium alloy smelting comprise raw materials, equipment and processes, each element has an influence and interference effect on the quality of titanium alloy smelting products, in order to obtain effective consideration and compensation of the production elements on the effect of smelting titanium alloy, the production element characteristics of each batch of titanium alloy smelting are processed to obtain the effect interference coefficient of each batch of smelting production, wherein, the extracted smelting production element characteristic data of the smelting production batch comprise titanium alloy raw material characteristic data, smelting equipment processing characteristic data and smelting processing technology monitoring data, the smelting production element characteristic data is characteristic data which is contained in the smelting element information and is related to the titanium alloy smelting, wherein, the characteristic data comprises raw material proportion data and raw material granularity data, the proportion and granularity influence on the smelting strength, plasticity and hardness, the smelting equipment processing characteristic data comprises smelting equipment reliability data and smelting cavity cleanliness data, the reliability of the smelting equipment is obtained by monitoring through presetting a titanium alloy smelting database platform, the smelting cavity cleanliness influence on the purity and metallographic distribution of the titanium alloy, the processing technology data comprises temperature control reliability, the temperature monitoring data and super-amplitude monitoring data and the super-amplitude monitoring data have a proper influence on the quality of the titanium alloy smelting, the quality is suitable for the quality of the titanium alloy, the quality is controlled, the quality is suitable for avoiding the phase transition, the quality is suitable for the quality of the transition, the quality is reduced, the quality is suitable for the quality is controlled, and the quality is reduced, the quality is suitable for the quality of the transition is reduced, and the quality is easy to be reduced, monitoring the over-temperature and over-pressure amplitude frequency in smelting to avoid titanium alloy quality degradation caused by temperature and pressure discomfort, respectively calculating to obtain a raw material texture compensation coefficient, an equipment performance compensation coefficient and a process steady-state compensation coefficient according to the data, and then processing and calculating to obtain smelting production effect interference coefficients of corresponding batches.
According to the embodiment of the invention, the smelting efficiency index of the product sample corresponding to each smelting production batch is corrected and polymerized according to the smelting production efficiency interference coefficient of each smelting production batch to obtain smelting quality efficiency evaluation data of the smelting batch sample set, specifically:
Carrying out correction polymerization treatment through a preset alloy smelting quality evaluation model according to the smelting production effect interference coefficient corresponding to each smelting production batch and the smelting effect index corresponding to the product sample, so as to obtain smelting quality evaluation data of the smelting batch sample set;
the calculation formula of the smelting quality evaluation data is as follows:
；
Wherein, For the evaluation of smelting quality and efficacy data,/>Smelting achievement index for the product sample of the jth smelting production lot,/>For the smelting production effect interference coefficient of the jth smelting production batch, m is the number of smelting production batches contained in the smelting batch sample set,/>And (3) corresponding preset characteristic coefficients for a smelting batch sample group of the jth smelting production batch (the characteristic coefficients are obtained through query of a preset titanium alloy smelting database).
And finally, in order to obtain quality evaluation and inspection of all production product batches in a preset time period, correcting and performing aggregation calculation on smelting effect indexes of corresponding batches according to smelting production effect interference coefficients of products in each batch through a calculation formula of a preset alloy smelting quality evaluation model, so as to obtain smelting quality evaluation data of smelting batch sample sets of all product batches, namely, total smelting quality evaluation results of the titanium alloy products smelted and processed in the preset time period.
The invention discloses a smelting effect intelligent analysis method and a system applied to titanium alloy smelting, which are characterized in that element information and attribute characteristic information of category titanium alloy batch smelting are obtained, a sample group of multiple smelting batches is obtained by corresponding to product sampling, detection result data is obtained by detecting each product sample in the sample group, then the detection result data of each sample is processed to obtain a product sample smelting effect index, element characteristic data of each batch is extracted according to smelting element information and interference coefficients are obtained by processing, and then the smelting effect indexes of each batch of product samples are corrected and aggregated to obtain smelting quality effect evaluation data, and the smelting quality of all batches of titanium alloy is evaluated by comparing the detection result data with a threshold value; therefore, effect detection and full-batch smelting quality effect evaluation are carried out on the titanium alloy smelting batch product samples based on big data, a smelting quality evaluation result of the titanium alloy smelting product is obtained, and the effect evaluation of titanium alloy smelting is realized.
In the several embodiments provided by the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above described device embodiments are only illustrative, e.g. the division of the units is only one logical function division, and there may be other divisions in practice, such as: multiple units or components may be combined or may be integrated into another system, or some features may be omitted, or not performed. In addition, the various components shown or discussed may be coupled or directly coupled or communicatively coupled to each other via some interface, whether indirectly coupled or communicatively coupled to devices or units, whether electrically, mechanically, or otherwise.
The units described above as separate components may or may not be physically separate, and components shown as units may or may not be physical units; can be located in one place or distributed to a plurality of network units; some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in each embodiment of the present invention may be integrated in one processing unit, or each unit may be separately used as one unit, or two or more units may be integrated in one unit; the integrated units may be implemented in hardware or in hardware plus software functional units.
Those of ordinary skill in the art will appreciate that: all or part of the steps for implementing the above method embodiments may be implemented by hardware related to program instructions, and the foregoing program may be stored in a readable storage medium, where the program, when executed, performs steps including the above method embodiments; and the aforementioned storage medium includes: a mobile storage device, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk or optical disk, or the like, which can store program codes.
Or the above-described integrated units of the invention may be stored in a readable storage medium if implemented in the form of software functional modules and sold or used as separate products. Based on such understanding, the technical solution of the embodiments of the present invention may be embodied in essence or a part contributing to the prior art in the form of a software product stored in a storage medium, including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the methods described in the embodiments of the present invention. And the aforementioned storage medium includes: a removable storage device, ROM, RAM, magnetic or optical disk, or other medium capable of storing program code.
Claims (5)
1. The intelligent analysis method for the smelting effect applied to the titanium alloy smelting is characterized by comprising the following steps of:
obtaining smelting element information of a batch of titanium alloy smelting products of a smelting preset type of titanium alloy and smelting attribute characteristic information of titanium alloy smelting processing;
Sampling products of titanium alloy products of a plurality of smelting production batches according to the smelting attribute characteristic information according to a corresponding sampling method, obtaining smelting batch sample groups of each smelting production batch, and aggregating each sampling sample group into a smelting batch sample set;
Carrying out sample test detection on each smelting product sample in the smelting batch sample group, and extracting sample detection result data of the smelting product test samples;
Processing corresponding sample detection result data of each smelting product sample in the smelting batch sample group of each smelting production batch to obtain a product sample smelting achievement index;
Extracting smelting production element characteristic data of each smelting production batch according to the smelting element information, and processing to obtain smelting production effect interference coefficients of each smelting production batch;
Correcting and polymerizing the smelting achievement indexes of the product samples of the corresponding smelting production batches according to the smelting production achievement interference coefficients of the smelting production batches to obtain smelting quality evaluation data of the smelting batch sample set;
Threshold comparison is carried out according to the smelting quality evaluation data and a preset smelting quality detection threshold corresponding to the smelting attribute characteristic information, and smelting quality of the titanium alloy smelting products of the smelting production batches is evaluated according to threshold comparison results;
The obtaining smelting element information of a batch of titanium alloy smelting products of the smelted preset type titanium alloy and smelting attribute characteristic information of titanium alloy smelting processing comprises the following steps:
obtaining a batch of titanium alloy smelting products of a preset type of titanium alloy obtained by smelting in a preset time period, and extracting smelting element information of the titanium alloy smelting products, wherein the smelting element information comprises titanium alloy raw material information, smelting equipment processing information and smelting process information;
Inquiring through a preset titanium alloy smelting database according to the titanium alloy raw material information and smelting process information to obtain smelting attribute characteristic information of smelting processing of a titanium alloy smelting product;
The smelting attribute characteristic information comprises smelting method modes, alloy components and smelting process attribute types;
Processing the corresponding sample detection result data of each smelting product sample in the smelting batch sample group of each smelting production batch to obtain a product sample smelting achievement index, including:
processing corresponding sample physicochemical detection data, sample metallographic analysis detection data and sample mechanical property detection data of each smelting product sample in the smelting batch sample group of each smelting production batch through a preset alloy smelting detection model to obtain a product sample smelting achievement index of the smelting batch sample group;
The calculation formula of the smelting achievement index of the product sample is as follows:
；
Wherein, Smelting achievement index for product sample,/>Oxide content data, impurity granularity data and pore shrinkage density distribution data of an ith smelting product sample are respectively obtained by using the method of,/>Grain size data and grain boundary migration data and crystallization unevenness data of the ith smelting product sample are respectively obtained,Respectively the intensity data, the toughness data and the hardness data of the ith smelting product sample, wherein n is the number of smelting product samples in a smelting batch sample group,/>Is a preset characteristic coefficient;
extracting the characteristic data of the smelting production elements of each smelting production batch according to the smelting element information, and processing to obtain smelting production effect interference coefficients of each smelting production batch, wherein the method comprises the following steps:
Extracting smelting production element characteristic data corresponding to smelting production batches according to the smelting element information of each batch of titanium alloy smelting products, wherein the smelting production element characteristic data comprises titanium alloy raw material characteristic data, smelting equipment processing characteristic data and smelting processing technology monitoring data;
the titanium alloy raw material characteristic data comprises raw material proportion data and raw material granularity data, the smelting equipment processing characteristic data comprises smelting equipment reliability data and smelting cavity cleanliness data, and the smelting processing technology monitoring data comprises temperature control reliability monitoring data, smelting atmosphere adaptation degree data and overtemperature and superpressure amplitude frequency monitoring data;
Respectively processing according to the titanium alloy raw material characteristic data, the smelting equipment processing characteristic data and the smelting processing technology monitoring data to respectively obtain a raw material texture compensation coefficient, an equipment performance compensation coefficient and a technology steady-state compensation coefficient;
processing according to the raw material texture compensation coefficient, the equipment performance compensation coefficient and the process steady-state compensation coefficient to obtain smelting production effect interference coefficients of each smelting production batch;
the calculation formulas of the texture compensation coefficient, the equipment performance compensation coefficient and the process steady-state compensation coefficient of the raw materials are respectively as follows:
；
Wherein, Compensation coefficient for raw material texture,/>Compensation coefficient for device Performance,/>For the process steady state compensation coefficient,/>Respectively raw material proportion data and raw material granularity data,/>Respectively smelting equipment reliability data and smelting cavity cleanliness data,/>Respectively temperature control reliability monitoring data, smelting atmosphere adaptation degree data and overtemperature and overpressure amplitude-frequency monitoring data,/>Is a preset characteristic coefficient;
the calculation formula of the smelting production effect interference coefficient is as follows:
；
Wherein, For smelting production effect interference coefficient,/>Respectively a raw material texture compensation coefficient, an equipment performance compensation coefficient and a process steady state compensation coefficient,/>Is a preset characteristic coefficient;
The smelting production efficiency index of the product sample corresponding to each smelting production batch is corrected according to the smelting production efficiency interference coefficient of each smelting production batch and is subjected to polymerization treatment, and smelting quality evaluation data of the smelting batch sample set are obtained, and the method comprises the following steps:
Carrying out correction polymerization treatment through a preset alloy smelting quality evaluation model according to the smelting production effect interference coefficient corresponding to each smelting production batch and the smelting effect index corresponding to the product sample, so as to obtain smelting quality evaluation data of the smelting batch sample set;
the calculation formula of the smelting quality evaluation data is as follows:
；
Wherein, For the evaluation of smelting quality and efficacy data,/>Smelting achievement index for the product sample of the jth smelting production lot,/>For the smelting production effect interference coefficient of the jth smelting production batch, m is the number of smelting production batches contained in the smelting batch sample set,/>And the preset characteristic coefficient corresponding to the smelting batch sample group of the jth smelting production batch is set.
2. The intelligent analysis method for smelting effect under titanium alloy smelting according to claim 1, wherein the product sampling is performed on titanium alloy products of a plurality of smelting production batches according to the smelting attribute feature information according to a corresponding sampling method, smelting batch sample groups of each smelting production batch are obtained, and each sampling sample group is aggregated into a smelting batch sample set, and the intelligent analysis method comprises the following steps:
Obtaining a corresponding titanium alloy product sampling method and a titanium alloy product inspection method through a preset titanium alloy smelting database according to the smelting method mode, alloy components and smelting process attribute types corresponding to the titanium alloy smelting product;
Respectively sampling titanium alloy smelting products of a plurality of smelting production batches according to the titanium alloy product sampling method to obtain smelting batch sample groups corresponding to each smelting production batch;
The smelting batch sample set includes a plurality of smelting product samples;
corresponding smelting batch sample sets of the plurality of smelting production batches are aggregated into a smelting batch sample set.
3. The intelligent analysis method for smelting effect under titanium alloy smelting according to claim 2, wherein the performing sample test detection on each smelting product sample in the smelting batch sample group and extracting sample detection result data of the smelting product test sample comprises:
sample detection is carried out on each smelting product sample in the smelting batch sample group according to the titanium alloy product detection method;
extracting sample detection result data of a smelting product test sample, wherein the sample detection result data comprises sample physicochemical detection data, sample metallographic analysis detection data and sample mechanical property detection data;
the sample physical and chemical detection data comprise oxide content data, impurity particle data and air hole shrinkage density distribution data, the sample metallographic analysis detection data comprise grain size data, grain boundary migration data and crystallization non-uniformity data, and the sample mechanical property detection data comprise strength data, toughness data and hardness data.
4. Be applied to intelligent analytic system of smelting effect under titanium alloy smelting, its characterized in that, this system includes: the intelligent analysis device comprises a memory and a processor, wherein the memory comprises a program applied to the intelligent analysis method of the smelting effect under the titanium alloy smelting, and the program applied to the intelligent analysis method of the smelting effect under the titanium alloy smelting realizes the following steps when being executed by the processor:
obtaining smelting element information of a batch of titanium alloy smelting products of a smelting preset type of titanium alloy and smelting attribute characteristic information of titanium alloy smelting processing;
Sampling products of titanium alloy products of a plurality of smelting production batches according to the smelting attribute characteristic information according to a corresponding sampling method, obtaining smelting batch sample groups of each smelting production batch, and aggregating each sampling sample group into a smelting batch sample set;
Carrying out sample test detection on each smelting product sample in the smelting batch sample group, and extracting sample detection result data of the smelting product test samples;
Processing corresponding sample detection result data of each smelting product sample in the smelting batch sample group of each smelting production batch to obtain a product sample smelting achievement index;
Extracting smelting production element characteristic data of each smelting production batch according to the smelting element information, and processing to obtain smelting production effect interference coefficients of each smelting production batch;
Correcting and polymerizing the smelting achievement indexes of the product samples of the corresponding smelting production batches according to the smelting production achievement interference coefficients of the smelting production batches to obtain smelting quality evaluation data of the smelting batch sample set;
Threshold comparison is carried out according to the smelting quality evaluation data and a preset smelting quality detection threshold corresponding to the smelting attribute characteristic information, and smelting quality of the titanium alloy smelting products of the smelting production batches is evaluated according to threshold comparison results;
The obtaining smelting element information of a batch of titanium alloy smelting products of the smelted preset type titanium alloy and smelting attribute characteristic information of titanium alloy smelting processing comprises the following steps:
obtaining a batch of titanium alloy smelting products of a preset type of titanium alloy obtained by smelting in a preset time period, and extracting smelting element information of the titanium alloy smelting products, wherein the smelting element information comprises titanium alloy raw material information, smelting equipment processing information and smelting process information;
Inquiring through a preset titanium alloy smelting database according to the titanium alloy raw material information and smelting process information to obtain smelting attribute characteristic information of smelting processing of a titanium alloy smelting product;
The smelting attribute characteristic information comprises smelting method modes, alloy components and smelting process attribute types;
Processing the corresponding sample detection result data of each smelting product sample in the smelting batch sample group of each smelting production batch to obtain a product sample smelting achievement index, including:
Processing corresponding sample physicochemical detection data, sample metallographic analysis detection data and sample mechanical property detection data of each smelting product sample in the smelting batch sample group of each smelting production batch through a preset alloy smelting detection model to obtain a product sample smelting achievement index of the smelting batch sample group;
The calculation formula of the smelting achievement index of the product sample is as follows:
；
Wherein, Smelting achievement index for product sample,/>Oxide content data, impurity granularity data and pore shrinkage density distribution data of an ith smelting product sample are respectively obtained by using the method of,/>Grain size data and grain boundary migration data and crystallization unevenness data of the ith smelting product sample are respectively obtained,Respectively the intensity data, the toughness data and the hardness data of the ith smelting product sample, wherein n is the number of smelting product samples in a smelting batch sample group,/>Is a preset characteristic coefficient;
extracting the characteristic data of the smelting production elements of each smelting production batch according to the smelting element information, and processing to obtain smelting production effect interference coefficients of each smelting production batch, wherein the method comprises the following steps:
Extracting smelting production element characteristic data corresponding to smelting production batches according to the smelting element information of each batch of titanium alloy smelting products, wherein the smelting production element characteristic data comprises titanium alloy raw material characteristic data, smelting equipment processing characteristic data and smelting processing technology monitoring data;
the titanium alloy raw material characteristic data comprises raw material proportion data and raw material granularity data, the smelting equipment processing characteristic data comprises smelting equipment reliability data and smelting cavity cleanliness data, and the smelting processing technology monitoring data comprises temperature control reliability monitoring data, smelting atmosphere adaptation degree data and overtemperature and superpressure amplitude frequency monitoring data;
Respectively processing according to the titanium alloy raw material characteristic data, the smelting equipment processing characteristic data and the smelting processing technology monitoring data to respectively obtain a raw material texture compensation coefficient, an equipment performance compensation coefficient and a technology steady-state compensation coefficient;
processing according to the raw material texture compensation coefficient, the equipment performance compensation coefficient and the process steady-state compensation coefficient to obtain smelting production effect interference coefficients of each smelting production batch;
the calculation formulas of the texture compensation coefficient, the equipment performance compensation coefficient and the process steady-state compensation coefficient of the raw materials are respectively as follows:
；
Wherein, Compensation coefficient for raw material texture,/>Compensation coefficient for device Performance,/>For the process steady state compensation coefficient,/>Respectively raw material proportion data and raw material granularity data,/>Respectively smelting equipment reliability data and smelting cavity cleanliness data,/>Respectively temperature control reliability monitoring data, smelting atmosphere adaptation degree data and overtemperature and overpressure amplitude-frequency monitoring data,/>Is a preset characteristic coefficient;
the calculation formula of the smelting production effect interference coefficient is as follows:
；
Wherein, For smelting production effect interference coefficient,/>Respectively a raw material texture compensation coefficient, an equipment performance compensation coefficient and a process steady state compensation coefficient,/>Is a preset characteristic coefficient;
The smelting production efficiency index of the product sample corresponding to each smelting production batch is corrected according to the smelting production efficiency interference coefficient of each smelting production batch and is subjected to polymerization treatment, and smelting quality evaluation data of the smelting batch sample set are obtained, and the method comprises the following steps:
Carrying out correction polymerization treatment through a preset alloy smelting quality evaluation model according to the smelting production effect interference coefficient corresponding to each smelting production batch and the smelting effect index corresponding to the product sample, so as to obtain smelting quality evaluation data of the smelting batch sample set;
the calculation formula of the smelting quality evaluation data is as follows:
；
Wherein, For the evaluation of smelting quality and efficacy data,/>Smelting achievement index for the product sample of the jth smelting production lot,/>For the smelting production effect interference coefficient of the jth smelting production batch, m is the number of smelting production batches contained in the smelting batch sample set,/>And the preset characteristic coefficient corresponding to the smelting batch sample group of the jth smelting production batch is set.
5. The intelligent analysis system for smelting effect under titanium alloy smelting according to claim 4, wherein the sampling of the titanium alloy products of the plurality of smelting production batches according to the smelting attribute feature information according to the corresponding sampling method, obtaining smelting batch sample groups of each smelting production batch, and aggregating each sampling sample group into a smelting batch sample set, comprises:
Obtaining a corresponding titanium alloy product sampling method and a titanium alloy product inspection method through a preset titanium alloy smelting database according to the smelting method mode, alloy components and smelting process attribute types corresponding to the titanium alloy smelting product;
Respectively sampling titanium alloy smelting products of a plurality of smelting production batches according to the titanium alloy product sampling method to obtain smelting batch sample groups corresponding to each smelting production batch;
The smelting batch sample set includes a plurality of smelting product samples;
corresponding smelting batch sample sets of the plurality of smelting production batches are aggregated into a smelting batch sample set.
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