CN118098459A - Automatic analysis system and method for material test data - Google Patents
Automatic analysis system and method for material test data Download PDFInfo
- Publication number
- CN118098459A CN118098459A CN202410480419.5A CN202410480419A CN118098459A CN 118098459 A CN118098459 A CN 118098459A CN 202410480419 A CN202410480419 A CN 202410480419A CN 118098459 A CN118098459 A CN 118098459A
- Authority
- CN
- China
- Prior art keywords
- data
- test data
- sub
- analysis
- representing
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000012360 testing method Methods 0.000 title claims abstract description 188
- 239000000463 material Substances 0.000 title claims abstract description 108
- 238000004458 analytical method Methods 0.000 title claims abstract description 61
- 238000000034 method Methods 0.000 title claims description 54
- 238000007405 data analysis Methods 0.000 claims abstract description 143
- 230000007797 corrosion Effects 0.000 claims abstract description 67
- 238000005260 corrosion Methods 0.000 claims abstract description 67
- 238000011056 performance test Methods 0.000 claims abstract description 59
- 239000000126 substance Substances 0.000 claims abstract description 54
- 230000005856 abnormality Effects 0.000 claims abstract description 33
- 238000002076 thermal analysis method Methods 0.000 claims abstract description 28
- 238000013178 mathematical model Methods 0.000 claims abstract description 8
- 238000004154 testing of material Methods 0.000 claims description 10
- OKTJSMMVPCPJKN-UHFFFAOYSA-N Carbon Chemical compound [C] OKTJSMMVPCPJKN-UHFFFAOYSA-N 0.000 claims description 8
- 229910052799 carbon Inorganic materials 0.000 claims description 8
- 239000000203 mixture Substances 0.000 claims description 7
- 238000010521 absorption reaction Methods 0.000 claims description 6
- 230000009477 glass transition Effects 0.000 claims description 6
- 239000012535 impurity Substances 0.000 claims description 6
- 238000005259 measurement Methods 0.000 claims description 6
- 238000002844 melting Methods 0.000 claims description 6
- 230000008018 melting Effects 0.000 claims description 6
- 239000013077 target material Substances 0.000 claims description 6
- 238000007373 indentation Methods 0.000 claims description 5
- 238000000638 solvent extraction Methods 0.000 claims description 5
- 239000002131 composite material Substances 0.000 claims description 3
- 238000005530 etching Methods 0.000 claims description 3
- 238000011156 evaluation Methods 0.000 abstract description 5
- 230000008676 import Effects 0.000 description 5
- 238000012545 processing Methods 0.000 description 5
- 230000008569 process Effects 0.000 description 3
- 238000011161 development Methods 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 230000006872 improvement Effects 0.000 description 2
- 230000002159 abnormal effect Effects 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 238000004140 cleaning Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000003909 pattern recognition Methods 0.000 description 1
- 230000000704 physical effect Effects 0.000 description 1
- 230000001737 promoting effect Effects 0.000 description 1
- 238000007619 statistical method Methods 0.000 description 1
- 230000009897 systematic effect Effects 0.000 description 1
Landscapes
- Testing Resistance To Weather, Investigating Materials By Mechanical Methods (AREA)
Abstract
The invention discloses an automatic analysis system and an automatic analysis method for material test data, and particularly relates to the field of data analysis. The invention can automatically collect mechanical performance test data such as tensile strength, impact toughness, hardness and the like, and chemical performance test data such as components, thermal analysis, corrosion resistance and the like, converts the mechanical performance test data into valuable evaluation on material performance through a mathematical model, and finally calculates the material abnormality index of each sub-data area through a comprehensive analysis module, thereby providing powerful support for accurate judgment of material quality.
Description
Technical Field
The invention relates to the technical field of data analysis, in particular to an automatic analysis system and method for material test data.
Background
With the rapid development of technology, new materials are continuously emerging, and the performance and application of the new materials are directly related to the product quality and technological progress, so that the material test is particularly important, and the new materials are not only key links for ensuring the quality and safety of the materials, but also important means for promoting the development and application of the new materials. Through scientific and systematic tests, the performance characteristics of the material can be deeply known, and powerful support is provided for material selection and application.
The existing material test data analysis system collects various material test data including mechanical property data, chemical property data, physical property data and the like of materials through corresponding sensors and test equipment, specifically depends on the purpose of the test and the material characteristics required to be analyzed, then performs operations such as cleaning, arrangement, conversion and the like on the collected raw data to eliminate interference factors such as noise, abnormal values and the like, unifies the data formats so as to facilitate subsequent analysis and processing, and then performs deep analysis on the preprocessed data by utilizing a predefined data analysis model and algorithm, wherein the method may comprise various methods such as statistical analysis, trend prediction, pattern recognition and the like, and aims at extracting useful information and characteristics from the data.
However, when the system is actually used, some disadvantages still exist, such as the existing material test data processing system can only process single type of test data, comprehensive analysis of multiple types of test data cannot be performed, and other systems can process multiple types of data, but still have defects in accuracy and efficiency of data processing and analysis, and in addition, the systems often lack effective management and division of different batches of material test data, so that it is difficult to accurately evaluate the performance of materials in the analysis process.
Disclosure of Invention
In order to overcome the above-mentioned drawbacks of the prior art, embodiments of the present invention provide an automated analysis system and method for material test data, which solve the problems set forth in the background art.
In order to achieve the above purpose, the present invention provides the following technical solutions: an automated material testing data analysis system comprising:
Material test data dividing module: the method comprises the steps of determining target material test data as target data areas, dividing the target data areas into sub data areas according to a material test batch dividing mode, and marking the sub data areas as 1 and 2 … … n in sequence;
the mechanical performance test data acquisition module: the system comprises a mechanical performance test data analysis module, a tensile strength test data acquisition module, a mechanical performance test data analysis module and a hardness test module, wherein the mechanical performance test data acquisition module is used for acquiring tensile strength test data, impact toughness test data and hardness test data of each sub-data area;
Mechanical performance test data analysis module: the system comprises a tensile strength test data analysis unit, an impact toughness test data analysis unit and a hardness test data analysis unit, and transmits analyzed data to a comprehensive analysis module;
The chemical performance test data acquisition module: the system comprises a chemical property test data analysis module, a chemical property test data analysis module and a data analysis module, wherein the chemical property test data analysis module is used for analyzing the chemical property test data of each sub-data area;
Chemical performance test data analysis module: the system comprises a component data analysis unit, a thermal analysis data analysis unit and a corrosion resistance test data analysis unit, and transmits the analyzed data to a comprehensive analysis module;
And the comprehensive analysis module is used for: the material abnormality index of each sub-data area is calculated through the material test data comprehensive analysis model and is transmitted to the judging module;
and a judging module: and the method is used for judging the material abnormality index of each sub-data area according to the material abnormality index target value.
Preferably, the tensile strength test data includes maximum tensile force, elongation at break, young's modulus, and tensile rate, respectively labeled as、/>、/>And/>Impact toughness test data including impact absorption energy, impact velocity, specimen notch depth, and specimen thickness, respectively labeled/>、/>、/>And/>The hardness test data includes Vickers hardness value, loading force, time to hold, and indentation diagonal length, respectively labeled/>、/>、/>And/>。
Preferably, the tensile strength test data analysis unit is configured to establish a tensile strength test data analysis model, import tensile strength test data transmitted by the mechanical performance test data acquisition module into the tensile strength test data analysis module, and calculate a tensile strength characteristic coefficient of each sub-data area, where the tensile strength characteristic coefficient is specifically expressed as:，/> Representing the tensile strength characteristic coefficient of the ith sub-data region,/> Representing the maximum tensile force of the i-th sub-data area,/>Representing the elongation at break of the ith sub-data region,/>Representing Young's modulus of the ith sub-data region,/>Representing the stretch rate of the ith sub-data region,/>Representing the maximum stretching force of the target data area.
Preferably, the impact toughness test data analysis unit is configured to establish an impact toughness test data analysis model, guide the impact toughness test data transmitted by the mechanical performance test data acquisition module into the impact toughness test data analysis module, and calculate the impact toughness characteristic coefficient of each sub-data area, where the impact toughness characteristic coefficient is specifically expressed as:，/> impact toughness characteristic coefficient representing the ith sub-data region,/> Impact absorption energy representing the i-th sub-data area,/>Representing the impact velocity of the ith sub-data region,/>Sample notch depth representing the i-th sub-data region,/>The sample thickness of the i-th sub data area is shown.
Preferably, the hardness test data analysis unit is configured to establish a hardness test data analysis model, import the hardness test data transmitted by the mechanical performance test data acquisition module into the hardness test data analysis module, and calculate the hardness characteristic coefficient of each sub-data area, where the hardness characteristic coefficient is specifically expressed as:，/> hardness characteristic coefficient of the ith sub-data area,/>, is represented Vickers hardness number,/>, representing the i-th sub-data areaRepresenting the loading force of the ith sub-data region,/>Representing the time of the payload of the ith sub-data region,/>Representing the indentation diagonal length of the i-th sub-data area.
Preferably, the mechanical performance test data analysis module calculates the comprehensive mechanical performance index of the ith sub-data area through the tensile strength characteristic coefficient of the ith sub-data area, the impact toughness characteristic coefficient of the ith sub-data area and the hardness characteristic coefficient of the ith sub-data area, and the specific mathematical model is as follows:。
Preferably, the composition data includes a main element content, an impurity element content, a carbon equivalent, and a density, respectively labeled as 、/>、/>And/>Thermal analysis data includes coefficient of thermal expansion, thermal conductivity, thermal stability temperature, glass transition temperature, and melting point, labeled/>, respectively、/>、/>、/>And/>Corrosion resistance test data including corrosion rate, corrosion medium concentration, corrosion temperature, and corrosion time, respectively labeled/>、/>、/>And/>。
Preferably, the component data analysis unit is configured to establish a component data analysis model, import the component data transmitted by the chemical property measurement data acquisition module into the component data analysis model, and calculate a material component characteristic value of each sub-data area, where the material component characteristic value is specifically expressed as:，/> Characteristic value of material composition representing the ith sub-data area,/> Representing the main element content of the ith sub-data area,/>Represents the impurity element content of the i-th sub data region,/>Representing the carbon equivalent of the ith sub-data region,/>Representing the density of the i-th sub data area.
Preferably, the thermal analysis data analysis unit is configured to establish a thermal analysis data analysis model, import thermal analysis data transmitted by the chemical property measurement data acquisition module into the thermal analysis data analysis model, and calculate a thermal property comprehensive feature value of each sub-data area, where the thermal property comprehensive feature value is specifically expressed as:，/> representing the thermal performance composite characteristic value of the ith sub-data region,/> Representing the coefficient of thermal expansion of the ith sub-data region,/>Representing the thermal conductivity of the ith sub-data region,/>Representing the thermal stability temperature of the ith sub-data region,/>Representing the glass transition temperature of the ith sub-data region,/>The melting point of the i-th sub data area is indicated.
Preferably, the corrosion resistance test data analysis unit is configured to establish a corrosion resistance test data analysis model, import the corrosion resistance test data transmitted by the chemical property test data acquisition module into the corrosion resistance test data analysis model, and calculate corrosion resistance coefficients of each sub-data area, where the corrosion resistance coefficients are specifically expressed as:， representing the corrosion resistance coefficient of the ith sub-data area,/> Representing the corrosion rate of the ith sub-data region,/>Represents the etching medium concentration of the ith sub-data area,/>Represents the corrosion temperature of the ith sub-data area,/>The corrosion time of the ith sub data area is represented by j, the corrosion time of the ith sub data area is divided into time areas by equal time division, and j=1 and 2 … … m.
Preferably, the chemical performance test data analysis module calculates the comprehensive chemical performance index of the ith sub-data area through the material component characteristic value of the ith sub-data area, the thermal performance comprehensive characteristic value of the ith sub-data area and the corrosion resistance coefficient of the ith sub-data area, and the specific mathematical model is as follows:。
Preferably, the comprehensive analysis module is configured to introduce the data transmitted by the mechanical performance test data analysis module and the chemical performance test data analysis module into a comprehensive analysis model of material test data, and calculate a material anomaly index of each sub-data area, where a specific mathematical model is: ，/> Material anomaly index representing the ith sub-data region,/> Index of integrated mechanical properties representing the ith sub-data region,/>Index of comprehensive chemical Properties representing the ith sub-data region,/>Representing the preset value of the comprehensive mechanical property index/>Indicating the preset value of the comprehensive chemical property index.
Preferably, the material abnormality index target value is marked asWhen/>When, it is stated that the material quality of the ith test batch is good, when/>When this is the case, the material quality of the ith test batch is poor.
Preferably, an automatic analysis method for material test data comprises the following specific steps:
Step 1: material test data partitioning: the method comprises the steps of determining target material test data as target data areas, dividing the target data areas into sub data areas according to a material test batch dividing mode, and numbering;
step 2: mechanical property test data acquisition: the method comprises the steps of collecting tensile strength test data, impact toughness test data and hardness test data of each sub-data area, and transmitting the collected data to a mechanical performance test data analysis step;
step 3: mechanical property test data analysis: the method comprises a tensile strength test data analysis method, an impact toughness test data analysis method and a hardness test data analysis method, and the analyzed data are transmitted to a comprehensive analysis step;
Step 4: chemical property test data acquisition: the method comprises the steps of collecting component data, thermal analysis data and corrosion resistance test data of each sub-data area, and transmitting the collected data to a chemical performance test data analysis step;
step 5: analysis of chemical property test data: the method comprises a component data analysis method, a thermal analysis data analysis method and a corrosion resistance test data analysis method, and the analyzed data is transmitted to a comprehensive analysis step;
step 6: comprehensive analysis: the method comprises the steps of establishing a comprehensive analysis model of material test data, calculating the material abnormality index of each sub-data area through the comprehensive analysis model of the material test data, and transmitting the material abnormality index to a judging step;
step 7: judging: and the method is used for judging the material abnormality index of each sub-data area according to the material abnormality index target value.
The invention has the technical effects and advantages that:
According to the invention, a data partitioning strategy is adopted, a target data area is partitioned into a plurality of sub-data areas, so that data processing is more efficient, in the aspect of mechanical performance test, the system can automatically collect key data such as tensile strength, impact toughness, hardness and the like, and the key data are deeply analyzed through a special data analysis unit, so that characteristic coefficients and comprehensive mechanical performance indexes of all the sub-data areas are calculated, comprehensive and accurate data support is provided for mechanical performance test, and the improvement of product quality and performance evaluation level is facilitated; in the aspect of chemical performance test, the system collects multidimensional data such as components, thermal analysis, corrosion resistance and the like, a model is built through an analysis module, a characteristic value, a comprehensive characteristic value and a corrosion resistance coefficient are calculated, factors such as element content, carbon equivalent, density, thermal expansion coefficient, thermal conductivity, corrosion rate, medium concentration, temperature and time are comprehensively considered, and a scientific basis is provided for material performance evaluation; finally, the system calculates the material abnormality index of each sub-data area through the comprehensive analysis module by combining the mechanical and chemical performance test data so as to evaluate the quality of the material, and if the material abnormality index is within a preset range, the material abnormality index is judged to be good in quality; if the test data exceeds the range, the quality is judged to be poor, the comprehensive and efficient analysis of the material performance is realized, and the utilization rate and accuracy of the test data are improved.
Drawings
Fig. 1 is a schematic diagram of the overall structure of the present invention.
FIG. 2 is a schematic diagram of the method of the present invention.
Detailed Description
The following description of the embodiments of the present invention 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 invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The automatic analysis system for the material test data comprises a material test data dividing module, a mechanical performance test data acquisition module, a mechanical performance test data analysis module, a chemical performance test data acquisition module, a chemical performance test data analysis module, a comprehensive analysis module and a judgment module.
The material test data dividing module is used for determining target material test data as target data areas, dividing the target data areas into sub data areas according to a material test batch dividing mode, and marking the sub data areas as 1 and 2 … … n in sequence.
The mechanical performance test data acquisition module is used for acquiring tensile strength test data, impact toughness test data and hardness test data of each sub-data area and transmitting the acquired data to the mechanical performance test data analysis module.
The tensile strength test data includes maximum tensile force, elongation at break, young's modulus, and tensile rate, respectively labeled、/>、/>And/>Impact toughness test data including impact absorption energy, impact velocity, specimen notch depth, and specimen thickness, respectively labeled/>、/>、/>And/>The hardness test data includes Vickers hardness value, loading force, time to hold, and indentation diagonal length, respectively labeled/>、/>、/>And/>。
The mechanical performance test data analysis module comprises a tensile strength test data analysis unit, an impact toughness test data analysis unit and a hardness test data analysis unit, and transmits the analyzed data to the comprehensive analysis module.
The tensile strength test data analysis unit is used for establishing a tensile strength test data analysis model, importing tensile strength test data transmitted by the mechanical performance test data acquisition module into the tensile strength test data analysis module, and calculating the tensile strength characteristic coefficients of all the sub-data areas, wherein the tensile strength characteristic coefficients are specifically expressed as follows:，/> Representing the tensile strength characteristic coefficient of the ith sub-data region,/> Representing the maximum tensile force of the i-th sub-data area,/>Representing the elongation at break of the ith sub-data region,/>Representing Young's modulus of the ith sub-data region,/>Representing the stretch rate of the ith sub-data region,/>Representing the maximum stretching force of the target data area.
The impact toughness test data analysis unit is used for establishing an impact toughness test data analysis model, importing the impact toughness test data transmitted by the mechanical performance test data acquisition module into the impact toughness test data analysis module, and calculating the impact toughness characteristic coefficients of all the sub-data areas, wherein the impact toughness characteristic coefficients are specifically expressed as follows:，/> impact toughness characteristic coefficient representing the ith sub-data region,/> Impact absorption energy representing the i-th sub-data area,/>Representing the impact velocity of the ith sub-data region,/>Sample notch depth representing the i-th sub-data region,/>The sample thickness of the i-th sub data area is shown.
The hardness test data analysis unit is used for establishing a hardness test data analysis model, importing the hardness test data transmitted by the mechanical performance test data acquisition module into the hardness test data analysis module, and calculating the hardness characteristic coefficients of all the sub-data areas, wherein the hardness characteristic coefficients are specifically expressed as follows:，/> hardness characteristic coefficient of the ith sub-data area,/>, is represented Vickers hardness number,/>, representing the i-th sub-data areaRepresenting the loading force of the i-th sub data area,Representing the time of the payload of the ith sub-data region,/>Representing the indentation diagonal length of the i-th sub-data area.
The mechanical performance test data analysis module calculates the comprehensive mechanical performance index of the ith sub-data area through the tensile strength characteristic coefficient of the ith sub-data area, the impact toughness characteristic coefficient of the ith sub-data area and the hardness characteristic coefficient of the ith sub-data area, and the specific mathematical model is as follows:。
The chemical performance test data acquisition module is used for acquiring component data, thermal analysis data and corrosion resistance test data of each sub-data area and transmitting the acquired data to the chemical performance test data analysis module.
The composition data includes main element content, impurity element content, carbon equivalent, and density, respectively marked as、/>、/>And/>Thermal analysis data includes coefficient of thermal expansion, thermal conductivity, thermal stability temperature, glass transition temperature, and melting point, labeled/>, respectively、/>、/>、/>And/>Corrosion resistance test data including corrosion rate, corrosion medium concentration, corrosion temperature, and corrosion time, respectively labeled/>、/>、/>And/>。
The chemical performance test data analysis module comprises a component data analysis unit, a thermal analysis data analysis unit and a corrosion resistance test data analysis unit, and transmits the analyzed data to the comprehensive analysis module.
The component data analysis unit is used for establishing a component data analysis model, importing the component data transmitted by the chemical property measurement data acquisition module into the component data analysis model, and calculating the characteristic values of the material components of each sub-data area, wherein the characteristic values are specifically expressed as follows:，/> Characteristic value of material composition representing the ith sub-data area,/> Representing the main element content of the ith sub-data area,/>Represents the impurity element content of the i-th sub data region,/>Representing the carbon equivalent of the ith sub-data region,/>Representing the density of the i-th sub data area.
The thermal analysis data analysis unit is used for establishing a thermal analysis data analysis model, importing thermal analysis data transmitted by the chemical property measurement data acquisition module into the thermal analysis data analysis model, and calculating the thermal property comprehensive characteristic value of each sub-data area, wherein the thermal property comprehensive characteristic value is specifically expressed as follows:，/> representing the thermal performance composite characteristic value of the ith sub-data region,/> Representing the coefficient of thermal expansion of the ith sub-data region,/>Representing the thermal conductivity of the ith sub-data region,/>Representing the thermal stability temperature of the ith sub-data region,/>Representing the glass transition temperature of the ith sub-data region,/>The melting point of the i-th sub data area is indicated.
The corrosion resistance test data analysis unit is used for establishing a corrosion resistance test data analysis model, importing corrosion resistance test data transmitted by the chemical property test data acquisition module into the corrosion resistance test data analysis model, and calculating corrosion resistance coefficients of all the sub-data areas, wherein the corrosion resistance coefficients are specifically expressed as:，/> representing the corrosion resistance coefficient of the ith sub-data area,/> Representing the corrosion rate of the ith sub-data region,/>Represents the etching medium concentration of the ith sub-data area,/>Represents the corrosion temperature of the ith sub-data area,/>The corrosion time of the ith sub data area is represented by j, the corrosion time of the ith sub data area is divided into time areas by equal time division, and j=1 and 2 … … m.
The chemical performance test data analysis module calculates the comprehensive chemical performance index of the ith sub-data area through the material composition characteristic value of the ith sub-data area, the thermal performance comprehensive characteristic value of the ith sub-data area and the corrosion resistance coefficient of the ith sub-data area, and the specific mathematical model is as follows:。
The comprehensive analysis module is used for establishing a comprehensive analysis model of the material test data, calculating the material abnormality index of each sub-data area through the comprehensive analysis model of the material test data, and transmitting the material abnormality index to the judgment module.
The comprehensive analysis module is used for importing the data transmitted by the mechanical performance test data analysis module and the chemical performance test data analysis module into a material test data comprehensive analysis model, and calculating the material abnormality index of each sub-data area, wherein the specific mathematical model is as follows:，/> Material anomaly index representing the ith sub-data region,/> Index of integrated mechanical properties representing the ith sub-data region,/>Index of comprehensive chemical Properties representing the ith sub-data region,/>Representing the preset value of the comprehensive mechanical property index/>Indicating the preset value of the comprehensive chemical property index.
The judging module is used for judging the material abnormality index of each sub-data area according to the material abnormality index target value.
The material abnormality index target value is marked asWhen/>When, it is stated that the material quality of the ith test batch is good, when/>When this is the case, the material quality of the ith test batch is poor.
Referring to fig. 2, an automated analysis method for material testing data includes the following specific steps:
Step 1: material test data partitioning: the method comprises the steps of determining target material test data as target data areas, dividing the target data areas into sub data areas according to a material test batch dividing mode, and numbering;
step 2: mechanical property test data acquisition: the method comprises the steps of collecting tensile strength test data, impact toughness test data and hardness test data of each sub-data area, and transmitting the collected data to a mechanical performance test data analysis step;
step 3: mechanical property test data analysis: the method comprises a tensile strength test data analysis method, an impact toughness test data analysis method and a hardness test data analysis method, and the analyzed data are transmitted to a comprehensive analysis step;
Step 4: chemical property test data acquisition: the method comprises the steps of collecting component data, thermal analysis data and corrosion resistance test data of each sub-data area, and transmitting the collected data to a chemical performance test data analysis step;
step 5: analysis of chemical property test data: the method comprises a component data analysis method, a thermal analysis data analysis method and a corrosion resistance test data analysis method, and the analyzed data is transmitted to a comprehensive analysis step;
step 6: comprehensive analysis: the method comprises the steps of establishing a comprehensive analysis model of material test data, calculating the material abnormality index of each sub-data area through the comprehensive analysis model of the material test data, and transmitting the material abnormality index to a judging step;
step 7: judging: and the method is used for judging the material abnormality index of each sub-data area according to the material abnormality index target value.
According to the invention, a data partitioning strategy is adopted, a target data area is partitioned into a plurality of sub-data areas, so that data processing is more efficient, in the aspect of mechanical performance test, the system can automatically collect key data such as tensile strength, impact toughness, hardness and the like, and the key data are deeply analyzed through a special data analysis unit, so that characteristic coefficients and comprehensive mechanical performance indexes of all the sub-data areas are calculated, comprehensive and accurate data support is provided for mechanical performance test, and the improvement of product quality and performance evaluation level is facilitated; in the aspect of chemical performance test, the system collects multidimensional data such as components, thermal analysis, corrosion resistance and the like, a model is built through an analysis module, a characteristic value, a comprehensive characteristic value and a corrosion resistance coefficient are calculated, factors such as element content, carbon equivalent, density, thermal expansion coefficient, thermal conductivity, corrosion rate, medium concentration, temperature and time are comprehensively considered, and a scientific basis is provided for material performance evaluation; finally, the system calculates the material abnormality index of each sub-data area through the comprehensive analysis module by combining the mechanical and chemical performance test data so as to evaluate the quality of the material, and if the material abnormality index is within a preset range, the material abnormality index is judged to be good in quality; if the test data exceeds the range, the quality is judged to be poor, the comprehensive and efficient analysis of the material performance is realized, and the utilization rate and accuracy of the test data are improved.
Secondly: in the drawings of the disclosed embodiments, only the structures related to the embodiments of the present disclosure are referred to, and other structures can refer to the common design, so that the same embodiment and different embodiments of the present disclosure can be combined with each other under the condition of no conflict;
Finally: the foregoing description of the preferred embodiments of the invention is not intended to limit the invention to the precise form disclosed, and any such modifications, equivalents, and alternatives falling within the spirit and principles of the invention are intended to be included within the scope of the invention.
Claims (9)
1. An automated material testing data analysis system, comprising:
Material test data dividing module: the method comprises the steps of determining target material test data as target data areas, dividing the target data areas into sub data areas according to a material test batch dividing mode, and marking the sub data areas as 1 and 2 … … n in sequence;
the mechanical performance test data acquisition module: the system comprises a mechanical performance test data analysis module, a tensile strength test data acquisition module, a mechanical performance test data analysis module and a hardness test module, wherein the mechanical performance test data acquisition module is used for acquiring tensile strength test data, impact toughness test data and hardness test data of each sub-data area;
Mechanical performance test data analysis module: the system comprises a tensile strength test data analysis unit, an impact toughness test data analysis unit and a hardness test data analysis unit, and transmits analyzed data to a comprehensive analysis module;
The chemical performance test data acquisition module: the system comprises a chemical property test data analysis module, a chemical property test data analysis module and a data analysis module, wherein the chemical property test data analysis module is used for analyzing the chemical property test data of each sub-data area;
Chemical performance test data analysis module: the system comprises a component data analysis unit, a thermal analysis data analysis unit and a corrosion resistance test data analysis unit, and transmits the analyzed data to a comprehensive analysis module;
And the comprehensive analysis module is used for: the material abnormality index of each sub-data area is calculated through the material test data comprehensive analysis model and is transmitted to the judging module;
and a judging module: and the method is used for judging the material abnormality index of each sub-data area according to the material abnormality index target value.
2. An automated material testing data analysis system according to claim 1, wherein: the tensile strength test data includes maximum tensile force, elongation at break, young's modulus, and tensile rate, respectively labeled、/>、/>And/>Impact toughness test data including impact absorption energy, impact velocity, specimen notch depth, and specimen thickness, respectively labeled/>、/>、/>And/>The hardness test data includes Vickers hardness value, loading force, time to hold, and indentation diagonal length, respectively labeled/>、/>、/>And/>；
The composition data includes main element content, impurity element content, carbon equivalent, and density, respectively marked as、、/>And/>Thermal analysis data includes coefficient of thermal expansion, thermal conductivity, thermal stability temperature, glass transition temperature, and melting point, labeled/>, respectively、/>、/>、/>And/>Corrosion resistance test data including corrosion rate, corrosion medium concentration, corrosion temperature, and corrosion time, respectively labeled/>、/>、/>And/>。
3. An automated material testing data analysis system according to claim 1, wherein: the tensile strength test data analysis unit is used for establishing a tensile strength test data analysis model, importing tensile strength test data transmitted by the mechanical performance test data acquisition module into the tensile strength test data analysis module, and calculating the tensile strength characteristic coefficients of all the sub-data areas, wherein the tensile strength characteristic coefficients are specifically expressed as follows:，/> Representing the tensile strength characteristic coefficient of the ith sub-data region,/> Representing the maximum tensile force of the i-th sub-data area,/>Representing the elongation at break of the ith sub-data region,/>Representing Young's modulus of the ith sub-data region,/>Representing the stretch rate of the ith sub-data area,Representing the maximum stretching force of the target data area.
4. An automated material testing data analysis system according to claim 1, wherein: the impact toughness test data analysis unit is used for establishing an impact toughness test data analysis model, importing the impact toughness test data transmitted by the mechanical performance test data acquisition module into the impact toughness test data analysis module, and calculating the impact toughness characteristic coefficients of all the sub-data areas, wherein the impact toughness characteristic coefficients are specifically expressed as follows:，/> impact toughness characteristic coefficient representing the ith sub-data region,/> Impact absorption energy representing the i-th sub-data area,/>Representing the impact velocity of the ith sub-data region,/>Sample notch depth representing the i-th sub-data region,/>The sample thickness of the i-th sub data area is shown.
5. An automated material testing data analysis system according to claim 1, wherein: the component data analysis unit is used for establishing a component data analysis model, importing the component data transmitted by the chemical property measurement data acquisition module into the component data analysis model, and calculating the characteristic values of the material components of each sub-data area, wherein the characteristic values are specifically expressed as follows:，/> Characteristic value of material composition representing the ith sub-data area,/> Representing the main element content of the ith sub-data area,/>Represents the impurity element content of the i-th sub data region,/>Representing the carbon equivalent of the ith sub-data region,/>Representing the density of the i-th sub data area.
6. An automated material testing data analysis system according to claim 1, wherein: the thermal analysis data analysis unit is used for establishing a thermal analysis data analysis model, importing thermal analysis data transmitted by the chemical property measurement data acquisition module into the thermal analysis data analysis model, and calculating the thermal property comprehensive characteristic value of each sub-data area, wherein the thermal property comprehensive characteristic value is specifically expressed as follows:，/> representing the thermal performance composite characteristic value of the ith sub-data region,/> Representing the coefficient of thermal expansion of the ith sub-data region,/>Representing the thermal conductivity of the ith sub-data area,Representing the thermal stability temperature of the ith sub-data region,/>Indicating the glass transition temperature of the i-th sub data area,The melting point of the i-th sub data area is indicated.
7. An automated material testing data analysis system according to claim 1, wherein: the corrosion resistance test data analysis unit is used for establishing a corrosion resistance test data analysis model, importing corrosion resistance test data transmitted by the chemical property test data acquisition module into the corrosion resistance test data analysis model, and calculating corrosion resistance coefficients of all the sub-data areas, wherein the corrosion resistance coefficients are specifically expressed as:，/> representing the corrosion resistance coefficient of the ith sub-data area,/> Representing the corrosion rate of the ith sub-data region,/>Represents the etching medium concentration of the ith sub-data area,/>Represents the corrosion temperature of the ith sub-data area,/>The corrosion time of the ith sub data area is represented by j, the corrosion time of the ith sub data area is divided into time areas by equal time division, and j=1 and 2 … … m.
8. An automated material testing data analysis system according to claim 1, wherein: the comprehensive analysis module is used for importing the data transmitted by the mechanical performance test data analysis module and the chemical performance test data analysis module into a material test data comprehensive analysis model, and calculating the material abnormality index of each sub-data area, wherein the specific mathematical model is as follows:，/> Material anomaly index representing the ith sub-data region,/> Index of integrated mechanical properties representing the ith sub-data region,/>Index of comprehensive chemical Properties representing the ith sub-data region,/>Representing the preset value of the comprehensive mechanical property index/>Indicating the preset value of the comprehensive chemical property index.
9. A method of automated analysis of material test data using a system of automated analysis of material test data as claimed in any one of claims 1 to 8, comprising the steps of:
Step 1: material test data partitioning: the method comprises the steps of determining target material test data as target data areas, dividing the target data areas into sub data areas according to a material test batch dividing mode, and numbering;
step 2: mechanical property test data acquisition: the method comprises the steps of collecting tensile strength test data, impact toughness test data and hardness test data of each sub-data area, and transmitting the collected data to a mechanical performance test data analysis step;
step 3: mechanical property test data analysis: the method comprises a tensile strength test data analysis method, an impact toughness test data analysis method and a hardness test data analysis method, and the analyzed data are transmitted to a comprehensive analysis step;
Step 4: chemical property test data acquisition: the method comprises the steps of collecting component data, thermal analysis data and corrosion resistance test data of each sub-data area, and transmitting the collected data to a chemical performance test data analysis step;
step 5: analysis of chemical property test data: the method comprises a component data analysis method, a thermal analysis data analysis method and a corrosion resistance test data analysis method, and the analyzed data is transmitted to a comprehensive analysis step;
step 6: comprehensive analysis: the method comprises the steps of establishing a comprehensive analysis model of material test data, calculating the material abnormality index of each sub-data area through the comprehensive analysis model of the material test data, and transmitting the material abnormality index to a judging step;
step 7: judging: and the method is used for judging the material abnormality index of each sub-data area according to the material abnormality index target value.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202410480419.5A CN118098459B (en) | 2024-04-22 | Automatic analysis system and method for material test data |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202410480419.5A CN118098459B (en) | 2024-04-22 | Automatic analysis system and method for material test data |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN118098459A true CN118098459A (en) | 2024-05-28 |
| CN118098459B CN118098459B (en) | 2024-07-05 |
Family
ID=
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20160001355A1 (en) * | 2013-02-26 | 2016-01-07 | Deepak Chowdhary | Computer implemented systems and methods for optimization of sand for reducing casting rejections |
| CN110472349A (en) * | 2019-08-20 | 2019-11-19 | 武汉科技大学 | A kind of hot-rolled steel performance prediction method based on EEMD and depth convolutional network |
| CN114330114A (en) * | 2021-12-20 | 2022-04-12 | 郑州信大先进技术研究院 | Beryllium bronze alloy corrosion rate prediction method based on quantum support vector machine |
| CN115906566A (en) * | 2022-11-18 | 2023-04-04 | 中国航空综合技术研究所 | Equipment mechanical reliability analysis method and system based on durability analysis |
| CN117807398A (en) * | 2024-01-09 | 2024-04-02 | 连云港原秀科技有限公司 | Intelligent die management and control system based on data analysis |
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20160001355A1 (en) * | 2013-02-26 | 2016-01-07 | Deepak Chowdhary | Computer implemented systems and methods for optimization of sand for reducing casting rejections |
| CN110472349A (en) * | 2019-08-20 | 2019-11-19 | 武汉科技大学 | A kind of hot-rolled steel performance prediction method based on EEMD and depth convolutional network |
| CN114330114A (en) * | 2021-12-20 | 2022-04-12 | 郑州信大先进技术研究院 | Beryllium bronze alloy corrosion rate prediction method based on quantum support vector machine |
| CN115906566A (en) * | 2022-11-18 | 2023-04-04 | 中国航空综合技术研究所 | Equipment mechanical reliability analysis method and system based on durability analysis |
| CN117807398A (en) * | 2024-01-09 | 2024-04-02 | 连云港原秀科技有限公司 | Intelligent die management and control system based on data analysis |
Non-Patent Citations (1)
| Title |
|---|
| 曹子林 等: "铝基复合材料的制备和研究现状", 《金属功能材料》, vol. 30, no. 2, 20 March 2023 (2023-03-20) * |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN114861509B (en) | Special steel heat treatment process data processing method and system | |
| CN107885928A (en) | Consider the stepstress acceleration Degradation Reliability analysis method of measurement error | |
| CN116128260B (en) | Data sample-based key enterprise environment analysis method | |
| CN116167640B (en) | LCP film production quality detection data analysis method and system | |
| CN109725133B (en) | Soil moisture real-time monitoring system and monitoring method thereof | |
| CN114266537A (en) | Product performance testing system based on industrial internet | |
| CN116070527B (en) | Milling cutter residual life prediction method based on degradation model | |
| CN117312816B (en) | Special steel smelting effect evaluation method and system | |
| CN111105082A (en) | Workpiece quality prediction model construction method and prediction method based on machine learning | |
| CN110414086B (en) | Sensitivity-based comprehensive stress acceleration factor calculation method | |
| CN118098459B (en) | Automatic analysis system and method for material test data | |
| CN118098459A (en) | Automatic analysis system and method for material test data | |
| CN111881800A (en) | Concrete filled steel tube void defect detection method based on AR model and self-service inspection | |
| CN116662800A (en) | Rolling bearing fault diagnosis method based on self-adaptive attention mechanism | |
| CN111124816A (en) | HDP algorithm-based server log analysis method and system | |
| CN117235489A (en) | Graph variation self-coding feature extraction method for multi-source monitoring data of transmission system | |
| CN113889274B (en) | Method and device for constructing risk prediction model of autism spectrum disorder | |
| CN115985411A (en) | Soft measurement method for polymer melt index based on Gaussian process regression model | |
| CN113588266B (en) | Rolling bearing composite fault diagnosis method with embedded fault semantic space | |
| AU2021104998A4 (en) | Evaluation method system of quality control index for the whole process of monitoring organic pollutants in basin water environment | |
| CN112069621B (en) | Method for predicting residual service life of rolling bearing based on linear reliability index | |
| CN115421045A (en) | Method and device for analyzing influence factors of battery health degree | |
| CN111861271B (en) | Pipeline heat insulation performance evaluation method | |
| CN117554762B (en) | Transformer insulation part aging model building method, medium and system | |
| CN116682505B (en) | HRB400E steel mechanical property prediction method based on quantile regression forest |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant |