CN117291477A - Metal hot working quality control method and system - Google Patents
Metal hot working quality control method and system Download PDFInfo
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Abstract
The invention discloses a metal hot working quality control method and a metal hot working quality control system, which belong to the field of machining control, wherein the method comprises the following steps: collecting target material characteristics and target performance characteristics of a target workpiece; determining a tempering process scheme by analyzing the target material characteristics and the target performance characteristics, including a heating process scheme and a cooling process scheme; the heating chamber in the continuous tempering furnace is used for carrying out heating treatment on the target workpiece based on a heating process scheme to obtain a target heated workpiece; the cooling chamber in the continuous tempering furnace carries out cooling treatment on the target heating workpiece based on a cooling process scheme to obtain a target cooling workpiece; and conveying the target cooled workpiece serving as a target tempered workpiece from the continuous tempering furnace to the next processing stage through a conveying belt. The technical problem that the product quality level of metal hot working is lower in the prior art is solved, the technical effects of accurately controlling metal hot working parameters and improving the product quality of metal hot working are achieved.
Description
Technical Field
The invention relates to the field of processing control, in particular to a metal hot processing quality control method and system.
Background
Tempering is a key process for ensuring the quality of metal materials during metal hot working. At present, in the tempering process, metal hot working control is mainly carried out by virtue of preset experience parameters, the tempering process cannot be dynamically adjusted according to the material characteristics and performance requirements of different workpieces, the fine control capability is poor, the parameters can not be changed according to the workpiece characteristics, the tempering effect in the metal hot working is difficult to reach the best, and the product quality is poor.
Disclosure of Invention
The application aims to solve the technical problem of lower quality level of metal hot working products in the prior art by providing a metal hot working quality control method and system.
In view of the above, the present application provides a method and a system for controlling the quality of metal hot working.
In a first aspect of the present disclosure, a method for controlling quality of hot working of metal is provided, the method comprising: collecting target workpiece features of a target workpiece, wherein the target workpiece features comprise target material features and target performance features; determining a tempering process scheme, wherein the tempering process scheme is determined by analyzing the characteristics of the target material and the characteristics of the target performance; the heating chamber in the continuous tempering furnace carries out heating treatment on the target workpiece based on a heating process scheme in the tempering process scheme to obtain the target heated workpiece; the cooling chamber in the continuous tempering furnace carries out cooling treatment on the target heating workpiece based on a cooling process scheme in the tempering process scheme to obtain a target cooling workpiece; and conveying the target tempered workpiece serving as the target cooled workpiece from the continuous tempering furnace to the next processing stage through a conveying belt.
In another aspect of the present disclosure, a metal hot working quality control system is provided, the system comprising: the workpiece feature acquisition module is used for acquiring target workpiece features of a target workpiece, wherein the target workpiece features comprise target material features and target performance features; the tempering process determining module is used for determining a tempering process scheme, wherein the tempering process scheme is determined by analyzing the characteristics of the target material and the characteristics of the target performance; the workpiece heating treatment module is used for heating the target workpiece by the heating chamber in the continuous tempering furnace based on the heating process scheme in the tempering process scheme to obtain the target heated workpiece; the workpiece cooling treatment module is used for cooling the target heating workpiece by the cooling chamber in the continuous tempering furnace based on the cooling process scheme in the tempering process scheme to obtain a target cooling workpiece; and the target workpiece conveying module is used for conveying the target cooled workpiece serving as a target tempered workpiece from the continuous tempering furnace to the next processing stage through the conveying belt.
One or more technical solutions provided in the present application have at least the following technical effects or advantages:
the key information such as specific material composition, hardness, strength and the like of the workpiece is acquired by acquiring the target material characteristics and the target performance characteristics of the target workpiece, so that a basis is provided for determining a reasonable tempering scheme; determining a tempering process scheme by analyzing the characteristics of the target material and the characteristics of the target performance, wherein the tempering process scheme comprises a heating process scheme and a cooling process scheme, and realizing targeted customization of the tempering process scheme of the target workpiece; in a heating chamber of the continuous tempering furnace, processing the target workpiece according to a determined heating process scheme, so as to ensure accurate control of a heating process; in a cooling chamber of the continuous tempering furnace, according to a determined cooling process scheme, the cooling rate is accurately controlled, so that the cooling is prevented from being too fast or too slow; the technical scheme of the whole automatic tempering process is completed by conveying the target cooled workpiece subjected to accurate tempering to the next process, the technical problem of lower quality level of the metal hot-working product in the prior art is solved, and the technical effects of accurately controlling metal hot-working parameters and improving the quality of the metal hot-working product are achieved.
The foregoing description is only an overview of the technical solutions of the present application, and may be implemented according to the content of the specification in order to make the technical means of the present application more clearly understood, and in order to make the above-mentioned and other objects, features and advantages of the present application more clearly understood, the following detailed description of the present application will be given.
Drawings
Fig. 1 is a schematic flow chart of a metal hot working quality control method according to an embodiment of the present application;
FIG. 2 is a schematic flow chart of a tempering process decision model obtained in a metal hot working quality control method according to an embodiment of the present application;
fig. 3 is a schematic structural diagram of a metal hot working quality control system according to an embodiment of the present application.
Reference numerals illustrate: the device comprises a workpiece characteristic acquisition module 11, a tempering process determination module 12, a workpiece heating processing module 13, a workpiece cooling processing module 14 and a target workpiece transmission module 15.
Detailed Description
The technical scheme provided by the application has the following overall thought:
the embodiment of the application provides a metal hot working quality control method and system. Firstly, collecting detailed characteristics such as material composition, hardness, performance indexes and the like of a target workpiece, obtaining characteristics of the target workpiece, and obtaining comprehensive data of the workpiece. Then, an optimized tempering process scheme is determined aiming at the target workpiece, so that the accurate customization of the tempering process scheme is realized. And then, the tempering scheme is issued to a central control system of the continuous tempering furnace, and the scheme requirement is accurately executed, so that the intelligent closed-loop control of the whole tempering process is realized. And finally, conveying the target workpiece subjected to the tempering process to the next processing stage. The stability and the controllability of the tempering process quality are improved, the aim of accurately controlling according to the workpiece requirements is fulfilled, and the technical effect of improving the product quality of metal hot working is achieved.
Having described the basic principles of the present application, various non-limiting embodiments of the present application will now be described in detail with reference to the accompanying drawings.
Embodiment one: as shown in fig. 1, the embodiment of the application provides a metal hot working quality control method, which is applied to a metal hot working quality control system, and the system is in communication connection with a continuous tempering furnace.
The embodiment of the application discloses a metal hot working quality control method, which is applied to a metal hot working quality control system to realize accurate control on metal hot working. The metal hot working quality control system is in communication connection with a continuous tempering furnace, wherein the continuous tempering furnace is equipment capable of continuously tempering and comprises a heating chamber, a cooling chamber, a conveying belt and the like. In the tempering process of metal hot working, a workpiece enters a heating chamber through a conveying belt to be heated, then enters a cooling chamber to be cooled, and finally is output, so that mass production of the workpiece is realized, and the production efficiency is improved.
The quality control method comprises the following steps:
before collecting target workpiece features of a target workpiece, the method comprises the following steps:
the system is in communication connection with a metal hot working cloud control platform;
The method comprises the steps of calling historical metal hot working quality control records in the metal hot working cloud management and control platform, and randomly extracting to obtain a first historical record;
taking a plurality of historical workpiece features in the first history record as independent variables;
taking a historical tempered workpiece comprehensive quality index calculated based on the tempered workpiece performance characteristic parameter in the first historical record as a dependent variable;
screening and determining a key factor set according to the first correlation analysis result of the independent variable and the dependent variable, wherein the key factor set comprises material composition, material proportion, workpiece toughness and workpiece hardness;
and carrying out multidimensional feature acquisition on the target workpiece according to the key factor set.
In one possible embodiment, the metal hot working quality control system establishes a data transmission connection with the metal hot working cloud control platform through a network so as to acquire data from the cloud control platform. Firstly, the metal hot working quality control system retrieves historical data of workpiece machining and tempering quality control from a database of a metal hot working cloud control platform, and the historical data is used as historical metal hot working quality control records, including information of workpiece characteristics, machining parameters, quality detection results and the like. And secondly, sequentially carrying out non-repeated random acquisition on the histories in the historical metal hot working quality control record through a random number generation algorithm, wherein the acquired histories are first histories and comprise parameters such as material components, hardness, thickness, length, width and the like of the workpiece. And then, according to the detected performance characteristic parameters of the tempered workpiece, such as strength, hardness, toughness, uniformity and the like of the tempered workpiece in the first historical record, the tempering quality of the workpiece is calculated in proportion by the empirically set weight, so that the historical tempering workpiece comprehensive quality index is obtained.
Subsequently, features of the workpiece, such as materials, dimensions, geometries, etc., are described in the first history as arguments; taking the comprehensive quality index of the historical tempered work piece as a dependent variable; and calculating the pearson correlation coefficient between each independent variable and the dependent variable to represent the correlation degree of the independent variable and the dependent variable, and screening out the independent variable with stronger correlation with the quality index dependent variable as a key factor according to the size of the correlation coefficient, thereby obtaining a key factor set. Preferred sets of key factors include material composition, material ratio, workpiece toughness, and workpiece hardness, which are strongly correlated with final temper quality, with variations that have a more pronounced effect on the result. The main factors influencing the tempering workpiece in the metal processing process can be obtained by carrying out multidimensional characteristic acquisition on the target workpiece through the key factor set, so that the tempering process scheme can be customized accurately.
Collecting target workpiece features of a target workpiece, the target workpiece features including target material features and target performance features;
in the embodiment of the application, a key factor set is read, and the characteristics of the target workpiece are acquired according to the key factors in the key factor set, so that the target material characteristics and the target performance characteristics of the target workpiece are obtained, and the target workpiece characteristics are formed. The target material characteristics refer to characteristic parameters describing the properties of the target workpiece material, such as the material composition and the material proportion of the target workpiece; the target performance characteristics refer to characteristic parameters representing target workpiece performance indicators, such as workpiece toughness, workpiece hardness, and the like.
For example, detecting the components of the target workpiece by adopting a spectrum analyzer, determining the types and the contents of elements, and obtaining material composition data; measuring the density of a workpiece by using a density densimeter, and calculating theoretical density according to the material composition to obtain material proportion data by using the ratio of the two densities; performing impact test by using an impact tester, recording the energy value of the impact power to damage the sample, and converting the energy value into a toughness energy index serving as the toughness of the workpiece; and (3) carrying out hardness test by using a Brinell hardness tester or a Vickers hardness tester, keeping hardness marks on the surface of the workpiece according to specifications, and measuring the mark parameters and converting the mark parameters into hardness values to obtain the hardness of the workpiece.
The tempering process scheme reasonably designed according to the actual condition of the workpiece is facilitated by obtaining the target material characteristics and the target performance characteristics of the target workpiece, so that the performance of the workpiece is improved.
Determining a tempering process recipe, the tempering process recipe being determined by analyzing the target material characteristics and the target performance characteristics;
further, the embodiment of the application further includes:
if the comprehensive quality index of the historical tempered work piece accords with a preset index threshold value, adding the first historical record into a to-be-supervised learning list;
Acquiring a first learning record to be supervised from the learning list to be supervised;
traversing the first learning record to be supervised based on the key factor set to obtain a first learning workpiece feature to be supervised;
wherein the first workpiece feature to be supervised learning includes a first material feature and a first performance feature, the first material feature including a first material composition and a first material ratio, the first performance feature including a first workpiece toughness and a first workpiece hardness;
traversing the first learning record to be supervised based on a preset tempering process index set to obtain a first tempering process index parameter set;
wherein the first tempering process index parameter set includes a first tempering temperature, a first tempering time, and a first cooling rate;
performing supervised learning on the first workpiece feature to be supervised and the first tempering process index parameter set, and checking to obtain a tempering process decision model;
and analyzing the target material characteristics and the target performance characteristics through the tempering process decision model to determine the tempering process scheme.
Further, as shown in fig. 2, the embodiment of the present application further includes:
taking the first material composition, the first material proportion, the first workpiece toughness, the first workpiece hardness and the first tempering temperature in the first tempering process index parameter set in the first workpiece feature to be supervised as a first data set;
Obtaining a tempering temperature decision unit based on the first data set;
taking the first material composition, the first material proportion, the first workpiece toughness, the first workpiece hardness and the first tempering time in the first tempering process index parameter set in the first workpiece feature to be supervised as a second data set;
obtaining a tempering time decision unit based on the second data set;
taking the first material composition, the first material proportion, the first workpiece toughness, the first workpiece hardness, and the first cooling rate in the first tempering process index parameter set in the first to-be-supervised learning workpiece feature as a third data set;
obtaining a cooling rate decision unit based on the third data set;
the tempering temperature decision unit, the tempering time decision unit and the cooling speed decision unit jointly form the tempering process decision model.
In a preferred embodiment, first, the historical tempered work piece integrated quality index of a first history obtained from a historical metal hot working quality control record is compared with a predetermined index threshold value set according to a target work piece quality requirement, and if the historical tempered work piece integrated quality index is greater than or equal to the predetermined index threshold value, the historical record reflects a better tempering quality control effect, and at this time, the first history is added to a to-be-supervised learning list to be used as training data for subsequent supervised learning. And secondly, traversing the constructed learning list to be supervised, and selecting a sample record from the constructed learning list to be supervised as a first learning record to be supervised. Then, according to the determined key factor set, analyzing the first to-be-supervised learning record, and extracting corresponding workpiece features in the first history record, including a first material composition, a first material proportion, a first workpiece hardness and a first workpiece toughness, to form a standardized first to-be-supervised learning workpiece feature.
The preset tempering process index set comprises a tempering temperature index, a tempering time index and a cooling speed. Tempering temperature and tempering time are important factors influencing the tempering effect, different material tempering temperatures and times are different, adjustment is needed according to the composition, hardness and the like of specific materials, and test verification is carried out to ensure the best tempering effect; the cooling speed after tempering also affects the performance of the material, and the too fast or too slow cooling can cause the problems of deformation, cracking and the like of the material, and the proper cooling speed needs to be determined according to the type of the material, so that a preset tempering process index set comprises a tempering temperature index, a tempering time index and a cooling speed is determined. And extracting a corresponding first tempering temperature, a first tempering time and a first cooling speed from the first study record to be supervised according to the preset tempering process index set to form a first tempering process index parameter set of the sample.
And then, constructing a tempering process decision model according to the first workpiece feature to be supervised and the first tempering process index parameter set. First, a first material composition, a first material proportion, a first workpiece toughness, a first workpiece hardness and a corresponding first tempering temperature of a first workpiece to be supervised and learned are combined to be used as a first data set, wherein the data set reflects the relation between different workpiece characteristic parameters and tempering temperatures. And modeling the tempering temperature based on the first data set, adopting a convolutional neural network, training and learning to establish a mapping relation from the workpiece characteristics to the tempering temperature, and forming a tempering temperature decision unit, wherein the decision unit receives the workpiece characteristic parameter input and outputs the workpiece characteristic parameter input as the corresponding optimal tempering temperature. In the model training process, firstly, a potential relation between workpiece characteristic parameters and tempering temperature is extracted based on a first data set, then weight parameters in a network model are adjusted, so that a predicted output value of the model gradually approaches to the first tempering temperature in the first data set, and after repeated iterative optimization, a stable mapping model from the input workpiece characteristic to the output tempering temperature, namely a tempering temperature decision unit, is obtained. Similarly, in the same manner as the tempering temperature decision unit, a tempering time decision unit and a cooling rate decision unit are respectively constructed with the second data set and the third data set. The second data set is formed by combining a first material composition, a first material proportion, first workpiece toughness, first workpiece hardness and first tempering time in a first tempering process index parameter set in the first workpiece feature to be supervised and learned, and reflects the relation between different workpiece features and tempering time; the third data set is formed by combining a first material composition, a first material proportion, a first workpiece toughness, a first workpiece hardness and a first cooling speed in a first tempering process index parameter set in the first workpiece feature to be supervised and learned, and reflects the relation between different workpiece features and cooling speeds. And then, the obtained tempering temperature decision unit, tempering time decision unit and cooling speed decision unit are combined into a complete tempering process decision model, so that the tempering process decision model can decide optimal tempering temperature, tempering time and cooling speed parameters according to the input material characteristics and performance characteristics, thereby guiding the actual tempering process.
And then, inputting the acquired target material characteristics and target performance characteristics of the target workpiece into a tempering process decision model, wherein the tempering process decision model respectively inputs the input target material characteristics and target performance characteristics into a tempering temperature decision unit, a tempering time decision unit and a cooling speed decision unit, and decides a target tempering temperature, a target tempering time and a target cooling speed according to input data by the tempering temperature decision unit, the tempering time decision unit and the cooling speed decision unit to form a tempering process scheme so as to guide the tempering processing of the target workpiece and accurately improve the quality of a metal hot processed product.
Further, the embodiment of the application further includes:
and after the tempering process scheme is determined, adding a preset tempering atmosphere scheme to the tempering process scheme, wherein the preset tempering atmosphere scheme refers to that the tempering atmosphere is neutral or reducing atmosphere.
In a preferred embodiment, after determining the tempering temperature, tempering time and cooling rate parameters in the tempering process scheme, atmosphere parameters in the tempering process are determined to guide the actual tempering furnace operation so as to realize a high-quality tempering effect.
And a preset tempering atmosphere scheme is additionally added in the tempering process scheme, wherein the preset tempering atmosphere scheme refers to setting the tempering atmosphere to be neutral or reducing atmosphere. Wherein, the neutral atmosphere is an atmosphere environment without oxygen, and is realized by inert gases such as nitrogen, argon and the like; the reducing atmosphere is an environment containing a certain amount of combustible gas, such as hydrogen, carbon monoxide and the like, and has strong reducing effect. Compared with the oxidizing atmosphere, the neutral or reducing atmosphere can prevent the workpiece from being oxidized in the high-temperature tempering process, thereby ensuring the tempering quality.
The heating chamber in the continuous tempering furnace carries out heating treatment on the target workpiece based on a heating process scheme in the tempering process scheme to obtain a target heated workpiece;
in the embodiment of the application, the target tempering temperature and the target tempering time in the determined tempering process scheme are extracted to form a heating process scheme. And then, setting parameters of a heating chamber in the continuous tempering furnace according to the heating process scheme, heating the target workpiece by an electric heating device or a gas heating device in the heating chamber, and finishing heating treatment after the target workpiece passes through the tempering temperature and the tempering time set in the heating process scheme to obtain the target heated workpiece.
The heating chamber is operated strictly according to the heating parameters extracted from the tempering process scheme, so that the target workpiece is ensured to be subjected to accurate heat treatment, a foundation is laid for subsequent cooling treatment, and the accurate control and quality assurance of the whole tempering process are realized.
The cooling chamber in the continuous tempering furnace carries out cooling treatment on the target heating workpiece based on the cooling process scheme in the tempering process scheme to obtain a target cooling workpiece;
in the embodiment of the application, after the heating chamber of the continuous tempering furnace heats the target workpiece, a cooling process scheme is extracted according to the determined tempering process scheme, wherein the cooling process scheme comprises a cooling speed parameter aiming at the target heated workpiece. And the cooling chamber in the continuous tempering furnace carries out cooling treatment on the heated target heating workpiece at a strictly controlled cooling speed through a water cooling device or an air cooling device according to the cooling speed set in the cooling process scheme, so that the target heating workpiece is gradually cooled, and the cooled target cooling workpiece is obtained.
The cooling chamber is operated strictly according to the cooling process scheme in the tempering process scheme, so that the cooling process is accurate and controllable, the generation of cooling defects is avoided, the target cooling workpiece is ensured to obtain the required mechanical property, and the quality control of the whole tempering process is realized.
And conveying the target cooled workpiece serving as a target tempering workpiece of the target workpiece from the continuous tempering furnace to the next processing stage through a conveying belt.
In the embodiment of the application, the continuous tempering furnace adopts the conveying belt to continuously convey and process the workpiece, so that mass production is realized, and the efficiency is improved. After the target workpiece is subjected to heating treatment and cooling treatment in the continuous tempering furnace, the finally obtained target cooling workpiece is conveyed out of the tempering furnace through a conveying belt in the continuous tempering furnace and is used as a yield of the target workpiece after the tempering process is finished, namely the target tempered workpiece. The target tempered workpiece is automatically conveyed to the subsequent next processing procedure, such as stamping, welding and other forming processing procedures, so that the automatic and continuous conveying of the target tempered workpiece is realized, the yield is improved, the seamless connection among different processing procedures is realized, and the whole production flow is efficient and smooth.
Further, the embodiment of the application further includes:
the continuous tempering furnace is provided with a safety equipment assembly, and the safety equipment assembly comprises a thermometer, a pressure gauge, a protective cover and an audible and visual alarm device;
The temperature meter is used for dynamically monitoring the temperature in the heating treatment and cooling treatment processes of the target workpiece, so that the real-time workpiece temperature is obtained;
and when the temperature of the real-time workpiece reaches a preset temperature threshold, starting the audible and visual alarm device to perform overtemperature early warning.
In a preferred embodiment, to ensure safe operation of the continuous tempering furnace, a safety device assembly is provided that includes a thermometer, a pressure gauge, a protective cover, and an audible and visual alarm. The thermometer is used for monitoring the temperature change of the target workpiece in real time; the pressure gauge is used for monitoring the change of the pressure of the atmosphere in the furnace; the protective cover is started to protect when the pressure is abnormal; the audible and visual alarm device is used for giving out audible and visual alarms when the temperature exceeds the limit so as to comprehensively monitor the running state of the continuous tempering furnace, and can quickly respond and give an alarm once abnormality occurs, thereby ensuring the safe and stable performance of the metal hot working process.
Then, in the process of heating and cooling the target workpiece in the continuous tempering furnace, a thermometer is used for monitoring the temperature change of the workpiece in the tempering process in real time, and the real-time workpiece temperature of the target workpiece is obtained. The probe of the thermometer is directly contacted with the surface of the target workpiece or is arranged near the target workpiece, the temperature of the target workpiece is detected through a temperature sensing element such as a thermocouple and a resistance temperature detector, an electric signal is converted into a temperature reading, the temperature information of the target workpiece is reflected in real time, and the temperature change curve of the workpiece in the continuous conveying process in the tempering furnace is accurately reflected, wherein the temperature change curve comprises a heating section in a heating chamber and a cooling section in a cooling chamber.
A temperature threshold database is established in the metal hot working quality control system, and the temperature limit value of each process section, namely a preset temperature threshold value, is recorded. The metal hot working quality control system reads the temperature of the real-time workpiece and continuously compares the temperature with a preset temperature threshold value of a corresponding working stage. When the temperature of the real-time workpiece exceeds or is lower than a preset temperature threshold, the real-time workpiece reaches the preset temperature threshold, the control system sends out a trigger signal, an audible and visual alarm device connected with the continuous tempering furnace is automatically started, a visual and audible alarm is sent out, an alarm prompt of temperature overrun is formed, an operator is timely prompted, and potential damage to equipment and personnel caused by abnormal high temperature or low temperature is avoided.
Further, the embodiment of the application further includes:
dynamic pressure monitoring is carried out on the heating treatment and cooling treatment processes of the target workpiece through the pressure gauge, so that real-time indoor pressure is obtained;
and when the real-time indoor pressure reaches a preset pressure threshold, opening the protective cover to perform tempering safety protection.
In a preferred embodiment, in order to monitor the air pressure in the continuous tempering furnace, the air pressure in the furnace during the tempering process of the workpiece is dynamically monitored by a pressure gauge arranged in a safety equipment assembly in the tempering furnace, so as to obtain the real-time indoor pressure in the furnace, wherein the real-time indoor pressure comprises a heating chamber and a cooling chamber. The pressure gauge adopts pressure sensors to monitor the gas pressure of the heating chamber and the cooling chamber in real time and converts the gas pressure into pressure values so as to monitor the real-time change condition of the gas pressure in the heating chamber and the cooling chamber.
A pressure threshold database is established in the metal hot working quality control system, and the pressure limit value of each process section, namely a preset pressure threshold value, is recorded. When the heating chamber or the cooling chamber is too high or too low, the real-time indoor pressure reaches a preset pressure threshold value, and abnormal conditions occur. At the moment, the control system sends out a signal, and the protective cover in the safety equipment component is opened to cover, so that the air flow connection between the interior of the furnace and the outside is cut off, and the operation safety is ensured.
The tempering safety accidents caused by abnormal pressure can be effectively prevented through the real-time monitoring and protection linkage of the indoor pressure, and the safety of equipment and personnel is ensured.
In summary, the metal hot working quality control method provided by the embodiment of the application has the following technical effects:
and collecting target workpiece characteristics of a target workpiece, wherein the target workpiece characteristics comprise target material characteristics and target performance characteristics, and providing a basis for formulating a reasonable tempering scheme. And determining a tempering process scheme, wherein the tempering process scheme is determined by analyzing the characteristics of the target material and the characteristics of the target performance, so that the customized tempering process scheme is obtained, and support is provided for improving the quality of the metal product. The heating chamber in the continuous tempering furnace is used for heating the target workpiece based on the heating process scheme in the tempering process scheme, so that the target heated workpiece is obtained, the formulated heating parameters are accurately executed, and customized tempering is performed. The cooling chamber in the continuous tempering furnace carries out cooling treatment on the target heating workpiece based on the cooling process scheme in the tempering process scheme, so as to obtain the target cooling workpiece, and the cooling rate is strictly controlled, so that the cooling is prevented from being too fast or too slow. And conveying the target tempered workpiece serving as the target cooled workpiece from the continuous tempering furnace to the next processing stage through the conveying belt, completing a complete special customized tempering process, outputting the tempered workpiece with stable quality, realizing special customized tempering treatment aiming at specific workpiece requirements, and improving the control capability of a tempering process and the quality stability of products.
Embodiment two: based on the same inventive concept as one of the metal hot working quality control methods in the foregoing embodiments, as shown in fig. 3, an embodiment of the present application provides a metal hot working quality control system, which is communicatively connected to a continuous tempering furnace, and includes:
a workpiece feature collection module 11 for collecting target workpiece features of a target workpiece, the target workpiece features including target material features and target performance features;
a tempering process determination module 12 for determining a tempering process recipe, the tempering process recipe being determined by analyzing the target material characteristic and the target performance characteristic;
the workpiece heating treatment module 13 is used for heating the target workpiece by the heating chamber in the continuous tempering furnace based on the heating process scheme in the tempering process scheme to obtain a target heated workpiece;
a workpiece cooling processing module 14, configured to cool the target heated workpiece by using a cooling chamber in the continuous tempering furnace based on a cooling process scheme in the tempering process scheme, so as to obtain a target cooled workpiece;
and a target workpiece conveying module 15, configured to convey the target cooled workpiece as a target tempered workpiece of the target workpiece from the continuous tempering furnace to a next processing stage through a conveyor belt.
Further, the embodiment of the application further comprises a quality control factor module, wherein the quality control factor module comprises the following execution steps:
the system is in communication connection with a metal hot working cloud control platform;
the method comprises the steps of calling historical metal hot working quality control records in the metal hot working cloud management and control platform, and randomly extracting to obtain a first historical record;
taking a plurality of historical workpiece features in the first history record as independent variables;
taking a historical tempered workpiece comprehensive quality index calculated based on the tempered workpiece performance characteristic parameter in the first historical record as a dependent variable;
screening and determining a key factor set according to the first correlation analysis result of the independent variable and the dependent variable, wherein the key factor set comprises material composition, material proportion, workpiece toughness and workpiece hardness;
and carrying out multidimensional feature acquisition on the target workpiece according to the key factor set.
Further, the tempering process determining module 12 includes the following steps:
if the comprehensive quality index of the historical tempered work piece accords with a preset index threshold value, adding the first historical record into a to-be-supervised learning list;
acquiring a first learning record to be supervised from the learning list to be supervised;
Traversing the first learning record to be supervised based on the key factor set to obtain a first learning workpiece feature to be supervised;
wherein the first workpiece feature to be supervised learning includes a first material feature and a first performance feature, the first material feature including a first material composition and a first material ratio, the first performance feature including a first workpiece toughness and a first workpiece hardness;
traversing the first learning record to be supervised based on a preset tempering process index set to obtain a first tempering process index parameter set;
wherein the first tempering process index parameter set includes a first tempering temperature, a first tempering time, and a first cooling rate;
performing supervised learning on the first workpiece feature to be supervised and the first tempering process index parameter set, and checking to obtain a tempering process decision model;
and analyzing the target material characteristics and the target performance characteristics through the tempering process decision model to determine the tempering process scheme.
Further, the tempering process determination module 12 further includes the following steps:
taking the first material composition, the first material proportion, the first workpiece toughness, the first workpiece hardness and the first tempering temperature in the first tempering process index parameter set in the first workpiece feature to be supervised as a first data set;
Obtaining a tempering temperature decision unit based on the first data set;
taking the first material composition, the first material proportion, the first workpiece toughness, the first workpiece hardness and the first tempering time in the first tempering process index parameter set in the first workpiece feature to be supervised as a second data set;
obtaining a tempering time decision unit based on the second data set;
taking the first material composition, the first material proportion, the first workpiece toughness, the first workpiece hardness, and the first cooling rate in the first tempering process index parameter set in the first to-be-supervised learning workpiece feature as a third data set;
obtaining a cooling rate decision unit based on the third data set;
the tempering temperature decision unit, the tempering time decision unit and the cooling speed decision unit jointly form the tempering process decision model.
Further, the tempering process determination module 12 further includes the following steps:
and after the tempering process scheme is determined, adding a preset tempering atmosphere scheme to the tempering process scheme, wherein the preset tempering atmosphere scheme refers to that the tempering atmosphere is neutral or reducing atmosphere.
Further, an embodiment of the present application further includes a processing monitoring module, which includes the following execution steps:
the continuous tempering furnace is provided with a safety equipment assembly, and the safety equipment assembly comprises a thermometer, a pressure gauge, a protective cover and an audible and visual alarm device;
the temperature meter is used for dynamically monitoring the temperature in the heating treatment and cooling treatment processes of the target workpiece, so that the real-time workpiece temperature is obtained;
and when the temperature of the real-time workpiece reaches a preset temperature threshold, starting the audible and visual alarm device to perform overtemperature early warning.
Further, the processing monitoring module further includes the following steps:
dynamic pressure monitoring is carried out on the heating treatment and cooling treatment processes of the target workpiece through the pressure gauge, so that real-time indoor pressure is obtained;
and when the real-time indoor pressure reaches a preset pressure threshold, opening the protective cover to perform tempering safety protection.
Any of the steps of the methods described above may be stored as computer instructions or programs in a non-limiting computer memory and may be called by a non-limiting computer processor to identify any of the methods to implement embodiments of the present application, without unnecessary limitations.
Further, the first or second element may not only represent a sequential relationship, but may also represent a particular concept, and/or may be selected individually or in whole among a plurality of elements. It will be apparent to those skilled in the art that various modifications and variations can be made in the present application without departing from the scope of the application. Thus, if such modifications and variations of the present application fall within the scope of the present application and the equivalents thereof, the present application is intended to cover such modifications and variations.
Claims (5)
1. A method of controlling quality of metal hot working, the method being applied to a metal hot working quality control system, the system being in communication with a continuous tempering furnace, the method comprising:
collecting target workpiece features of a target workpiece, the target workpiece features including target material features and target performance features;
determining a tempering process recipe, the tempering process recipe being determined by analyzing the target material characteristics and the target performance characteristics;
the heating chamber in the continuous tempering furnace carries out heating treatment on the target workpiece based on a heating process scheme in a tempering process scheme to obtain a target heated workpiece;
The cooling chamber in the continuous tempering furnace carries out cooling treatment on the target heating workpiece based on a cooling process scheme in a tempering process scheme to obtain a target cooling workpiece;
conveying the target tempered workpiece serving as the target workpiece from the continuous tempering furnace to the next processing stage through a conveying belt;
the system is in communication connection with a metal hot working cloud control platform, and before collecting target workpiece features of a target workpiece, the system further comprises:
the method comprises the steps of calling historical metal hot working quality control records in the metal hot working cloud management and control platform, and randomly extracting to obtain a first historical record;
taking a plurality of historical workpiece features in a first history record as independent variables;
taking a historical tempered workpiece comprehensive quality index calculated based on the characteristic parameters of the tempered workpiece performance in the first historical record as a dependent variable;
screening and determining a key factor set according to the first correlation analysis result of the independent variable and the dependent variable, wherein the key factor set comprises material composition, material proportion, workpiece toughness and workpiece hardness;
carrying out multidimensional feature acquisition on the target workpiece according to the key factor set;
The determining tempering process scheme comprises the following steps:
if the comprehensive quality index of the historical tempered work piece accords with a preset index threshold value, adding the first historical record into a to-be-supervised learning list;
acquiring a first learning record to be supervised from the learning list to be supervised;
traversing the first learning record to be supervised based on the key factor set to obtain a first learning workpiece feature to be supervised;
wherein the first workpiece feature to be supervised learning includes a first material feature and a first performance feature, the first material feature including a first material composition and a first material ratio, the first performance feature including a first workpiece toughness and a first workpiece hardness;
traversing the first learning record to be supervised based on a preset tempering process index set to obtain a first tempering process index parameter set;
wherein the first tempering process index parameter set includes a first tempering temperature, a first tempering time, and a first cooling rate;
performing supervised learning on the first workpiece feature to be supervised and the first tempering process index parameter set, and checking to obtain a tempering process decision model;
analyzing the target material characteristics and the target performance characteristics through the tempering process decision model to determine the tempering process scheme;
The performing supervised learning on the first workpiece feature to be supervised and the first tempering process index parameter set, and checking to obtain a tempering process decision model, including:
taking the first material composition, the first material proportion, the first workpiece toughness, the first workpiece hardness and the first tempering temperature in the first tempering process index parameter set in the first workpiece feature to be supervised as a first data set;
obtaining a tempering temperature decision unit based on the first data set;
taking the first material composition, the first material proportion, the first workpiece toughness, the first workpiece hardness and the first tempering time in the first tempering process index parameter set in the first workpiece feature to be supervised as a second data set;
obtaining a tempering time decision unit based on the second data set;
taking the first material composition, the first material proportion, the first workpiece toughness, the first workpiece hardness, and the first cooling rate in the first tempering process index parameter set in the first to-be-supervised learning workpiece feature as a third data set;
Obtaining a cooling rate decision unit based on the third data set;
the tempering temperature decision unit, the tempering time decision unit and the cooling speed decision unit jointly form the tempering process decision model.
2. The method according to claim 1, characterized in that a preset tempering atmosphere scheme is added to the tempering process scheme after determining the tempering process scheme, wherein the preset tempering atmosphere scheme means that the tempering atmosphere is neutral or reducing atmosphere.
3. The method of claim 1, wherein the continuous tempering furnace is equipped with a safety equipment assembly and the safety equipment assembly includes a thermometer, a pressure gauge, a protective cover, and an audible and visual alarm, the method further comprising:
the temperature meter is used for dynamically monitoring the temperature in the heating treatment and cooling treatment processes of the target workpiece, so that the real-time workpiece temperature is obtained;
and when the temperature of the real-time workpiece reaches a preset temperature threshold, starting the audible and visual alarm device to perform overtemperature early warning.
4. A method according to claim 3, wherein the method further comprises:
dynamic pressure monitoring is carried out on the heating treatment and cooling treatment processes of the target workpiece through the pressure gauge, so that real-time indoor pressure is obtained;
And when the real-time indoor pressure reaches a preset pressure threshold, opening the protective cover to perform tempering safety protection.
5. A metal hot working quality control system for carrying out a metal hot working quality control method as claimed in any one of claims 1 to 4, said system being in communication with a continuous tempering furnace, said method comprising:
the workpiece feature collection module is used for collecting target workpiece features of a target workpiece, wherein the target workpiece features comprise target material features and target performance features;
a tempering process determination module for determining a tempering process recipe determined by analyzing the target material characteristics and the target performance characteristics;
the workpiece heating treatment module is used for heating the target workpiece by the heating chamber in the continuous tempering furnace based on the heating process scheme in the tempering process scheme to obtain a target heated workpiece;
the workpiece cooling treatment module is used for cooling the target heating workpiece by the cooling chamber in the continuous tempering furnace based on the cooling process scheme in the tempering process scheme to obtain a target cooling workpiece;
The target workpiece conveying module is used for conveying the target cooled workpiece serving as a target tempering workpiece of the target workpiece from the continuous tempering furnace to the next processing stage through a conveying belt;
the system is in communication connection with a metal hot working cloud control platform, and before collecting target workpiece features of a target workpiece, the system further comprises:
the method comprises the steps of calling historical metal hot working quality control records in the metal hot working cloud management and control platform, and randomly extracting to obtain a first historical record;
taking a plurality of historical workpiece features in a first history record as independent variables;
taking a historical tempered workpiece comprehensive quality index calculated based on the characteristic parameters of the tempered workpiece performance in the first historical record as a dependent variable;
screening and determining a key factor set according to the first correlation analysis result of the independent variable and the dependent variable, wherein the key factor set comprises material composition, material proportion, workpiece toughness and workpiece hardness;
carrying out multidimensional feature acquisition on the target workpiece according to the key factor set;
the determining tempering process scheme comprises the following steps:
if the comprehensive quality index of the historical tempered work piece accords with a preset index threshold value, adding the first historical record into a to-be-supervised learning list;
Acquiring a first learning record to be supervised from the learning list to be supervised;
traversing the first learning record to be supervised based on the key factor set to obtain a first learning workpiece feature to be supervised;
wherein the first workpiece feature to be supervised learning includes a first material feature and a first performance feature, the first material feature including a first material composition and a first material ratio, the first performance feature including a first workpiece toughness and a first workpiece hardness;
traversing the first learning record to be supervised based on a preset tempering process index set to obtain a first tempering process index parameter set;
wherein the first tempering process index parameter set includes a first tempering temperature, a first tempering time, and a first cooling rate;
performing supervised learning on the first workpiece feature to be supervised and the first tempering process index parameter set, and checking to obtain a tempering process decision model;
analyzing the target material characteristics and the target performance characteristics through the tempering process decision model to determine the tempering process scheme;
the performing supervised learning on the first workpiece feature to be supervised and the first tempering process index parameter set, and checking to obtain a tempering process decision model, including:
Taking the first material composition, the first material proportion, the first workpiece toughness, the first workpiece hardness and the first tempering temperature in the first tempering process index parameter set in the first workpiece feature to be supervised as a first data set;
obtaining a tempering temperature decision unit based on the first data set;
taking the first material composition, the first material proportion, the first workpiece toughness, the first workpiece hardness and the first tempering time in the first tempering process index parameter set in the first workpiece feature to be supervised as a second data set;
obtaining a tempering time decision unit based on the second data set;
taking the first material composition, the first material proportion, the first workpiece toughness, the first workpiece hardness, and the first cooling rate in the first tempering process index parameter set in the first to-be-supervised learning workpiece feature as a third data set;
obtaining a cooling rate decision unit based on the third data set;
the tempering temperature decision unit, the tempering time decision unit and the cooling speed decision unit jointly form the tempering process decision model.
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