CN117852972A - Casting quality control system and method based on casting process monitoring data - Google Patents
Casting quality control system and method based on casting process monitoring data Download PDFInfo
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Abstract
The invention discloses a casting quality control system and method based on casting process monitoring data, in particular to the technical field of casting process management and control, comprising the following steps: based on the performance index set and the preset performance index set of the cast finished product, the comprehensive quality evaluation coefficient Zp of the cast finished product is obtained through joint analysis; the casting qualification rate, the quality evaluation index average value and the quality evaluation index discrete coefficient of each production line are obtained based on the casting qualification rate, the quality evaluation index average value of qualified products, the quality evaluation index discrete coefficient of qualified products, the quality evaluation coefficient average value of defective products and the quality evaluation index discrete coefficient of defective products, and the process monitoring demand factors of each production line are obtained through joint analysis, the process monitoring demand factors are distributed based on the process monitoring demand factors, and the problem that the casting quality control is not intelligent enough, so that the casting monitoring resources are scientifically distributed is solved.
Description
Technical Field
The invention relates to the technical field of casting process control, in particular to a casting quality control system and method based on casting process monitoring data.
Background
In the casting process, each step has its specific requirements and operating details and requires strict control to obtain high quality castings. The current casting process mainly comprises the following steps: preparing raw materials: according to the type of the cast alloy, preparing corresponding raw materials such as pig iron, scrap steel, furnace returns and the like; smelting and pouring: mixing raw materials according to a certain proportion, adding the raw materials into a smelting furnace to smelt into liquid metal meeting requirements, and then injecting the liquid metal into a mould through a pouring system; cooling and solidifying: cooling and solidifying the liquid metal in a mould to form a casting; demolding and cleaning: after the casting is removed from the die, necessary cleaning work such as casting head and burr removal is carried out; and (3) quality detection: the quality detection of the castings, including appearance inspection, size measurement, nondestructive detection and the like, is carried out, so that the quality of the products is ensured to meet the requirements; post-treatment: and (3) carrying out post-treatment procedures such as surface treatment, heat treatment, machining and the like on the casting according to requirements.
The existing casting quality control mode is that a manager controls casting quality through experience based on a casting production manual, but in actual conditions, the method still has more defects, such as unscientific allocation of casting monitoring resources caused by insufficient intellectualization of casting quality control, different production lines have different conditions, and the allocation of the same monitoring resources to each production line is not beneficial to finding out the casting production process in time; lack of real-time monitoring control on casting risk results in low casting yield and increased production cost.
Disclosure of Invention
In order to overcome the above-mentioned drawbacks of the prior art, the present invention provides a casting quality control system and method based on casting process monitoring data, so as to solve the above-mentioned problems in the prior art.
In order to achieve the above purpose, the present invention provides the following technical solutions: a casting quality control system based on casting process monitoring data, comprising:
the cast product performance analysis module is used for acquiring a cast product comprehensive quality evaluation coefficient Zp of a cast product, acquiring a performance index set of the cast product through a test, and acquiring the cast product comprehensive quality evaluation coefficient Zp based on the actual performance index set and the preset performance index set of the cast product through joint analysis;
the production line quality analysis module is used for dividing the cast finished product into qualified products and defective products based on the cast finished product comprehensive quality evaluation coefficient Zp, and obtaining the casting qualification rate, the quality evaluation index average value, the quality evaluation index discrete coefficient, the quality evaluation coefficient average value and the quality evaluation index discrete coefficient of the defective products of the casting production line;
monitoring demand assessment module: the process monitoring demand factor Szi is used for acquiring the process monitoring demand factor of the ith production line, acquiring the process monitoring demand factor of the ith production line based on the production stability description parameter Wm and the production reliability description parameter Kmi of the ith production line, and distributing the process monitoring demand based on the process monitoring demand factor;
the process monitoring module is used for monitoring the casting process, obtaining an actual environment characteristic parameter set and an actual process characteristic parameter set by monitoring the casting process, obtaining the electrical stability parameter and the equipment function execution precision of the casting equipment by monitoring the casting equipment, analyzing the monitoring content, and obtaining an environment risk index, a process risk index and an equipment risk index;
and the process management and control module is used for taking corresponding measures based on the acquired environment risk index, equipment risk index and process risk index.
Preferably, by the formula The calculated comprehensive quality evaluation coefficients Zp of the cast finished product, wherein gamma 1, gamma 2, gamma 3 and gamma 4 respectively represent the weight coefficients of each item, and Z1, Z2, Z3 and Z4 respectively represent the actual appearance quality description index, physical property evaluation index, mechanical property evaluation index and environmental stability evaluation index of the cast finished product based on the setting of a manager; z01, Z02, Z03 and Z04 respectively represent the preset appearance quality description index, physical property evaluation index, mechanical property evaluation index,Environmental stability assessment index.
Preferably, the qualification rate of the cast product is set as Zp Pre-preparation The cast finished product comprehensive quality evaluation coefficient Zp and the qualification evaluation standard Zp Pre-preparation Comparing, namely marking the cast finished products meeting the preset standard as qualified products, and marking the cast finished products not meeting the preset standard as unqualified products, so as to obtain the casting qualification rate hgi of the ith production line; analyzing the discrete coefficient and the average value of the comprehensive quality evaluation coefficient of the casting finished product of the qualified product of the ith production line, and respectively marking the discrete coefficient and the average value as qui _avg and qui_dis; analyzing the discrete coefficient and the average value of the comprehensive quality evaluation coefficient of the casting finished product of the i-th production line defective product; are respectively denoted as dei _avg and dei_dis.
Preferably, the production stability description parameter Wm and the production reliability description parameter Kmi of the ith production line are obtained based on the qualification rate of the cast finished product, the quality evaluation index average value of the qualified product, the quality evaluation index discrete coefficient of the qualified product, the quality evaluation coefficient average value of the defective product and the quality evaluation index discrete coefficient of the defective product;
by the formulaAcquiring a production stability description parameter Wmi of an ith monitoring area; by the formula kmi= hgi (qui _avg-dei _avg) 2 Acquiring a production reliability description parameter Km of an ith monitoring area; based on the production stability description parameter and the reliability parameter, the process monitoring requirement factor Szi of the ith production line is obtained through the formula Szi =wmi+kmi combined analysis.
Preferably, the process monitoring module comprises a casting environment monitoring unit, a casting equipment monitoring unit and a casting process monitoring unit, wherein the casting environment monitoring unit is used for monitoring environment characteristic parameters of the casting process, and analyzing to obtain a real-time environment risk index based on the actual environment characteristic parameters and preset environment characteristic parameters; the casting equipment monitoring unit is used for monitoring the running condition of casting equipment and analyzing to obtain an equipment risk index; the casting process monitoring unit is used for monitoring process characteristic parameters in a casting process and analyzing and obtaining a real-time process risk index based on the actual process characteristic parameters and preset process characteristic parameters.
Preferably, the process of obtaining the environmental risk index is:
obtaining the deviation rate of the environmental characteristic parameters: substituting the actual environment characteristic parameter set Ga into the parameter X in the environment characteristic parameter deviation value calculation model a1 The preset environment characteristic parameter set G a0 Substituting parameter X in environmental characteristic parameter deviation value calculation model in sequence a0 Obtaining the deviation value of each environmental characteristic description parameter, marking the set of environmental characteristic parameter deviation values as hp, and calculating the model of the environmental characteristic parameter deviation values as hp
The deviation rate of a plurality of environmental characteristic parameters is marked as hp, influence factors are matched for each environmental characteristic parameter, qk represents the influence factor of the kth environmental characteristic parameter, an environmental risk index is obtained through weighted summation, s environmental characteristic parameters are arranged, and the deviation rate of the kth environmental characteristic parameter is marked as hpk; calculating model through environment characteristic parameter deviation valueAnd calculating to obtain an environmental risk index Hz.
Preferably, the process of obtaining the process risk index Gz is:
obtaining the deviation rate of the characteristic parameters of the process: substituting the actual process characteristic parameter set Gb into the parameter X in the process characteristic parameter deviation value calculation model b1 The preset technological characteristic parameter set G b0 Substituting parameter X in environmental quality assessment index calculation model in sequence b0 Obtaining the deviation value of each process characteristic parameter, marking the process characteristic parameter deviation value set as gp,
the deviation rate of a plurality of process characteristic parameters is recorded as gp, each process is matched with an influence factor, and qr representsThe influence factor of the r-th process characteristic parameter is weighted and summed to obtain a process risk index Gz, p environmental characteristic parameters are arranged, and the deviation rate of the r-th environmental characteristic parameter is recorded as gpr; calculation of model by Process Risk indexAnd calculating a process risk index Gz.
Preferably, the process of obtaining the risk index Jz of the casting equipment is:
obtaining an electrical stability parameter dw of the casting equipment through a formulaAn electrical stability parameter dw is obtained, wherein δ1 represents the voltage fluctuation variance, δ2 represents the current fluctuation variance, +.>Representing a preset voltage fluctuation variance +.>Representing a preset current fluctuation variance;
acquiring the function execution precision zd of casting equipment, and calculating the precision zd of the equipment according to the deviation between the actual output function and the theoretical output function of the equipment and dividing the deviation between the actual output function and the theoretical output function by the theoretical output function;
after the electrical stability parameter dw and the function execution precision zd are subjected to linear normalization, a casting equipment risk index Jz is obtained through calculation of a formula jz=dw×zd.
Preferably, the acquired environmental risk index, the casting equipment risk index, the process risk index, the environmental risk index preset value Fth1, the casting equipment risk index preset value Fth2 and the process risk index preset value Fth3 are respectively compared, when the acquired environmental risk index exceeds the preset value Fth1, the casting environment is indicated to be abnormal, early warning is carried out to a manager, and the casting environment is indicated to be abnormal; when the acquired risk index of the casting equipment exceeds a preset value Fth2, indicating that the casting equipment is abnormal, early warning a manager, and prompting that the casting equipment is abnormal; when the acquired process risk index exceeds a preset value Fth3, the casting process is abnormal, early warning is given to a manager, and the casting process is abnormal.
Preferably, when the obtained environmental risk index, the casting equipment risk index and the process risk index do not exceed preset values, predicting to obtain a casting product quality anomaly prediction coefficient Cy through a formula cy=hz×α1+gz×α2+jz×α3, and taking corresponding measures based on the casting product quality anomaly prediction coefficient Cy, wherein α1 represents an influence factor of the environment on the casting product quality, α2 represents an influence factor of the process on the casting product quality, α3 represents an influence factor of the casting equipment on the casting product quality, and 0 < α1 < 1, 0 < α2 < 1, and 0 < α3 < 1; when the abnormal prediction coefficient Cy of the quality of the cast finished product exceeds a preset range, the quality of the cast finished product obtained according to the current casting environment, casting process and casting equipment is not in line with the expectations, the casting process needs to be monitored and maintained, and the environment, process and equipment of the casting process are adjusted.
In order to achieve the above purpose, the present invention provides the following technical solutions: a casting quality control method based on casting process monitoring data, comprising the steps of:
step S001, analyzing the performance of the casting finished product: the comprehensive quality evaluation system comprises a casting finished product comprehensive quality evaluation coefficient Zp, a performance index set of the casting finished product is obtained through a test, and the comprehensive quality evaluation coefficient Zp of the casting finished product is obtained through joint analysis based on the actual performance index set and the preset performance index set of the casting finished product;
step S002, a production line quality analysis step: acquiring casting qualification rate of a casting production line, quality evaluation index average value of qualified products, quality evaluation index discrete coefficient of qualified products, quality evaluation coefficient average value of defective products and quality evaluation index discrete coefficient of defective products based on a casting finished product comprehensive quality evaluation coefficient Zp;
step S003, a process monitoring demand distribution step: the process monitoring demand factors Szi are used for acquiring the process monitoring demand factors of the production lines, obtaining the process monitoring demand factors of the production lines based on the production stability description parameters Wm and the production reliability description parameters Kmi of the production lines, and distributing process monitoring demands based on the process monitoring demand factors;
step S004, process monitoring step: acquiring an environment risk index based on the actual environment characteristic parameter set, acquiring a process risk index based on the actual process characteristic parameter set, and acquiring an equipment risk index based on the electrical stability parameter of the casting equipment and the equipment function execution precision;
step S005, process control step: based on the obtained environment risk index, equipment risk index and process risk index, corresponding measures are taken.
The invention has the technical effects and advantages that:
(1) According to the casting quality control system based on casting process monitoring data, the appearance quality description index Z1, the physical property evaluation index Z2, the mechanical property evaluation index Z3 and the environmental stability evaluation index Z4 of a cast finished product are obtained through a cast finished product performance analysis module, and the cast finished product comprehensive quality evaluation coefficient Zp is obtained through joint analysis based on an actual performance index set and a preset performance index set of the cast finished product; the casting qualification rate, the quality evaluation index average value of qualified products, the quality evaluation index discrete coefficient of qualified products, the quality evaluation coefficient average value of defective products and the quality evaluation index discrete coefficient of defective products of each production line are obtained based on the casting qualification rate, the quality evaluation index average value of qualified products, the quality evaluation index discrete coefficient of qualified products, the quality evaluation coefficient average value of defective products and the quality evaluation index discrete coefficient of defective products of each production line, and the process monitoring demand factors of each production line are obtained through joint analysis, the process monitoring demand is distributed based on the process monitoring demand factors, and the problem that casting quality control is not intelligent enough and the unscientific distribution of casting monitoring resources is caused is solved.
(2) According to the casting quality control system based on the casting process monitoring data, the process monitoring module is used for monitoring the casting process, and the real-time environment risk index is obtained through analysis based on the actual environment characteristic parameters and the preset environment characteristic parameters; monitoring the running condition of casting equipment, and analyzing to obtain a risk index of the casting equipment; based on the actual process characteristic parameters and the preset process characteristic parameters, analyzing to obtain a real-time process risk index; based on the acquired environment risk index, the casting equipment risk index and the process risk index, corresponding measures are taken, so that the problems of low casting yield and increased production cost caused by the lack of real-time monitoring control of casting risks in the existing casting production are solved.
Drawings
FIG. 1 is a block diagram of a casting quality control system of the present invention.
FIG. 2 is a flow chart of a casting quality control method of the present invention.
FIG. 3 is a training flow chart of the cast product comprehensive quality prediction model of the present invention.
Detailed Description
Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
The following description of at least one exemplary embodiment is merely exemplary in nature and is in no way intended to limit the application, its application, or uses.
Techniques, methods, and apparatus known to one of ordinary skill in the relevant art may not be discussed in detail, but are intended to be part of the specification where appropriate.
A computer system/server may be described in the general context of computer-system-executable instructions, such as program modules, being executed by a computer system. Generally, program modules may include routines, programs, objects, components, logic, data structures, etc., that perform particular tasks or implement particular abstract data types. The computer system/server may be implemented in a distributed cloud computing environment in which tasks are performed by remote processing devices that are linked through a communications network. In a distributed cloud computing environment, program modules may be located in both local and remote computing system storage media including memory storage devices.
Example 1
Referring to the block diagram of the casting quality control system of fig. 1, the present invention provides a casting quality control system based on casting process monitoring data as shown in fig. 1, comprising:
the cast product performance analysis module is used for acquiring a cast product comprehensive quality evaluation coefficient Zp of a cast product, acquiring a performance index set of the cast product through a test, and acquiring the cast product comprehensive quality evaluation coefficient Zp based on the actual performance index set and the preset performance index set of the cast product through joint analysis;
in the cast finished product performance analysis module, the performance index set of the cast finished product at least comprises an appearance quality description index, a mechanical performance description parameter, a physical performance description parameter and an environmental stability evaluation index; detecting the appearance of the cast finished product, and obtaining an appearance quality description index of the cast finished product; carrying out tensile test, bearing test, bending test and mechanical property test on the cast finished product to obtain mechanical property description parameters of the cast finished product; performing physical property tests on the cast finished product, including density, thermal expansion coefficient and residual stress tests, and obtaining physical property description parameters of the cast finished product; and (3) carrying out reliability test on the cast finished product: carrying out salt spray tests, gas tests, IP grades, wet heat tests and high and low temperature tests, obtaining mechanical performance description parameters, physical performance description parameters and loss rate of reliability tests of cast finished products in different environments, and obtaining environmental stability evaluation indexes based on the loss rate; obtaining an appearance quality description index Z1, a physical performance evaluation index Z2, a mechanical performance evaluation index Z3 and an environmental stability evaluation index Z4 of a cast finished product, and obtaining a performance index set A= { Z1, Z2, Z3, Z4}; and obtaining a preset performance index set B= { Z01, Z02, Z03, Z04} of the cast finished product from the database. The invention does not specifically limit the acquisition modes of the appearance quality description index, the physical property evaluation index, the mechanical property evaluation index and the environmental stability evaluation index of the cast finished product, and the range of the appearance quality description index Z1, the physical property evaluation index Z2, the mechanical property evaluation index Z3 and the environmental stability evaluation index Z4 of the cast finished product is (0, 1).
It should be further explained in the embodiments of the present invention that the following formula is adopted The calculated comprehensive quality evaluation coefficients Zp of the cast finished product, wherein gamma 1, gamma 2, gamma 3 and gamma 4 respectively represent the weight coefficients of each item, and Z1, Z2, Z3 and Z4 respectively represent the actual appearance quality description index, physical property evaluation index, mechanical property evaluation index and environmental stability evaluation index of the cast finished product based on the setting of a manager; z01, Z02, Z03 and Z04 respectively represent a preset appearance quality description index, a physical property evaluation index, a mechanical property evaluation index and an environmental stability evaluation index of the casting finished product.
The production line quality analysis module is used for dividing the cast finished product into qualified products and defective products based on the cast finished product comprehensive quality evaluation coefficient Zp, and obtaining the casting qualification rate, the quality evaluation index average value, the quality evaluation index discrete coefficient, the quality evaluation coefficient average value and the quality evaluation index discrete coefficient of the defective products of the casting production line;
it should be further explained that the qualification criteria of the cast product are set to Zp Pre-preparation The cast finished product comprehensive quality evaluation coefficient Zp and the qualification evaluation standard Zp Pre-preparation Comparing, namely marking the cast finished products meeting the preset standard as qualified products, and marking the cast finished products not meeting the preset standard as unqualified products, so as to obtain the casting qualification rate hgi of the ith production line; analyzing the discrete coefficient and average value of the cast product comprehensive quality evaluation coefficient of the qualified product of the ith production line, and respectively marking the discrete coefficient and average value as qui _avg,qui _dis; analyzing the discrete coefficient and the average value of the comprehensive quality evaluation coefficient of the casting finished product of the i-th production line defective product; are respectively denoted as dei _avg and dei_dis.
Monitoring demand assessment module: the process monitoring demand factor Szi is used for acquiring the process monitoring demand factor of the ith production line, acquiring the process monitoring demand factor of the ith production line based on the production stability description parameter Wm and the production reliability description parameter Kmi of the ith production line, and distributing the process monitoring demand based on the process monitoring demand factor;
it should be noted that the process monitoring requirement refers to a requirement of monitoring various parameters and indexes in real time in the production process so as to ensure the quality and production stability of the product. By monitoring the production process, the abnormality and the problem can be found in time, and corresponding measures are taken to correct, so that the smooth production is ensured. Rational distribution and meeting process monitoring requirements are important means to ensure production stability and quality.
In the embodiment of the invention, the production stability description parameter Wm and the production reliability description parameter Kmi of the ith production line are obtained based on the qualification rate of the cast finished product, the quality evaluation index average value of the qualified product, the quality evaluation index discrete coefficient of the qualified product, the quality evaluation coefficient average value of the defective product and the quality evaluation index discrete coefficient of the defective product;
by the formulaAcquiring a production stability description parameter Wmi of an ith monitoring area; by the formula kmi= hgi (qui _avg-dei _avg) 2 Acquiring a production reliability description parameter Km of an ith monitoring area; based on the production stability description parameter and the reliability parameter, the process monitoring requirement factor Szi of the ith production line is obtained through the formula Szi =wmi+kmi combined analysis.
The process monitoring module is used for monitoring the casting process, obtaining an actual environment characteristic parameter set and an actual process characteristic parameter set by monitoring the casting process, obtaining the electrical stability parameter and the equipment function execution precision of the casting equipment by monitoring the casting equipment, analyzing the monitoring content, and obtaining an environment risk index, a process risk index and an equipment risk index;
the embodiment of the invention further discloses that the process monitoring module comprises a casting environment monitoring unit, a casting equipment monitoring unit and a casting process monitoring unit, wherein the casting environment monitoring unit is used for monitoring environment characteristic parameters of a casting process and analyzing to obtain a real-time environment risk index based on the actual environment characteristic parameters and preset environment characteristic parameters; the casting equipment monitoring unit is used for monitoring the running condition of casting equipment and analyzing to obtain an equipment risk index; the casting process monitoring unit is used for monitoring process characteristic parameters in a casting process and analyzing and obtaining a real-time process risk index based on the actual process characteristic parameters and preset process characteristic parameters.
In the embodiment of the invention, the process of obtaining the environmental risk index is as follows:
obtaining the deviation rate of the environmental characteristic parameters: substituting the actual environment characteristic parameter set Ga into the parameter X in the environment characteristic parameter deviation value calculation model a1 The preset environment characteristic parameter set G a0 Substituting parameter X in environmental characteristic parameter deviation value calculation model in sequence a0 Obtaining the deviation value of each environmental characteristic description parameter, marking the set of environmental characteristic parameter deviation values as hp, and calculating the model of the environmental characteristic parameter deviation values as hp
The deviation rate of a plurality of environmental characteristic parameters is marked as hp, influence factors are matched for each environmental characteristic parameter, qk represents the influence factor of the kth environmental characteristic parameter, an environmental risk index is obtained through weighted summation, s environmental characteristic parameters are arranged, and the deviation rate of the kth environmental characteristic parameter is marked as hpk; calculating model through environment characteristic parameter deviation valueAnd calculating to obtain an environmental risk index Hz.
In the embodiment of the present invention, it needs to be further explained that the process of obtaining the process risk index Gz is:
obtaining the deviation rate of the characteristic parameters of the process: substituting the actual process characteristic parameter set Gb into the parameter X in the process characteristic parameter deviation value calculation model b1 The preset technological characteristic parameter set G b0 Substituting parameter X in environmental quality assessment index calculation model in sequence b0 Obtaining the deviation value of each process characteristic parameter, marking the process characteristic parameter deviation value set as gp,
marking the deviation rate of a plurality of process characteristic parameters as gp, matching influence factors for each process, wherein qr represents the influence factor of the r-th process characteristic parameter, obtaining a process risk index Gz through weighted summation, and marking the deviation rate of the r-th process characteristic parameter as gpr if p environmental characteristic parameters are arranged; calculation of model by Process Risk indexAnd calculating a process risk index Gz.
In the embodiment of the invention, the process of obtaining the risk index Jz of the casting equipment is as follows:
obtaining an electrical stability parameter dw of the casting equipment through a formulaAn electrical stability parameter dw is obtained, wherein δ1 represents the voltage fluctuation variance, δ2 represents the current fluctuation variance, +.>Representing a preset voltage fluctuation variance +.>Representing a preset current fluctuation variance;
acquiring the function execution precision zd of casting equipment, and calculating the precision zd of the equipment according to the deviation between the actual output function and the theoretical output function of the equipment and dividing the deviation between the actual output function and the theoretical output function by the theoretical output function;
after the electrical stability parameter dw and the function execution precision zd are subjected to linear normalization, a casting equipment risk index Jz is obtained through calculation of a formula jz=dw×zd.
For example, the functions of a casting machine in casting equipment are casting, heating and stirring, and the actual casting temperature, casting weight and stirring time of the casting machine are obtained and recorded as actual output functions; the casting temperature, the casting weight and the stirring time preset by the casting machine are recorded as theoretical output functions; and calculating the difference value of each function, dividing the difference value by the theoretical output function, and then carrying out weighted summation calculation to obtain the function execution precision.
Further, when there are s casting devices, the risk index of each casting device is obtained, and the risk index of the kth casting device is recorded as Jz k And matching a weight coefficient for each casting device, and obtaining a risk index Jz of the casting device by weighted summation.
And the process management and control module is used for taking corresponding measures based on the acquired environment risk index, equipment risk index and process risk index.
The process management and control module is used for comparing the acquired environment risk index, the casting equipment risk index, the process risk index, the environment risk index preset value Fth1, the casting equipment risk index preset value Fth2 and the process risk index preset value Fth3 respectively, and when the acquired environment risk index exceeds the preset value Fth1, the casting environment is indicated to be abnormal, and early warning is given to a manager to prompt that the casting environment is abnormal; when the acquired risk index of the casting equipment exceeds a preset value Fth2, indicating that the casting equipment is abnormal, early warning a manager, and prompting that the casting equipment is abnormal; when the acquired process risk index exceeds a preset value Fth3, the casting process is abnormal, early warning is given to a manager, and the casting process is abnormal.
In the embodiment of the invention, it is further explained that when the obtained environmental risk index, the risk index of the casting equipment and the process risk index do not exceed preset values, a casting product quality anomaly prediction coefficient Cy is obtained through prediction by a formula cy=hz+gz+α2+jz+α3, and corresponding measures are taken based on the casting product quality anomaly prediction coefficient Cy, wherein α1 represents an influence factor of the environment on the quality of the casting product, α2 represents an influence factor of the process on the quality of the casting product, α3 represents an influence factor of the casting equipment on the quality of the casting product, and 0 < α1 < 1, 0 < α2 < 1, 0 < α3 < 1; when the abnormal prediction coefficient Cy of the quality of the cast finished product exceeds a preset range, the quality of the cast finished product obtained according to the current casting environment, casting process and casting equipment is not in line with the expectations, the casting process needs to be monitored and maintained, and the environment, process and equipment of the casting process are adjusted.
Further, a casting equipment risk index Jz ' is obtained by weighting and summing and is used for replacing Jz in a formula Cy=Hz+α1+gz+α2+Jz+α3, a casting product quality abnormality prediction coefficient Cy ' is obtained by prediction, and corresponding measures are taken based on the casting product quality abnormality prediction coefficient Cy '.
Referring to the casting quality control method flowchart of fig. 2, the invention provides a casting quality control method based on casting process monitoring data, comprising the following steps:
step S001, analyzing the performance of the casting finished product: the comprehensive quality evaluation system comprises a casting finished product comprehensive quality evaluation coefficient Zp, a casting finished product comprehensive quality evaluation system and a casting finished product comprehensive quality evaluation system, wherein the casting finished product comprehensive quality evaluation coefficient Zp is obtained through joint analysis based on an actual performance index set and a preset performance index set of the casting finished product;
step S002, a production line quality analysis step: acquiring casting qualification rate of a casting production line, quality evaluation index average value of qualified products, quality evaluation index discrete coefficient of qualified products, quality evaluation coefficient average value of defective products and quality evaluation index discrete coefficient of defective products based on a casting finished product comprehensive quality evaluation coefficient Zp;
step S003, a process monitoring demand distribution step: obtaining a process monitoring demand factor of the production line based on the production stability description parameter Wm and the production reliability description parameter Kmi of the production line, and distributing a process monitoring demand based on the process monitoring demand factor;
step S004, process monitoring step: acquiring an environment risk index based on the actual environment characteristic parameter set, acquiring a process risk index based on the actual process characteristic parameter set, and acquiring an equipment risk index based on the electrical stability parameter of the casting equipment and the equipment function execution precision;
step S005, process control step: based on the obtained environment risk index, equipment risk index and process risk index, corresponding measures are taken.
Example 2
The embodiment of the invention provides a casting quality control method based on casting process monitoring data, which comprises the following steps:
step S01, acquiring real-time data in a casting process, and preprocessing the acquired real-time data;
s02, inputting the preprocessed monitoring data into a trained comprehensive quality prediction model of the cast finished product, and outputting a comprehensive quality prediction index of the cast finished product;
and S03, taking corresponding measures by the manager based on the relation between the comprehensive quality prediction index of the cast finished product and the preset value.
Further, based on the big casting process history data, training to obtain a cast product comprehensive quality prediction model, referring to a training flow chart of the cast product comprehensive quality prediction model of fig. 3, training of the cast product comprehensive quality prediction model includes the following steps:
step S21, data collection and pretreatment: collecting historical data of the casting process including, but not limited to, properties of raw materials, process parameters, environmental factors, casting equipment;
step S22, data characteristic engineering: according to the characteristics and historical data of the casting process, carrying out characteristic engineering to extract characteristics influencing the quality of a cast finished product;
step S23, model selection and training: selecting a deep learning model for training, defining initial parameters of the deep learning model, defining weight parameters, bias parameters and activation functions among the neural networks, inputting the preprocessed monitoring data into the deep learning model, and outputting a cast finished product comprehensive quality prediction index Yc;
the deep learning model is any one of a Convolutional Neural Network (CNN), a cyclic neural network (RNN) and a long-short-term memory network (LSTM).
Step S24, model evaluation: after training is completed, the model is required to be evaluated, a loss function L is constructed by using a cast product comprehensive quality prediction index of historical data and an actual cast product quality abnormality prediction coefficient Cy, and a trained loss function value is obtained;
step S25, model optimization: and when the loss function value does not accord with the preset condition, adjusting and optimizing the deep learning model until the loss function value meets the preset requirement, and obtaining the trained cast product comprehensive quality prediction model.
The deep learning model is adjusted and optimized, for example, by adjusting parameters of the model, changing the architecture of the model.
Further, assuming that n times of training are performed, the predicted value of the ith training is Yci, the theoretical value of the ith training is Cyi, and the training is performed through a loss functionAnd obtaining the loss function value of the deep learning model after each training.
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 (10)
1. A casting quality control system based on casting process monitoring data, comprising:
the cast product performance analysis module is used for acquiring a cast product comprehensive quality evaluation coefficient Zp of a cast product, acquiring a performance index set of the cast product through a test, and acquiring the cast product comprehensive quality evaluation coefficient Zp based on the actual performance index set and the preset performance index set of the cast product through joint analysis;
the production line quality analysis module is used for dividing the cast finished product into qualified products and defective products based on the cast finished product comprehensive quality evaluation coefficient Zp, and obtaining the casting qualification rate, the quality evaluation index average value, the quality evaluation index discrete coefficient, the quality evaluation coefficient average value and the quality evaluation index discrete coefficient of the defective products of the casting production line;
the monitoring demand assessment module is used for acquiring a process monitoring demand factor Szi of the ith production line, obtaining the process monitoring demand factor of the ith production line based on the production stability description parameter Wm and the production reliability description parameter Kmi of the ith production line, and distributing process monitoring demands based on the process monitoring demand factor;
the process monitoring module is used for monitoring the casting process to obtain an actual environment characteristic parameter set and an actual process characteristic parameter set; obtaining electrical stability parameters and equipment function execution precision of casting equipment through monitoring the casting equipment, analyzing monitoring content, and obtaining an environment risk index, a process risk index and an equipment risk index;
and the process management and control module is used for taking corresponding measures based on the acquired environment risk index, equipment risk index and process risk index.
2. A casting quality control system based on casting process monitoring data as recited in claim 1, wherein the casting quality control system is characterized by the formula The calculated comprehensive quality evaluation coefficients Zp of the cast finished product, wherein gamma 1, gamma 2, gamma 3 and gamma 4 respectively represent the weight coefficients of each item, and Z1, Z2, Z3 and Z4 respectively represent the actual appearance quality description index, physical property evaluation index, mechanical property evaluation index and environmental stability evaluation index of the cast finished product; z01, Z02, Z03Z04 respectively represents a preset appearance quality description index, a physical property evaluation index, a mechanical property evaluation index and an environmental stability evaluation index of the cast product.
3. A casting quality control system based on casting process monitoring data as claimed in claim 1, wherein the qualification criteria of the cast product is set to Zp Pre-preparation The cast finished product comprehensive quality evaluation coefficient Zp and the qualification evaluation standard Zp Pre-preparation Comparing, namely marking the cast finished products meeting the preset standard as qualified products, and marking the cast finished products not meeting the preset standard as unqualified products, so as to obtain the casting qualification rate hgi of the ith production line; analyzing the discrete coefficient and the average value of the comprehensive quality evaluation coefficient of the casting finished product of the qualified product of the ith production line, and respectively marking the discrete coefficient and the average value as qui _avg and qui_dis; analyzing the discrete coefficient and the average value of the comprehensive quality evaluation coefficient of the casting finished product of the i-th production line defective product; are respectively denoted as dei _avg and dei_dis.
4. A casting quality control system based on casting process monitoring data according to claim 3, characterized by the formulaAcquiring a production stability description parameter Wmi of an ith monitoring area; by the formula kmi= hgi (qui _avg-dei _avg) 2 Acquiring a production reliability description parameter Km of an ith monitoring area; based on the production stability description parameter and the reliability parameter, the process monitoring requirement factor Szi of the ith production line is obtained through the formula Szi =wmi+kmi combined analysis.
5. The casting quality control system based on casting process monitoring data of claim 1, wherein the process of obtaining the environmental risk index is:
obtaining the deviation rate of the environmental characteristic parameters: substituting the actual environment characteristic parameter set Ga into the parameter X in the environment characteristic parameter deviation value calculation model a1 Preset environmental characteristicsParameter set G a0 Substituting parameter X in environmental characteristic parameter deviation value calculation model in sequence a0 Obtaining the deviation value of each environmental characteristic description parameter, marking the set of environmental characteristic parameter deviation values as hp, and calculating the model of the environmental characteristic parameter deviation values as hp
The deviation rate of a plurality of environmental characteristic parameters is marked as hp, influence factors are matched for each environmental characteristic parameter, qk represents the influence factor of the kth environmental characteristic parameter, an environmental risk index is obtained through weighted summation, s environmental characteristic parameters are arranged, and the deviation rate of the kth environmental characteristic parameter is marked as hpk; calculating model through environment characteristic parameter deviation valueAnd calculating to obtain an environmental risk index Hz.
6. The casting quality control system based on casting process monitoring data according to claim 1, wherein the process of obtaining the process risk index Gz is:
obtaining the deviation rate of the characteristic parameters of the process: substituting the actual process characteristic parameter set Gb into the parameter X in the process characteristic parameter deviation value calculation model b1 The preset technological characteristic parameter set G b0 Substituting parameter X in environmental quality assessment index calculation model in sequence b0 Obtaining the deviation value of each process characteristic parameter, marking the set of the process characteristic parameter deviation values as gp, and calculating the model of the process characteristic parameter deviation values as gp
The deviation rate of a plurality of process characteristic parameters is recorded as gp, influence factors are matched for each process, qr represents the influence factor of the r-th process characteristic parameter, a process risk index Gz is obtained through weighted summation, p environmental characteristic parameters are arranged, and the r-th environmental characteristic parameter is obtainedThe deviation rate is recorded as gpr; calculation of model by Process Risk indexAnd calculating a process risk index Gz.
7. The casting quality control system based on casting process monitoring data according to claim 1, wherein the process of obtaining the casting equipment risk index Jz is:
obtaining an electrical stability parameter dw of the casting equipment through a formulaAn electrical stability parameter dw is obtained, wherein δ1 represents the voltage fluctuation variance, δ2 represents the current fluctuation variance, +.>Representing a preset voltage fluctuation variance +.>Representing a preset current fluctuation variance;
acquiring the function execution precision zd of casting equipment, and calculating the precision zd of the equipment according to the deviation between the actual output function and the theoretical output function of the equipment and dividing the deviation between the actual output function and the theoretical output function by the theoretical output function;
after the electrical stability parameter dw and the function execution precision zd are subjected to linear normalization, a casting equipment risk index Jz is obtained through calculation of a formula jz=dw×zd.
8. The casting quality control system based on casting process monitoring data according to claim 1, wherein when the obtained environmental risk index, casting equipment risk index and process risk index do not exceed preset values, a casting quality anomaly prediction coefficient Cy is predicted by the formula cy=hz+gz+α2+jz+α3, and corresponding measures are taken based on the casting quality anomaly prediction coefficient Cy, wherein α1 represents an environmental impact factor on casting quality, α2 represents a process impact factor on casting quality, α3 represents a casting equipment impact factor on casting quality, and 0 < α1 < 1, 0 < α2 < 1, and 0 < α3 < 1.
9. The casting quality control system based on casting process monitoring data according to claim 8, wherein when the abnormal prediction coefficient Cy of the quality of the cast product exceeds a preset range, it indicates that the quality of the cast product obtained according to the current casting environment, casting process and casting equipment is not in line with expectations, and the casting process needs to be monitored and maintained, and the environment, process and equipment of the casting process are adjusted.
10. A casting quality control method based on casting process monitoring data for implementing a casting quality control system based on casting process monitoring data as claimed in claim 1, comprising the steps of:
step S001, analyzing the performance of the casting finished product: the comprehensive quality evaluation system comprises a casting finished product comprehensive quality evaluation coefficient Zp, a performance index set of the casting finished product is obtained through a test, and the comprehensive quality evaluation coefficient Zp of the casting finished product is obtained through joint analysis based on the actual performance index set and the preset performance index set of the casting finished product;
step S002, a production line quality analysis step: acquiring casting qualification rate of a casting production line, quality evaluation index average value of qualified products, quality evaluation index discrete coefficient of qualified products, quality evaluation coefficient average value of defective products and quality evaluation index discrete coefficient of defective products based on a casting finished product comprehensive quality evaluation coefficient Zp;
step S003, a process monitoring demand distribution step: the process monitoring demand factors Szi are used for acquiring the process monitoring demand factors of the production lines, obtaining the process monitoring demand factors of the production lines based on the production stability description parameters Wm and the production reliability description parameters Kmi of the production lines, and distributing process monitoring demands based on the process monitoring demand factors;
step S004, process monitoring step: acquiring an environment risk index based on the actual environment characteristic parameter set, acquiring a process risk index based on the actual process characteristic parameter set, and acquiring an equipment risk index based on the electrical stability parameter of the casting equipment and the equipment function execution precision;
step S005, process control step: based on the obtained environment risk index, equipment risk index and process risk index, corresponding measures are taken.
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