CN114632922B - High-efficiency high-quality aluminum alloy damping tower high-pressure vacuum die-casting process control system and method - Google Patents
High-efficiency high-quality aluminum alloy damping tower high-pressure vacuum die-casting process control system and method Download PDFInfo
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- 238000004512 die casting Methods 0.000 title claims abstract description 101
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- B22D17/00—Pressure die casting or injection die casting, i.e. casting in which the metal is forced into a mould under high pressure
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B22—CASTING; POWDER METALLURGY
- B22D—CASTING OF METALS; CASTING OF OTHER SUBSTANCES BY THE SAME PROCESSES OR DEVICES
- B22D17/00—Pressure die casting or injection die casting, i.e. casting in which the metal is forced into a mould under high pressure
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Abstract
The invention discloses a high-efficiency high-quality aluminum alloy damping tower high-pressure vacuum die-casting process control system and a method, and the structure of the system comprises a detection module, a threshold judgment and prediction module and a control module, wherein the detection module is connected with the threshold judgment and prediction module, the threshold judgment and prediction module is connected with the control module, and the detection module and the control module are respectively connected with a high-pressure vacuum die-casting machine; the detection module detects the vacuum degree, the die temperature, the temperature of the aluminum alloy liquid, the injection speed and the injection force of the aluminum alloy damping tower in the high-pressure vacuum die-casting machine in real time. The invention can improve the stability of the vacuum high-pressure die-casting process, realize the self-adaptive adjustment and intervention control of the process and ensure the high-quality and high-efficiency production of the shock absorption tower.
Description
Technical Field
The invention relates to the technical field of die-casting processes, in particular to a high-efficiency high-quality aluminum alloy damping tower high-pressure vacuum die-casting process control system and method.
Background
The vacuum high-pressure die-casting technology refers to a molding process in which liquid metal fills a mold cavity at a very high speed under the action of high pressure, and is cooled and solidified under the action of certain pressure to obtain a casting. Compared with the traditional casting technology and a common die casting piece, the vacuum high-pressure die casting can reduce air holes and casting defects, so that the mechanical property of the casting piece is obviously improved, and the service requirement of the casting piece under the actual working condition is met.
The damping tower all uses aluminum alloy material at present, is the important structure on the car, except shock-absorbing function, still needs to satisfy the security performance demand of whole car collision to further improve the lightweight degree of car. In order to ensure the mechanical properties of the shock absorption tower, such as strength, elongation and the like, the current manufacturing method adopts a high-pressure vacuum casting process. However, the existing vacuum high-pressure die-casting process of the aluminum alloy damping tower is unstable and limited by a single production process, so that the requirement of large-scale, long-time and repetitive large-scale production is difficult to meet, and inferior products or defective parts with poor mechanical properties are easy to generate, thereby greatly influencing the high-quality and high-efficiency production of the damping tower.
Disclosure of Invention
Aiming at the problems, the invention provides a high-efficiency high-quality aluminum alloy damping tower high-pressure vacuum die-casting process control system and method, which can improve the stability of a vacuum high-pressure die-casting process and ensure the high-quality high-efficiency production of the damping tower.
According to one object of the invention, the invention provides a high-efficiency high-quality aluminum alloy damping tower high-pressure vacuum die-casting process control system which comprises a detection module, a threshold value judging and predicting module and a control module, wherein the detection module is connected with the threshold value judging and predicting module, the threshold value judging and predicting module is connected with the control module, and the detection module and the control module are respectively connected with a high-pressure vacuum die-casting machine;
the detection module detects the vacuum degree, the die temperature, the temperature of the aluminum alloy liquid, the injection speed and the injection force of the aluminum alloy damping tower in the high-pressure vacuum die-casting machine in real time;
the threshold judgment and prediction module carries out threshold judgment according to the vacuum degree and the mold temperature signal provided by the detection module at the last moment so as to determine whether to adjust the vacuum degree and the aluminum alloy liquid temperature signal at the current moment;
the threshold value judging and predicting module is used for respectively subtracting the target injection speed and the target injection force from the injection speed and the injection force signals provided by the detection module at the last moment to obtain the deviation amplitude of the injection speed and the deviation amplitude of the injection force at the last moment, and constructing a die casting quality predicting model by combining the vacuum fluctuation difference at the last moment and the temperature fluctuation difference at the last moment;
the threshold value judging and predicting module judges and predicts the quality mu of the die casting according to the previous moment 1 And optimum die casting quality mu 0 Calculating the injection force dynamic gain sigma at the current moment 1 And the injection velocity dynamic gain σ 2 Obtaining the injection force lambda at the current moment 1 And current time injection velocity lambda 2 ；
the control module extracts the current-time vacuum degree, the current-time aluminum alloy liquid temperature, the current-time injection force and the current-time injection speed of the threshold value judging and predicting module, and sends the signal values to the vacuum high-pressure die-casting machine for real-time control.
Further, the previous time refers to the time when the previous die-casting experiment is completely completed; the current time refers to the time when the process parameters are set during the current die-casting experiment.
Further, the threshold value judging and predicting module respectively differentiates the vacuum degree and the mold temperature signal at the last moment with the optimal vacuum degree and the optimal mold temperature to obtain a vacuum fluctuation difference at the last moment and a temperature fluctuation difference at the last moment, and respectively differentiates the vacuum degree and the temperature fluctuation difference with a vacuum degree allowable threshold value beta 1 Allowable threshold value beta of die temperature 2 And comparing to determine whether to adjust the vacuum degree and the aluminum alloy liquid temperature signal at the current moment.
Further, if the difference between the vacuum degree at the previous time and the optimum vacuum degree is larger than the vacuum degree allowable threshold β 1 And improving the vacuum degree at the current moment to ensure the vacuum degree required by the high-quality die casting, otherwise, setting the vacuum degree at the current moment to be consistent with the vacuum degree at the last moment.
Further, if the difference between the mold temperature at the last moment and the optimal mold temperature is larger than the allowable mold temperature threshold β 2 And reducing the temperature of the aluminum alloy liquid to ensure the mold temperature required by the high-quality die casting, otherwise, setting the temperature of the aluminum alloy liquid at the current moment to be consistent with the temperature of the aluminum alloy liquid at the last moment.
Further, the nonlinear mapping relation of the die casting quality prediction model can be constructed by an artificial neural network or a numerical fitting prediction formula.
Further, the input of the artificial neural network model is the deviation amplitude of the injection speed at the last moment, the deviation amplitude of the injection force, the vacuum fluctuation difference at the last moment and the temperature fluctuation difference at the last moment, and the output of the model is the quality of the die casting at the last moment.
Further, the nonlinear mapping relation of the die casting quality prediction model can be constructed by a numerical fitting prediction formula, and the die casting quality mu at the last moment 1 The numerical fitting prediction formula of (a) is:
μ 1 ＝f(η 1 ,η 2 ,η 3 ,η 4 )
wherein eta is 1 For the injection force of the last moment, eta 2 For the injection velocity, η, of the last moment 3 Is the temperature fluctuation difference of the last moment, eta 4 The vacuum fluctuation difference at the last moment;
according to another object of the invention, the invention provides a high-efficiency high-quality aluminum alloy damping tower high-pressure vacuum die-casting process control method, which comprises the following steps:
the detection module detects the vacuum degree, the die temperature, the temperature of the aluminum alloy liquid, the injection speed and the injection force at the last moment in real time;
the threshold judgment and prediction module carries out threshold judgment according to the vacuum degree and the mold temperature signal provided by the detection module at the last moment so as to determine whether to adjust the vacuum degree and the aluminum alloy liquid temperature signal at the current moment;
the threshold value judging and predicting module respectively makes difference with the target injection speed and the target injection force according to the injection speed and the injection force signals provided by the detecting module at the last moment to obtain the deviation amplitude of the injection speed and the deviation amplitude of the injection force at the last moment, and a die casting quality predicting model is constructed by combining the vacuum fluctuation difference at the last moment and the temperature fluctuation difference at the last moment to obtain the quality mu of the die casting at the last moment 1 (ii) a The nonlinear mapping relation of the die casting quality prediction model can be constructed by an artificial neural network or a numerical fitting prediction formula.
The input of the artificial neural network model is the deviation amplitude of the injection speed, the deviation amplitude of the injection force, the vacuum fluctuation difference of the last moment and the temperature fluctuation difference of the last moment, and the output of the model is the quality of the die casting of the last moment.
Fitting of numerical valuesThe prediction formula is: mu.s 1 ＝f(η 1 ,η 2 ,η 3 ,η 4 )
Wherein eta is 1 For the injection force of the last moment, eta 2 For the injection velocity, η, of the last moment 3 Is the temperature fluctuation difference of the last moment, eta 4 The vacuum fluctuation difference at the last moment;
wherein, the previous moment refers to the moment when the previous die-casting experiment is completely finished; the current time refers to the time when the process parameters are set during the current die-casting experiment.
The threshold value judging and predicting module respectively differentiates the vacuum degree and the mould temperature signal at the last moment with the optimal vacuum degree and the optimal mould temperature to obtain the vacuum fluctuation difference and the temperature fluctuation difference at the last moment, and respectively differentiates the vacuum degree and the temperature fluctuation difference with a vacuum degree allowable threshold value beta 1 Allowable threshold value beta of die temperature 2 And comparing to determine whether to adjust the vacuum degree and the aluminum alloy liquid temperature signal at the current moment. If the difference between the vacuum degree at the last moment and the optimal vacuum degree is larger than the allowable threshold beta of the vacuum degree 1 And improving the vacuum degree at the current moment to ensure the vacuum degree required by the high-quality die casting, otherwise, setting the vacuum degree at the current moment to be consistent with the vacuum degree at the last moment. If the difference between the mold temperature at the last moment and the optimal mold temperature is larger than the allowable threshold value beta of the mold temperature 2 Reducing the temperature of the aluminum alloy liquid to ensure the mold temperature required by the high-quality die casting, otherwise, setting the temperature of the aluminum alloy liquid at the current moment to be consistent with the temperature of the aluminum alloy liquid at the previous moment;
the threshold value judging and predicting module judges and predicts the quality mu of the die casting according to the previous moment 1 And optimum die casting quality mu 0 Calculating the injection force dynamic gain sigma at the current moment 1 And shot velocity dynamic gain σ 2 Obtaining the injection force lambda at the current moment 1 And current time injection velocity lambda 2 ；
the control module extracts threshold values to judge and predict the current vacuum degree, the current aluminum alloy liquid temperature, the current injection force and the current injection speed of the module, and sends the signal values to the vacuum high-pressure die-casting machine for real-time control.
The invention has the beneficial effects that: the vacuum degree, the temperature of the die, the temperature of the aluminum alloy liquid, the injection speed and the injection speed of the aluminum alloy damping tower at the last moment are detected in real time to correct the vacuum degree, the temperature of the aluminum alloy liquid, the injection speed and the injection speed at the current moment, so that the stability of the vacuum high-pressure die-casting process can be improved, the self-adaptive adjustment and the intervention control of the process are realized, and the high-quality and high-efficiency production of the damping tower is ensured.
Drawings
FIG. 1 is a schematic structural diagram of an embodiment of the present invention;
FIG. 2 is a signal control schematic of an embodiment of the present invention;
FIG. 3 is a schematic structural diagram of a control module according to an embodiment of the present invention;
FIG. 4 is a process flow diagram of an embodiment of the invention;
fig. 5 is a schematic structural diagram of an artificial neural network prediction model according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Example 1
As shown in fig. 1-5, the high-efficiency high-quality aluminum alloy damping tower high-pressure vacuum die-casting process control system comprises a detection module, a threshold judgment and prediction module and a control module, wherein the detection module is connected with the threshold judgment and prediction module, the threshold judgment and prediction module is connected with the control module, and the detection module and the control module are respectively connected with a high-pressure vacuum die-casting machine;
the detection module detects the vacuum degree, the die temperature, the temperature of the aluminum alloy liquid, the injection speed and the injection force of the aluminum alloy damping tower in the high-pressure vacuum die-casting machine in real time;
the threshold judgment and prediction module carries out threshold judgment according to the vacuum degree and the mold temperature signal provided by the detection module at the last moment so as to determine whether to adjust the vacuum degree and the aluminum alloy liquid temperature signal at the current moment;
the threshold value judging and predicting module is used for respectively subtracting the target injection speed and the target injection force according to the injection speed and the injection force signals provided by the detecting module at the last moment to obtain the deviation amplitude of the injection speed and the deviation amplitude of the injection force at the last moment, and constructing a die casting quality predicting model by combining the vacuum fluctuation difference at the last moment and the temperature fluctuation difference at the last moment;
the threshold value judging and predicting module judges and predicts the quality mu of the die casting according to the previous moment 1 And optimum die casting quality mu 0 Calculating the injection force dynamic gain sigma at the current moment 1 And shot velocity dynamic gain σ 2 Obtaining the injection force lambda at the current moment 1 And current time injection velocity lambda 2 ；
the control module extracts the current-time vacuum degree, the current-time aluminum alloy liquid temperature, the current-time injection force and the current-time injection speed of the threshold value judging and predicting module, and sends the signal values to the vacuum high-pressure die-casting machine for real-time control.
Preferably, the previous time refers to the time when the previous die-casting experiment is completely completed; the current time refers to the time when the process parameters are set during the current die-casting experiment.
Preferably, the threshold judgment and prediction module performs subtraction on the vacuum degree and the mold temperature signal at the previous moment and the optimal vacuum degree and the optimal mold temperature respectively to obtain a vacuum fluctuation difference and a temperature fluctuation difference at the previous moment, and the difference and the vacuum degree allowable threshold β are obtained respectively 1 Allowable threshold value beta of die temperature 2 And comparing to determine whether to adjust the vacuum degree and the aluminum alloy liquid temperature signal at the current moment.
Preferably, if the difference between the vacuum degree at the previous moment and the optimal vacuum degree is larger than the vacuum degree allowable threshold value beta 1 And improving the vacuum degree at the current moment to ensure the vacuum degree required by the high-quality die casting, otherwise, setting the vacuum degree at the current moment to be consistent with the vacuum degree at the last moment.
Preferably, if the difference between the mold temperature at the last moment and the optimal mold temperature is greater than the mold temperature allowable threshold β 2 And reducing the temperature of the aluminum alloy liquid to ensure the mold temperature required by the high-quality die casting, otherwise, setting the temperature of the aluminum alloy liquid at the current moment to be consistent with the temperature of the aluminum alloy liquid at the last moment.
Preferably, the nonlinear mapping relation of the die casting quality prediction model can be constructed by an artificial neural network or a numerical fitting prediction formula.
Preferably, the input of the artificial neural network model is the deviation amplitude of the injection speed at the last moment, the deviation amplitude of the injection force, the vacuum fluctuation difference at the last moment and the temperature fluctuation difference at the last moment, and the output of the model is the quality of the die casting at the last moment.
Preferably, the non-linear mapping relation of the die casting quality prediction model can be constructed by a numerical fitting prediction formula, and the die casting quality mu at the last moment 1 The numerical fitting prediction formula of (1) is:
μ 1 ＝f(η 1 ,η 2 ,η 3 ,η 4 )
wherein eta is 1 Injection force, eta, at the last moment 2 In order to inject the speed at the last moment,η 3 is the temperature fluctuation difference of the last moment, eta 4 The vacuum fluctuation difference at the last moment;
a high-pressure vacuum die-casting process control method for a high-efficiency high-quality aluminum alloy damping tower comprises the following steps:
the detection module detects the vacuum degree, the die temperature, the temperature of the aluminum alloy liquid, the injection speed and the injection force at the last moment in real time;
the threshold judgment and prediction module carries out threshold judgment according to the vacuum degree and the mold temperature signal provided by the detection module at the last moment so as to determine whether to adjust the vacuum degree and the aluminum alloy liquid temperature signal at the current moment;
the threshold value judging and predicting module respectively makes difference with the target injection speed and the target injection force according to the injection speed and the injection force signals provided by the detecting module at the last moment to obtain the deviation amplitude of the injection speed and the deviation amplitude of the injection force at the last moment, and a die casting quality predicting model is constructed by combining the vacuum fluctuation difference at the last moment and the temperature fluctuation difference at the last moment to obtain the quality mu of the die casting at the last moment 1 (ii) a The nonlinear mapping relation of the die casting quality prediction model can be constructed by an artificial neural network or a numerical fitting prediction formula.
The input of the artificial neural network model is the deviation amplitude of the injection speed, the deviation amplitude of the injection force, the vacuum fluctuation difference of the last moment and the temperature fluctuation difference of the last moment, and the output of the model is the quality of the die casting of the last moment.
The numerical fitting prediction formula is: mu.s 1 ＝f(η 1 ,η 2 ,η 3 ,η 4 )
Wherein eta is 1 Injection force, eta, at the last moment 2 For the injection velocity, η, of the last moment 3 Is the temperature fluctuation difference of the last moment, eta 4 The vacuum fluctuation difference at the last moment;
wherein, the previous moment refers to the moment when the previous die-casting experiment is completely finished; the current time refers to the time when the process parameters are set during the current die-casting experiment.
The threshold value judging and predicting module respectively compares the vacuum degree and the mold temperature signal at the last moment with the maximumThe optimal vacuum degree and the optimal mold temperature are differentiated to obtain the vacuum fluctuation difference and the temperature fluctuation difference of the last moment, and the difference and the allowable vacuum degree threshold value beta are respectively obtained 1 Allowable threshold value beta of die temperature 2 And comparing to determine whether to adjust the vacuum degree and the aluminum alloy liquid temperature signal at the current moment. If the difference between the vacuum degree at the last moment and the optimal vacuum degree is larger than the allowable threshold beta of the vacuum degree 1 And improving the vacuum degree at the current moment to ensure the vacuum degree required by the high-quality die casting, otherwise, setting the vacuum degree at the current moment to be consistent with the vacuum degree at the last moment. If the difference between the mold temperature at the last moment and the optimal mold temperature is larger than the allowable threshold value beta of the mold temperature 2 Reducing the temperature of the aluminum alloy liquid to ensure the mold temperature required by the high-quality die casting, otherwise, setting the temperature of the aluminum alloy liquid at the current moment to be consistent with the temperature of the aluminum alloy liquid at the previous moment;
the threshold value judging and predicting module judges and predicts the quality mu of the die casting according to the previous moment 1 And optimum die casting quality mu 0 Calculating the injection force dynamic gain sigma at the current moment 1 And shot velocity dynamic gain σ 2 Obtaining the injection force lambda at the current moment 1 And current time injection velocity lambda 2 ；
the control module extracts threshold values to judge and predict the current vacuum degree, the current aluminum alloy liquid temperature, the current injection force and the current injection speed of the module, and sends the signal values to the vacuum high-pressure die-casting machine for real-time control.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.
Claims (8)
1. The high-efficiency high-quality aluminum alloy damping tower high-pressure vacuum die-casting process control system is characterized by comprising a detection module, a threshold judgment and prediction module and a control module, wherein the detection module is connected with the threshold judgment and prediction module, the threshold judgment and prediction module is connected with the control module, and the detection module and the control module are respectively connected with a high-pressure vacuum die-casting machine;
the detection module detects the vacuum degree, the die temperature, the temperature of the aluminum alloy liquid, the injection speed and the injection force of the aluminum alloy damping tower in the high-pressure vacuum die-casting machine in real time;
the threshold judgment and prediction module carries out threshold judgment according to the vacuum degree and the mold temperature signal provided by the detection module at the last moment so as to determine whether to adjust the vacuum degree and the aluminum alloy liquid temperature signal at the current moment;
the threshold value judging and predicting module is used for respectively subtracting the target injection speed and the target injection force according to the injection speed and the injection force signals provided by the detecting module at the last moment to obtain the deviation amplitude of the injection speed and the deviation amplitude of the injection force at the last moment, and constructing a die casting quality predicting model by combining the vacuum fluctuation difference at the last moment and the temperature fluctuation difference at the last moment;
the threshold value judging and predicting module judges and predicts the quality mu of the die casting according to the previous moment 1 And optimum die casting quality mu 0 Calculating the injection force dynamic gain sigma at the current moment 1 And shot velocity dynamic gain σ 2 Obtaining the injection force lambda at the current moment 1 And current time injection velocity lambda 2 ；
Wherein x is 1 Adjusting the coefficient for the injection force, x 2 For adjusting the coefficient of injection velocity, η 1 For the injection force of the last moment, eta 2 The injection speed at the last moment;
the control module extracts the current-time vacuum degree, the current-time aluminum alloy liquid temperature, the current-time injection force and the current-time injection speed of the threshold value judging and predicting module, and sends the signal values to the vacuum high-pressure die-casting machine for real-time control.
2. The high-pressure vacuum die-casting process control system for the high-efficiency high-quality aluminum alloy shock absorption tower as claimed in claim 1, wherein the previous moment is the moment when the previous die-casting experiment is completely completed; the current time refers to the time when the process parameters are set during the current die-casting experiment.
3. The high-efficiency high-quality aluminum alloy damping tower high-pressure vacuum die-casting process control system according to claim 2, wherein the threshold judgment and prediction module is used for subtracting the vacuum degree and the die temperature signal at the last moment from the optimal vacuum degree and the optimal die temperature respectively to obtain a vacuum fluctuation difference at the last moment and a temperature fluctuation difference at the last moment, and respectively comparing the vacuum degree fluctuation difference with a vacuum degree allowable threshold beta 1 Allowable threshold value beta of die temperature 2 And comparing to determine whether to adjust the vacuum degree and the aluminum alloy liquid temperature signal at the current moment.
4. The high-efficiency high-quality aluminum alloy shock absorber tower high-pressure vacuum die-casting process control system as claimed in claim 3, wherein if the difference between the vacuum degree at the last moment and the optimal vacuum degree is larger than the allowable vacuum degree threshold beta 1 And improving the vacuum degree at the current moment to ensure the vacuum degree required by the high-quality die casting, otherwise, setting the vacuum degree at the current moment to be consistent with the vacuum degree at the last moment.
5. High efficiency according to claim 3The high-pressure vacuum die-casting process control system for the high-quality aluminum alloy damping tower is characterized in that if the difference between the temperature of the die at the last moment and the optimal die temperature is larger than the allowable threshold beta of the die temperature 2 And reducing the temperature of the aluminum alloy liquid to ensure the mold temperature required by the high-quality die casting, otherwise, setting the temperature of the aluminum alloy liquid at the current moment to be consistent with the temperature of the aluminum alloy liquid at the last moment.
6. The high-efficiency high-quality aluminum alloy shock absorber tower high-pressure vacuum die-casting process control system as claimed in claim 1, wherein the nonlinear mapping relation of the die-casting quality prediction model can be constructed by an artificial neural network or a numerical fitting prediction formula, the input of the artificial neural network model is the shot velocity deviation amplitude at the last moment, the shot force deviation amplitude, the vacuum fluctuation difference at the last moment and the temperature fluctuation difference at the last moment, and the output of the model is the die-casting quality at the last moment.
7. The high-efficiency high-quality aluminum alloy shock absorber tower high-pressure vacuum die-casting process control system as claimed in claim 6, wherein the nonlinear mapping relation of the die-casting quality prediction model can be constructed by numerical fitting prediction formula, and the mass μ of the die-casting at the last moment 1 The numerical fitting prediction formula of (1) is:
the numerical fitting prediction formula is: mu.s 1 ＝f(η 1 ,η 2 ,η 3 ,η 4 )
Wherein eta is 1 For the injection force of the last moment, eta 2 For the injection velocity, η, of the last moment 3 Is the temperature fluctuation difference of the last moment, eta 4 The difference in vacuum fluctuation at the previous time.
8. The high-pressure vacuum die-casting process control method for the high-efficiency high-quality aluminum alloy damping tower is characterized by comprising the following steps of:
the detection module detects the vacuum degree, the die temperature, the temperature of the aluminum alloy liquid, the injection speed and the injection force at the last moment in real time;
the threshold judgment and prediction module carries out threshold judgment according to the vacuum degree and the mold temperature signal provided by the detection module at the last moment so as to determine whether to adjust the vacuum degree and the aluminum alloy liquid temperature signal at the current moment;
the threshold value judging and predicting module respectively makes difference with the target injection speed and the target injection force according to the injection speed and the injection force signals provided by the detecting module at the last moment to obtain the deviation amplitude of the injection speed and the deviation amplitude of the injection force at the last moment, and a die casting quality predicting model is constructed by combining the vacuum fluctuation difference at the last moment and the temperature fluctuation difference at the last moment to obtain the quality mu of the die casting at the last moment 1 (ii) a The nonlinear mapping relation of the die casting quality prediction model can be constructed by an artificial neural network or a numerical fitting prediction formula;
inputting the deviation amplitude of the injection speed, the deviation amplitude of the injection force, the vacuum fluctuation difference of the last moment and the temperature fluctuation difference of the last moment into an artificial neural network model, and outputting the model as the quality of the die casting of the last moment;
the numerical fitting prediction formula is: mu.s 1 ＝f(η 1 ,η 2 ,η 3 ,η 4 )
Wherein eta is 1 For the injection force of the last moment, eta 2 For the injection velocity, η, of the last moment 3 Is the temperature fluctuation difference of the last moment, eta 4 The vacuum fluctuation difference at the last moment;
the previous moment refers to the moment when the previous die-casting experiment is completely finished; the current moment refers to the moment when the technological parameters are set during the current die-casting experiment;
the threshold value judging and predicting module respectively differentiates the vacuum degree and the mould temperature signal at the last moment with the optimal vacuum degree and the optimal mould temperature to obtain the vacuum fluctuation difference and the temperature fluctuation difference at the last moment, and respectively differentiates the vacuum degree and the temperature fluctuation difference with a vacuum degree allowable threshold value beta 1 Allowable threshold value beta of die temperature 2 Comparing to determine whether to adjust the vacuum degree and the aluminum alloy liquid temperature signal at the current moment; if the difference between the vacuum degree at the last moment and the optimal vacuum degree is larger than the allowable threshold beta of the vacuum degree 1 The vacuum degree at the current moment is improved to ensure the vacuum required by high-quality die castingIf not, the vacuum degree at the current moment is consistent with the vacuum degree setting at the last moment; if the difference between the mold temperature at the last moment and the optimal mold temperature is larger than the allowable threshold value beta of the mold temperature 2 Reducing the temperature of the aluminum alloy liquid to ensure the mold temperature required by the high-quality die casting, otherwise, setting the temperature of the aluminum alloy liquid at the current moment to be consistent with the temperature of the aluminum alloy liquid at the previous moment;
the threshold value judging and predicting module judges and predicts the quality mu of the die casting according to the previous moment 1 And optimum die casting quality mu 0 Calculating the injection force dynamic gain sigma at the current moment 1 And shot velocity dynamic gain σ 2 Obtaining the injection force lambda at the current moment 1 And current time injection velocity lambda 2 ；
Wherein, χ 1 For adjusting the coefficient of the pressure, χ 2 For adjusting the coefficient of injection velocity, eta 1 Injection force, eta, at the last moment 2 The injection speed at the last moment;
the control module extracts threshold values to judge and predict the current vacuum degree, the current aluminum alloy liquid temperature, the current injection force and the current injection speed of the module, and sends the signal values to the vacuum high-pressure die-casting machine for real-time control.
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| CN101786150A (en) * | 2010-02-10 | 2010-07-28 | 广东伊之密精密机械有限公司 | Die casting machine and automatic judgment method of die casting quality |
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Effective date of registration: 20231115 Address after: 410082 No. 1, lushanmen, Lushan South Road, Yuelu District, Changsha City, Hunan Province Patentee after: HUNAN University Patentee after: Suzhou Research Institute of Hunan University Address before: 410082 No. 1, lushanmen, Lushan South Road, Yuelu District, Changsha City, Hunan Province Patentee before: HUNAN University |