CN114632922A - 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 97
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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
- B22D17/20—Accessories: Details
- B22D17/32—Controlling equipment
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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
- B22D17/14—Machines with evacuated die cavity
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 system structurally 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 vacuum high-pressure 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 damping 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 is a molding process of filling a mold cavity with liquid metal at a very high speed under the action of high pressure, and cooling and solidifying the liquid metal 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 shock absorption tower is unstable, is limited by a single production process, is difficult to meet the large-scale, long-time and repetitive large-scale production requirements, and easily produces inferior-quality products or defective parts with poor mechanical properties, thereby greatly influencing the high-quality and high-efficiency production of the shock absorption 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 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 vacuum high-pressure 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 to judge whether to adjust the vacuum degree and the aluminum alloy liquid temperature signal at the current moment according to the vacuum degree and the mold temperature signal provided by the detection module at the last 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 moment1And optimum die casting quality mu0Calculating the injection force dynamic gain sigma at the current moment1And shot velocity dynamic gain σ2Obtaining the injection force lambda at the current moment1And current time injection velocity lambda2；
Wherein, χ1For adjusting the coefficient of the pressure, χ2The coefficient is adjusted for the injection speed,
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 beta1Allowable threshold value beta of die temperature2And 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 β1The vacuum degree at the current moment is improved to ensure the vacuum degree required by the high-quality die casting, otherwise, the vacuum degree at the current moment and the vacuum degree at the last moment are trueThe degree of hollowness settings are consistent.
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 β2And 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 moment1The numerical fitting prediction formula of (a) is:
μ1＝f(η1,η2,η3,η4)
wherein eta1For the injection force of the last moment, eta2For the injection velocity, η, of the last moment3Is the temperature fluctuation difference of the last moment, eta4The 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 to judge whether to adjust the vacuum degree and the aluminum alloy liquid temperature signal at the current moment according to the vacuum degree and the mold temperature signal provided by the detection module at the last moment;
the threshold judging and predicting module respectively compares the injection speed and the injection force signal provided by the detecting module at the last moment with the target injection speedMaking a difference between the degree and the injection force to obtain the deviation amplitude of the injection speed and the deviation amplitude of the injection force at the previous moment, and combining the vacuum fluctuation difference and the temperature fluctuation difference at the previous moment to construct a die casting quality prediction model so as to obtain the quality mu of the die casting at the previous moment1(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.s1＝f(η1,η2,η3,η4)
Wherein eta is1For the injection force of the last moment, eta2For the injection velocity, η, at the last moment3Is the temperature fluctuation difference of the last moment, eta4The 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 beta1Allowable threshold value beta of die temperature2And 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 degree1And 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 temperature2The temperature of the aluminum alloy liquid is reduced to ensure the mold temperature required by the high-quality die casting, otherwise, the temperature of the aluminum alloy liquid at the current moment is reducedThe temperature setting is consistent with the temperature setting of the aluminum alloy liquid at the last moment;
the threshold judging and predicting module is used for judging whether to adjust the vacuum degree and the aluminum alloy liquid temperature signal at the current moment or not according to the vacuum degree and the mold temperature signal provided by the detection module 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 moment1And optimum die casting quality mu0Calculating the injection force dynamic gain sigma at the current moment1And shot velocity dynamic gain σ2Obtaining the injection force lambda at the current moment1And current time injection velocity lambda2；
Wherein, χ1For adjusting the coefficient of the pressure, χ2The coefficient is adjusted for the injection speed,
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: according to the invention, the vacuum degree, the die temperature, the aluminum alloy liquid temperature, the injection speed and the injection speed signal of the aluminum alloy damping tower at the last moment are detected in real time to correct the vacuum degree, the aluminum alloy liquid temperature, 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 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 vacuum high-pressure 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 to judge whether to adjust the vacuum degree and the aluminum alloy liquid temperature signal at the current moment according to the vacuum degree and the mold temperature signal provided by the detection module at the last 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 moment1And optimum die casting quality mu0Calculating the injection force dynamic gain sigma at the current moment1And injection velocityThe state gain sigma2Obtaining the injection force lambda at the current moment1And current time injection velocity lambda2；
Wherein, χ1For adjusting the coefficient of the pressure, χ2The coefficient is adjusted for the injection speed,
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 respectively1Allowable threshold value beta of die temperature2And 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 beta1And 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 β2And 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 moment1The numerical fitting prediction formula of (a) is:
μ1＝f(η1,η2,η3,η4)
wherein eta is1For the injection force of the last moment, eta2For the injection velocity, η, of the last moment3Is the temperature fluctuation difference of the last moment, eta4The 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 to judge whether to adjust the vacuum degree and the aluminum alloy liquid temperature signal at the current moment according to the vacuum degree and the mold temperature signal provided by the detection module at the last 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 moment1(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.s1＝f(η1,η2,η3,η4)
Wherein eta is1For the injection force of the last moment, eta2For the injection velocity, η, of the last moment3Is the temperature fluctuation difference of the last moment, eta4The 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 beta1Allowable threshold value beta of die temperature2And 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 degree1And 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 temperature2Reducing 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 judgment and prediction module carries out threshold judgment to judge whether to adjust the vacuum degree and the aluminum alloy liquid temperature signal at the current moment according to the vacuum degree and the mold temperature signal provided by the detection module 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 moment1And optimum die casting quality mu0Calculating the injection force dynamic gain sigma at the current moment1And shot velocity dynamic gain σ2Obtaining the injection force lambda at the current moment1And current time injection velocity lambda2；
Wherein, χ1For adjusting the coefficient of the pressure, χ2The coefficient is adjusted for the speed of injection,
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 vacuum high-pressure casting machine;
the detection module detects the vacuum degree, the die temperature, the aluminum alloy liquid temperature, 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 to judge whether to adjust the vacuum degree and the aluminum alloy liquid temperature signal at the current moment according to the vacuum degree and the mold temperature signal provided by the detection module at the last 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 moment1And optimum die casting quality mu0Calculating the injection force dynamic gain sigma at the current moment1And shot velocity dynamic gain σ2Obtaining the injection force lambda at the current moment1And current time injection velocity lambda2；
Wherein, χ1For adjusting the coefficient of the pressure, χ2The coefficient is adjusted for the injection speed,
the control module extracts the current vacuum degree, the current aluminum alloy liquid temperature, the current injection force and the current 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 shock absorption tower high-pressure vacuum die-casting process control system of claim 2, wherein the threshold judgment and prediction module respectively compares the vacuum degree and the mold temperature signal at the last moment with the optimal vacuum degreeAnd subtracting the optimal mold temperature to obtain the last-time vacuum fluctuation difference and the last-time temperature fluctuation difference, and respectively comparing the last-time vacuum fluctuation difference and the last-time temperature fluctuation difference with a vacuum degree allowable threshold value beta1Allowable threshold value beta of die temperature2And 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 beta1And 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. 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 mold temperature at the last moment and the optimal mold temperature is greater than the allowable mold temperature threshold β2And 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 non-linear mapping relation of the die-casting quality prediction model can be constructed by a numerical fitting prediction formula, and the last time isMass of die-cast part mu1The numerical fitting prediction formula of (a) is:
the numerical fitting prediction formula is: mu.s1＝f(η1,η2,η3,η4)
Wherein eta1For the injection force of the last moment, eta2For the injection velocity, η, of the last moment3Is the temperature fluctuation difference of the last moment, eta4The vacuum fluctuation difference at the last time.
8. The control method for the high-pressure vacuum die-casting process of the high-efficiency high-quality aluminum alloy shock absorption 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 to judge whether to adjust the vacuum degree and the aluminum alloy liquid temperature signal at the current moment according to the vacuum degree and the mold temperature signal provided by the detection module at the last 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 moment1(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.s1＝f(η1,η2,η3,η4)
Wherein eta is1For the injection force of the last moment, eta2For the injection velocity, η, of the last moment3Is the temperature fluctuation difference of the last moment, eta4The difference of the vacuum fluctuation at the last moment;
wherein, 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 subtracts the vacuum degree and the mould temperature signal at the last moment from 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 compares the vacuum degree and the temperature fluctuation difference with a vacuum degree allowable threshold value beta1Allowable threshold value beta of die temperature2Comparing 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 degree1Improving 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 previous 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 temperature2Reducing 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 judgment and prediction module carries out threshold judgment to judge whether to adjust the vacuum degree and the aluminum alloy liquid temperature signal at the current moment according to the vacuum degree and the mold temperature signal provided by the detection module 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 moment1And optimum die casting quality mu0Calculating the injection force dynamic gain sigma at the current moment1And shot velocity dynamic gain σ2Obtaining the injection force lambda at the current moment1And current time injection velocity lambda2；
Wherein, χ1For adjusting the coefficient of the pressure, χ2The coefficient is adjusted for the injection speed,
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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Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2002103409A (en) * | 2000-09-29 | 2002-04-09 | Sanyo Denki Co Ltd | Method for controlling injection molding machine, and injection molding machine |
| CN1727095A (en) * | 2005-05-30 | 2006-02-01 | 上海压铸机厂 | Computer measurement and control system for die-casting machine |
| JP2006281662A (en) * | 2005-04-01 | 2006-10-19 | Nissei Plastics Ind Co | Controller device of injection molding machine |
| JP2007125593A (en) * | 2005-11-04 | 2007-05-24 | Toyota Motor Corp | Apparatus and method for analyzing casting process |
| 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 |
| CN110059738A (en) * | 2019-04-11 | 2019-07-26 | 清华大学深圳研究生院 | A kind of method for early warning and system of quality of die casting |
| CN111442001A (en) * | 2020-03-20 | 2020-07-24 | 宁波海天金属成型设备有限公司 | Oil circuit structure for double closed-loop control of injection speed and injection force and control mode |
-
2022
- 2022-02-15 CN CN202210136235.8A patent/CN114632922B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2002103409A (en) * | 2000-09-29 | 2002-04-09 | Sanyo Denki Co Ltd | Method for controlling injection molding machine, and injection molding machine |
| JP2006281662A (en) * | 2005-04-01 | 2006-10-19 | Nissei Plastics Ind Co | Controller device of injection molding machine |
| CN1727095A (en) * | 2005-05-30 | 2006-02-01 | 上海压铸机厂 | Computer measurement and control system for die-casting machine |
| JP2007125593A (en) * | 2005-11-04 | 2007-05-24 | Toyota Motor Corp | Apparatus and method for analyzing casting process |
| 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 |
| CN110059738A (en) * | 2019-04-11 | 2019-07-26 | 清华大学深圳研究生院 | A kind of method for early warning and system of quality of die casting |
| CN111442001A (en) * | 2020-03-20 | 2020-07-24 | 宁波海天金属成型设备有限公司 | Oil circuit structure for double closed-loop control of injection speed and injection force and control mode |
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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 |