CN116277690A - Composite material molding press electric control system based on mold parameter detection - Google Patents
Composite material molding press electric control system based on mold parameter detection Download PDFInfo
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- 238000001514 detection method Methods 0.000 title claims abstract description 56
- 239000002131 composite material Substances 0.000 title claims abstract description 24
- 238000000465 moulding Methods 0.000 title claims abstract description 24
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- 238000007723 die pressing method Methods 0.000 claims description 7
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- 238000007405 data analysis Methods 0.000 claims description 5
- 238000004458 analytical method Methods 0.000 claims description 3
- 230000010354 integration Effects 0.000 claims description 3
- 238000004519 manufacturing process Methods 0.000 abstract description 20
- 238000003825 pressing Methods 0.000 description 13
- 238000010438 heat treatment Methods 0.000 description 7
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B29—WORKING OF PLASTICS; WORKING OF SUBSTANCES IN A PLASTIC STATE IN GENERAL
- B29C—SHAPING OR JOINING OF PLASTICS; SHAPING OF MATERIAL IN A PLASTIC STATE, NOT OTHERWISE PROVIDED FOR; AFTER-TREATMENT OF THE SHAPED PRODUCTS, e.g. REPAIRING
- B29C43/00—Compression moulding, i.e. applying external pressure to flow the moulding material; Apparatus therefor
- B29C43/32—Component parts, details or accessories; Auxiliary operations
- B29C43/58—Measuring, controlling or regulating
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B29—WORKING OF PLASTICS; WORKING OF SUBSTANCES IN A PLASTIC STATE IN GENERAL
- B29C—SHAPING OR JOINING OF PLASTICS; SHAPING OF MATERIAL IN A PLASTIC STATE, NOT OTHERWISE PROVIDED FOR; AFTER-TREATMENT OF THE SHAPED PRODUCTS, e.g. REPAIRING
- B29C43/00—Compression moulding, i.e. applying external pressure to flow the moulding material; Apparatus therefor
- B29C43/32—Component parts, details or accessories; Auxiliary operations
- B29C43/58—Measuring, controlling or regulating
- B29C2043/5808—Measuring, controlling or regulating pressure or compressing force
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B29—WORKING OF PLASTICS; WORKING OF SUBSTANCES IN A PLASTIC STATE IN GENERAL
- B29C—SHAPING OR JOINING OF PLASTICS; SHAPING OF MATERIAL IN A PLASTIC STATE, NOT OTHERWISE PROVIDED FOR; AFTER-TREATMENT OF THE SHAPED PRODUCTS, e.g. REPAIRING
- B29C43/00—Compression moulding, i.e. applying external pressure to flow the moulding material; Apparatus therefor
- B29C43/32—Component parts, details or accessories; Auxiliary operations
- B29C43/58—Measuring, controlling or regulating
- B29C2043/5816—Measuring, controlling or regulating temperature
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- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
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Abstract
The invention discloses a composite material molding press electric control system based on mold parameter detection, which comprises a central controller, a pressure control unit, a temperature acquisition unit, a mold detection unit and the like. The die detection unit is used for detecting a product gap, the temperature acquisition unit is used for acquiring the temperatures of the hot plate and the die in real time, and the central controller generates a temperature control instruction and a pressure control instruction by using a preset adjustment model according to the acquisition result, so that the control of the temperature and the pressure of the system is realized. The temperature adjustment model adopts a Markov chain model, and abnormal values are eliminated by analyzing the acquisition result to generate a temperature control instruction. The pressure adjustment model adopts a fuzzy control method, and high-precision control of the pressure of the model is realized by mapping a gap detection result into a fuzzy set. The invention has the advantages of high precision, high efficiency, high automation and the like, can improve the product quality and the production efficiency, and has wide application prospect.
Description
Technical Field
The invention relates to the technical field of composite material molding presses, in particular to an electric control system of a composite material molding press based on mold parameter detection.
Background
With the continuous progress of technology, composite materials are widely used in various fields. And the manufacturing process of composite molds is becoming more and more important. The traditional composite material molding press controls the temperature of the heating plate in a heating pipe mode and the like, and then the heating plate is used for transferring heat to the die to achieve the purpose of heating the die. In the process, the temperature and the pressing degree of the product in the pressing process are detected by extremely large amount of human intervention, and the temperature, the pressure, the air exhaust and other processes are converted and the final forming of the product are carried out by human modification. This method, although widely used, has some problems.
First, the conventional composite molding press control system requires a lot of manual intervention, which not only increases the production cost, but also affects the production efficiency. Secondly, because the adjustment of temperature and pressing degree needs to be manually judged, errors are easy to occur, and the quality of products is influenced. In addition, the method has the problems of high energy consumption, inconvenient adjustment and the like. Therefore, a new control system is urgently needed to solve these problems.
In order to solve these problems, many new control methods have been proposed. For example, a method based on PID control has been proposed. The method detects the temperature and the pressure through the sensor, and then adjusts the heating plate and the pressure through the PID control algorithm, thereby realizing the automatic control of the manufacturing process of the composite material mould. However, this method still has some problems. For example, the PID control algorithm needs to be adjusted according to the actual situation, and the adjustment process is complicated and requires a professional technician to operate. In addition, the method only considers temperature and pressure, so that the mold parameters cannot be detected, and the quality of the product cannot be well ensured.
In addition, there is a method based on PLC control. According to the method, parameters such as the heating plate, the pressure, the temperature and the time are controlled by the PLC, and the automatic control of the manufacturing process of the composite material die can be realized. However, since the method requires a large amount of programming, the requirements for technicians are high, and the parameters of the mold cannot be detected, and the quality of the product cannot be well ensured.
In view of the above, there are many problems in the conventional composite molding press manufacturing process, and a new control system is required to solve the problems. The new control system needs to be able to automatically control parameters such as heating, pressure, time, etc., and to be able to detect and control mold parameters, thus realizing effective guarantee of product quality.
Disclosure of Invention
The invention aims to provide a composite material molding press electric control system based on mold parameter detection, which realizes automatic adjustment of mold pressing parameters, improves production efficiency, product quality stability and consistency, reduces production cost and promotes development of intelligent manufacturing.
In order to solve the technical problems, the invention provides an electric control system of a composite material molding press based on mold parameter detection, which comprises: the device comprises a central controller, a pressure control unit, a temperature acquisition unit and a die detection unit; the die detection unit is configured to detect a product gap in the die pressing process to obtain a gap detection result; the temperature acquisition unit comprises a plurality of temperature sensors which are respectively and uniformly arranged on the hot plate and the die and are configured to acquire the temperatures of the hot plate and the die in real time to obtain a temperature acquisition result; the central controller is configured to receive a gap detection result and a temperature acquisition result, generate a temperature control instruction by using a preset temperature control adjustment model based on the temperature acquisition result, send the temperature control instruction to the temperature control unit, and simultaneously generate a pressure control instruction by using a preset pressure adjustment model based on the gap detection result and send the pressure control instruction to the pressure control unit; the temperature control unit is configured to control the system temperature in response to the temperature control instruction; the pressure control unit is configured to control a system pressure in response to the pressure control command.
Furthermore, the central controller is respectively in communication connection with the pressure control unit, the temperature acquisition unit and the die detection unit in an industrial Ethernet communication mode.
Further, when the temperature control instruction is generated, the temperature adjustment model performs data analysis on the temperature acquisition result so as to eliminate abnormal results.
Further, the die detection unit is a magnetic ruler arranged between the upper die and the lower die of the die.
Further, the temperature control adjustment model is constructed by the following method: defining a discrete state transition process for
Representing the state space of the system->
Representing slave status +.>
To state->
The markov chain model is expressed as: />
；/>
The method comprises the steps of carrying out a first treatment on the surface of the Wherein the state space->
Is defined as a triplet: />
The method comprises the steps of carrying out a first treatment on the surface of the Wherein (1)>
Indicating the current temperature +_>
Indicating the temperature at the last moment,/->
Indicating a desired temperature; assume that the current temperature is +.>
The desired temperature is +.>
The temperature deviation is e, the proportionality coefficient is +.>
The integral coefficient is +.>
Differential coefficient of +.>
Output signal +.>
Expressed as: />
；
The method comprises the steps of carrying out a first treatment on the surface of the Using sliding window integration, the most recent +.>
Integrating the data; thus, the output signal +.>
The method comprises the following steps:
the method comprises the steps of carrying out a first treatment on the surface of the Finally, the generated temperature control instruction is expressed as: />
The method comprises the steps of carrying out a first treatment on the surface of the Wherein (1)>
For temperature control command, ">
Is a time variable.
Further, the temperature control adjustment model is based on temperatureThe method for generating the temperature control instruction comprises the following steps of: comparing the temperature acquisition result with the expected temperature to calculate the current temperature deviation
；/>
The method comprises the steps of carrying out a first treatment on the surface of the According to the current state->
And temperature deviation->
Calculate the state transition probability +.>
The method comprises the steps of carrying out a first treatment on the surface of the Calculating the expected state value +.>
；
The method comprises the steps of carrying out a first treatment on the surface of the Calculating an output signal according to the state expectation value and the temperature deviation>
The method comprises the steps of carrying out a first treatment on the surface of the According to the state expectation->
And temperature deviation->
The output signal can be calculated>
：
The method comprises the steps of carrying out a first treatment on the surface of the Outputting the controller signal
Converts into a temperature control instruction and sends the temperature control instruction toThe temperature control unit is used for controlling the temperature of the system; the temperature control instruction is as follows:
。
further, when the temperature adjustment model generates a temperature control instruction, the method for analyzing the data of the temperature acquisition result to eliminate the abnormal result includes: for temperature acquisition result
First, the average value +.>
And standard deviation->
The method comprises the steps of carrying out a first treatment on the surface of the Then, analysis is performed using an abnormal value detection formula based on the mean deviation: />
The method comprises the steps of carrying out a first treatment on the surface of the Wherein (1)>
Representing sampling points
Deviation measure of>
Mean value->
Representing standard deviation; if->
Exceeding a preset threshold ∈>
The sampling point is considered to be an outlier, which needs to be excluded.
Further, the method for generating the pressure control command by the pressure adjustment model based on the gap detection result comprises the following steps: mapping the gap detection result into a fuzzy set to obtain fuzzy input; initializing a fuzzy rule base, wherein the fuzzy rule base comprises fuzzy sets and fuzzy rules of input variables and output variables; fuzzy reasoning is carried out through a fuzzy rule base, and fuzzy output is obtained; and mapping the fuzzy output to the actual control quantity to obtain a pressure control instruction.
The invention has the following beneficial effects:
1. the production efficiency and the production quality are improved: the invention realizes the omnibearing monitoring and control of the pressing process of the die by integrating a plurality of functional modules, such as the die detection unit, the temperature acquisition unit, the pressure control unit and the like, and greatly improves the efficiency and the precision of the die pressing. By adopting the Markov chain model and the fuzzy control method, the invention can quickly and accurately generate the temperature control instruction and the pressure control instruction according to the data acquired in real time, thereby realizing the accurate control of the temperature and the pressure of the system and further improving the quality and the yield of products.
2. The risk of manual intervention and misoperation is reduced: the central controller is connected with other components in an industrial Ethernet communication mode, so that high-speed and reliable data exchange and control are realized, and the risk of manual intervention and the possibility of misoperation are greatly reduced. Meanwhile, by using a preset adjustment model and algorithm, the invention can automatically and accurately adjust and control parameters, and reduces the workload of manual intervention and the risk of misoperation.
3. Stability and reliability of the device are improved: the invention can comprehensively monitor and control the pressing process of the die by adopting various detection modules and adjustment models, thereby ensuring the stability and reliability of the equipment. By collecting parameter data such as temperature and gaps in real time and analyzing and controlling the parameter data, the accurate control of the system can be realized, deviation or faults of equipment are prevented, and the stability and reliability of the equipment are improved.
4. Has wide application prospect: the invention adopts various detection modules and adjustment models, can realize the omnibearing monitoring and control of the pressing process of the die, and is suitable for the die pressing production process in the fields of composite materials, plastics, rubber and the like. Through automatic and accurate parameter adjustment and control, production efficiency and production quality can be improved, cost and risk are reduced, and the method has wide application prospect and market value.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are required to be used in the embodiments or the description of the prior art will be briefly described below, and it is obvious that the drawings in the following description are only embodiments of the present invention, and that other drawings can be obtained according to the provided drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic system structure diagram of an electric control system of a composite molding press based on mold parameter detection according to an embodiment of the present invention.
Detailed Description
The core of the invention is to provide a composite material molding press electric control system based on mold parameter detection, wherein the composite material molding press electric control system based on mold parameter detection adopts an industrial Ethernet communication technology and an automatic control technology, thereby realizing intelligent control of the composite material molding press. The technology can realize the automation, the intellectualization and the optimization of the production process of the composite material molding press by means of model optimization, intelligent prediction and the like on the basis of continuously collecting and analyzing the parameter data in the pressing process of the mold, and provides powerful support for the development of intelligent manufacturing.
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Example 1
Referring to fig. 1, fig. 1 is a schematic diagram of an electronic control system of a composite material molding press based on mold parameter detection, which includes: the device comprises a central controller, a pressure control unit, a temperature acquisition unit and a die detection unit; the die detection unit is configured to detect a product gap in the die pressing process to obtain a gap detection result; the temperature acquisition unit comprises a plurality of temperature sensors which are respectively and uniformly arranged on the hot plate and the die and are configured to acquire the temperatures of the hot plate and the die in real time to obtain a temperature acquisition result; the central controller is configured to receive a gap detection result and a temperature acquisition result, generate a temperature control instruction by using a preset temperature control adjustment model based on the temperature acquisition result, send the temperature control instruction to the temperature control unit, and simultaneously generate a pressure control instruction by using a preset pressure adjustment model based on the gap detection result and send the pressure control instruction to the pressure control unit; the temperature control unit is configured to control the system temperature in response to the temperature control instruction; the pressure control unit is configured to control a system pressure in response to the pressure control command.
Specifically, the die detecting unit is a component for detecting the gap of the product in the die pressing process, and the function of the die detecting unit is to obtain the gap detection result. The component can help the system to realize more accurate pressing control and improve the quality of products.
The temperature acquisition unit is a component for acquiring the temperatures of the hot plate and the die in real time and comprises a plurality of temperature sensors which are uniformly arranged on the hot plate and the die, and the temperatures of the hot plate and the die can be acquired in real time. The function of this part is to obtain temperature acquisition result, provide data basis for follow-up temperature control adjustment model.
The central controller is a core control component of the whole system, and has the main functions of receiving a gap detection result and a temperature acquisition result, and generating a temperature control instruction by using a preset temperature control adjustment model based on the results. Meanwhile, based on a gap detection result, a preset pressure adjustment model is used for generating pressure control instructions, and the control instructions and commands are sent to a temperature control unit and a pressure control unit to control the temperature and the pressure of the system, so that control over composite material die pressing is achieved.
The temperature control unit and the pressure control unit are respectively used for responding to the temperature control instruction and the pressure control instruction and controlling the temperature and the pressure of the system. The two components are executing components in the system, and the function of the executing components is to translate control instructions and commands sent by the central controller into actual operations, so that the accurate control of temperature and pressure is realized.
In a comprehensive view, the technical scheme of the patent provides a composite material molding press electric control system based on mold parameter detection, which can realize the control of the molding process by detecting the product gap in the mold pressing process and collecting the mold temperature in real time, thereby improving the quality and stability of the product. Meanwhile, the system adopts the central controller to control the temperature and the pressure of the system, and has the advantages of simple and convenient operation, accurate control and the like.
Example 2
On the basis of the above embodiment, the central controller is respectively in communication connection with the pressure control unit, the temperature acquisition unit and the mold detection unit in an industrial Ethernet communication mode.
Industrial ethernet is a communication protocol commonly used in the field of industrial automation, and has advantages of high speed, high reliability, large capacity, and the like, and can meet the requirements of the industrial field on communication rate and reliability. Through the communication mode of industrial Ethernet, the central controller can realize high-speed data exchange with other components, thereby realizing the accurate control of the molding press.
The pressure control unit is a means for controlling the system pressure in response to a pressure control command. The central controller can send the pressure control instruction to the pressure control unit in an industrial Ethernet communication mode, so that the control of the system pressure is realized.
The temperature control unit is a means for controlling the temperature of the system in response to a temperature control instruction. The central controller can send a temperature control instruction to the temperature control unit in an industrial Ethernet communication mode, so that the control of the system temperature is realized.
The temperature acquisition unit is a component for acquiring the temperatures of the hot plate and the mold in real time. The acquired temperature data can be transmitted to the central controller in an industrial Ethernet communication mode, and a data base is provided for a subsequent temperature control adjustment model.
The mold detecting unit is a member for detecting a product gap during the mold pressing process. The detected product gap data may be transmitted to a central controller by way of industrial ethernet communication to provide a data base for a subsequent pressure regulation model.
In a comprehensive view, the central controller can realize high-speed data exchange with other components in an industrial Ethernet communication mode, so that the molding press is accurately controlled.
Example 3
On the basis of the above embodiment, the temperature adjustment model performs data analysis on the temperature acquisition result to eliminate abnormal results when generating the temperature control instruction.
Specifically, during operation of the molding press, the temperature acquisition may be affected by various factors, such as ambient temperature, sensor errors, system noise, and the like. These factors may cause abnormal values to occur in the temperature acquisition result, thereby affecting the accuracy of temperature control. To exclude the effects of these outliers, the collected temperature data needs to be analyzed and processed.
The temperature adjustment model can be analyzed according to temperature data acquired in real time, including checking the continuity, change trend, deviation range and the like of the data. By carrying out statistical analysis on the data, abnormal values in the temperature acquisition result can be eliminated, and the accuracy and reliability of temperature control are improved.
Therefore, the temperature adjustment model of the technical scheme can eliminate abnormal values in the temperature acquisition result, thereby ensuring the accuracy of temperature control instructions and improving the stability and the production efficiency of the molding press.
Example 4
On the basis of the previous embodiment, the die detection unit is a magnetic ruler arranged between the upper die and the lower die of the die.
Specifically, the magnetic ruler is a position sensor commonly used in the field of industrial automation, and the magnetic ruler is mainly used for detecting the position and the motion state of a machine in real time so as to realize accurate control of the machine. In this patent solution, a magnetic ruler is mounted between the upper and lower dies of the die for detecting the gap between the products during the pressing of the die.
Through the use of magnetic scale, can realize the real-time supervision and the detection to the product clearance, and then realize the accurate control to the mould. Meanwhile, the stability and the production efficiency of the system can be improved by using the magnetic ruler, and the normal operation of the molding press is ensured.
Example 5
On the basis of the above embodiment, the temperature control adjustment model is constructed by the following method: defining a discrete state transition process for
Representing the state space of the system->
Representing slave status +.>
To state->
The markov chain model is expressed as: />
；/>
The method comprises the steps of carrying out a first treatment on the surface of the Wherein the state space->
Is defined as a triplet: />
The method comprises the steps of carrying out a first treatment on the surface of the Wherein (1)>
Indicating the current temperature +_>
Indicating the temperature at the last moment,/->
Indicating a desired temperature; assume that the current temperature is +.>
The desired temperature is +.>
The temperature deviation is e, the proportionality coefficient is +.>
The integral coefficient is +.>
Differential coefficient of +.>
Output signal +.>
Expressed as: />
；
The method comprises the steps of carrying out a first treatment on the surface of the Using sliding window integration, the most recent +.>
Integrating the data; thus, the output signal +.>
The method comprises the following steps:
the method comprises the steps of carrying out a first treatment on the surface of the Finally, the generated temperature control instruction is expressed as: />
The method comprises the steps of carrying out a first treatment on the surface of the Wherein (1)>
For temperature control command, ">
Is a time variable.
Example 6
Based on the above embodiment, the method for generating a temperature control instruction by the temperature control adjustment model based on a temperature acquisition result includes: comparing the temperature acquisition result with the expected temperature to calculate the current temperature deviation
；
The method comprises the steps of carrying out a first treatment on the surface of the According to the current state->
And temperature deviation->
Calculating state transition probability
The method comprises the steps of carrying out a first treatment on the surface of the Calculating the expected state value +.>
；/>
The method comprises the steps of carrying out a first treatment on the surface of the Calculating an output signal according to the state expectation value and the temperature deviation>
The method comprises the steps of carrying out a first treatment on the surface of the According to the state expectation->
And temperature deviation->
The output signal can be calculated>
：/>
The method comprises the steps of carrying out a first treatment on the surface of the Output signal of controller +.>
Converting into a temperature control instruction, sending the temperature control instruction to a temperature control unit, and controlling the temperature of the system; the temperature control instruction is as follows: />
。
Specifically, through this control by temperature change adjustment model, can carry out high accuracy control to the mould temperature to realize improving product quality and production efficiency's improvement.
Example 7
On the basis of the above embodiment, the method for performing data analysis on the temperature acquisition result to eliminate abnormal results when the temperature adjustment model generates the temperature control instruction includes: for temperature acquisition result
First, the average value +.>
And standard deviation->
The method comprises the steps of carrying out a first treatment on the surface of the Then, analysis is performed using an abnormal value detection formula based on the mean deviation: />
The method comprises the steps of carrying out a first treatment on the surface of the Wherein, the liquid crystal display device comprises a liquid crystal display device,
representing the sampling point +.>
Deviation measure of>
Representing the mean value，/>
Representing standard deviation; if->
Exceeding a preset threshold ∈>
The sampling point is considered to be an outlier, which needs to be excluded.
Example 8
Based on the above embodiment, the method for generating a pressure control command by the pressure adjustment model based on the gap detection result includes: mapping the gap detection result into a fuzzy set to obtain fuzzy input; initializing a fuzzy rule base, wherein the fuzzy rule base comprises fuzzy sets and fuzzy rules of input variables and output variables; fuzzy reasoning is carried out through a fuzzy rule base, and fuzzy output is obtained; and mapping the fuzzy output to the actual control quantity to obtain a pressure control instruction.
Specifically, mapping the gap detection result into a fuzzy set to obtain fuzzy input. And mapping the gap detection result into a fuzzy set according to a certain rule so as to facilitate the subsequent fuzzy reasoning processing. The common mapping methods include an equidistant method, a trigonometric function method, a trapezoidal function method and the like.
And initializing a fuzzy rule base, wherein the fuzzy rule base comprises fuzzy sets and fuzzy rules of input variables and output variables. Based on experience or expert knowledge, fuzzy sets and fuzzy rule bases including input variables and output variables are initialized. Wherein the input variables typically include gap deviation and gap rate of change and the output variables typically are pressure control commands. For each input variable, several fuzzy sets need to be defined, such as 'small', 'medium', 'large', etc.; for output variables, it is also necessary to define several fuzzy sets and set fuzzy rules, i.e. the relationship between input and output variables.
And carrying out fuzzy reasoning through a fuzzy rule base to obtain fuzzy output. And carrying out fuzzy reasoning on the fuzzy input through a fuzzy rule base to obtain fuzzy output. In the fuzzy reasoning process, firstly, an input variable is mapped to a fuzzy set to which the input variable belongs, and then fuzzy reasoning is carried out according to fuzzy rules in a fuzzy rule base to obtain fuzzy output.
And mapping the fuzzy output to the actual control quantity to obtain a pressure control instruction. And mapping the fuzzy output to the actual control quantity to obtain a pressure control instruction. Common mapping methods include weighted average, center average, etc.
Specifically, the control instruction of the pressure adjustment model is expressed as:
. In the above formula, parameter->
Indicating the gap detection deviation at the present moment, i.e. the difference between the actual gap value and the target gap value,/>
Indicating the rate of change of the gap detection deviation at the present moment, i.e +.>
+.>
Difference(s) of (I) and (II)>
Representing the sampling time interval, +.>
Alpha 2 and->
Respectively representing the proportional, differential and integral coefficients of the pressure controller.
It should be noted that parameters of the pressure adjustment model need to be adjusted and optimized according to actual control requirements, so as to improve control accuracy and stability of the algorithm. In general, online learning, incremental learning and other methods can be adopted to update and optimize the fuzzy rule base.
In short, the pressure adjustment model in the invention adopts a fuzzy self-adaptive control algorithm to generate a pressure control instruction. The algorithm has strong adaptability and robustness, and can effectively control the pressure in the pressing process of the die in practical application.
In the description, each embodiment is described in a progressive manner, and each embodiment is mainly described by the differences from other embodiments, so that the same similar parts among the embodiments are mutually referred. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant points refer to the description of the method section.
Those of skill would further appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the various illustrative elements and steps are described above generally in terms of functionality in order to clearly illustrate the interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. The software modules may be disposed in Random Access Memory (RAM), memory, read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.
The principles and embodiments of the present invention have been described herein with reference to specific examples, the description of which is intended only to facilitate an understanding of the method of the present invention and its core ideas. It should be noted that it will be apparent to those skilled in the art that various modifications and adaptations of the invention can be made without departing from the principles of the invention and these modifications and adaptations are intended to be within the scope of the invention as defined in the following claims.
Claims (8)
1. Composite molding press electrical system based on mold parameter detection, characterized in that the system comprises: the device comprises a central controller, a pressure control unit, a temperature acquisition unit and a die detection unit; the die detection unit is configured to detect a product gap in the die pressing process to obtain a gap detection result; the temperature acquisition unit comprises a plurality of temperature sensors which are respectively and uniformly arranged on the hot plate and the die and are configured to acquire the temperatures of the hot plate and the die in real time to obtain a temperature acquisition result; the central controller is configured to receive a gap detection result and a temperature acquisition result, generate a temperature control instruction by using a preset temperature control adjustment model based on the temperature acquisition result, send the temperature control instruction to the temperature control unit, and simultaneously generate a pressure control instruction by using a preset pressure adjustment model based on the gap detection result and send the pressure control instruction to the pressure control unit; the temperature control unit is configured to control the system temperature in response to the temperature control instruction; the pressure control unit is configured to control a system pressure in response to the pressure control command.
2. The system of claim 1, wherein the central controller is communicatively coupled to the pressure control unit, the temperature acquisition unit, and the mold detection unit, respectively, via industrial ethernet communications.
3. The system of claim 1, wherein the temperature adjustment model, when generating the temperature control command, performs a data analysis on the temperature acquisition result to exclude abnormal results.
4. The system of claim 1, wherein the mold detection unit is a magnetic scale mounted between upper and lower molds.
5. The system of claim 1 or 2 or 3 or 4, wherein the temperature control adjustment model is constructed by: defining a discrete state transition process for
Representing the state space of the system->
Representing slave status +.>
To state
The markov chain model is expressed as: />
；
The method comprises the steps of carrying out a first treatment on the surface of the Wherein the state space->
Is defined as a triplet:
the method comprises the steps of carrying out a first treatment on the surface of the Wherein (1)>
Indicating the current temperature +_>
Indicating the temperature at the last moment,/->
Indicating a desired temperature; assume that the current temperature is +.>
The desired temperature is +.>
The temperature deviation is e, the proportionality coefficient is +.>
The integral coefficient is +.>
Differential coefficient of
Output signal +.>
Expressed as: />
The method comprises the steps of carrying out a first treatment on the surface of the Wherein (1)>
The method comprises the steps of carrying out a first treatment on the surface of the Using sliding window integration, the most recent +.>
Integrating the data; thus, the output signal +.>
The method comprises the following steps: />
The method comprises the steps of carrying out a first treatment on the surface of the Finally, the generated temperature control instruction is expressed as: />
The method comprises the steps of carrying out a first treatment on the surface of the Wherein (1)>
For temperature controlAn instruction; />
Is a time variable.
6. The system of claim 5, wherein the temperature control adjustment model is based on temperature acquisition results, the method of generating temperature control instructions comprising: comparing the temperature acquisition result with the expected temperature to calculate the current temperature deviation
；
The method comprises the steps of carrying out a first treatment on the surface of the According to the current state->
And temperature deviation->
Calculating state transition probability
The method comprises the steps of carrying out a first treatment on the surface of the Calculating the expected state value +.>
；/>
The method comprises the steps of carrying out a first treatment on the surface of the Calculating an output signal according to the state expectation value and the temperature deviation>
The method comprises the steps of carrying out a first treatment on the surface of the According to the state expectation->
And temperature deviation->
The output signal can be calculated>
：/>
The method comprises the steps of carrying out a first treatment on the surface of the Output signal of controller +.>
Converting into a temperature control instruction, sending the temperature control instruction to a temperature control unit, and controlling the temperature of the system; the temperature control instruction is as follows: />
。
7. The system of claim 3, wherein the temperature adjustment model, when generating the temperature control command, performs data analysis on the temperature acquisition result to eliminate abnormal results, the method comprising: for temperature acquisition result
First, the average value +.>
And standard deviation->
The method comprises the steps of carrying out a first treatment on the surface of the Then, analysis is performed using an abnormal value detection formula based on the mean deviation:
the method comprises the steps of carrying out a first treatment on the surface of the Wherein (1)>
Representing the sampling point +.>
Deviation measure of>
Mean value->
Representing standard deviation; if->
Exceeding a preset threshold ∈>
The sampling point is considered to be an outlier, which needs to be excluded.
8. The system of claim 1 or 2 or 3 or 4, wherein the method of generating the pressure control command based on the gap detection result by the pressure adjustment model comprises: mapping the gap detection result into a fuzzy set to obtain fuzzy input; initializing a fuzzy rule base, wherein the fuzzy rule base comprises fuzzy sets and fuzzy rules of input variables and output variables; fuzzy reasoning is carried out through a fuzzy rule base, and fuzzy output is obtained; and mapping the fuzzy output to the actual control quantity to obtain a pressure control instruction.
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