CN103522526B - A kind of Multi-layer co-extrusion die head intelligent temperature control system and control method thereof - Google Patents

Abstract

The present invention is an intelligent temperature control system for a multi-layer co-extrusion die head, comprising a temperature acquisition module, an FPGA temperature control module, a drive heating module and a control panel; the temperature acquisition module includes N temperature acquisition units; the FPGA temperature control module includes an AD conversion circuit, an FPGA control chip for realizing the fuzzy PID control algorithm, and a PWM output circuit; the driving heating module includes N driving heating units corresponding to the heater in the control partition; the temperature signal of the control partition is collected and input to the FPGA by the temperature acquisition unit The temperature control module outputs N channels of PWM control values after processing, and the PWM output circuits output single channels to the driving heating unit. Its control method adopts the double parameter input of deviation e and deviation change rate e _c , and corrects the correction amount of PID parameter value obtained through fuzzy reasoning to obtain the final PID input parameter value; thus realizing intelligent control of the temperature of the heating ring .

Description

An intelligent temperature control system and control method for a multi-layer co-extrusion die head

technical field

The invention relates to the technical field of multi-layer co-extrusion blow molding machines in the plastics industry, in particular to a multi-layer co-extrusion die head intelligent temperature control system and a control method thereof.

Background technique

Blow molding technology is an important method of plastic molding process, and blow molding products account for an increasing proportion of plastic products. Among them, the multi-layer co-extrusion die head is the key equipment of blow molding equipment. Blow molding is mainly formed by melting and extruding resins with different melting points and different functions through multiple extruders, and compounding and co-extruding blow molding through multi-layer co-extrusion dies. There are mainly two types of existing co-extrusion dies, plane superimposed dies and spiral axial co-extrusion dies. As shown in Figure 1, it is a cross-sectional structure diagram of a five-layer plane superimposed co-extrusion die head, including an outer die 1, an inner die 2, a die ring 3, a superimposed disc 4, a die neck 5, and a die core 6; Heating rings are respectively installed on the outer side of the ring 3, the superimposed disc 4, the mold neck 5 and the inner side of the mold core. According to the needs of different packaging films, different plastic particles are used to fuse and co-extrude to obtain film products. Since the melting points of the plastic particles in each layer are different, the temperature required for stacking discs in different layers is different, so it is difficult to control the temperature of each layer individually in the control part of the co-extrusion die. If the temperature is too low, the flow channel will be blocked, and if the temperature is too high, it will cause over-burning or even scorching, which will cause the material to decompose, and the packaging film will lose the corresponding performance requirements.

At present, the temperature control of the co-extrusion die head of the blow molding unit mainly adopts the traditional PID control method based on PLC, and controls by selecting the proportional coefficient K _p , the integral coefficient K _d , and the differential coefficient K _i . The PID control principle is shown in Figure 2. The PID control method is widely used because of its simple algorithm, good robustness, and high reliability. However, since the temperature control system is a multivariable nonlinear time-varying system with large inertia, strong coupling, and large lag, it is difficult for real-time performance. The requirements are very high. Although the control requirements can be well met when the PID control process parameters are adjusted to appropriate values under a given temperature condition, if some or all of the set temperature values change, the control parameters need to be readjusted. For this new type of planar stacking die, readjusting the PID parameter values is not only demanding on the operator, but also time-consuming and laborious. Therefore, after adopting the traditional PID control method, its robustness is poor, it is extremely inconvenient for users, and it is difficult to achieve High-precision control directly affects the quality of the product. In order to meet the needs of control and adjustment when the temperature value changes, the traditional temperature control system of the blow molding unit adopts a PLC-based computer integrated control method. This kind of controller is not conducive to the improvement of system integration, and its cost is high, and its weight and volume are large. ; Therefore, changing the temperature control method and realizing real-time acquisition and rapid response to the temperature have become urgent problems to be solved in the design of the co-extrusion die temperature control system.

Contents of the invention

The problem to be solved by the present invention is to provide a multi-layer co-extrusion die head intelligent temperature control system and its control method capable of rapid response, simple operation, and automatic adaptive control of temperature changes.

The present invention is achieved through the following technical solutions:

A multi-layer co-extrusion die head intelligent temperature control system, including a temperature acquisition module, an FPGA temperature control module, a drive heating module, and a control panel for setting system initial values and displaying work information; the temperature acquisition module includes N temperature acquisition units corresponding to the control partition of the co-extrusion die temperature; the FPGA temperature control module includes an AD conversion circuit, an FPGA control chip for realizing a fuzzy PID control algorithm, and a PWM output circuit; the drive heating The module includes N driving heating units corresponding to the heaters in the control zone for temperature control;

The temperature signal of the control partition is collected by the corresponding temperature acquisition unit and input into one or more parallel cascaded FPGA temperature control modules, converted into a digital signal by the corresponding AD conversion circuit and processed by the FPGA control chip to output N-way PWM control quantity, Each channel of PWM control quantity is output to the corresponding driving and heating unit in a single channel by the PWM output circuit.

Preferably, the temperature collection unit includes a thermocouple sensor for collecting temperature signals and a temperature transmitter for converting the temperature signal into a 0-5v standard voltage signal or a 4-20mA standard current signal; the thermocouple sensor corresponds to Installed in the control partition inside the co-extrusion die head, the output terminals of the temperature transmitter are respectively connected with the input terminals of the AD conversion circuit.

Preferably, the FPGA temperature control module further includes a reset circuit for realizing a reset operation, a clock circuit for providing a reference clock, and an expansion interface for realizing data communication with a host computer.

Preferably, the driving heating unit includes a driving circuit for amplifying the output signal of the PWM circuit, a heating coil for heating, and a solid state relay for adjusting the power of the heating coil.

Further, described FPGA control chip comprises the ROM that is used to store fuzzy control table and the processor that is used to realize programming PID logic control; Store in ROM by the fuzzy control table that simulation and off-line calculation obtain by MATLAB tool, solidify in the processor There is a fuzzy PID control algorithm implemented by hardware description language.

A kind of multi-layer co-extrusion die head intelligent temperature control method, based on further described a kind of multi-layer co-extrusion die head intelligent temperature control system, comprises the steps:

a. System initialization, input the initial set temperature value and the initial parameter value of the fuzzy PID control algorithm through the control panel;

b. Collect the temperature of the co-extrusion die head, and collect the temperatures of the N control partitions in the co-extrusion die head respectively through the temperature acquisition unit to obtain temperature signals;

c. Adjustment of control output; realized by the fuzzy PID control algorithm, the temperature signal collected in step b is converted into a digital collection temperature value through the AD conversion circuit, and input into the FPGA control chip; according to the input collection temperature value and the set temperature value input in step a, the processor calculates the deviation e and the deviation change rate e _c , where e _c =de/dt; the fuzzy quantization of e and e _c obtains the coded values E, Ec, corresponding to E and E _c are obtained by inquiring the fuzzy control table in the ROM to obtain the correction values of PID parameters △K _p , △K _i , △K _d , and combined with the initial PID parameter values to calculate the PID input parameter values K _p , K _i , K _d ; output N-way parallel PID control quantities through incremental PID logic control;

d. Control signal output, each PID control quantity outputs a control signal through the PWM output circuit, and the control signal output by a single channel corresponds to the drive heating unit; realizes intelligent control of the temperature of different control zones;

e. Steps b to d are repeated to realize intelligent control of the temperature adjustment of different control zones in the co-extrusion die when the set temperature value is changed.

Preferably, the control partitions are obtained by partitioning in a matrix according to the temperature distribution of the co-extrusion die, and its number N=(n+3)m, where n is the number of film layers of the product produced by the co-extrusion die , m is the number of heating coils required for each layer of superimposed disks.

Preferably, in step b, the temperature of the co-extrusion die is collected through the thermocouple sensor in the temperature collection unit, and the temperature signal is converted into a standard voltage signal of 0-5v or 4-20mA through the temperature transmitter in the temperature collection unit The standard current signal is input to the AD conversion circuit after passing through the filtering links including median filtering and mean filtering.

Preferably, in step c, the fuzzy control table is to use the Matlab tool to carry out Simulink simulation to the temperature mathematical model of the control partition, after determining the quantitative factor, the basic domain of discourse, and the fuzzy domain of discourse, the fuzzy control rule table is established according to expert experience and simulation debugging , which is obtained after performing fuzzy reasoning and defuzzification by the center of gravity method.

Preferably, in step d, after amplifying the PWM output signal by driving the driving circuit in the heating unit, the on-off of the solid-state relay in the driving heating unit is controlled, and then the power of the corresponding heating coil is adjusted to realize the temperature control of different control zones. intelligent control.

Compared with the prior art, the present invention has the following beneficial technical effects:

The present invention is an intelligent temperature control system for a multi-layer co-extrusion die head, which realizes the control and adjustment of temperature changes through the FPGA temperature control module, and specifically utilizes the FPGA control chip as a programmable logic device to combine fuzzy control and PID control to realize The self-adaptive fuzzy PID control algorithm can make corresponding changes and adjustments to the control signal output by the FPGA control chip when the temperature changes, and realize corresponding and relatively independent temperature acquisition, transmission and decoupling control for the control partitions. The temperature of each partition is controlled individually, which can meet the temperature control requirements of each partition; it has high integration, small size, good robust performance, stable and reliable work, strong scalability, high control precision, small cumulative error, and strong adaptability.

Further, the temperature analog quantity is directly collected through the thermocouple sensor, converted into a voltage or current signal by the temperature transmitter, and finally converted into a digital signal by the AD converter and input to the FPGA control chip for processing, which improves data parallelism. Processing capacity, greatly improving the accuracy of temperature control.

Further, the fuzzy control table obtained by MATLAB offline calculation is used, and then stored in ROM to realize offline calculation when data is determined and online table lookup when calling, which greatly reduces the calculation amount of FPGA, thus speeding up the real-time system. The speed of control improves the system response speed.

The present invention is an intelligent temperature control method for a multi-layer co-extrusion die head. On the basis of the control system, the dual parameter input of the deviation e and the deviation change rate e _c is adopted, and the correction amount of the PID parameter value is obtained by fuzzy reasoning. The initial parameter value is corrected to obtain the final PID input parameter value; the fixed PID input parameter value in the transmission technology is continuously corrected in real time through the change of the deviation e and the deviation change rate e _c , and the value that changes with the actual situation is obtained. PID input parameter value, so as to realize the regulation and control of the temperature of the heating ring, and realize the intelligent control of the corresponding temperature.

Further, the filter link is used to reduce the acquisition error, ensuring the control accuracy from the source; through the call of the online self-tuning parameters in the fuzzy PID control algorithm, intelligent control is realized, and the PID parameter value is optimized through the limitation of the fuzzy control table, without precise control The mathematical model is simple in design and easy to apply. It has changed the defect that the PID parameter value does not change in the traditional PID control method, and satisfies the adjustment and change of the temperature control when changing the temperature setting during the working process; The fuzzy reasoning of online look-up table greatly simplifies fuzzy control, reduces the calculation amount of FPGA, reduces the difficulty of programming and shortens the design cycle.

Description of drawings

Fig. 1 is a cross-sectional structure diagram of a five-layer planar superimposed co-extrusion die head in the prior art; wherein, 1 is an outer die, 2 is an inner die, 3 is a die ring, 4 is a superimposed disc, and 5 is a die neck , 6 are mold cores.

Fig. 2 is a schematic block diagram of traditional PID control in the prior art.

Fig. 3 is a block diagram of the composition of the single-path temperature control in the example of the present invention.

Fig. 4 is a schematic diagram of division of the control partitions in the example of the present invention.

Fig. 5 is a functional block diagram of the fuzzy PID control algorithm described in the example of the present invention.

Fig. 6 is a structural block diagram of the temperature control system in the example of the present invention.

Fig. 7 is a block diagram of the single-path control flow of the temperature control method in the example of the present invention.

detailed description

The present invention will be further described in detail below in conjunction with specific embodiments, which are explanations of the present invention rather than limitations.

As shown in Figure 6, a multi-layer co-extrusion die head intelligent temperature control system of the present invention includes a temperature acquisition module, an FPGA temperature control module, a drive heating module and a control panel for setting the initial value of the system and displaying working information The temperature acquisition module includes N temperature acquisition units corresponding to the control partitions of the co-extrusion die head temperature; the FPGA temperature control module includes an AD conversion circuit, an FPGA control chip for realizing a fuzzy PID control algorithm, and a PWM output circuit; the drive heating module Including N drive heating units for temperature control corresponding to the heater in the control zone; the temperature signal of the control zone is collected by the corresponding temperature acquisition unit and input into one or more parallel cascaded FPGA temperature control modules, and converted by corresponding AD The circuit is converted into a digital signal and processed by the FPGA control chip to output N channels of PWM control quantities, and each channel of PWM control quantities is output to the corresponding driving and heating unit in a single channel by the PWM output circuit. In this preferred example, a 12-bit AD conversion circuit is used, the corresponding digital value ranges from 0 to 4095, and the accuracy can reach 0.32°C, which meets the accuracy requirements; and XC3S400 is used as the FPGA control chip, which has 141 I/O ports, 400K logic gates, 896 configurable logic blocks, 8064 logic units, up to 56K distributed memory and 288K block memory, can meet the temperature control requirements of multi-layer co-extrusion die head. For large-diameter multi-layer co-extrusion dies, there are many temperature zones that need to be controlled, and one XC3S400 chip cannot meet the requirements, and the FPGA control chip can be upgraded or multiple parallel XC3S400 chips can be used to meet the control requirements.

Preferably, as shown in Figure 3, the temperature acquisition unit includes a thermocouple sensor for acquiring temperature signals and a temperature transmitter for converting the temperature signals into 0-5v standard voltage signals or 4-20mA standard current signals; The dual sensor is correspondingly installed in the control partition inside the co-extrusion die head, and the output terminals of the temperature transmitter are respectively connected with the input terminals of the AD conversion circuit. In this preferred example, the thermocouple sensor can use a K-type thermocouple sensor with a measurement temperature range of 0-1300 °C, which can not only meet the requirements of the measurement range of 0-400 °C required for multi-layer co-extrusion die head temperature measurement, but also meet the measurement Accuracy ±1°C requirement.

Preferably, the driving heating unit includes a driving circuit for amplifying the output signal of the PWM circuit, a heating coil for heating, and a solid state relay for adjusting the power of the heating coil. Among them, the input voltage required by the heating coil is AC220V, which cannot be directly provided by the hardware control circuit, and the heating coil is indirectly controlled through the solid state relay. In this preferred embodiment, the SSR-40DA solid-state relay is used, and its input voltage range is 4 to 32VDC. However, the output voltage of the FPGA control module is 3.3V, which cannot directly drive the solid-state relay. It is necessary to add a driving circuit based on switching elements. The 3.3 The V signal is converted into a 24V voltage signal to ensure the normal operation of the solid state relay; this preferred example uses a 2N3904 triode, the maximum collector voltage is 60V, the maximum collector current is 200mA, the maximum base voltage is 6V, and the maximum base current is 100mA . In this preferred example, the heating ring can be made of single-piece or multi-piece ceramic heating ring or cast aluminum heating ring according to the diameter of the die head, and the power of the heating ring can be adjusted by switching on and off the solid state relay to realize the control of the temperature of the die head.

Among them, the implementation structure of single-channel temperature control is shown in Figure 3. The thermocouple sensor collects the temperature signal in one of the control partitions of the co-extrusion die, and performs voltage stabilization filtering, operational amplification, and nonlinear correction through the temperature transmitter. Wait for the circuit to process the conversion, input it to the AD conversion circuit and convert it into a digital signal and input it to the FPGA control chip, then output the PWM control value to the PWM output circuit, and finally output the control signal to amplify in the drive circuit to control the on-off of the solid-state relay. Thereby, the power of the heating coil in the corresponding control zone is adjusted, and the closed-loop adjustment and control of the temperature of the control zone is realized.

In this preferred example, the control panel connected to the FPGA temperature control module consists of a touch screen and buttons. The functions that can be realized include: sending and receiving temperature data, setting a given temperature, setting PID initial parameter values, different control The drawing of the actual temperature change curve of the partition and the storage and display of the temperature data.

Preferably, the FPGA temperature control module further includes a reset circuit for realizing a reset operation, a clock circuit for providing a reference clock, and an expansion interface for realizing data communication with a host computer. Among them, the FPGA control chip includes a ROM for storing fuzzy control tables and a processor for implementing programming PID logic control; ROM stores fuzzy control tables simulated by MATLAB tools and obtained offline calculations; The fuzzy PID control algorithm realized by description language realizes the integration of intelligent control algorithm on a single FPGA chip.

An intelligent temperature control method for a multi-layer co-extrusion die head of the present invention, based on the above preferred intelligent temperature control system, comprises the following steps:

a. System initialization, input the initial set temperature value and the initial parameter value of the fuzzy PID control algorithm through the control panel; if the initialization is completed, proceed to the next step, if the initialization is not completed, perform the initialization operation again until the initialization is completed.

b. Collect the temperature of the co-extrusion die head, and collect the temperature of the N control subregions in the co-extrusion die head by the temperature acquisition unit correspondingly, and obtain the temperature signal; preferably collect the co-extrusion die head through the thermocouple sensor in the temperature acquisition unit temperature, and through the temperature transmitter in the temperature acquisition unit, the temperature signal is converted into a 0-5v standard voltage signal or a 4-20mA standard current signal, and after filtering links including median filtering and mean filtering, if the acquisition is completed Then input the AD conversion circuit for AD conversion. If the acquisition is not completed, continue to collect the temperature until the acquisition is completed and output the standard voltage or current signal after the error is reduced by the filter link.

c. Adjustment of control output; realized by the fuzzy PID control algorithm, the temperature signal collected in step b is converted into a digital collection temperature value through the AD conversion circuit, and input into the FPGA control chip; according to the input collection temperature value and the set temperature value input in step a, the processor calculates the deviation e and the deviation change rate e _c , where e _c =de/dt; the fuzzy quantization of e and e _c obtains the coded values E, E _c , corresponding to The obtained E and E _c are obtained by calling the fuzzy control table in the ROM to obtain the correction values of the PID parameters △K _p , △K _i , △K _d , and calculating the PID input parameter values K _p , K _i combined with the initial PID parameter values , K _d ; output N-way parallel PID control quantities through incremental PID logic control; specifically, as shown in Figure 5, read the temperature data after AD conversion, calculate e in the current state, and read e ₁ and e ₂ , e ₁ is the deviation of the previous state, e ₂ is the deviation of the previous two states, combined with e in the current state, according to e _c =de/dt, calculate the e _c in the current state; Perform fuzzy quantization on the obtained precise values e and e _c to obtain coded values E and E _c , use the fuzzy inference process, that is, query the corresponding obtained E and E _c through the fuzzy control table in the ROM, and obtain the PID The correction amount of the parameter value △K _p , △K _i , △K _d , combined with the initial PID parameter value to calculate the PID input parameter value K _p , K _i , K _d , and output N parallel PID through incremental PID logic control The control quantity realizes online self-tuning; at the same time, the deviation of the current state and the deviation of the previous state in the step is replaced in turn by the deviation of the previous state as the read e ₁ and e ₂ when the next step is executed.

d. Control signal output, each PID control quantity outputs a control signal through the PWM output circuit, and the control signal output by a single channel corresponds to the driving heating unit; realizes intelligent control of the temperature of different control zones; specifically, the PWM output circuit controls Signal output, if the output is completed successfully, then realize the driving and heating control of the driving heating unit, if the output fails to complete, then continue to output the control signal until the output is completed successfully; in this preferred example, the PWM output signal is performed by driving the driving circuit in the heating unit After amplification, control the on-off of the solid-state relay in the driving heating unit, and then adjust the power of the corresponding heating coil to realize the intelligent control of the temperature of the control zone.

e. Steps b to d are repeated to realize intelligent control of the temperature adjustment of different control zones in the co-extrusion die when the set temperature value is changed. The single-path control process is shown in Figure 7. Through the circulation of the single-path control process, the intelligent control of the temperature adjustment of different control zones in the co-extrusion die is realized.

Preferably, in step c, the fuzzy control table is to use the Matlab tool to carry out Simulink simulation to the temperature mathematical model of the control partition, after determining the quantitative factor, the basic domain of discourse, and the fuzzy domain of discourse, the fuzzy control rule table is established according to expert experience and simulation debugging , which is obtained after performing fuzzy reasoning and defuzzification by the center of gravity method.

Concrete, in this preferred embodiment, at first obtain the step response curve of temperature in each control partition by field test, approximate system mathematical model, then adopt Matlab tool box and Simulink simulation tool to simulate system mathematical model; Simulation The steps include: first determine the structure of the fuzzy controller, the input and output language variables, the basic domain of discourse and the membership function; secondly, fuzzy quantify the deviation and the deviation change rate, establish a fuzzy control rule table, and obtain the fuzzy subset of the output variable; then Defuzzification is carried out by de-centering method to obtain the correction values of PID parameters △Kp, △Ki, △Kd, and the online self-tuning of PID parameters is input to the PID controller to obtain the PWM output control value.

On the basis of the feasibility of the simulation results, the fuzzy control table is obtained by querying the Matlab tool, and the control table is stored in the ROM of the FPGA control chip in the format of .mif, and the correction amount of PID parameters △Kp, △Ki, △Kd; through this off-line calculation and online look-up table method, the fuzzy control process can be simplified, the calculation amount of the FPGA control chip is greatly reduced, the speed of real-time system control is improved, the programming difficulty is reduced and the design cycle is shortened .

Further, the control partition is obtained by partitioning the temperature distribution of the co-extrusion die in a matrix manner, and its number N=(n+3)m, where n is the number of film layers of the product produced by the co-extrusion die, and m is The number of heating rings required for stacking disks in each layer, and the division structure of the control partitions in this preferred example are shown in FIG. 4 .

Claims (7)

1. a Multi-layer coextruding die head intelligent temperature control method, based on Multi-layer co-extrusion die head intelligent temperature control system, is characterized in that,

Described control system, comprises temperature collect module, FPGA temperature control modules, drives heating module and carries out the control panel of job information display for initialization system initial value;

Described temperature collect module comprises the N number of temperature collecting cell corresponding with the control partition of co-extrusion die head temperature;

Described FPGA temperature control modules comprises A/D converter circuit, for realizing the FPGA control chip of Fuzzy PID, and PWM output circuit;

Described driving heating module comprises and correspondingly with heater in control partition carries out temperature controlled N number of driving heating unit;

The temperature signal of control partition, in FPGA temperature control modules by the one or more parallel cascade of corresponding temperature collecting unit Gather and input, A/D converter circuit through correspondence is converted to data signal and exports N road PWM controlled quentity controlled variable through FPGA control chip process, each road PWM controlled quentity controlled variable by PWM output circuit respectively single channel output in corresponding driving heating unit;

Described FPGA control chip comprises the ROM for storing fuzzy control table and the processor for realizing the control of programming PID logic; Store in ROM by the emulation of MATLAB instrument and the fuzzy control table that obtains of off-line calculation, in processor, be solidified with the Fuzzy PID realized by hardware description language;

Described control method comprises the steps:

A. system initialization, inputs initial set temperature value and Fuzzy PID initial parameter value by control panel;

B. gather co-extrusion die head temperature, by temperature collecting cell to the temperature of control partition N number of in co-extrusion die head respectively correspondence gather, obtain temperature signal;

C. the adjustment of output quantity is controlled; Realized by Fuzzy PID, the temperature signal collected is converted to the collecting temperature value of digital quantity by A/D converter circuit, and is input in FPGA control chip in step b; According to the set temperature value inputted in the collecting temperature value inputted and step a, processor calculates deviation e and deviation variation rate e _c, wherein e _c=de/dt; By e and e _cfuzzy quantization draws encoded radio E, Ec, E and E that correspondence obtains _cthe correction △ K of pid parameter value is obtained through the fuzzy control table inquiry of calling in ROM _p, △ K _i, △ K _d, calculate PID input parameter value K in conjunction with PID initial parameter value _p, K _i, K _d; The parallel PID controlled quentity controlled variable in N road is exported by increment type PID logic control;

D. control signal exports, and every road PID controlled quentity controlled variable exports control signal through PWM output circuit, the driving heating unit that the control signal that single channel exports is corresponding respectively; Realize the Based Intelligent Control to different control partition temperature;

E. repeat step b ~ d, when the change of set temperature value, realize the Based Intelligent Control to temperature adjustment in different control partition in co-extrusion die head;

Described control partition obtains with the mode subregion of matrix by the Temperature Distribution of co-extrusion die head, its quantity N=(n+3) m, wherein the film number of plies of n produce to by co-extrusion die head product, and m is the every stacked heating collar number added needed for disc.

2. a kind of Multi-layer coextruding die head intelligent temperature control method according to claim 1, it is characterized in that, in step b, co-extrusion die head temperature is gathered by the thermocouple sensor in temperature collecting cell, and by the temperature transmitter in temperature collecting cell, temperature signal is converted to 0 ~ 5v standard voltage signal or 4 ~ 20mA standard current signal, and inputs A/D converter circuit after the filtering link comprising medium filtering and mean filter.

3. a kind of Multi-layer coextruding die head intelligent temperature control method according to claim 1, it is characterized in that, in step c, fuzzy control table uses the temperature Mathematical Modeling of Matlab instrument to control partition to carry out Simulink emulation, determining quantizing factor, basic domain, fuzzy domain, set up fuzzy control rule table according to expertise and artificial debugging, carry out fuzzy reasoning and inquiry obtains after adopting gravity model appoach ambiguity solution.

4. a kind of Multi-layer coextruding die head intelligent temperature control method according to claim 1, it is characterized in that, in steps d, after PWM output signal being amplified by driving the drive circuit in heating unit, control the break-make of the solid-state relay driven in heating unit, and then regulate the power of corresponding heating collar, realize the Based Intelligent Control to different control partition temperature.

5. a kind of Multi-layer coextruding die head intelligent temperature control method according to claim 1, it is characterized in that, described temperature collecting cell comprises for the thermocouple sensor of collecting temperature signal and the temperature transmitter for temperature signal being converted to 0 ~ 5v standard voltage signal or 4 ~ 20mA standard current signal; Thermocouple sensor correspondence is installed in the control partition of co-extrusion die head inside, and the output of temperature transmitter is connected with the input of A/D converter circuit respectively.

6. a kind of Multi-layer coextruding die head intelligent temperature control method according to claim 1, it is characterized in that, described FPGA temperature control modules also comprises the reset circuit for realizing reset operation, for providing the clock circuit of reference clock, and for realizing the expansion interface of data communication with host computer.

7. a kind of Multi-layer coextruding die head intelligent temperature control method according to claim 1, it is characterized in that, described driving heating unit comprises the drive circuit for amplifying pwm circuit output signal, for carrying out the heating collar heated, and for regulating the solid-state relay of heating collar power.