Partitioned heating plate temperature control method of plastic pipeline welding machine

Abstract

The invention discloses a partitioned heating plate temperature control method for a plastic pipeline welding machine, which comprises the following steps of: performing partitioned treatment on heating plate temperatures in different periods, and adopting different heating plate temperature control algorithms; therefore, the problems of low temperature rise efficiency, large temperature control error, limited generalization ability of a single temperature control algorithm and the like caused by the characteristics of large temperature target value of the heating plate of the welding machine, high temperature precision requirement, slow temperature change, uncertain environment temperature, adjustable temperature target value of the heating plate and the like are avoided.

Description

Technical Field

[0001] The invention relates to a temperature control method of a zoned heating plate of a plastic pipe welding machine. Background Art

[0002] Pipeline connections are divided into three types according to different principles: mechanical fixing connection, adhesive connection and welding. Compared with the other two connection methods, welding has the advantages of strong connection rigidity, long aging time and low cost, and has become the most widely used connection method for plastic pipes. Plastic welding can be divided into three categories according to the plastic heating method: thermal welding, friction welding and electromagnetic welding. Among them, hot melt welding in thermal welding is suitable for welding occasions with large parts, high pressure and high precision requirements.

[0003] At present, most of the research on hot-melt welding technology for plastic pipes is about welding process and welding quality detection. It is generally believed that temperature and pressure are the key factors affecting the quality of hot-melt welding, but there is little research on the implementation of its temperature control system. In addition, most of the current temperature control research in other scenarios is single algorithm temperature control, that is, to improve the control accuracy of a control algorithm by adding corresponding coefficients or optimizing corresponding parameters, but this optimization method will make the algorithm too complicated and the operating cost too high. In addition, the working environment of plastic pipe welding machines is complex and changeable. Working in different ambient temperatures indoors or outdoors will inevitably affect the control accuracy of the algorithm.

[0004] Based on this, in order to make up for the research gap in the direction of plastic pipe welding temperature control and improve the accuracy and generalization ability of the temperature control algorithm, and combined with the characteristics of large target value of the heating plate temperature of the welding machine, high temperature accuracy requirement, slow temperature change, uncertain ambient temperature and adjustable target value, the present invention proposes a partitioned heating plate temperature control method for a plastic pipe welding machine, performs fuzzy error partition control on the heating plate temperature, uses a more accurate control algorithm for different temperature change conditions, and improves the control accuracy and generalization ability through the thermal balance fuzzy PID control algorithm, thereby improving the welding efficiency and accuracy. Summary of the invention

[0005] The present invention provides a zoned heating plate temperature control method for a plastic pipe welding machine in order to solve the problems existing in the prior art.

[0006] The technical solutions adopted in the present invention are:

[0007] A temperature control method for a zoned heating plate of a plastic pipe welding machine comprises the following steps:

[0008] S1: Collect the heating plate temperature of the plastic pipe welding machine and the ambient temperature of the working area where the welding machine is located, and then use a composite digital filtering method to filter the collected heating plate temperature and ambient temperature data;

[0009] S2: The error between the temperature sampling value of the heating plate after the composite digital filtering and the voltage value corresponding to the set heating target value and the error change rate are fuzzy controlled, and a fuzzy error partition rule table of the partition results of the error and the error change rate is established. According to the fuzzy error partition rule table, it is determined which partition the heating plate temperature is in at this time, so that different temperature control algorithms are used in different heating plate temperature stages;

[0010] S3: dividing the temperature of the heating plate into a high error zone, a medium error zone and a low error zone according to the temperature partition result of the heating plate;

[0011] The hysteresis control algorithm is used in the high error area;

[0012] The integral separation PID control algorithm is adopted in the middle error zone;

[0013] The low error zone adopts a thermal balance fuzzy PID control algorithm, that is, the heating plate heat dissipation equation is introduced based on the fuzzy PID control algorithm and combined with the ambient temperature at this time, so that the actual temperature value of the heating plate approaches the set different heating target values ​​under different indoor or outdoor ambient temperatures.

[0014] Further, in S1, the composite digital filtering method is:

[0015] First, median filtering is used to remove the sampled values ​​that are biased due to pulse interference, and then arithmetic mean filtering is used to smooth the sampled values; the formula for composite digital filtering is as follows:

[0016]

[0017] Among them, median() means taking the median of a set of voltage values ​​corresponding to the ambient temperature and the heating plate temperature, i represents the window index, N is the median filter window size and is an odd number, M is the mean filter window size, V combined [t] is the voltage value corresponding to the filtered ambient temperature and the heating plate temperature.

[0018] Furthermore, in S2, the error between the temperature sampling value of the heating plate and the voltage value corresponding to the set heating target value is first calculated, and the error change rate is calculated according to the error value. The calculation formula is:

[0019] err(t)=V target [t]-V combined [t]

[0020]

[0021] Where err(t) represents the error value, V target [t] represents the voltage value corresponding to the heating target value set by the heating plate, V combined[t] represents the voltage value corresponding to the temperature sampling value of the heating plate after composite digital filtering;

[0022] errc(t) represents the error change rate, T s Indicates the sampling period, err(tT s ) represents the sample value after composite digital filtering at the previous moment;

[0023] The error and the error change rate are normalized, and the fuzzy subsets are determined according to the size of the error and the error change rate, which are: negative large (NB), negative medium (NM), negative small (NS), positive small (PS), positive medium (PM) and positive large (PB).

[0024] Furthermore, the formula for normalizing the error is:

[0025]

[0026] Among them, err(t)′ represents the normalized value, err min (t) represents the minimum error, err max (t) represents the maximum error value;

[0027] The error fuzzy subset can be obtained from the normalized result, and the formula is expressed as:

[0028]

[0029] Among them, err NB (t), err NM (t), err NS (t), err PS (t), err PM (t) and err PB (t) represent the corresponding subsets where the error is located at this time, namely, large negative, medium negative, small negative, small positive, medium positive and large positive.

[0030] Furthermore, the fuzzy error partition rule table can be obtained by combining the fuzzy subsets of error and error change rate in pairs. The formula is as follows:

[0031] h(err(t)′,errc(t)′)={(X,Y)|X

[0032] ∈(err NB (t), err NM (t), err NS (t), err PS (t), err PM (t), err PB (t), Y

[0033] ∈(errcNB (t)errc NM (t), errc NS (t), errc PS (t), errc PM (t), errc PB (t)}={Z|Z

[0034] ∈H,M,L}

[0035] Among them, h represents the fuzzy error partition rule table, H represents high error partition, M represents medium error partition, and L represents low error partition;

[0036] The error partition of each heating plate temperature change is obtained from the fuzzy error partition rule table, and the formula is as follows:

[0037]

[0038] Among them, f Bang_Bang represents the hysteresis control algorithm, f IS_PID represents the integral separation PID control algorithm, f Thermal_Fuzzy_PID Represents the thermal balance fuzzy PID control algorithm.

[0039] Furthermore, in S3, the high error region adopts the hysteresis control algorithm, and the formula is as follows:

[0040]

[0041] Where D is the PWM wave duty cycle, T pwm is the time for a complete cycle of the output square wave signal, f Bang_Bang represents the hysteresis control algorithm;

[0042] T on_pwm is the time that the output square wave signal is at a high level in one cycle, a represents the PWM duty cycle control coefficient, 0 <a<1。

[0043] Furthermore, in S3, when the temperature of the heating plate enters the medium error zone, an integral separation PID control algorithm is adopted, that is, the integral term is removed based on the original PID control algorithm, and the formula is expressed as:

[0044]

[0045] Where t is the sampling sequence number, err(t) is the sampling error of the heating plate temperature at the tth time, err(t-1) is the sampling error of the heating plate temperature at the t-1th time, that is, the last sampling error, K p is the proportional term coefficient, K d is the differential coefficient.

[0046] Furthermore, in S3, when the temperature of the heating plate enters the low error zone, the heat dissipation equation of the heating plate is introduced into the traditional fuzzy PID control algorithm to form a thermal balance fuzzy PID control, and the heat dissipation equation of the heating plate is obtained by Newton's cooling law to meet the temperature control requirements under different indoor or outdoor ambient temperatures and target values;

[0047] The heat dissipation equation of the heating plate is:

[0048] Q=h*A*(T h -T a )

[0049] Among them, Q represents the heat dissipated per unit time, h represents the heat dissipation coefficient of the heating plate surface, A represents the surface area of ​​the heating plate, T h Indicates the heating plate temperature, T a Indicates the ambient temperature.

[0050] Furthermore, the control formula of the thermal balance fuzzy PID control is:

[0051] u(t)=m0Q+(K p0 +k1ΔK p +m1Q)err(t)+(K i0 +k2ΔK i +m2Q)∑err(t)+(K d0

[0052] +k3ΔK d +m3Q)(err(t)-err(t-1))

[0053]

[0054] Among them, K p0 , K i0 and K d0 is the initial value of the thermal balance fuzzy PID control, k1, k2 and k3 are proportional factors, Q is the heat dissipated by the heating plate per unit time, and m0, m1, m2 and m3 are the proportional factors of heat dissipation.

[0055] The present invention has the following beneficial effects:

[0056] The present invention partitions the temperature of the heating plate at different times and adopts different heating plate temperature control algorithms to avoid the problems of low heating efficiency, large temperature control error and limited generalization ability of a single temperature control algorithm caused by the characteristics of the welding machine heating plate having a large temperature target value, high temperature accuracy requirement, slow temperature change, uncertain ambient temperature and adjustable heating plate temperature target value. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Figure 1 It is a control strategy flow chart of the present invention.

[0058] Figure 2 This is a hardware circuit schematic diagram of the control strategy application of the present invention.

[0059] Figure 3 is the fuzzy error partition rule graph.

[0060] Figure 4 This is the principle block diagram of thermal balance fuzzy PID control.

[0061] Figure 5 This is the simulation result diagram.

[0062] Figure 6 This is a real picture of the polyethylene pipe welding effect. DETAILED DESCRIPTION

[0063] The present invention will be further described below in conjunction with the accompanying drawings.

[0064] The present invention is used for the following heating plate temperature control circuit:

[0065] The temperature control circuit of the welding machine heating plate is based on STM32 as the main control chip. The real-time temperature information is obtained through the temperature signal acquisition module, and the temperature change of the heating plate is realized through the heating plate temperature execution module.

[0066] The temperature signal acquisition module includes heating plate temperature signal acquisition and ambient temperature signal acquisition. The heating plate temperature signal acquisition is based on the AD8496 chip, which performs signal amplification, cold end compensation, and nonlinear calibration on the voltage signal output by the heating plate temperature sensor collected by the thermocouple sensor, thereby generating a linear output of 5mV / °C. The ambient temperature signal acquisition uses the DS18B20 sensor to directly read the ambient temperature using the single bus protocol. For the heating plate temperature execution module, the conduction of the metal-oxide semiconductor field effect transistor (MOSFET, MOS) is controlled by outputting a PWM wave to further control the on and off of the solid-state relay, thereby indirectly controlling the power supply time of the heating plate to complete the control of the heating plate temperature. The specific implementation circuit schematic diagram is shown below. Figure 2 shown.

[0067] like Figure 1 The present invention provides a temperature control method for a zoned heating plate of a plastic pipe welding machine, comprising the following steps:

[0068] S1: Perform composite digital filtering on the read temperature signal. First, perform median filtering on the voltage corresponding to the sampled heating plate temperature and ambient temperature to remove other random noises such as salt and pepper noise in the sampled signal. Perform arithmetic mean filtering on the result obtained by median filtering to smooth the sampled value.

[0069] The formula for composite digital filtering is as follows:

[0070]

[0071] Among them, median() means taking the median of a set of voltage values ​​corresponding to the ambient temperature and the heating plate temperature, i represents the window index, N is the median filter window size and is an odd number, M is the mean filter window size, V combined [t] is the voltage value corresponding to the filtered ambient temperature and the heating plate temperature.

[0072] S2: The error between the temperature sampling value of the heating plate after the composite digital filtering and the voltage value corresponding to the set heating target value and the error change rate are fuzzy controlled, and a fuzzy error partition rule table of the partition results of the error and the error change rate is established. According to the fuzzy error partition rule table, it is determined which partition the heating plate temperature is in at this time, so that different temperature control algorithms are used in different heating plate temperature stages;

[0073] First, find the error between the temperature sampling value of the heating plate and the voltage value corresponding to the set heating target value, and calculate the error change rate based on the error value. The calculation formula is:

[0074] err(t)=V target [t]-V combined [t]

[0075]

[0076] Where err(t) represents the error value, V target [t] represents the voltage value corresponding to the heating target value set by the heating plate, V combined [t] represents the voltage value corresponding to the temperature sampling value of the heating plate after composite digital filtering;

[0077] errc(t) represents the error change rate, T s Indicates the sampling period, err(tT s ) represents the sample value after composite digital filtering at the previous moment;

[0078] At this time, the error and error change rate are normalized, and the fuzzy subsets are determined according to the size of the error and the error change rate, which correspond to: negative large (NB), negative medium (NM), negative small (NS), positive small (PS), positive medium (PM) and positive large (PB). At this time, the case where the error and the error change rate are 0 is omitted in combination with the actual situation and to reduce the amount of calculation.

[0079] The error normalization formula is as follows:

[0080]

[0081] Among them, err(t)′ represents the normalized value, err min (t) represents the minimum error, err max (t) represents the maximum error; the same is true for the error change rate.

[0082] The mis-fuzzy subset can be obtained from the normalized result, and the formula is as follows:

[0083]

[0084] Among them: err NB (t), err NM (t), err NS (t), err PS (t), err PM (t) and err PB (t) represent the corresponding subsets where the error is located at this time, namely, large negative, medium negative, small negative, small positive, medium positive and large positive.

[0085] The fuzzy error partition rule table can be obtained by combining the fuzzy subsets of error and error change rate. The formula is as follows:

[0086] h(errr(t)′,errc(t)′)={(X,Y)|X

[0087] ∈(err NB (t), err NM (t), err NS (t), err PS (t), err PM (t), err PB (t), Y

[0088] ∈(errc NB (t)errc NM (t), errc NS (t), errc PS (t), errc PM (t), errc PB (t)}

[0089] ={Z|Z∈H,M,L}

[0090] Among them: h represents the fuzzy error partition rule table, H represents high error partition, M represents medium error partition, and L represents low error partition.

[0091] The error partition of each heating plate temperature change is obtained from the fuzzy error partition rule table, and the formula is as follows:

[0092]

[0093] Where: f Bang_Bang represents the hysteresis control algorithm, f IS_PID represents the integral separation PID control algorithm, f Thermal_Fuzzy_PID Represents the thermal balance fuzzy PID control algorithm.

[0094] Based on the fuzzy subset, a fuzzy error partition rule table for the partition results of errors and error change rates is established. The fuzzy error partition rule table is as follows: Figure 3 As shown, when the error is large, it is uniformly determined to be a high error area. At this time, the hysteresis control algorithm is used to increase the heating plate temperature rise rate to reduce the response time.

[0095] When the error is negative and small, it is uniformly determined to be a low error area. At this time, thermal balance fuzzy PID control is used to improve control accuracy.

[0096] When the error is negative and the error change rate is negative and large, it is determined to be the medium error zone, and coarse adjustment is performed using the integral separation PID algorithm.

[0097] It should be noted that the actual values ​​of the error and error change rate corresponding to the fuzzy processing subset at this time are completely different from the actual values ​​of the error and error change rate in the high error partition. And the control output is also different. The fuzzy error partition control algorithm outputs the temperature partition result, while the fuzzy control in the high error partition outputs ΔK p , ΔK i and ΔK d .

[0098] S3: Combined with this temperature control strategy, the sampling value is partitioned and controlled according to the result of the heating plate temperature error partition operation. When the heating plate temperature enters the high error zone, since the actual value is far from the target value, the heating plate temperature rise rate can be maximized under certain conditions to reduce the response time, that is, the hysteresis control algorithm is adopted. The formula is as follows:

[0099]

[0100] Where D is the PWM wave duty cycle, T pwm is the time for a complete cycle of the output square wave, f Bang_Bang Represents the hysteresis control algorithm.

[0101] T on_pwm is the time that the output square wave is at a high level in one cycle, and a represents the PWM duty cycle control coefficient (0 <a<1)。

[0102] In order to improve the heating time, full duty cycle heating is theoretically required in the high error area. However, combined with the actual situation such as the rated power of the heating plate, it is necessary to introduce the PWM wave duty cycle control coefficient to complete the transition of the algorithm from theoretical calculation to practical application.

[0103] When the temperature of the heating plate enters the medium error zone, the hysteresis control is no longer suitable for the temperature control of the heating plate at this time. Since the heating power of the welding machine heating plate is limited, and there is a certain deviation between the actual value and the target value at this time, if the conventional PID control algorithm is directly used, the system error will continue to accumulate in one direction, and the integral term will continue to accumulate, resulting in integral saturation and overshoot. The integral separation PID control algorithm is now used, that is, the integral term is removed based on the original PID control algorithm. The formula is expressed as follows:

[0104]

[0105] Where t is the sampling sequence number, err(t) is the sampling error of the heating plate temperature at the tth time, err(t-1) is the sampling error of the heating plate temperature at the t-1th time, that is, the last sampling error, K p is the proportional term coefficient, K d is the differential coefficient.

[0106] When the temperature of the heating plate enters the low error zone, the temperature control of the heating plate needs to be fine-tuned to meet the temperature control accuracy requirements of the welding machine. At this time, the temperature control accuracy of the heating plate can be improved by increasing the algorithm calculation cost.

[0107] Based on the traditional fuzzy PID control, the heat dissipation equation of the heating plate is introduced to form thermal balance fuzzy PID control. That is, for the heating plate at different target temperatures and indoor or outdoor ambient temperatures, the heat dissipation equation of the heating plate is obtained by Newton's cooling law to meet the temperature control requirements under different indoor or outdoor ambient temperatures and target values, and improve the generalization ability of fuzzy control.

[0108] The heat dissipation equation of the heating plate is:

[0109] Q=h*A*(T h -T a )

[0110] Where Q represents the heat dissipated per unit time, h represents the heat dissipation coefficient of the heating plate surface, A represents the surface area of ​​the heating plate, T h Indicates the heating plate temperature, T a Indicates the ambient temperature.

[0111] In addition, the input of the thermal balance fuzzy PID controller is the error err(t) and error change rate errc(t) between the actual value of the heating plate temperature and the target value of the heating plate temperature. After fuzzification, fuzzy reasoning after ambient temperature correction and clarification, the three parameter adjustment values ​​ΔK of PID are output. p , ΔK i and ΔK d, then multiplied by the corresponding proportional factor and superimposed into the PID controller, and the temperature correction coefficient composed of the heat emitted by the heating plate and the proportional factor is added to ensure that when the error and the error change rate are both 0, the PWM output ratio is 0, resulting in temperature instability.

[0112] Thermal balance fuzzy PID control principle diagram Figure 4 As shown. The formula for thermal balance fuzzy PID control is:

[0113] u(t)=m0Q+(K p0 +k1ΔK p +m1Q)err(t)+(K i0 +k2ΔK i +m2Q)∑err(t)+(K d0

[0114] +k3ΔK d +m3Q)(err(t)-err(t-1))

[0115]

[0116] Among them, K p0 , K i0 and K d0 is the initial value of the PID controller, k1, k2 and k3 are proportional factors, Q is the heat dissipated by the heating plate per unit time, and m0, m1, m2 and m3 are proportional factors for heat dissipation. It should be noted that the PID control algorithm used in the low error zone is not the integral separation PID algorithm used in the medium error zone, that is, two sets of completely parallel PID parameters that do not affect each other. And when the temperature exits the corresponding error partition, its algorithm parameters are retained until it returns again.

[0117] The MATLAB simulation analysis and actual welding effect of the present invention are as follows:

[0118] For MATLAB simulation, according to the above heating plate temperature control strategy, the feasibility and superiority of the zoned heating plate temperature control strategy are verified by adding corresponding component modules, in which the traditional PID control strategy is used for comparative analysis. The simulation output results of the zoned heating plate temperature control strategy are as follows: Figure 5 As shown, from Figure 5 It can be seen that for the zoned heating plate temperature control strategy, the hysteresis control algorithm is used in the high error zone to shorten the initial response time of the heating plate temperature control. The integral separation PID control algorithm is used in the medium error zone to avoid the overshoot phenomenon caused by integral saturation. The thermal balance fuzzy PID control algorithm is used in the low error zone to make the heating plate temperature more accurately controlled under different indoor or outdoor ambient temperatures and target values.

[0119] Finally, this zoned heating plate temperature control strategy was applied to the actual welding machine, and the polyethylene pipe was hot-melt welded in combination with the pressure control in the welding control system. The welding effect is shown in the figure below. Figure 6 As shown. Figure 6 It can be seen that the welding effect meets the non-destructive inspection requirements for welded pipes in GB / T 32434-2015 "Plastic pipes and fittings - Procedure for connecting polyethylene (PE) pipes and fittings for gas and water distribution systems".

[0120] The above description is only a preferred embodiment of the present invention. It should be pointed out that a person skilled in the art can make several improvements without departing from the principle of the present invention, and these improvements should also be regarded as within the protection scope of the present invention.

Claims

1. A zoned heating plate temperature control method for a plastic pipe welding machine, characterized in that: The steps include: S1: Collect the heating plate temperature of the plastic pipe welding machine and the ambient temperature of the working area where the welding machine is located, and then use a composite digital filtering method to filter the collected heating plate temperature and ambient temperature data; S2: The error between the temperature sampling value of the heating plate after the composite digital filtering and the voltage value corresponding to the set heating target value and the error change rate are fuzzy controlled, and a fuzzy error partition rule table of the partition results of the error and the error change rate is established. According to the fuzzy error partition rule table, it is determined which partition the heating plate temperature is in at this time, so that different temperature control algorithms are used in different heating plate temperature stages; S3: dividing the temperature of the heating plate into a high error zone, a medium error zone and a low error zone according to the temperature partition result of the heating plate; The high error area adopts the hysteresis control algorithm; The integral separation PID control algorithm is adopted in the middle error zone; The low error zone adopts a thermal balance fuzzy PID control algorithm, that is, the heating plate heat dissipation equation is introduced based on the fuzzy PID control algorithm and combined with the ambient temperature at this time, so that the actual temperature value of the heating plate approaches the set different heating target values ​​under different indoor or outdoor ambient temperatures.

2. The temperature control method of the zoned heating plate of the plastic pipe welding machine according to claim 1, characterized in that: In S1, the composite digital filtering method is: First, median filtering is used to remove the sampled values ​​that are biased due to pulse interference, and then arithmetic mean filtering is used to smooth the sampled values; the formula for composite digital filtering is as follows: Among them, median() means taking the median of a set of voltage values ​​corresponding to the ambient temperature and the heating plate temperature, i represents the window index, N is the median filter window size and is an odd number, M is the mean filter window size, V combined [t] is the voltage value corresponding to the filtered ambient temperature and the heating plate temperature.

3. The temperature control method of the zoned heating plate of the plastic pipe welding machine according to claim 1, characterized in that: In S2, the error between the temperature sampling value of the heating plate and the voltage value corresponding to the set heating target value is first calculated, and the error change rate is calculated according to the error value. The calculation formula is: Where err(t) represents the error value, V target [t] represents the voltage value corresponding to the heating target value set by the heating plate, V combined [t] represents the voltage value corresponding to the temperature sampling value of the heating plate after composite digital filtering; errc(t) represents the error change rate, T s Indicates the sampling period, err(tT s ) represents the sample value after composite digital filtering at the previous moment; The error and the error change rate are normalized, and the fuzzy subsets are determined according to the size of the error and the error change rate, which are: negative large (NB), negative medium (NM), negative small (NS), positive small (PS), positive medium (PM) and positive large (PB).

4. The temperature control method of the zoned heating plate of the plastic pipe welding machine according to claim 3, characterized in that: The formula for normalizing the error is: Among them, err(t)′ represents the normalized value, err min (t) represents the minimum error, err max (t) represents the maximum error value; The error fuzzy subset can be obtained from the normalized result, and the formula is expressed as: Among them, err NB (t), err NM (t), err NS (t), err PS (t), err PM (t) and err PB (t) represent the corresponding subsets where the error is located at this time, namely, large negative, medium negative, small negative, small positive, medium positive and large positive.

5. The temperature control method of the zoned heating plate of the plastic pipe welding machine according to claim 4, characterized in that: The fuzzy error partition rule table can be obtained by combining the fuzzy subsets of error and error change rate. The formula is as follows: h(err(t)′,errc(t)′)={(X,Y)|X ∈(err NB (t),err NM (t),err NS (t),err OS (t),err OM (t),err PB (t),Y∈(errc NB (t)errc NM (t),errc NS (t),errc PS (t),errc PM (t),errc PB (t)}={Z|Z∈H,M,L} Among them, h represents the fuzzy error partition rule table, H represents high error partition, M represents medium error partition, and L represents low error partition; The error partition of each heating plate temperature change is obtained from the fuzzy error partition rule table, and the formula is as follows: Among them, f Bang_Bang represents the hysteresis control algorithm, f IS_PID represents the integral separation PID control algorithm, f Thermal_Fuzzy_PID Represents the thermal balance fuzzy PID control algorithm.

6. The temperature control method of the zoned heating plate of the plastic pipe welding machine according to claim 1, characterized in that: In S3, the high error area adopts the hysteresis control algorithm, and the formula is as follows: Where D is the PWM wave duty cycle, T pwm is the time for a complete cycle of the output square wave signal, f Bang_Bang represents the hysteresis control algorithm; T on_pwm is the time that the output square wave signal is at a high level in one cycle, a represents the PWM duty cycle control coefficient, 0 <a<1。 7. The temperature control method of the zoned heating plate of the plastic pipe welding machine according to claim 1, characterized in that: In S3, when the temperature of the heating plate enters the medium error zone, the integral separation PID control algorithm is adopted, that is, the integral term is removed based on the original PID control algorithm, and the formula is expressed as: Where t is the sampling sequence number, err(t) is the sampling error of the heating plate temperature at the tth time, err(t-1) is the sampling error of the heating plate temperature at the t-1th time, that is, the last sampling error, K p is the proportional term coefficient, K d is the differential coefficient.

8. The temperature control method of the zoned heating plate of the plastic pipe welding machine according to claim 1, characterized in that: In S3, When the temperature of the heating plate enters the low error zone, the heat dissipation equation of the heating plate is introduced into the traditional fuzzy PID control algorithm to form a thermal balance fuzzy PID control. The heat dissipation equation of the heating plate is obtained through Newton's cooling law to meet the temperature control requirements under different indoor or outdoor ambient temperatures and target values; The heat dissipation equation of the heating plate is: Q=h*A*(T h -T a ) Among them, Q represents the heat dissipated per unit time, h represents the heat dissipation coefficient of the heating plate surface, A represents the surface area of ​​the heating plate, T h Indicates the heating plate temperature, T a Indicates the ambient temperature.

9. The temperature control method of the zoned heating plate of the plastic pipe welding machine according to claim 8, characterized in that: The control formula of the thermal balance fuzzy PID control is: u(t)=m0Q+(K p0 +k1ΔK p +m1Q)err(t)+(K i0 +k2ΔK i +m2Q)∑err(t)+(K d0 +k3ΔK d +m3Q)(err(t)-err(t-1)) Among them, K p0 , K i0 and K d0 is the initial value of the thermal balance fuzzy PID control, k1, k2 and k3 are proportional factors, Q is the heat dissipated by the heating plate per unit time, and m0, m1, m2 and m3 are the proportional factors of heat dissipation.

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