JP3234099B2 - Vulcanizer mold temperature controller - Google Patents

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a temperature control apparatus which is preferably used for controlling the temperature of a rubber vulcanizer, for example.

[0002]

2. Description of the Related Art Vulcanization of rubber or the like is carried out by charging a material to be vulcanized into a mold and heating the mold with a hot plate. In this vulcanization treatment, temperature conditions such as a heating temperature of the material to be vulcanized, a variation in the heating temperature, and a heating time are very important. Therefore, as a temperature control method of a vulcanizer, various methods have been tried conventionally. In a general vulcanizer temperature control method, a temperature sensor detects the temperature of a heater or a hot platen, calculates a deviation between the detected temperature and a preset temperature, and controls the heater based on the deviation. The amount is determined and the heater is controlled. In determining the heater control amount, an example in which PID control or fuzzy control is applied is also known.

[0003]

However, even in such a temperature control method, it was difficult to prevent the temperature from fluctuating, and it was difficult to control the temperature with a small error according to the set conditions. In particular, when the vulcanizer is switched from the standby state to the vulcanized state, or when the vulcanizer is switched from the vulcanized state to the standby state, the temperature is maintained in a steady state, or a predetermined temperature. It was difficult to follow. Therefore, in such a temperature control method, there is a problem that a homogeneous and high-quality vulcanizate is hardly generated.

Accordingly, an object of the present invention is to reduce the disturbance in the vulcanization temperature even when the state of the vulcanizer is switched from the standby state to the vulcanization state, or from the vulcanization state to the standby state. Another object of the present invention is to provide a vulcanizer-type temperature control device which can quickly restore a disturbance temperature to a set temperature.

[0005]

In order to solve the above problem, the inventor of the present invention controls the heater by detecting a slow response temperature, taking into consideration that the response time is limited, and taking some other measures into consideration. A change in temperature was estimated by means, and a method of controlling the heater in advance based on the estimation was examined.

The vulcanizer mold temperature control device according to the present invention comprises: a hot plate temperature sensor for detecting a temperature of a hot plate; a means for calculating a deviation between the hot plate temperature and a predetermined hot plate set temperature; Means for detecting that the state of the vulcanizer has changed, means for correcting the deviation based on the detection result, means for determining the operation amount of the heater based on the corrected deviation, and operation of the operation Means for controlling the heater based on the amount. Preferably, the vulcanizer mold temperature control device includes means for detecting a time change in the temperature of the hot platen, a mold temperature sensor for detecting a temperature of the mold of the vulcanizer, and a mold temperature which is predetermined. Means for calculating a deviation from the mold set temperature, means for detecting a time change of the mold temperature, and means for calculating a correction amount of the hot platen set temperature based on the mold temperature deviation and the time change. The means for correcting the deviation is a correction means for further performing the correction using the correction amount of the hot platen set temperature, and the means for determining the operation amount of the heater is the corrected deviation And a means for determining the operation amount of the heater based on the time change of the temperature of the hot platen.

[0007] More specifically, the means for detecting that the state of the vulcanizer has been switched includes a control means for decoding a control signal of a control device for operating the vulcanizer to detect a change in the state. Means. More specifically, the means for detecting that the state of the vulcanizer has been switched is a detecting means for detecting an operation of an operation switch for operating the vulcanizer and detecting a change in the state. More specifically, the means for detecting that the state of the vulcanizer has been switched is provided based on a signal from a switch provided to input that the state of the vulcanizer has been switched. It is a detecting means for detecting a change. Preferably, the method of obtaining the correction amount of the hot platen set temperature and the method of determining the operation amount of the heater are performed by executing fuzzy inference using a predetermined fuzzy rule and a membership function.

[0008]

The vulcanizer mold temperature control apparatus of the present invention detects that the vulcanizer has switched from the standby state to the vulcanized state or vulcanized state to the standby state, and switches the state. The temperature deviation value, which is the basis for determining the heater operation amount, is corrected immediately at the time point when is detected. This is equivalent to predicting the effect of switching the state on the temperature and taking a countermeasure. Therefore, since the operation is performed after detecting a slow temperature change in response, it is possible to prevent a situation in which control cannot be performed quickly or a temperature fluctuates due to excessive operation, that is, a so-called overshoot or undershoot state. , Appropriate temperature control becomes possible.

[0009]

DESCRIPTION OF THE PREFERRED EMBODIMENTS First Embodiment A first embodiment of a vulcanizer mold temperature control apparatus according to the present invention is shown in FIGS.
This will be described with reference to FIG. FIG. 1 is a configuration diagram of a vulcanizer using a mold temperature control device according to a first embodiment of the present invention. The vulcanizer includes a vulcanizing section 10 and a mold temperature controller 20. The vulcanizing section 10 includes an upper mold 12, a lower mold 13, an upper hot platen 14, and a lower hot platen 15. The mold temperature control device 20 includes a hot platen temperature sensor 21, a temperature deviation calculation unit 2
3, state change detection unit 25, correction amount determination unit 26, correction unit 3
3, an operation amount determination unit 34 and a control unit 35.

First, the structure of the vulcanizing section 10 will be described. The material to be vulcanized is charged between the upper mold 12 and the lower mold 13. When the upper and lower dies 12 and 13 are clamped, a cavity 11 is formed inside the mold, and the cavity 11 is formed.
The object to be vulcanized is appropriately shaped into a desired shape while being subjected to a vulcanization treatment. The upper mold 12 and the lower mold 13 are
Upper heating plate 14 and lower heating plate 1 having a heater (not shown) inside
5 respectively. The upper mold 12 and the lower mold 13 are further heated by the upper heating plate 14 and the lower heating plate 15 heated by the heater, and vulcanization is performed. Inside the upper hot platen 14, a hot platen temperature sensor 21 of the mold temperature control device 20 is embedded. The heater is controlled by a control unit 35 of the mold temperature control device 20. Control unit 3 of the present embodiment
5 is an O which interrupts the power supply to the heater at an appropriate cycle.
N-OFF control is performed. Therefore, the amount of heat generated by the heater is controlled by the ON-OFF time ratio of the heater, that is, the so-called duty ratio.

Next, the operation of each part of the mold temperature control device 20 will be described. The hot platen temperature sensor 21 is provided in the vulcanizing section 1
The sensor is embedded in the upper heating plate 14 and detects the temperature th of the heating plate. The detected temperature th of the hot plate can be read from the temperature deviation calculator 23 at any time. The temperature deviation calculation unit 23 calculates a deviation δ between the temperature of the hot platen detected by the hotplate temperature sensor 21 and a preset temperature of the hot platen Th.
1 is calculated by Expression 1 and output to the correction amount determination unit 26 and the correction unit 33.

[0012]

(Equation 1)

The state change detecting section 25 detects that the vulcanizing section 10 has switched from the vulcanized state to the standby state, or has switched from the standby state to the vulcanized state, and indicates that the state has been switched. The signal S is output to the correction amount determining unit 26.
Various methods can be considered as a method of detecting the change of the state depending on the operation mode of the vulcanizer. For example, when the vulcanizer is controlled and automatically operated by a control unit of the entire vulcanizer (not shown), a signal indicating vulcanization start and vulcanization end of the control unit is decoded to generate a signal S. Is preferred. When a series of vulcanization processes are performed manually by an operator, the signal S is generated in conjunction with a vulcanization start / stop switch provided on an operation unit for operating the vulcanizer. It is desirable to use a simple configuration. Further, regardless of the operation mode of the vulcanizer, a method may be used in which an operator operates a signal generation switch to generate the signal S.

The correction amount determining section 26 includes a state change detecting section 25.
When the signal S indicating the state change is input,
Temperature deviation δ of hot platen calculated by temperature deviation calculation unit 23
1, a correction amount δ2 for the temperature deviation of the hot platen is determined with reference to Table 1, and output to the correction unit 33. The correction amount δ2 is output for a predetermined period after the input of the signal S, and after the elapse of the period, the correction amount 0 is output.

[0015]

[Table 1]

The correction unit 33 corrects the temperature deviation δ1 of the hot platen calculated by the temperature deviation calculation unit 23 based on the correction amount δ2 determined by the correction amount determination unit 26 according to Equation 2, and the correction result Of the operation amount determination unit 34
Output to

[0017]

(Equation 2)

The operation amount determination unit 34 determines the heater operation amount α by fuzzy inference based on the corrected temperature deviation δ3 of the hot platen calculated by the correction unit 33, and controls the control unit 35.
Output to 2 and 3 show the fuzzy inference method.
This will be described with reference to FIG. FIG. 2 is a graph showing a membership function of the fuzzy inference, wherein (A) shows a membership function of a temperature deviation of a hot platen, and (B) shows a membership function of an operation amount of a duty ratio of a heater. First, from the corrected temperature deviation δ3 of the hot platen calculated by the correction unit 33, NL and NL are calculated by the membership function shown in FIG.
The suitability μ1 to μ7 for each fuzzy set using NM, NS, ZR, PS, PM, and PL as labels are obtained.

Each of the fuzzy labels is NL
(Negative large), NM (negative medium), NS (negative small), ZR (zero),
It means PS (positive small), PM (positive medium), and PL (positive large). The fitness levels μ1 to μ7 are membership values of the membership functions of the respective fuzzy sets, and are obtained by Expression 3 when the membership functions are A1 to A7, respectively.

[0020]

(Equation 3)

Next, based on the fuzzy control rules shown in Table 2, the degree of conformity μ1 to the condition of the antecedent part of each rule is obtained.
Based on μ7, the fitness ω1 to ω7 of each fuzzy set in the consequent is obtained.

[0022]

[Table 2]

Since the fuzzy inference of the present embodiment has one input and one output, the conformity of the antecedent part becomes the conformity of the consequent part as it is as shown in Expression 4.

[0024]

(Equation 4)

Then, the entire inference is performed based on the membership function of the consequent part and each of the fitness levels ω1 to ω7. This inference method will be described with reference to FIG. FIG. 3 is a diagram for explaining how to obtain an inference result. First, for each membership function in the consequent part, each fitness ω1 to ω7
Create a new membership function with the top removed from the value of. For example, as shown in FIG. 3, when both the fitness ω4 of the consequent part and the fitness ω5 of the PS are 0.5 and all the other fitnesses are 0, the membership function whose top is cut off is Functions 51 and 52 are obtained. next,
An overall membership function obtained by combining the membership functions is obtained. The hatched area in FIG. 3 is the combined membership function. Then, the center of gravity 53 of the entire membership function is used as the inference result.

The determination of the operation amount in the operation amount determination section 34 will be specifically described. The corrected temperature deviation δ3 of the hot platen calculated by the correction unit 33 is, for example, −2.
Assume that the temperature was 5 ° C. Thereby, referring to the membership function of FIG. 2A, this −2.5 ° C. is added to the fuzzy set NS and the fuzzy set ZR by 0.5, respectively.
Fit. Referring to the fuzzy rules in Table 2 as an antecedent, as a consequent, the fuzzy set PS and the fuzzy set ZR each conform to 0.5. Therefore, the tops of the membership functions PS and ZR shown in FIG. 2B are cut off at 0.5, and the entire membership function as shown in FIG. 3 is obtained. And from this center of gravity +
An operation amount of 2.5% is obtained. The value of this inference result is
The heater operation amount α is output to the control unit 35.

In the control unit 35, an operation amount determination unit 34
A new duty ratio is determined on the basis of the increase / decrease value α of the heater duty ratio, which is the heater operation amount determined by the above, and the heaters embedded in the upper heating plate 14 and the lower heating plate 15 are turned ON in accordance with the duty ratio. OFF control.

As described above, in this embodiment, the switching of the state of the vulcanizer is detected, the heater operation amount is immediately determined based on the temperature deviation of the hot platen at that time, and the temperature is controlled. . In other words, the control is performed by predicting the temperature change before the influence of the switching of the vulcanizer appears as the temperature change. Therefore, a stable mold temperature control device with little temperature variation can be realized.

Second Embodiment A second embodiment of a vulcanizer mold temperature control apparatus according to the present invention is shown in FIGS.
This will be described with reference to FIG. The mold temperature control device of the vulcanizer of the second embodiment is similar to the mold temperature control device of the vulcanizer of the first embodiment,
Means for detecting the time change of the temperature of the hot platen, the deviation of the temperature of the mold, and the time change of the temperature of the mold are further provided, and the temperature control is performed by referring to the respective data. FIG.
It is a block diagram of a vulcanizer using a mold temperature control device of a second embodiment of the present invention. This vulcanizer includes a vulcanizing section 10 and a mold temperature controller 40. The structure of the vulcanizing section 10 is such that the mold temperature sensor 2 of the mold temperature control device 40 is provided in the upper mold 12.
7 is the same as the first embodiment, except that 7 is embedded. The mold temperature controller 40 includes a temperature change detector 24 and a mold temperature sensor 2 in addition to the mold temperature controller 20 of the first embodiment.
7, a temperature deviation calculating unit 29, a temperature change detecting unit 30, a second correction amount determining unit 31, and a correction amount totalizing unit 32.

The operation of each part of the mold temperature control device 40 will be described. Hot platen temperature sensor 21, temperature deviation calculator 23,
The operations of the state change detection unit 25 and the correction amount determination unit 26 are the same as those in the first embodiment. Temperature change detector 2
4 is based on the temperature th of the hot plate detected by the hot plate temperature sensor 21 and the temperature th-1 of the hot plate stored in the temperature change detection unit 24 a predetermined time ago, and is expressed by the following equation (5). The time change Δ1 of the temperature of the panel is detected and output to the manipulated variable determiner 36.

[0031]

(Equation 5)

The mold temperature sensor 27 is embedded in the upper mold 12 of the vulcanizing section 10 and detects the mold temperature tm. The detected mold temperature tm is calculated by a temperature deviation calculator 29,
Further, it can be read from the temperature change detection unit 30 at any time. The temperature deviation calculator 29 calculates a mold temperature tm detected by the mold temperature sensor 27 and a preset mold temperature Tm.
Is calculated by Equation 6 and output to the second correction amount determination unit 31.

[0033]

(Equation 6)

The temperature change detecting section 30 includes a mold temperature sensor 27
The temperature tm of the mold detected by the
Based on the temperature tm-1 of the hot platen a fixed time before stored in the table, the time change Δ2 of the mold temperature is detected by Expression 7,
Output to the second correction amount determination unit 31.

[0035]

(Equation 7)

The second correction amount determining section 31 calculates the temperature difference δ4 of the mold calculated by the temperature deviation calculating section 29 and the time change Δ2 of the mold temperature detected by the temperature change detecting section 30.
And the correction amount δ5 of the set temperature of the hot platen based on the mold temperature is determined by fuzzy inference and output to the correction amount totalizing unit 32. The fuzzy inference method will be described with reference to FIGS. FIG. 5 is a graph showing a membership function of the fuzzy inference, wherein (A) is a membership function of the temperature deviation of the mold, (B) is a membership function of the time change of the temperature of the mold, and (C) is a thermal function. The membership function of the manipulated variable of the set temperature of the panel is shown.

First, from the mold temperature deviation δ4 calculated by the temperature deviation calculator 29, NL, NM, NS, ZR, PS, P are obtained by the membership function shown in FIG.
The degree of conformity ν1 to ν7 for each fuzzy set using M and PL as labels is obtained. The fitness levels ν1 to ν7 are obtained by Expression 8 when the membership functions of the respective fuzzy sets are C1 to C7. The meaning of the fuzzy label is the same as in the first embodiment.

[0038]

(Equation 8)

Next, from the time change Δ2 of the mold temperature detected by the temperature change detecting section 30, the NL, NM, NS, ZR, PS, P are obtained by the membership function shown in FIG.
The degree of conformity η1 to η7 for each fuzzy set with M and PL as labels is determined. The fitness levels η1 to η7 are obtained by Expression 9 when the membership functions of the respective fuzzy sets are D1 to D7.

[0040]

(Equation 9)

Next, based on the fuzzy control rules shown in Table 3, the degree of conformity ν1 to the condition of the antecedent part of each rule.
Based on ν7 and η1 to η7, the fitness ε1 to ε7 of each fuzzy set in the consequent part is obtained based on Expression 10.

[0042]

[Table 3]

[0043]

(Equation 10)

In Equation 10, a 数 式 b is a and b
Represents the minimum value of. And the membership function of the consequent part,
In addition, the entire inference is performed based on each of the fitness levels ε1 to ε7. FIG. 6 is a diagram for explaining how to obtain an inference result. First, a new membership function is created for each membership function in the consequent part by cutting off the top from the values of the fitness ε1 to ε7. For example, as shown in FIG. 6, the conformity ε4 of the consequent part is 0.25, the conformity ω5 of the PS is 0.75, the conformity ε6 of the PM is 0.50, and the other conformity is 0. , The membership functions truncated at each top are like functions 54-56. Next, an overall membership function obtained by combining the membership functions is obtained. The hatched area in FIG. 6 is the combined membership function. The center of gravity 57 of this entire membership function is the inference result. The value of the inference result is the correction amount δ5 of the hot platen set temperature and is output to the correction amount totalizing unit 32.

The correction amount totalizing unit 32 calculates the correction amount δ2 of the temperature deviation of the hot platen determined by the correction amount determining unit 26 and the correction amount of the set temperature of the hot platen determined by the second correction amount determining unit 31. δ5 is calculated by Expression 11, and the correction amount δ6 of the calculation result is output to the correction unit 33.

[0046]

[Equation 11]

The correction unit 33 calculates the correction of the temperature deviation δ1 of the hot platen calculated by the temperature deviation calculation unit 23 based on the correction amount δ6 totalized by the correction amount totalization unit 32 according to the following equation (12).
And outputs the deviation δ3 of the correction result to the manipulated variable determiner 36.

[0048]

(Equation 12)

The operation amount determination unit 36 uses the temperature deviation δ3 of the hot platen calculated by the correction unit 33 and the time change Δ1 of the temperature of the hot platen detected by the temperature change detection unit 24 to calculate the heater operation amount α. Is determined by fuzzy inference, and the control unit 3
5 is output. This fuzzy inference method will be described with reference to FIG. FIG. 7 is a graph showing the membership function of the fuzzy inference, wherein (A) is a membership function of the temperature deviation of the hot platen, (B) is a membership function of the temperature change of the hot platen over time, and (C). Denotes a membership function of the operation amount of the duty ratio of the heater.

First, from the corrected temperature deviation δ3 of the hot platen calculated by the correction unit 33, NL, NM, NS, ZR, PS, P are obtained from the membership function shown in FIG.
The degree of conformity μ1 to μ7 for each fuzzy set using M and PL as labels is obtained. This calculation is performed according to Equation 3 in the same manner as described in the first embodiment. Second
In the embodiment, the time change Δ1 of the temperature of the hot platen detected by the temperature change detection unit 24 is further shown in FIG.
NL, NM, NS, Z by the membership function shown in
The suitability τ1 to τ7 for each fuzzy set with R, PS, PM, and PL as labels are determined. This fitness τ1
.Tau.7 represents the membership function of each fuzzy set as E
Assuming 1 to E7, it is obtained by Expression 13.

[0051]

(Equation 13)

Next, based on the fuzzy control rules shown in Table 4, the degree of conformity μ 1 to the condition of the antecedent part of each rule is obtained.
Based on μ7 and τ1 to τ7, the fitness χ1 to χ7 of each fuzzy set of the consequent part is obtained based on Expression 14.

[0053]

[Table 4]

[0054]

[Equation 14]

In Equation 14, a 数 式 b is a and b
Represents the minimum value of. And the membership function of the consequent part,
In addition, the entire inference is performed based on the fitness levels # 1 to # 7. This inference method is performed by the same method as the above-described method of obtaining the inference result in the second correction amount determination unit 31. That is, for each membership function in the consequent part, a new membership function is created by removing the top from the values of the fitness levels χ1 to χ7, and the center of gravity of the entire membership function obtained by combining those functions is obtained. Do. The value of the inference result is the heater operation amount α and is output to the control unit 35.

The control unit 35 controls the heater buried in the hot platen in the same manner as in the first embodiment, based on the heater operation amount α.

As described above, the temperature control device for the vulcanizer of the second embodiment detects the change of the state of the vulcanizer, corrects the temperature deviation of the hot platen, and furthermore, The temperature of each part of the vulcanizer is controlled by using the time variation of the hot platen temperature, the deviation of the mold temperature, and the time variation of the mold temperature. Therefore, more accurate and stable temperature control with less variation is possible.

The present invention is not limited to the first and second embodiments described above, but can be variously modified. For example, as the mold of the vulcanizing section 10, a mold composed of two upper and lower parts is used in the present embodiment, but the present invention is not limited to this, and a structure composed of three or more parts is used. It may be a mold or a mold having a shape that cannot be completely separated into two pieces. Further, in the present embodiment, the hot plate is also a plate-like hot plate having a concave portion capable of covering the upper and lower halves of the mold, corresponding to the shapes of the upper and lower molds, but is not limited thereto. Various types of hot plates, such as a hot plate having a simple flat plate shape, a hot plate having a shape completely encompassing a mold, and a hot plate having a structure that cannot be separated vertically, are considered.
You can use them without any problem.

The fuzzy inference method used for determining the correction amount of the hot platen set temperature and for determining the heater operation amount may be any of various fuzzy inference methods. For example,
The fitness of the membership function of the antecedent part of the fuzzy inference is obtained by using the MAX-MIN method, but may be obtained by a direct product method, a marginal product method, or the like. Also, each membership function is not limited to a triangular function, and a bell-shaped or trapezoidal membership function may be used. Although the number of each fuzzy set is all seven, any suitable number of membership functions other than seven may be defined according to the accuracy of temperature control, control time, and the like. Further, as a method of obtaining the entire membership function from each membership function and each fitness in the consequent part for performing inference, in the present embodiment, the top of the membership function is cut off according to each fitness. Then, the newly removed new membership function was synthesized to obtain the entire membership function. However, a new membership function may be created by reducing the height of each membership function in proportion to each fitness. That is, when the membership functions of the consequent part are B1 to B7 and the respective degrees of conformity are ρ1 to ρ7, the entire membership function B may be obtained by Expression 15.

[0060]

(Equation 15)

Further, a method for determining the correction amount of the hot platen set temperature,
As a method of determining the heater operation amount, a method other than fuzzy inference may be used. For example, an empirically optimum temperature control method may be described in an if-then-else format, and inference may be performed using a production rule technique in which inference is performed using the rules in multiple stages.

[0062]

The vulcanizer mold temperature control apparatus of the present invention corrects the value of the temperature deviation immediately after the change of the state of the vulcanizer is detected, and controls the heater operation amount. Therefore, it is possible to reduce disturbance of the vulcanization temperature and quickly restore the disturbance temperature to the set temperature. Therefore,
A vulcanizer type temperature controller capable of controlling the temperature with high accuracy can be realized. Further, it is possible to realize a vulcanizer mold temperature control device capable of stably producing a homogeneous high-quality vulcanizate.

[Brief description of the drawings]

FIG. 1 is a configuration diagram of a vulcanizer to which a mold temperature control device according to a first embodiment of the present invention is applied.

2A and 2B are graphs showing membership functions of fuzzy inference performed by an operation amount determination unit shown in FIG. 1, wherein FIG. 2A is a membership function of a temperature deviation of a hot platen, and FIG. 7 is a graph showing a membership function of a duty ratio of FIG.

FIG. 3 is a diagram illustrating an inference method of fuzzy inference performed by an operation amount determination unit illustrated in FIG. 1;

FIG. 4 is a configuration diagram of a vulcanizer to which a mold temperature control device according to a second embodiment of the present invention is applied.

FIG. 5 is a graph showing a membership function of fuzzy inference performed by the second correction amount determination unit shown in FIG. 4,
(A) is a membership function of the mold temperature deviation, (B) is a membership function of the time change of the mold temperature, and (C) is a membership function of the manipulated variable of the hot plate set temperature.

FIG. 6 is a diagram illustrating an inference method of fuzzy inference performed by a second correction amount determination unit illustrated in FIG. 4;

7 is a graph showing a membership function of fuzzy inference performed by the manipulated variable determination unit shown in FIG. 4, (A) is a membership function of a temperature deviation of a hot plate, and (B) is a temperature of the hot plate. (C) is a graph showing a membership function of a duty ratio which is an operation amount of a heater.

[Explanation of symbols]

DESCRIPTION OF SYMBOLS 10 Vulcanization processing part 11 Cavity 12 Upper die 13 Lower die 14 Upper heating plate 15 Lower heating plate 20, 40 Type temperature control device 21 Heating plate temperature sensor 22 Heating plate set temperature 23 Temperature deviation calculation part 24 Temperature change detection part 25 State Change detection unit 26 Correction amount determination unit 27 Type temperature sensor 28 Type set temperature 29 Temperature deviation calculation unit 30 Temperature change detection unit 31 Second correction amount determination unit 32 Correction amount aggregation unit 33 Correction unit 34, 36 Operation amount determination unit 35 Control units 51, 52, 54 to 56 Membership functions 53, 57 Center of gravity

Continuation of front page (56) References JP-A-63-209817 (JP, A) JP-A-61-84211 (JP, A) JP-A-4-189120 (JP, A) JP-A-61-259482 (JP, A) JP-A-63-302011 (JP, A) JP-A-7-144353 (JP, A) JP-A-7-104868 (JP, A) JP-A-6-126748 (JP, A) 4-58306 (JP, U) (58) Fields investigated (Int. Cl. ⁷ , DB name) B29C 33/00-35/18

Claims (3)

(57) [Claims] 1. A material to be vulcanized is charged into a mold (12, 13),
A mold temperature control device for a vulcanizer for vulcanizing said material to be vulcanized through said mold using a hot plate (14, 15) heated by a heater, wherein said hot plate (14, 15) A platen temperature sensor (21) for detecting the temperature (th) of the platen; a platen temperature (th) detected by the platen temperature sensor (21); and a preset platen temperature (Th) set in advance. A hot plate temperature deviation calculating means (23) for calculating a temperature deviation (δ1) of the hot plate based on the change of the state of the vulcanizer from a standby state to a vulcanized state or from a vulcanized state to a standby state; State change detecting means (25) for detecting the change; and the hot platen temperature deviation calculating means (2) when the state detected by the state change detecting means (25) is switched.
A correction amount determining means (26) for determining a correction amount (δ2) of the temperature deviation (δ1) of the hot platen based on the temperature deviation (δ1) of the hot platen calculated in 3); Based on the correction amount (δ2) determined in (26), the hot platen temperature deviation calculating means (2
A correcting means (33) for correcting the temperature deviation (δ1) of the hot plate calculated in 3), and an operation of the heater based on the temperature deviation (δ3) of the hot plate corrected by the correcting means (33). An operation amount determining means (34) for determining the amount (α); and a heater control means (35) for controlling the heater based on the heater operation amount (α) determined by the operation amount determining means (34). Temperature control device for vulcanizer having a. 2. A hot plate temperature change detecting means (24) for detecting a time change (Δ1) of the hot plate temperature (th) detected by the hot plate temperature sensor (21); and the molds (12, 13). A mold temperature sensor (27) for detecting the temperature (tm) of the mold; and a mold temperature (t) detected by the mold temperature sensor (27).
m) and a preset mold temperature (Tm),
A mold temperature deviation calculating means (29) for calculating a mold temperature deviation (δ4); and a mold temperature (t) detected by the mold temperature sensor (27).
m) a mold temperature change detecting means (30) for detecting a time change (Δ2), a mold temperature deviation (δ4) calculated by the mold temperature deviation calculating means (29), and a mold temperature change detecting means ( 30)
And a second correction amount determination means (31) for determining a correction amount (δ5) of the hot platen set temperature based on the time change (Δ2) of the mold temperature detected by the correction means (31). 32, 33) are the correction amount (δ2) determined by the correction amount determining means (26) and the second
The correction amount (δ) determined by the correction amount determining means (31)
5), the hot plate temperature deviation (δ1) is corrected, and the operation amount determining means (36) determines the temperature change of the hot platen determined by the hot plate temperature change detection unit (24). Δ1)
The mold temperature control of a vulcanizer according to claim 1, wherein the operation amount (α) of the heater is determined based on the temperature deviation (δ3) of the hot platen corrected by the correction means (32, 33). apparatus. 3. The determination of the correction amount (δ5) in the second correction amount determination means (31) and the determination of the heater operation amount (α) in the operation amount determination means (34, 36) are each predetermined. 3. The vulcanizer mold temperature control device according to claim 2, wherein fuzzy inference is executed by using the obtained fuzzy rule and membership function.