CN100358698C - Self adaptive glue discharging control method - Google Patents

Abstract

The present invention relates to a self-adaptive glue discharging control method. A control index for the Mooney viscosity of rubber compounds is used as the key technology for the control and the online judgment of the mixing implementation degree, and consequently, a multifunctional regression model between mixing process parameters and the Mooney viscosity of rubber compounds is established. On the basis, the information of a mixing process is collected in real time, and the Mooney viscosity of rubber compounds is predicted in the online manner. A mixing control model based on the online prediction of glue stock quality and the real-time processing of data is used in the self-adaptive glue discharging control method including a control method for the compensation and the track of glue discharge. The method has the advantages of low cost, reasonable data model, accurate analytical data and the like and offers an effective path and a preferentially used scheme for obtaining the Mooney viscosity index in the existing banbury production technology.

Description

Self adaptation binder removal control method

Technical field

The present invention relates to a kind of self adaptation binder removal control method in the compounding rubber production process, relate to the binder removal control of setting up mixing process parameter and regression model particularly.

Background technology

Along with the Chinese society rapid development of economy, the various utility car of doing are also increased sharply day by day with the various types of vehicles of private purchase.Increase with car quantity has not only brought a large amount of business opportunities to auto manufacturing, has also proposed higher quality and specification requirement for all kinds of auto parts machineries simultaneously, to guarantee the traffic safety with the car consumer.For the manufacturing firm of doughnut, various types of automobiles require to provide the technical standard that meets various special road conditions.

Have the banburying technology in the tire production now, can satisfy the refining glue production demand of substandard substantially.But the raising of prior art standard, desired mixing production has suitable complexity, and does not set up complete mixing theory as yet in the prior art so far.

In reality refining glue binder removal process, mainly be that the experience that relies on on-the-spot technologist is operated, thereby have limitation and higher error at present.And, can't grasp the progress in the mixing production comprehensively, have sizable hysteresis quality for the detection of refining the colloid figureofmerit.Generally about 60-80%, enterprise on a small scale then can be lower for existing refining glue qualification rate.So tire in actual use, exists potential safety hazard and product is paid compensation for problems such as rate height, also is not easy to control production cost.

If by means of rubber macromolecule theory, just must set up the mixing process theoretical model by a large amount of result of the test data, this solution still has shortcomings such as test period length, cost height, still can not satisfy the demand of existing tire production producer.

Thereby, set up a kind of low cost, the rational binder removal control method of data model, be the problem of present rubber banburying solution that production technology presses for.

Summary of the invention

Self adaptation binder removal control method of the present invention is intended to address the above problem and is not enough, to control the Mooney Viscosity of Rubber Mix index, as control online judgement mixing key technology of carrying out degree, thereby set up multi-functional regression model between mixing process parameter and the Mooney Viscosity of Rubber Mix.On this basis, gather mixing process information in real time, and the online forecasting Mooney Viscosity of Rubber Mix, design following self adaptation binder removal control flow and method.

Self adaptation binder removal control method of the present invention, the online forecasting technological process of control sizing material quality mainly comprises two parts: i.e. the real-time calculation process of data pretreatment process and predicted value.

Particularly, the data pretreatment process is:

The first step, input quality inspection and process control data, determining sample number m, variable number n, and count value is initially 0.Wherein variable is for can accurately reflecting the useful variable of rubber banburying degree, as numerical value such as temperature, power, energy;

Second goes on foot, and sets up the data matrix of m*n, and parameter is made as 1, and promptly the initialization matrix is the data model of m*1;

In the 3rd step, calculate all average that each variable in the sample is provided and variances one by one;

Whether in the 4th step, judging has greater than three times of samples more than the variance of average in all samples that provide (m).If have, the average that compares after then this sample being made as accumulates 1 with count value simultaneously; If do not have, then continue to judge this 4th step flow process, intact until whole judgements;

In the 5th step, judge that whether the counting aggregate-value is greater than 5% of sample number m.If have, then delete the data model that the initialization matrix is m*1, and then carry out from second step again; If do not have, then export this sample matrix.

The real-time calculation process of predicted value is:

The first step, the input action point variable.Transfer the sample matrix in the above-mentioned data pretreatment process, as the real-time data model that calculates of predicted value.Selected operating point variable is that what choose here is temperature, power, the energy values that adds carbon black at prediction variate-value at main operating point during Mooney viscosity;

Second step judged whether to satisfy the trend prediction entry condition, promptly judged whether to enter 30s before the binder removal, if last moving do a little with the binder removal point time interval less than 30s, then enter the 3rd forecast that goes on foot and calculate in real time; If not, then continue to repeat the first step;

The 3rd goes on foot, and quotes the real-time variable value of the operating point of last input;

The 4th step, the real-time variable value that the 3rd step quoted is carried out normalized, be about to each variate-value and subtract average except that the variance computing;

In the 5th step, call the Mooney viscosity value calculation process.

The 6th step, the contrary normalization of Mooney point that the 5th step drew is calculated, be about to data value and take advantage of variance, add average, and then draw the Mooney predicted value;

In the 7th step, trend prediction figure is exported and made to the Mooney predicted value that the 6th step drew.

Based on the above-mentioned online forecasting technology that comprises data preliminary treatment, the real-time calculation process of predicted value, self adaptation binder removal control method of the present invention comprises two kinds, promptly compensates the binder removal control method and follows the tracks of the binder removal control method.Wherein,

One, compensation binder removal control method is:

At first, define accumulation control variables and Instantaneous Control variable.

The useful variable that can accurately reflect rubber banburying degree is divided into accumulation control variables and Instantaneous Control variable.Wherein, the variable that transient state changed when the Instantaneous Control variable was meant banburying is as temperature, power etc.

The accumulation control variables mainly refers to the control variables that begins constantly to add up from banburying, as time, energy, commentaries on classics (week) number, heat etc.

When adopting the accumulation control variables to carry out binder removal control, can correspondingly produce invalid cumulant.As following two kinds of situations: carbon black can not normally add, and skidding occurs.

If adopt the accumulation control variables this moment, can cause invalid adding up, for avoiding this situation, invalid part must be rejected.From the accumulation variable, delete invalid part, thereby can be converted into useful variable.Following instantiation:

If N ₁Accumulation control variables during=" pressure floating weight ";

N ₂Accumulation control variables during=" adding carbon black ";

N ₃The accumulation variable that skids after " pressure floating weight " after=" oiling ";

N ₄Accumulation control variables during=" oiling ";

The accumulation control variables of the nearly binder removal point of N=.

Then the binder removal useful variable is: E=N-(N ₁-N ₂)-(N ₃-N ₄).

Secondly, need to determine variable combination control mode.

Reflect that mixing factor of carrying out degree is many-sided, therefore when binder removal is controlled, must need to take all factors into consideration.The variable selection principle of combination binder removal is as follows:

1, according to the primary and secondary relation, control variables can be divided into: main control variable and auxilliary control variables;

2, the general variable that gradually changes that adopts of main control variable as time T, temperature or energy F, and is taked Dan Xuanyi variables manner;

3, auxilliary control variables is as Dan Xuanyi from power P, energy F, time T or make up the mode of choosing of two variablees;

4, set the correlation of above-mentioned control variables and quality index, i.e. positive correlation or negative correlation.

Once more, set up binder removal control logic and enter binder removal condition calculation process.

1, sets up the control variables interval model.Promptly set up master variable parameter [X _m ^Min, X _m ^Max, X _m ^Set], and auxilliary variable parameter [X _Aux ^Min, X _Aux ^Max, X _m ^Set];

2, judge whether to satisfy the binder removal condition:

Check whether satisfy the main control condition: $X_m^{\min }<x<X_m^{\mathrm{set}},$ With auxilliary controlled condition: $X_{\mathrm{aux}}^{\min }>x_{\mathrm{aux}},$ Above-mentioned for adopting positively related logic Rule of judgment;

If auxilliary controlled condition is set to $X_{\mathrm{aux}}^{\max }<x_{\mathrm{aux}},$ It then is the logic Rule of judgment that adopts negative correlation.If above condition satisfies, illustrate that then sizing material is soft, can carry out the binder removal stage.

3, if do not satisfy the binder removal condition:

Promptly satisfy the main control condition $X_m^{\mathrm{set}}<x<X_m^{\max }$ With auxilliary controlled condition $X_{\mathrm{aux}}^{\max }<x_{\mathrm{aux}}$ (positive correlation) or/and $X_{\mathrm{aux}}^{\min }>x_{\mathrm{aux}}$ (negative correlation) illustrates that sizing material is also hard, can not binder removal, need refining more for a moment.

Two, be the control method of following the tracks of binder removal below:

Its algorithm basic thought is, according to the control variables of setting up the Mooney viscosity forecast model and gathering in real time, in the real-time estimate value of line computation Mooney viscosity, if Mooney viscosity value has reached the quality requirement of expectation then binder removal; If because factors such as mixing process fault cause mixing process normally to carry out, Mooney viscosity value can't reach requirement, then carry out the binder removal action according to the binder removal condition that transfinites.Its control flow is specifically:

At first, determine useful variable;

Promptly the useful variable of rubber banburying degree be can accurately reflect, as temperature, power P, ENERGY E etc. chosen as useful variable.

Secondly, need to determine the variable selection principle;

Because it is multiple to reflect that mixing factor of carrying out degree has, need take all factors into consideration so follow the tracks of when binder removal is controlled, its variable selection principle of following the tracks of binder removal must satisfy following two aspects simultaneously:

1., choose the binder removal operating point before, useful variables such as the temperature of all main operating point correspondences, power, energy, as add temperature, power, the energy datum of carbon black;

2., 30s reads the useful variable of mixing process in real time before the binder removal point, if the time interval of operating point before the binder removal point and binder removal point less than 30s, then moves from this.

Once more, implement modeling algorithm and set up accurate data-driven model;

On the basis of data-driven model, requirement (as the limit value of Mooney viscosity) according to technology and mixing qualified index, utilize prediction of quality (as soft measurement) model refining colloid figureofmerit can be converted to controlled amounts (as: instantaneous power etc.) in the mixing process, instruct binder removal production.

At last, foundation is followed the tracks of the binder removal control logic and is entered binder removal condition calculation process:

1, reads the reasonable value interval of corresponding model, controlled variable (Mooney viscosity), determine variable parameter [Y _m ^Min, Y _m ^Max, Y _m ^Set];

2, read the binder removal condition that transfinites, be specially overtime binder removal t _MaxOr overtemperature binder removal T _Max

3, judge whether to enter follow the tracks of the real-time calculation stages of binder removal (promptly whether reach 30s before the binder removal,

If last action and binder removal then judge whether it is last action at interval less than 30s).If then enter next step; If not, then continue to judge;

4, calculate the Mooney viscosity predicted value in real time.As do not reach the binder removal condition that transfinites, judge then whether continuous 5s all is positioned between the setting district Mooney viscosity predicted value.If then assign the binder removal instruction; As reaching the binder removal condition that transfinites, then assign the binder removal instruction immediately.

Aforesaid self adaptation binder removal control method, comprise the compensation binder removal and follow the tracks of the binder removal control method, be based on the mixing control model that sizing material quality online forecasting and data in real time are handled, it has advantages such as low cost, data model is reasonable, the analysis data are accurate, is effective way and the excellent scheme of getting that solves Mooney viscosity index in the existing banburying production technology.

Description of drawings

Fig. 1 is the data pretreatment process schematic diagram of online forecasting;

Fig. 2 is the real-time calculation flow chart of the predicted value of online forecasting;

Fig. 3 is the interval definite flow chart of feasible Mooney;

Fig. 4 is a compensation binder removal condition calculation flow chart;

Fig. 5 is the regression iterative algorithm flow chart;

Fig. 6 follows the tracks of binder removal condition calculation flow chart;

Fig. 7 is the Mooney viscosity value calculation flow chart;

The specific embodiment

Self adaptation binder removal control method of the present invention, the online forecasting technological process of control sizing material quality mainly comprises two parts: i.e. the real-time calculation process of data pretreatment process and predicted value.

As shown in Figure 1, the data pretreatment process is:

The first step, input quality inspection and process control data, determining sample number m, variable number n, and count value is initially 0.Wherein variable is for can accurately reflecting the useful variable of rubber banburying degree, as numerical value such as temperature, power, energy;

Second goes on foot, and sets up the data matrix of m*n, and parameter is made as 1, and promptly the initialization matrix is the data model of m*1;

In the 3rd step, calculate all average that each variable in the sample is provided and variances one by one;

Whether in the 4th step, judging has greater than three times of samples more than the variance of average in all samples that provide (m).If have, the average that compares after then this sample being made as accumulates 1 with count value simultaneously; If do not have, then continue to judge this 4th step flow process, intact until whole judgements;

In the 5th step, judge that whether the counting aggregate-value is greater than 5% of sample number m.If have, then delete the data model that the initialization matrix is m*1, and then carry out from second step again; If do not have, then export this sample matrix.

As shown in Figure 2, the real-time calculation process of predicted value is:

The first step, the input action point variable.Transfer the sample matrix in the above-mentioned data pretreatment process, as the real-time data model that calculates of predicted value.Selected operating point variable is that what choose here is temperature, power, the energy values that adds carbon black at prediction variate-value at main operating point during Mooney viscosity;

Second step judged whether to satisfy the trend prediction entry condition, promptly judged whether to enter the preceding 30s of binder removal.If last moving do a little with the binder removal point time interval less than 30s, then enter the 3rd forecast that goes on foot and calculate in real time; If not, then continue to repeat the first step;

The 3rd goes on foot, and quotes the real-time variable value of the operating point of last input;

The 4th step, the real-time variable value that the 3rd step quoted is carried out normalized, be about to each variate-value and subtract average except that the variance computing;

In the 5th step, call the Mooney viscosity value calculation process.

The 6th step, the contrary normalization of Mooney point that the 5th step drew is calculated, be about to data value and take advantage of variance, add average, and then draw the Mooney predicted value;

In the 7th step, trend prediction figure is exported and made to the Mooney predicted value that the 6th step drew.

Based on the above-mentioned online forecasting technology that comprises data preliminary treatment, the real-time calculation process of predicted value, self adaptation binder removal control method of the present invention comprises two kinds, promptly compensates the binder removal control method and follows the tracks of the binder removal control method.

As Fig. 3, Fig. 4, shown in Figure 5, compensation binder removal control flow is:

The first step, the real-time calculation process of reference data preliminary treatment and predicted value, input and definite Mooney are set average Mset; As shown in Figure 3.

Determine prescription number, modeling data group, determine sample Mooney average and round operation, export maximum and minimum of a value reference value then;

In second step, quote the regression iterative algorithm; As shown in Figure 4.

The initializing variable data; Draw the relevant parameter matrix; Import each variable and calculate minimum of a value, test value; Calculate maximum; Ask regression equation and corresponding amount; Greater than the virtual value of 3 times of standard deviations, and set up model database with maximum deviation as operating point.Be variable parameter [X _m ^Min, X _m ^Max, X _m ^Set].

In the 3rd step, input real time data and model data are to judge whether to reach the binder removal condition;

At first, determine the main control variable, singly selecting time T is the main control variable;

Secondly, determine auxilliary control variables, it is auxilliary control variables that power P, ENERGY E are selected in combination;

Once more, determine the correlation of above-mentioned control variables and quality index; Promptly close on binder removal point place, Mooney rises and descends along with temperature, reduces along with power drop, and energy increases and reduces.

At last, judge whether to carry out the binder removal stage according to above-mentioned compensation binder removal control logic.Also should be exactly:

1., T _Min＜T _t＜T _SetThe time, judge whether P _t＜P _Min, if not, then repeat 1. stage flow process;

If P _t＜P _MinSet up, then continue to judge whether E _t＞E _Max, if not, then repeat 1. stage flow process;

If T _Min＜T _t＜T _Set, P _t＜P _Min, E _t＞E _MaxAll set up, illustrate that then sizing material is soft, can binder removal, T needn't be waited until _MinConstantly;

2., work as T _Set＜T _t＜T _MaxThe time, judge whether P _t＞P _Max, if not, then can binder removal;

If P _t＞P _MaxSet up, then continue to judge whether E _t＜E _Min, if not, then can binder removal;

If T _Set＜T _t＜T _Max, P _t＞P _Max, E _t＜E _MinAll set up, illustrate that then sizing material is also hard, can not binder removal, repeat 2. stage flow process;

3., work as T _t＞T _MaxDuring establishment, binder removal then; Otherwise, just repeat 1. stage flow process.

As Fig. 3, shown in Figure 6, tracking binder removal control flow is:

The first step, the real-time calculation process of reference data preliminary treatment and predicted value, input and definite Mooney are set average Mset; As shown in Figure 3.

Determine prescription number, modeling data group, determine sample Mooney average and round operation, export maximum and minimum of a value reference value then;

In second step, input real time data and model data are to judge whether to reach the binder removal condition;

1, judge whether to be last operating point:

Judge whether to reach 30s before the binder removal, if with binder removal at interval less than 30s, then judge whether it is last action; If then enter next step; If not, then repeat this stage flow process.

2, input action point variable value and normalization computing:

Read last operating point variable instantaneous value, and definite range of variables parameter [Y _m ^Min, Y _m ^Max, Y _m ^Set];

All data normalizations are handled;

Call the Mooney viscosity value calculation process;

The Mooney point that aforementioned calculation the draws calculating of averaging;

3, judge whether to reach binder removal condition and enforcement:

Read the binder removal condition that transfinites, be specially overtime binder removal t _MaxOr overtemperature binder removal T _Max

Calculate in real time the Mooney viscosity predicted value,, continue then to judge that whether the Mooney viscosity predicted value all was positioned between the setting district in continuous 5 seconds if do not reach the binder removal condition that transfinites; If then assign the binder removal instruction; If not, then repeat " input action point variable value and the normalization computing " stage;

If reach the binder removal condition that transfinites, then assign the binder removal instruction immediately.

As shown in Figure 7, the online calculation process of Mooney viscosity value is to utilize the PLS model of having set up, according to the mixing process variable information, at the Mooney viscosity of line computation, forecast sizing material.

Wherein, input parameter is regression coefficient R, P, load W, and the mixing process variable X of forecast use;

Output parameter is sizing material Mooney viscosity predicted value Yp, i.e. PLS composition.

During initialization, the line number of wm=W, the columns of h=W; The line number of m=X, the columns of n=X; Yp=[0] m*1, T=[0] m*h, and T (:, k) the k row of expression T matrix, other are by that analogy.

Claims (8)

1, a kind of self adaptation binder removal control method, it is characterized in that: this method comprises compensation binder removal control method and follows the tracks of the binder removal control method that the online forecasting technological process of said method control sizing material quality mainly includes data pretreatment process and the real-time calculation process of predicted value;

The data pretreatment process is,

The first step, input quality inspection and process control data, determining sample number m, variable number n, and count value is initially 0; Wherein variable is a useful variable, i.e. temperature, power or energy;

Second goes on foot, and sets up the data matrix of m*n, and parameter is made as 1, and promptly the initialization matrix is the data model of m*1;

In the 3rd step, calculate all average that each variable in the sample is provided and variances one by one;

Whether in the 4th step, judging has in all samples that provide (m) greater than three times of samples more than the variance of average; If have, the average that compares after then this sample being made as accumulates 1 with count value simultaneously; If do not have, then continue to judge this 4th step flow process, intact until whole judgements;

In the 5th step, judge that whether the counting aggregate-value is greater than 5% of sample number m; If have, then delete the data model that the initialization matrix is m*1, and then carry out from second step again; If do not have, then export this sample matrix;

The real-time calculation process of predicted value is:

The first step, the input action point variable, described operating point variable is temperature, power and energy; Transfer the sample matrix in the above-mentioned flow process, as the real-time data model that calculates of predicted value;

Second step judged whether to satisfy the trend prediction entry condition, promptly judged whether to enter 30s before the binder removal, if last moving do a little with the binder removal point time interval less than 30s, then enter the 3rd forecast that goes on foot and calculate in real time; If not, then continue to repeat first step stage flow process;

The 3rd goes on foot, and quotes the real-time variable value of the operating point of last input;

The 4th step, the real-time variable value that the 3rd step quoted is carried out normalized, be about to each variate-value and subtract average except that the variance computing;

In the 5th step, call Mooney viscosity calculations flow process;

The 6th step, the contrary normalization of Mooney point that the 5th step drew is calculated, be about to data value and take advantage of variance, add average, and then draw the Mooney predicted value;

In the 7th step, trend prediction figure is exported and made to the Mooney predicted value that the 6th step drew.

2, self adaptation binder removal control method according to claim 1, it is characterized in that: the compensation binder removal control method in the described self adaptation binder removal control method, be to choose effective accumulation control variables and Instantaneous Control variable, by Dan Xuanyi main control variable, Dan Xuanyi or make up two auxilliary control variables and set up control variables interval model [X _m ^Min, X _m ^Max, X _m ^Set] and [X _Aux ^Min, X _Aux ^Max, X _m ^Set], and then judging whether that the mode that satisfies the binder removal condition controls the binder removal time, the variable that transient state changed when the Instantaneous Control variable was meant banburying comprises temperature and power; The accumulation control variables refers to the control variables that begins constantly to add up from banburying, comprises time, energy, commentaries on classics (week) number and heat; Main control variable list selects time T, temperature or energy F; Auxilliary control variables, from power P, energy F, time T Dan Xuanyi or make up two variablees.

3, self adaptation binder removal control method according to claim 2 is characterized in that: the correlation of setting main control and auxilliary control variables and quality index is positive correlation or negative correlation.

4, self adaptation binder removal control method according to claim 3, it is characterized in that: the positively related logic that is adopted judges whether to satisfy the binder removal condition and is, checks and whether satisfies the main control condition: $X_m^{\min }<x<X_m^{\mathrm{set}},$ With auxilliary controlled condition: $X_{\mathrm{aux}}^{\min }>x_{\mathrm{aux}},$ The logic of the negative correlation that is adopted judges whether to satisfy the binder removal condition, checks whether satisfy auxilliary controlled condition: $X_{\mathrm{aux}}^{\max }<x_{\mathrm{aux}}.$

5, according to claim 2 or 4 described self adaptation binder removal control methods, it is characterized in that: compensating the binder removal control flow is,

The first step, the real-time calculation process of reference data preliminary treatment and predicted value, input and definite Mooney are set average Mset;

In second step, quote the regression iterative algorithm;

In the 3rd step, input real time data and model data are to judge whether to reach the binder removal condition;

1., T _Min＜T _t＜T _SetThe time, judge whether P _t＜P _Min, if not, then repeat 1. stage flow process;

If P _t＜P _MinSet up, then continue to judge whether E _t＞E _Max, if not, then repeat 1. stage flow process;

If T _Min＜T _t＜T _Set, P _t＜P _Min, E _t＞E _MaxAll set up, illustrate that then sizing material is soft, can binder removal, T needn't be waited until _MinConstantly;

2., work as T _Set＜T _t＜T _MaxThe time, judge whether P _t＞P _Max, if not, then can binder removal;

If P _t＞P _MaxSet up, then continue to judge whether E _t＜E _Min, if not, then can binder removal;

If T _Set＜T _t＜T _Max, P _t＞P _Max, E _t＜E _MinAll set up, illustrate that then sizing material is also hard, can not binder removal, repeat 2. stage flow process;

3., work as T _t＞T _MaxDuring establishment, binder removal then; Otherwise, just repeat 1. stage flow process.

6, self adaptation binder removal control method according to claim 1, it is characterized in that: the tracking binder removal control method in the described self adaptation binder removal control method, be according to the control variables of setting up the Mooney viscosity forecast model and gathering in real time, in the real-time estimate value of line computation Mooney viscosity; If Mooney viscosity value has reached the quality requirement of expectation then binder removal; If because factors such as mixing process fault cause mixing process normally to carry out, Mooney viscosity value can't reach requirement, then carry out the binder removal action according to the binder removal condition that transfinites, control variables is the useful variable that can accurately reflect rubber banburying degree, includes temperature, power or energy.

7, self adaptation binder removal control method according to claim 6, it is characterized in that: the described quality requirement that reaches expectation, the temperature, power or the energy values that are meant all main operating point correspondences of choosing are as useful variable, and the useful variable that reads mixing process from the preceding 30s of binder removal point, if the operating point before the binder removal point and the time interval of binder removal point are less than 30s, then from this action.

8, self adaptation binder removal control method according to claim 7 is characterized in that: following the tracks of the binder removal control flow is,

The first step, the real-time calculation process of reference data preliminary treatment and predicted value, input and definite Mooney are set average Mset;

In second step, input real time data and model data are to judge whether to reach the binder removal condition;

1., judge whether to be last operating point,

Judge whether to reach 30s before the binder removal, if with binder removal at interval less than 30s, then judge whether it is last action; If then enter next step; If not, then repeat this stage flow process.

2., input action point variable value and normalization computing, read last operating point variable instantaneous value, and definite range of variables parameter [Y _m ^Min, Y _m ^Max, Y _m ^Set];

3., judge whether to reach the binder removal condition and implement,

Read the binder removal condition that transfinites, be specially overtime binder removal t _MaxOr overtemperature binder removal T _Max

Calculate in real time the Mooney viscosity predicted value,, continue then to judge that whether the Mooney viscosity predicted value all was positioned between the setting district in continuous 5 seconds if do not reach the binder removal condition that transfinites; If then assign the binder removal instruction; If not, then repeat " input action point variable value and the normalization computing " stage;

If reached the binder removal condition that transfinites, binder removal immediately then.

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