CN100557531C - Smelting furnace intelligence control system and method - Google Patents
Smelting furnace intelligence control system and method Download PDFInfo
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- CN100557531C CN100557531C CNB2006100806738A CN200610080673A CN100557531C CN 100557531 C CN100557531 C CN 100557531C CN B2006100806738 A CNB2006100806738 A CN B2006100806738A CN 200610080673 A CN200610080673 A CN 200610080673A CN 100557531 C CN100557531 C CN 100557531C
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Abstract
A kind of smelting furnace intelligence control system is provided, and this control system comprises temperature measurement unit, signal processing unit, performance element and human-computer interaction interface, and described temperature measurement unit is used to measure the current temperature value T of smelting furnace; Described signal processing unit is used to receive smelting furnace current temperature value T that described temperature measurement unit records and sends control command according to this temperature to described performance element; Described performance element receives the control command of described signal processing unit, and whether controls furnace heats according to this control command; Human-computer interaction interface is connected with described signal processing unit, is used for showing to the user procedure parameter of smelting furnace, thereby receives the running parameter that user's input changes this intelligence control system.This intelligence control system control accuracy is higher, and man-machine interaction is good, and environmental suitability is strong, can increase substantially product quality.
Description
Technical field
The present invention relates to a kind of control system, especially relate to a kind of intelligence control system and method that is used for the hot chamber machine smelting furnace.
Background technology
Smelting furnace is the important component part of hot chamber machine, and the quality of its control performance has significant impact to product quality.Because characteristics such as that temperature control has is non-linear, big inertia, and smelting furnace in use is subject to such as vibrations frequent under enchancement factor such as reinforced, voltage ripple of power network and the abominable site environment, the influence of electromagnetic interference (EMI), there are the shortcoming that control accuracy is lower, man-machine interaction is poor, environmental suitability is not strong in traditional control method and equipment, are difficult to obtain ideal control effect in die casting machine temperature of smelting furnace control system.
Summary of the invention
The objective of the invention is to overcome the shortcoming that control accuracy is lower in the conventional art, man-machine interaction is poor, environmental suitability is not strong, a kind of intelligence control system and method for smelting furnace is provided.
For achieving the above object, provide a kind of smelting furnace intelligence control system, this control system comprises temperature measurement unit, signal processing unit, performance element and human-computer interaction interface, and described temperature measurement unit is used to measure the current temperature value T of smelting furnace; Described signal processing unit is used to receive smelting furnace current temperature value T that described temperature measurement unit records and sends control command according to this temperature to described performance element; Described performance element receives the control command of described signal processing unit, and whether controls furnace heats according to this control command; Human-computer interaction interface is connected with described signal processing unit, is used for showing smelting furnace and procedure parameter to the user, thereby receives the running parameter that user's input changes this intelligence control system.
The present invention also provides a kind of smelting furnace intelligence control method, and this control method comprises temperature survey step, signal Processing step, execution in step and parameter I/O step, in described temperature survey step, measures the current temperature value T of smelting furnace; In described signal Processing step, be received in smelting furnace current temperature value T that the temperature survey step records and generate control command according to this temperature; In execution in step, be received in the control command that described signal Processing step generates, and control the heat time heating time of smelting furnace according to this control command; In parameter I/O step, provide the procedure parameter of smelting furnace to the user, import the running parameter that changes in this intelligence control method thereby receive the user.
Realize heating under the different situations owing to adopted multiple algorithm, make smelting furnace intelligence control system provided by the invention and method can improve the smelting furnace control accuracy, strengthen environmental suitability, improve the quality of products, the use of human-computer interaction interface makes the present invention have good man-machine interaction.
Description of drawings
Fig. 1 is the composition frame chart according to smelting furnace intelligence control system of the present invention;
Fig. 2 is the structured flowchart of signal processing unit according to the preferred embodiment of the present invention;
Fig. 3 is the structured flowchart of smelting furnace intelligence control system according to the preferred embodiment of the present invention;
Fig. 4 is the synoptic diagram according to smelting furnace intelligence control method of the present invention;
Fig. 5 is the process flow diagram of smelting furnace intelligence control method according to the preferred embodiment of the present invention.
Embodiment
Describe the specific embodiment of the present invention in detail below in conjunction with accompanying drawing.
As shown in Figure 1, smelting furnace intelligence control system provided by the invention comprises: temperature measurement unit 100, signal processing unit 200, performance element 300 and human-computer interaction interface 400, understand for convenient, also comprised smelting furnace 900 among Fig. 1, wherein, described temperature measurement unit 100 is used to measure the current temperature value T of smelting furnace 900; Described signal processing unit 200 is used to receive smelting furnace current temperature value T that described temperature measurement unit 100 records and sends control command according to this temperature to described performance element 300; Described performance element 300 receives the control command of described signal processing unit 200, and controls firing rate to molten metal in the smelting furnace 900 according to this control command; Human-computer interaction interface 400 is connected with described signal processing unit 200, is used for showing to the user procedure parameter of smelting furnace, and receives the running parameter of the control system of input.
Described temperature measurement unit 100 can be selected any suitable temperature sensor for use, but because the temperature that this sensor need be measured is higher, therefore under the preferable case, as shown in Figure 3, described temperature measurement unit 100 comprises a plurality of double end thermopairs 110 and thermopair module 120 (for example EM231 of Siemens Company), and the two connects by the compensating wire (not shown).Described double end thermopair 110 can be measured the temperature of the molten metal (for example magnesium melt) that is in diverse location in the smelting furnace, and can measure the temperature of crucible inner and outer wall in the smelting furnace, the safety factor and the product quality problem that can prevent to be heated because molten metal is heated inequality or crucible inside and outside wall like this inequality causes, thus the reliability of system improved.This double end thermopair 110 is connected with described thermopair module by compensating wire, generally, compensating wire is used for the signal transmission between thermopair and secondary instrument, can eliminate thermocouple cold junction and change the measuring error that causes, guarantee the accurate measurement of instrument to medium temperature, the single-point or the multiple spot that are applicable to industry such as electric power, metallurgy, oil, chemical industry, light textile and national defence, scientific research department's robotization temperature instrumentation connect, because this is the technology of using always to those skilled in the art, therefore will be not described in detail here.Described thermopair module 120 becomes digital quantity with the temperature transition that the double end thermopair senses, and sends it to then in the signal processing unit 200.
The temperature signal digital quantity that described signal processing unit 200 receives from temperature measurement unit 100 conversions, and to its further processing.According to the present invention, as shown in Figure 2, described signal processing unit 200 comprises: storer 210, pwm signal generator 220, intensification timer (not shown), comparer 240, P controller 250 and fuzzy controller 260.Wherein, described storer 210 is used to store the current temperature value T and the procedure parameter of described temperature measurement unit 100 sensings; Described pwm signal generator 220 is used to generate pwm control signal to control described performance element 300, according to the difference of pwm control signal dutycycle, can regulate the heating power of performance element 300; Described intensification timer (not shown) is used for setting the section duration that heats up; Described P controller 250 is used to carry out the P algorithm, the dutycycle of the pwm signal that generates with control pwm signal generator 220, the P algorithm is also referred to as proportional algorithm, the resonse characteristic of this algorithm is steeper, transit time is shorter, that is to say that can to make programming rate very fast, but this algorithm causes system's concussion when being used to control the large time delay object easily; Described fuzzy controller 260 is used to carry out fuzzy algorithm, the dutycycle of the pwm signal that generates with the control pwm signal generator, and this algorithm can reduce system overshoot, shortens the adjusting time, improves the robustness of system; Described comparer 240 is used for the current temperature value T of comparison storer 210 storages and the current goal temperature T that calculates
K, so-called current goal temperature T
KBe meant the temperature sum that requires rising in current temperature value T and each the section duration that heats up when each heats up the section beginning, for example, need in the production metal is elevated to design temperature 630 degree from Current Temperatures (as normal temperature), but common firing equipment only can provide the per hour programming rate of tens degree, perhaps sometimes in order to prevent owing to the too fast inequality that causes being heated that heats up causes the crucible distortion, can section (intensification hop count order be variable to dividing some intensification between design temperature 630 degree at Current Temperatures, depend primarily on the size of programming rate), each section has individual target temperature (to be called the current goal temperature T
K), for example, the intensification section duration that described intensification timer is set is 1 hour, and temperature of smelting furnace was a degree when first heated up the section beginning, and a temperature that requires to increase in this intensifications section is the h degree, shows that then temperature through smelting furnace after 1 hour will be raised to (a+h) from a degree and spend; In like manner, when heating up the section beginning for second, the temperature of smelting furnace is (a+h) degree, and when second section that heats up finished, the temperature of smelting furnace should be (a+2h), by that analogy.And programming rate h can revise by human-computer interaction interface at any time.When controlling, if current temperature value T and current goal temperature T
KBetween deviation greater than preset value (for example 20 degree), then utilize P controller 250 to carry out the P algorithms, make this control system can heating with full power, reduce deviation rapidly to improve the response speed of system, generally, when beginning, each cycle period switches to this algorithm in the temperature rise period; If current temperature value T and current goal temperature T
KDeviation less than this preset value (for example 20 degree), then switch to fuzzy controller 260 and carry out fuzzy algorithmes, to improve the robustness of system, prevent that temperature from too raising.Need to prove, K switch 1 among Fig. 2 and K2 only represent to be used for the virtual switch of switch controller (P controller and fuzzy controller), be not illustrated in physically necessarily to have these switches, and, Fig. 2 has only shown an operation in the section that heats up, and does not therefore show described intensification timer.
By top description, what it will be understood by those skilled in the art that the P controller of carrying out the P algorithm is input as current temperature value T and current goal temperature T
KBetween deviation, its output can be controlled the dutycycle of pwm control signal.This P controller can be by microprocessor, and digital signal processor DSP or Programmable Logic Controller PLC realize that those skilled in the art can regulate the correlation parameter of P algorithm according to the target that will realize.Here no longer describe in detail.
Describe fuzzy algorithm below in detail.
According to the present invention, as shown in Figure 2, described fuzzy controller 260 comprises differential module 261, fuzzy quantization module 262, table look-up module 263 and ambiguity solution module 264, and wherein, described differential module 261 is used to receive current temperature value T and current goal temperature T
KBetween deviation X, this deviation X is carried out just calculating the poor of two neighbouring sample points with respect to the differentiating of time, thereby generates deviation variable quantity Y; Described fuzzy quantization module 262 is used to receive current temperature value T and current goal temperature T
KBetween deviation X, and the deviation variable quantity Y that generates of described differential module 261, and described deviation X and deviation variable quantity Y carried out fuzzy quantization; Described lookup unit 263 is used for the basis look-up table (can calculate this look-up table by the mode of off-line) of storage in advance, pass through fuzzy reasoning, storage mode in conjunction with deviation X and deviation variable quantity Y calculates the memory address of fuzzy control quantity, and reads the fuzzy control quantity Z of requirement from this address; Described ambiguity solution module 264 is used for the fuzzy control quantity Z that reads from table look-up module is carried out ambiguity solution, and the fuzzy control quantity transform is become the determined value that can directly export, regulates the dutycycle of pwm control signal, and then described performance element 300 is controlled.
According to the present invention, described fuzzy quantization module 262 can be utilized described deviation and/or deviation variable quantity are carried out nonlinear quantization, owing to this method is readily appreciated that to those skilled in the art, therefore will no longer describe in detail here.
Under the preferable case, the membership function of described nonlinear quantization adopts plyability and overlapping robustness triangle preferably.Certainly, also can adopt trapezoidal function.
According to the present invention,, need to determine following parameter: current temperature value T and current goal temperature T for the mode by off-line obtains look-up table in the described table look-up module 263
KThe fuzzy domain X1 of deviation X; The fuzzy domain Y1 of deviation variable quantity Y; And, the fuzzy domain Z1 of fuzzy control quantity Z.For instance, the fuzzy domain that deviation X can adopt is X1{0,1,2,3 ..., m-1} is m rank altogether, and the fuzzy domain that deviation variable quantity Y adopts is Y1{0,1,2,3, ..., n-1} is n rank altogether, and the fuzzy domain that fuzzy control quantity Z adopts is Z1{0,1,2,3, ..., f-1} is f rank altogether, so just can calculate the address of fuzzy control quantity Z in conjunction with storage mode.Why will be in conjunction with storage mode, be because the fuzzy control table that needs to store is the array of a m * n dimension, and in storage, to convert thereof into one-dimension array, so can have by row or column and store dual mode successively, when by the row storage, can utilize m * X1+Y1 to calculate the address of fuzzy control quantity Z, when by the row storage, the available n of utilization * Y1+X1 calculates the address of fuzzy control quantity Z, and the numerical value of m and n can be selected according to actual conditions, for example can select m=13, n=7, certainly, the fuzzy domain Z of output quantity also can select no scope, for example f=15 for use according to actual conditions.This calculating contrast those skilled in the art are general general knowledge, will no longer describe in detail here.
According to preferred implementation of the present invention, the fuzzy reasoning of described look-up table correspondence adopts " IF......AND......THEN...... " rule.
According to the present invention, described ambiguity solution module 264 adopts commonly used, the smoother gravity model appoach of control effect.
Under the preferable case, as shown in Figure 2, signal processing unit 200 of the present invention further comprises PI controller 270, is used at temperature of smelting furnace during near design temperature (promptly require reach finishing temperature), and the dutycycle of control pwm control signal is eliminated steady-state error.So-called " approaching " design temperature, be meant that deviation between current temperature value T and the design temperature is less than a certain preset value (for example 3 degree), to those skilled in the art, can select suitable temperature to carry out the PI algorithm at an easy rate to switch to PI controller 270.As can be seen from the above description, described PI controller 270 only works when needs insulations (Current Temperatures is near design temperature), and it remains in the metastable temperature range smelting furnace that reaches design temperature.K3 among the figure represents to switch to the virtual switch of PI algorithm.
According to the present invention, can utilize Programmable Logic Controller PLC to realize the function of above-mentioned signal processing unit 200, for example Siemens CPU224DC/DC/DC.Can utilize analog quantity storage unit A IW0, AIW2, AIW4 and the AIW6 of this PLC to come the temperature at each position of smelting furnace of storing temperature sensing cell 100 measurements, thereby realize the function of storer 210.
According to the present invention, can utilize the inner resolution of this PLC to constitute oscillatory circuit for the timer (not shown) of 1ms, and equal the cycle of pwm control signal the oscillation period that makes this oscillatory circuit, this oscillatory circuit and comparison order are used the output that can realize pwm control signal, thereby have realized the function of pwm signal generator 220.
According to the present invention, can utilize the inner resolution of PLC to constitute the oscillatory circuit of oscillation period for 1h for the timer (not shown) sum counter (not shown) of 10ms cooperates, its cycle is as the foundation of intensification segmentation, thereby realized the function of intensification timer.
In fact, the P algorithm can be regarded as a kind of special case of PI algorithm, that is to say as parameter T
IIn the time of infinitely-great, the P algorithm just becomes the PI algorithm, this parameter T
ICan set by artificial, also can pass through subroutine automatic setting according to circumstances.According to the present invention, the PID that can utilize PLC to provide instructs and realizes P algorithm and PI algorithm easily, and in order to take into account two kinds of algorithms of P and PI, that can write band parameter transmission is used for revising pid loop control table K
p, T
I, T
DIsoparametric subroutine, the control signal of output can be by the outputs of specific port, and for example port Q0.0 and the Q0.1 of CPU224DC/DC/DC have so just realized the function of P controller 250 and PID controller 270.Because this programming is easy to realize for those of ordinary skill, therefore will no longer describes in detail here.
According to the present invention, can utilize the indirect addressing function of PLC to table look-up, with the fuzzy domain X1 of the deviation X that above mentioned and the fuzzy domain Y1 of deviation variable quantity Y is example, can directly calculate the offset address of storage fuzzy control quantity Z (being used to control the dutycycle of pwm control signal), for example 13 * X1+Y1 obtains the specific address of corresponding controlled quentity controlled variable with offset address and look-up table first address (just depositing the address of the start element of the look-up table that obtains by calculated off-line) addition again.Utilize indirect addressing instructions to take out after the control corresponding amount it be multiply by and determine good scale factor in advance, round after comparison order (with the period ratio of pwm control signal) can directly export (for example by CPU224DC/DC/DC port Q0.0 and Q0.1).So just realized the function of fuzzy controller 260.
Below in conjunction with Fig. 3 performance element 300 is described.
Described performance element 300 comprises driver for isolating 310, solid-state relay 320 and heating tube 330, wherein, described driver for isolating 310 is connected with described signal processing unit 200, is used for driving described solid-state relay 320 according to the control signal of signal processing unit 200 outputs; Whether described solid-state relay 320 is controlled heating tube 330 and is heated under the driving of described driver for isolating 310; Described heating tube 330 places smelting furnace to heat to molten metal.
According to the present invention, described driver for isolating 310 is two miniwatt solid-state relays, is used for electrical isolation and power amplification, and described solid-state relay 320 is six high power solid state relays (being divided into two groups), is connected on line or the industrial alternating current transmission line.Obviously, to those skilled in the art, adopting suitable solid-state relay and solid-state relay is carried out rational deployment is common-sense, will no longer describe in detail here.
According to the present invention, as shown in Figure 3, described human-computer interaction interface 400 can be used for the demonstration of text or figure, the procedure parameter that shows smelting furnace to the user, comprise Current Temperatures, current heat time heating time, current operation algorithm etc., and can receive user's input, change the running parameter of system, comprise programming rate, an intensification section duration, design temperature etc.Certainly; above-mentioned procedure parameter and running parameter be the limitation of above-mentioned example not; those skilled in the art can set the running parameter that needs the procedure parameter that shows and need to set as required; for example described procedure parameter can also comprise alarm signal etc., and described running parameter can also comprise the temperature of crucible protection temperature and feeding blanket gas etc.Be appreciated that some parameter is a procedure parameter, the running parameter that also can belong to system no longer describes in detail here.Human-computer interaction interface 400 can have multiple choices, and for example Siemens TD 200, also can select supporting touch-screen for use.
Under the preferable case, as shown in Figure 3, smelting furnace intelligence control system provided by the invention also comprises hummer 500, is used for sending when system's non-normal working alerting signal.In addition, intelligence control system provided by the invention can in the dead of night (detect whether leakage of crucible by two electrodes that are installed in furnace bottom and liquid level relay) at crucible, the temperature difference is too big or system is quit work during other abnormal operating states, thereby guarantees the safety of whole smelting furnace.
According to a further aspect in the invention, a kind of smelting furnace intelligence control method also is provided, as shown in Figure 4, this control method comprises temperature survey step 1000, signal Processing step 2000, execution in step 3000 and parameter I/O step 4000, in described temperature survey step 1000, measure the Current Temperatures of smelting furnace; In described signal Processing step 2000, be received in smelting furnace Current Temperatures that temperature survey step 1000 records and generate control command according to this temperature; In execution in step 3000, be received in the control command that described signal Processing step 2000 generates, and control the heating of smelting furnace according to this control command; In parameter I/O step 4000, provide the procedure parameter of smelting furnace to the user, import the running parameter that changes in this intelligence control method thereby receive the user.
In described temperature survey step 1000, can select any suitable temperature sensor for use, but because the temperature that this sensor need be measured is higher, therefore under the preferable case, can select for use double end thermopair and thermopair module (for example Siemens EM231) to measure temperature, the two connects by compensating wire.Described double end thermopair can be measured the temperature of the molten metal (for example magnesium melt) that is in diverse location in the smelting furnace, and can measure the temperature of crucible inner and outer wall in the smelting furnace, the safety factor and the product quality problem that can prevent to be heated because molten metal is heated inequality or crucible inside and outside wall like this inequality causes, thus the reliability of system improved.This double end thermopair is connected with described thermopair module by compensating wire, generally, compensating wire is used for the signal transmission between thermopair and secondary instrument, can eliminate thermocouple cold junction and change the measuring error that causes, guarantee the accurate measurement of instrument to medium temperature, the single-point or the multiple spot that are applicable to industry such as electric power, metallurgy, oil, chemical industry, light textile and national defence, scientific research department's robotization temperature instrumentation connect, because this is the technology of using always to those skilled in the art, therefore will be not described in detail here.Described thermopair module receives the simulating signal that the double end thermopair senses, and converts thereof into to deliver to signal Processing step 2000 behind the digital quantity and further handle.
In described signal Processing step 2000, be received in the temperature digital amount that temperature survey step 1000 obtains, and to its further processing.According to the present invention, as shown in Figure 5, described signal Processing step 2000 comprises: storing step 2100, the timing step that heats up (not shown), comparison step 2400, P algorithm controls step 2500, fuzzy algorithm controlled step 2600 and pwm signal controlled step 2800.Wherein, at described storing step 2100, storage is sensed and treated current temperature value T by described temperature survey step 1000; In described intensification timing step, set the section duration that heats up; In described P algorithm controls step 2500, carry out the P algorithm, dutycycle with the control pwm signal, the P algorithm is also referred to as proportional algorithm, the resonse characteristic of this algorithm is steeper, transit time is shorter, that is to say that can to make programming rate very fast, but this algorithm causes system's concussion when being used to control the large time delay object easily; In described fuzzy algorithm controlled step 2600, carry out the dutycycle that fuzzy algorithm is controlled pwm control signal, this algorithm can reduce system overshoot, shortens the adjusting time, improves the robustness of system; In described comparison step 2400, relatively in the current temperature value T of storing step 2100 storages and the current goal temperature T of presetting
K, so-called current goal temperature T
KBe meant the temperature sum that requires increase in current temperature value T and each the section duration that heats up when each heats up the section beginning, for example, need in the production metal is elevated to design temperature 630 degree from Current Temperatures (as normal temperature), but common firing equipment only can provide the per hour programming rate of tens degree, perhaps cause the crucible distortion for the inequality that prevents to cause being heated sometimes owing to heat temperature raising is too fast, can divide some intensification sections between design temperature 630 degree at Current Temperatures, each section has individual target temperature (to be called the current goal temperature T
K), for example, the intensification section duration that described intensification timer is set is 1 hour, and temperature of smelting furnace was a degree when first heated up the section beginning, and a temperature that requires to raise in this intensifications section is the h degree, shows that then temperature through smelting furnace after 1 hour will reach (a+h) from a degree and spend; In like manner, when heating up the section beginning for second, the temperature of smelting furnace is (a+h) degree, and when second section that heats up finished, the temperature of smelting furnace should be (a+2h) degree, by that analogy.When controlling, if current temperature value T and current goal temperature T
KBetween deviation greater than preset value (for example 20 degree), then forward P algorithm controls step 2500 to and carry out the P algorithm, make this control system can heating with full power, reduce deviation rapidly to improve the response speed of system, generally, when beginning, each cycle period switches to this algorithm in the temperature rise period; If current temperature value T and current goal temperature T
KDeviation less than this preset value (for example 20 degree), then forward fuzzy algorithm controlled step 2600 to and carry out fuzzy algorithmes, to improve the robustness of system, prevent that temperature from too raising; In described pwm signal controlled step 2800, control the dutycycle of PWM by corresponding algorithm.It should be noted that Fig. 5 has only shown the operation in heats up section, therefore do not show regularly step of described intensification.
By top description, it will be understood by those skilled in the art that in the P algorithm controls step of carrying out the P algorithm, be input as current temperature value T and current goal temperature T
KBetween deviation, its output can be controlled the dutycycle of pwm control signal.Can be by microprocessor, digital signal processor DSP or Programmable Logic Controller PLC realize this P algorithm controls step, those skilled in the art can regulate the correlation parameter of P algorithm according to the target that will realize, no longer describe in detail here.
Describe fuzzy algorithm below in detail.
According to the present invention, as shown in Figure 5, described fuzzy algorithm controlled step 2600 comprises differentiation step 2610, fuzzy quantization step 2620, the step 2630 of tabling look-up and ambiguity solution step 2640, wherein, in described differentiation step 2610, receive current temperature value T and current goal temperature T
KBetween deviation X, this deviation X is carried out just calculating the poor of two neighbouring sample points with respect to the differentiating of time, thereby generates deviation variable quantity Y; In described fuzzy quantization step 2620, receive current temperature value T and current goal temperature T
KBetween deviation X, and the deviation variable quantity Y that generates in described differentiation step 2610, and deviation X and the deviation variable quantity Y that receives carried out fuzzy quantization; In the described step 2630 of tabling look-up, the look-up table that calculated off-line obtains that passes through according to storage in advance, by fuzzy reasoning, calculate the memory address of fuzzy control quantity Z in conjunction with the storage mode of deviation X and deviation variable quantity Y, and from this memory address, read desired fuzzy control quantity Z; In described ambiguity solution step 2640, the fuzzy control quantity Z that reads in the step of tabling look-up is carried out ambiguity solution, with the determined value that the fuzzy control quantity transform becomes can directly export, the dutycycle of regulating pwm control signal.
According to the present invention, in described fuzzy quantization step 2620, can utilize the method that input quantity is compared with predetermined threshold value to carry out nonlinear quantization, owing to this method is readily appreciated that to those skilled in the art, therefore will no longer describe in detail here.
Under the preferable case, the membership function of described nonlinear quantization is selected plyability and overlapping robustness triangle preferably for use.Certainly, also can select trapezoidal function commonly used for use.
For how obtaining look-up table, above carried out detailed description, will omit this description here.
According to the present invention, under the preferable case, in this step 2630 of tabling look-up, corresponding fuzzy reasoning adopts " IF......AND......THEN...... " rule commonly used.
According to the present invention,, can adopt the smoother gravity model appoach of control effect commonly used to carry out ambiguity solution and handle in described ambiguity solution step 2640.
Under the preferable case, as shown in Figure 5, signal Processing step 2000 of the present invention further comprises PI algorithm controls step 2700, in this step, when temperature of smelting furnace during near design temperature (promptly require reach finishing temperature), the dutycycle of control pwm control signal is eliminated steady-state error.So-called " approaching " design temperature is meant that deviation between current temperature value T and the design temperature is less than a certain preset value (for example 3 degree).For a person skilled in the art, can select suitable temperature to carry out the PI algorithm at an easy rate to switch to the P1 controller.As can be seen from the above description, described PI algorithm controls step 2700 only works when needs insulations (Current Temperatures is near design temperature), and it remains in the metastable temperature range smelting furnace that reaches design temperature.When having PI algorithm controls step 2700, described comparison step 2400 also will further compare the deviation between Current Temperatures and the design temperature, as shown in Figure 5.
According to the present invention, can utilize Programmable Logic Controller PLC to realize the function that above-mentioned signal Processing step 2000 will be carried out, for example Siemens CPU224DC/DC/DC.Can utilize analog quantity storage unit A IW0, AIW2, AIW4 and the AIW6 of this PLC to come sense and the temperature treated each position of storing temperature sensing step 1000, thereby realize the function that to carry out at storing step 2100.
According to the present invention, can utilize the inner resolution of this PLC to constitute oscillatory circuit for the timer of 1ms, and equal the cycle of pwm control signal the oscillation period that makes this oscillatory circuit, this oscillatory circuit and comparison order are used the output that can realize pwm control signal, thereby have realized will carrying out function at pwm control signal generation step 2200.
According to the present invention, can utilize the inner resolution of PLC to constitute the oscillatory circuit of oscillation period for 1h for the timer sum counter of 10ms cooperates, its cycle is as the foundation of intensification segmentation, thereby realized the function that will carry out in the step that heats up regularly.
According to the present invention, can utilize the PID instruction that PLC provides to realize P algorithm and PI algorithm very easily, in order to take into account two kinds of algorithms of P and PI, that can write the transmission of band parameter is used for revising pid loop control table K
p, T
I, T
DIsoparametric subroutine, the control signal of output can be by the outputs of specific port, and for example port Q0.0 and the Q0.1 of CPU224DC/DC/DC have so just realized the function that will carry out in P algorithm controls step 2500 and PI algorithm controls step 2700.Because this programming is easy to realize for those of ordinary skill, therefore will no longer describe in detail here.
According to the present invention, can utilize the indirect addressing function of PLC to table look-up, with the fuzzy domain X1 of the deviation X that above mentioned and the fuzzy domain Y1 of deviation variable quantity Y is example, the offset address that can directly calculate storage fuzzy control quantity Z (dutycycle of control pwm control signal) is 13 * X1+Y1, offset address and the addition of look-up table first address is obtained the specific address of corresponding controlled quentity controlled variable again.Utilize indirect addressing instructions to take out after the control corresponding amount it be multiply by and determine good scale factor in advance, round after comparison order (with the period ratio of pwm control signal) after can directly export (for example by CPU224DC/DC/DC port Q0.0 and Q0.1).So just realized the function that to carry out in fuzzy algorithm controlled step 2600.
Below in conjunction with Fig. 3 execution in step 3000 is described.
In described execution in step 3000, as shown in Figure 3, can utilize driver for isolating 310, solid-state relay 320 and 330 pairs of smelting furnaces of heating tube to control, wherein, described driver for isolating 310 is received in the control signal that described signal Processing step 2000 generates, and drives described solid-state relay 320 according to this control signal; Whether described solid-state relay 320 is controlled heating tube 330 and is heated under the driving of described driver for isolating 310; Described heating tube 330 places smelting furnace to heat to molten metal.
According to the present invention, described driver for isolating 310 is two miniwatt solid-state relays, is used for electrical isolation and power amplification, and described solid-state relay 320 is six high power solid state relays (being divided into two groups), is connected on line or the industrial alternating current circuit.
According to the present invention, in described parameter I/O step 4000, can provide the demonstration of text or figure, show the procedure parameter of smelting furnace to the user, and can receive user's input, the parameter of change system operation.Can utilize such as Siemens TD200 or supporting touch-screen and realize described parameter I/O step 4000.
Under the preferable case, smelting furnace intelligence control system provided by the invention also comprises audible alarm step 5000, is used for sending alerting signal when system's non-normal working, can utilize hummer to realize this function.In addition, intelligence control system provided by the invention can be in crucible leakage, the temperature difference quits work system during too big or other abnormal operating states, thereby guarantees the safety of whole smelting furnace.
Claims (21)
1. smelting furnace intelligence control system, this control system comprises temperature measurement unit, signal processing unit, performance element and human-computer interaction interface, described temperature measurement unit is used to measure the current temperature value T of smelting furnace; Described signal processing unit is used to receive smelting furnace current temperature value T that described temperature measurement unit records and sends control command according to this temperature value T to described performance element; Described performance element receives the control command of described signal processing unit, and whether controls furnace heats according to this control command; Human-computer interaction interface is connected with described signal processing unit, is used to show the procedure parameter of smelting furnace, and receives the running parameter of the control system of input;
Described signal processing unit comprises: storer, pwm signal generator, intensification timer, comparer, P controller and fuzzy controller; Described storer is used to store the current temperature value T of described temperature measurement unit sensing; Described pwm signal generator is used to generate pwm control signal to control described performance element; Described intensification timer is used for setting the section duration that heats up; Described P controller is used to carry out the P algorithm, the dutycycle of the pwm signal that generates with the control pwm signal generator; Described fuzzy controller is used to carry out fuzzy algorithm, the dutycycle of the pwm signal that generates with the control pwm signal generator; Described comparer is used for the current goal temperature value T in the comparison one intensification section
KWith the current temperature value T in this intensification section of storing in the storer, if current temperature value T and current goal temperature value T
KBetween deviation X greater than preset value, then utilize the P controller to carry out the P algorithm, if the deviation X of current temperature value T and target temperature less than this preset value, then utilizes fuzzy controller to carry out fuzzy algorithm.
2. intelligence control system according to claim 1, wherein, described temperature measurement unit comprises a plurality of double end thermopairs and thermopair module, the two connects by compensating wire.
3. intelligence control system according to claim 1, wherein, described fuzzy controller comprises differential module, fuzzy quantization module, table look-up module and ambiguity solution module, described differential module is used to receive current temperature value T and current goal temperature value T
KBetween deviation X, this deviation is carried out with respect to the differentiating of time, generate deviation variable quantity Y; Described fuzzy quantization module is used to receive current temperature value T and current goal temperature value T
KBetween deviation X, and the deviation variable quantity Y that generates of described differential module, and deviation X and the deviation variable quantity Y that receives carried out fuzzy quantization; Described table look-up module is used for by fuzzy reasoning, calculating the memory address of fuzzy control quantity Z in conjunction with the storage mode of deviation X and deviation variable quantity Y according to the look-up table of storage in advance, reads the fuzzy control quantity Z of requirement from this address; Described ambiguity solution module is used for the fuzzy control quantity Z that reads from table look-up module is carried out ambiguity solution, with the determined value that the fuzzy control quantity transform becomes can directly export, the dutycycle of regulating pwm control signal.
4. intelligence control system according to claim 3, wherein, the storage mode of described deviation X and deviation variable quantity Y comprises by the row storage with by the row storage.
5. intelligence control system according to claim 3, wherein, described fuzzy quantization module is carried out nonlinear quantization to described deviation X and/or deviation variable quantity Y.
6. intelligence control system according to claim 5, wherein, the membership function during described nonlinear quantization is selected triangle for use.
7. intelligence control system according to claim 3, wherein, the fuzzy reasoning of described table look-up module correspondence adopts " IF......AND......THEN...... " rule.
8. intelligence control system according to claim 3, wherein, described ambiguity solution module adopts gravity model appoach to carry out ambiguity solution.
9. intelligence control system according to claim 1, wherein, described signal processing unit further comprises the PI controller, is used for the dutycycle at temperature of smelting furnace time control pwm control signal near design temperature, eliminates steady-state error.
10. intelligence control system according to claim 1, wherein, described performance element comprises driver for isolating, solid-state relay and heating tube, described driver for isolating is connected with described signal processing unit, is used for driving described solid-state relay according to the control signal of signal processing unit output; Whether described solid-state relay is controlled heating tube and is heated under the driving of described driver for isolating; Described heating tube places smelting furnace.
11. intelligence control system according to claim 1, wherein, described procedure parameter comprises Current Temperatures, current heat time heating time, current operation algorithm; Described running parameter comprises programming rate, a section duration, design temperature heat up.
12. a smelting furnace intelligence control method, this control method comprise temperature survey step, signal Processing step, execution in step and parameter I/O step, in described temperature survey step, measure the Current Temperatures of smelting furnace; In described signal Processing step, be received in smelting furnace Current Temperatures that the temperature survey step records and generate control command according to this temperature; In execution in step, be received in the control command that described signal Processing step generates, and control the heating of smelting furnace according to this control command; In parameter I/O step, provide the procedure parameter of smelting furnace to the user, receive the running parameter of this intelligence control method of input;
Described signal Processing step comprises storing step, regularly step, comparison step, P algorithm controls step, fuzzy algorithm controlled step and pwm signal controlled step heat up, at described storing step, be stored in the current temperature value T and the procedure parameter of described temperature survey step sensing; In described intensification timing step, set the section duration that heats up; In described P algorithm controls step, carry out the P algorithm, with the dutycycle of control pwm control signal; In described fuzzy algorithm controlled step, carry out the dutycycle of fuzzy algorithm with the control pwm control signal, in described comparison step, compare the current goal temperature T in the intensification section
KWith the current temperature value T in this section that heats up of storing step storage, if current temperature value T and current goal temperature value T
KBetween deviation greater than preset value, then arrive P algorithm controls step and carry out the P algorithm, if current temperature value T and current goal temperature value T
KDeviation less than this preset value, then arrive the fuzzy algorithm controlled step and carry out fuzzy algorithm; In described pwm signal controlled step, control the dutycycle of PWM by corresponding algorithm.
13. intelligence control method according to claim 12 wherein, in described temperature survey step, adopts a plurality of double end thermopairs and thermopair module to measure temperature, the two connects by compensating wire.
14. intelligence control method according to claim 12, wherein, described fuzzy algorithm controlled step comprises differentiation step, fuzzy quantization step, the step of tabling look-up and ambiguity solution step, in described differentiation step, receives current temperature value T and current goal temperature value T
KBetween deviation X, this deviation X is carried out with respect to the differentiating of time, generate deviation variable quantity Y; In described fuzzy quantization step, receive current temperature value T and current goal temperature value T
KBetween deviation X, and the deviation variable quantity Y that generates in described differentiation step, and deviation X and the deviation variable quantity Y that receives carried out fuzzy quantization; In the described step of tabling look-up,, by fuzzy reasoning, calculate the memory address of fuzzy control quantity Z, and from this memory address, take out desired fuzzy control quantity Z in conjunction with the storage mode of deviation X and deviation variable quantity Y according to the look-up table of storing in advance; In described ambiguity solution step, the fuzzy control quantity Z that takes out in the table look-up module is carried out ambiguity solution, with the determined value that the fuzzy control quantity transform becomes can directly export, the dutycycle of regulating pwm control signal.
15. intelligence control method according to claim 14, wherein, the storage mode of described deviation X and deviation variable quantity Y comprises by the row storage with by the row storage.
16. intelligence control method according to claim 14 wherein, in described fuzzy quantization step, carries out nonlinear quantization to described residual quantity X and/or error variable quantity Y.
17. intelligence control method according to claim 15, wherein, the membership function during described nonlinear quantization is selected triangle for use.
18. intelligence control method according to claim 14, wherein, the fuzzy reasoning of the described step correspondence of tabling look-up adopts " IF......AND......THEN...... " rule.
19. intelligence control method according to claim 14 wherein, in described ambiguity solution step, adopts gravity model appoach to carry out ambiguity solution.
20. intelligence control method according to claim 12, wherein, described signal Processing step further comprises PI algorithm controls step, and in this step, when temperature of smelting furnace during near design temperature, the dutycycle of control pwm control signal is eliminated steady-state error.
21. intelligence control method according to claim 12, described procedure parameter comprise Current Temperatures, current heat time heating time, current operation algorithm; Described running parameter comprises programming rate, a section duration, design temperature heat up.
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| CN103456158A (en) * | 2013-08-30 | 2013-12-18 | 广东省自动化研究所 | Data acquisition and monitoring system of vacuum pressure die-casting machine |
| CN103575091A (en) * | 2013-11-05 | 2014-02-12 | 安徽工贸职业技术学院 | Thermoelectric furnace provided with temperature control system |
| CN107807688A (en) * | 2017-11-09 | 2018-03-16 | 中国科学院电工研究所无锡分所 | Steel pipe application temperature Fuzzy control system |
| CN113137772A (en) * | 2021-04-26 | 2021-07-20 | 佳木斯大学 | Piston type water chilling unit PLC control system and method based on fuzzy algorithm |
| CN116397337B (en) * | 2023-05-15 | 2023-09-08 | 江苏阿代尔新材料科技有限公司 | Device for circularly heating and melting polyester chips |
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