CN115401274A - Electric spark self-adaptive control system based on fuzzy control - Google Patents
Electric spark self-adaptive control system based on fuzzy control Download PDFInfo
- Publication number
- CN115401274A CN115401274A CN202210461972.5A CN202210461972A CN115401274A CN 115401274 A CN115401274 A CN 115401274A CN 202210461972 A CN202210461972 A CN 202210461972A CN 115401274 A CN115401274 A CN 115401274A
- Authority
- CN
- China
- Prior art keywords
- circuit
- control
- fuzzy
- voltage
- current
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000010892 electric spark Methods 0.000 title claims abstract description 21
- 238000005070 sampling Methods 0.000 claims abstract description 11
- 230000003044 adaptive effect Effects 0.000 claims abstract description 9
- 238000001514 detection method Methods 0.000 claims description 10
- 230000001105 regulatory effect Effects 0.000 claims description 7
- 238000006243 chemical reaction Methods 0.000 claims description 4
- 238000004458 analytical method Methods 0.000 claims description 3
- 238000005457 optimization Methods 0.000 claims description 3
- 238000000034 method Methods 0.000 description 17
- 238000003754 machining Methods 0.000 description 6
- 230000007547 defect Effects 0.000 description 2
- 238000006073 displacement reaction Methods 0.000 description 2
- 238000009760 electrical discharge machining Methods 0.000 description 2
- 238000006467 substitution reaction Methods 0.000 description 2
- 230000005540 biological transmission Effects 0.000 description 1
- 238000004891 communication Methods 0.000 description 1
- 238000011217 control strategy Methods 0.000 description 1
- 238000007418 data mining Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 230000010365 information processing Effects 0.000 description 1
- 230000001575 pathological effect Effects 0.000 description 1
- 238000003672 processing method Methods 0.000 description 1
Classifications
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B23—MACHINE TOOLS; METAL-WORKING NOT OTHERWISE PROVIDED FOR
- B23H—WORKING OF METAL BY THE ACTION OF A HIGH CONCENTRATION OF ELECTRIC CURRENT ON A WORKPIECE USING AN ELECTRODE WHICH TAKES THE PLACE OF A TOOL; SUCH WORKING COMBINED WITH OTHER FORMS OF WORKING OF METAL
- B23H1/00—Electrical discharge machining, i.e. removing metal with a series of rapidly recurring electrical discharges between an electrode and a workpiece in the presence of a fluid dielectric
- B23H1/02—Electric circuits specially adapted therefor, e.g. power supply, control, preventing short circuits or other abnormal discharges
Landscapes
- Engineering & Computer Science (AREA)
- Mechanical Engineering (AREA)
- Electrical Discharge Machining, Electrochemical Machining, And Combined Machining (AREA)
Abstract
The invention discloses an electric spark self-adaptive control system based on fuzzy control, which comprises: the fuzzy system is divided into three layers of adaptive control modules, corresponding fuzzy controllers are established, the first layer of control module is used for collecting and judging real-time state information of a sampling point, and the second layer of control module is used for converting direct current/alternating current of the sampling point into an output target.
Description
Technical Field
The invention relates to the technical field of electric spark control, in particular to an electric spark self-adaptive control system based on fuzzy control.
Background
The conventional electric spark control method generally adopts an average voltage method, the average value of the collected discharge gap voltage is compared with a set servo reference voltage, and a servo mechanism is kept still when spark discharge occurs; when the gap is open, the servo mechanism performs small-displacement feeding; when the gap is short-circuited, the servo mechanism is moved back by a large displacement. The average voltage method has the disadvantages that the control rule is simpler, the processing experience is not fused in the control strategy, and the judgment basis and the adjustment quantity are simplified, but the discharge state of the conventional electric spark processing is slowly and stably changed, so that a better control effect can be obtained by using the average voltage control method. However, for micro electrical discharge machining, the pulse width is usually very narrow, the discharge energy is very weak, the average voltage amplitude of the gap is low, the interference in the machining process is severe, and the noise ratio in the acquired voltage signal is large, so that the average voltage method is not suitable for micro electrical discharge machining.
In recent years, fuzzy logic is proved to be a more effective control method, so that an electric spark electrode gap control method which applies fuzzy control to the online adjustment of PID parameters appears, namely, the method can simulate the thinking process of people to carry out 'imprecise reasoning', can process complex even 'pathological' systems such as micro electric spark machining and the like due to the intervention of human experience, and is widely applied to the field of micro electric spark machining. However, the establishment of the fuzzy control system includes several uncertain factors, for example, a fuzzy space requires a careful planning by several personnel, there are many detailed problems of the planning in practical application, and the establishment of the artificial output function has certain defects and uncontrollable properties in logic, and the collected parameter samples are not accurate enough, so the fuzzy control system itself has uncertainty, and its information processing method is simple, and when the processing environment is deteriorated, the dynamic performance of the system is deteriorated, and thus the high efficiency and stability of the micro electric discharge machining process cannot be ensured.
Disclosure of Invention
The present invention provides a fuzzy control based adaptive control system for electric spark, which is used for solving the problems mentioned in the background.
An electric spark adaptive control system based on fuzzy control comprises:
dividing a fuzzy system into three layers of adaptive control modules, establishing a corresponding fuzzy controller, wherein the first layer of control module is used for acquiring and judging real-time state information of a sampling point, the second layer of control module is used for converting direct current/alternating current of the sampling point into an output target, alternating current voltage outputs adjustable direct current voltage to a main circuit through a PFC converter and a DC/DC converter to supply power to the main circuit, the main circuit provides positive and negative polarity voltage for a gap, a detection circuit detects the voltage and current of the gap and sends the voltage and current to the control circuit, and the control circuit outputs a control signal; the third layer control module amplifies the control signal through the driving circuit to generate a driving signal to drive the on-off of the light opening tube of the main circuit, and the feeding speed of the output motor is controlled by the control signal;
the fuzzy controller respectively outputs and stores the information rules passing through the three layers of control modules, inputs the regulated voltage to the pulse forming circuit, correspondingly detects the generated pulse circuit, transmits the regulated voltage to the control circuit if the regulated voltage meets the requirements, and closes the pulse circuit if the regulated voltage does not meet the requirements; and (3) counting all circuit state information in an analysis period, storing the obtained data, performing cluster optimization, setting a cluster center as a new fuzzy subset, and setting the boundary of a data point as a new domain.
Preferably, the fuzzy controller is connected with the oscilloscope and the display through wires and is connected with the serial server through a network cable.
Preferably, the pulse circuit adopts a differential sampling circuit and a current sensor, the voltage detection value and the current detection value are subjected to digital-to-analog conversion through a high-speed AD chip, and the current gap state can be calculated in the controller according to the real-time voltage value and the real-time current value.
The electric spark self-adaptive control system based on fuzzy control effectively overcomes the defects of oversimplification, simplification of regulating quantity and the like of an average voltage control method and the limitation of the traditional one-type fuzzy logic in the aspect of processing uncertainty, ensures the stability and accuracy of the control system and a processing process, obviously improves the processing efficiency, ensures the real-time performance of processing control, and is a control method very suitable for micro electric spark processing.
Detailed Description
In order that the objects and advantages of the invention will be more clearly understood, the invention is further described below with reference to examples; it should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
It should be understood by those skilled in the art that these embodiments are only for explaining the technical principle of the present invention, and do not limit the scope of the present invention.
The invention relates to an electric spark self-adaptive control system based on fuzzy control, which comprises:
dividing a fuzzy system into three layers of adaptive control modules, establishing a corresponding fuzzy controller, wherein the first layer of control module is used for collecting and judging real-time state information of a sampling point, the second layer of control module is used for converting direct current/alternating current of the sampling point into an output target, alternating current voltage outputs adjustable direct current voltage through a PFC converter and a DC/DC converter to supply power to a main circuit, the main circuit provides positive and negative polarity voltage for a gap, a detection circuit detects the voltage and current of the gap and sends the voltage and the current to the control circuit, and the control circuit outputs a control signal; the third layer control module amplifies the control signal by the driving circuit to generate a driving signal to drive the on-off of the light opening tube of the main circuit, and the feeding speed of the output motor is controlled by the control signal;
the fuzzy controller respectively outputs and stores the information rules passing through the three layers of control modules, inputs the regulated voltage to the pulse forming circuit, correspondingly detects the generated pulse circuit, transmits the pulse circuit to the control circuit if the pulse circuit meets the requirements, and closes the pulse circuit if the pulse circuit does not meet the requirements; and (3) counting all circuit state information in an analysis period, storing the obtained data, performing cluster optimization, setting a cluster center as a new fuzzy subset, and setting the boundary of a data point as a new domain.
Preferably, the fuzzy controller is connected with the oscilloscope and the display through wires and is connected with the serial server through a network cable.
Preferably, the pulse circuit adopts a differential sampling circuit and a current sensor, the voltage detection value and the current detection value are subjected to digital-to-analog conversion through a high-speed AD chip, and the current gap state can be calculated in the controller according to the real-time voltage value and the real-time current value.
First stage
The circuit transmits high-frequency pulse voltage with adjustable pulse width to the primary side of a high-frequency pulse transformer T under the control of a pulse width modulation circuit, the pulse width modulation circuit can adjust the width according to the pulse generated by a pulse forming circuit 3, so that the secondary side of the pulse transformer T generates high-frequency alternating-current square waves with the same frequency and phase and reduced amplitude, a current detection circuit is connected in series in a main discharge loop,
second stage
The discharge current signal is collected and transmitted to the pulse trigger circuit, the upper square wave rectifying circuit and the lower square wave rectifying circuit form a full square wave rectifying circuit, the efficiency of converting high-frequency alternating current square waves into high-frequency direct current square waves can be effectively improved through the combined rectification of the upper square wave rectifying circuit and the lower square wave rectifying circuit, and the full-wave rectifying circuit converts the high-frequency alternating current square waves into the high-frequency direct current square waves.
And the electrode gap control of the electric spark grinding processing of the processing object selected in the first stage is realized by a fuzzy PID control method.
In operation, the electrode may not contact the workpiece for a long time at the stage of starting machining or the electrode may not discharge for a long time due to uneven profile of the workpiece during machining, so that the feeding speed is always maximized, and the electrode always contacts the workpiece to cause short circuit.
In the pulse application stage, the voltage signal and the current signal of the gap are sampled, and AD conversion is performed to obtain digital signals of the gap voltage and the gap current, respectively, and the digital signal of the gap voltage is amplified by kv times, the digital signal of the gap current is amplified by ki times, and the amplified voltage and current signals are added.
The object of the algorithm application is the repeated processing process of the electric spark, and the repeatability of the process of processing the cutting edge by the electric spark is just the same, namely the situation of processing one cutting edge each time is basically the same, so that the method of extracting information by using data mining and the like in an off-line state is effective and saves cost for determining fuzzy subsets and the like.
The oscilloscope is connected by the network port-to-serial server 4, a network cable and an RS522 connecting wire, and the oscilloscope establishes communication with the PLC controller to perform data transmission. The PLC reads the value calculated by the memory in the oscilloscope and compares the value with the test data of the standard machine to judge whether the product test result is qualified or unqualified.
So far, the technical solutions of the present invention have been described in connection with preferred embodiments, but it is apparent to those skilled in the art that the scope of the present invention is not limited to these specific embodiments. Equivalent changes or substitutions of related technical features can be made by those skilled in the art without departing from the principle of the invention, and the technical scheme after the changes or substitutions can fall into the protection scope of the invention.
Claims (3)
1. An electric spark adaptive control system based on fuzzy control is characterized by comprising:
dividing a fuzzy system into three layers of adaptive control modules, establishing a corresponding fuzzy controller, wherein the first layer of control module is used for collecting and judging real-time state information of a sampling point, the second layer of control module is used for converting direct current/alternating current of the sampling point into an output target, alternating current voltage outputs adjustable direct current voltage through a PFC converter and a DC/DC converter to supply power to a main circuit, the main circuit provides positive and negative polarity voltage for a gap, a detection circuit detects the voltage and current of the gap and sends the voltage and the current to the control circuit, and the control circuit outputs a control signal; the third layer control module amplifies the control signal by the driving circuit to generate a driving signal to drive the on-off of the light opening tube of the main circuit, and the feeding speed of the output motor is controlled by the control signal;
the fuzzy controller respectively outputs and stores the information rules passing through the three layers of control modules, inputs the regulated voltage to the pulse forming circuit, correspondingly detects the generated pulse circuit, transmits the pulse circuit to the control circuit if the pulse circuit meets the requirements, and closes the pulse circuit if the pulse circuit does not meet the requirements; and (3) counting all circuit state information in an analysis period, storing the obtained data, performing cluster optimization, setting a cluster center as a new fuzzy subset, and setting the boundary of a data point as a new domain.
2. The electric spark adaptive control system based on fuzzy control as claimed in claim 1, wherein said fuzzy controller is connected with oscilloscope and display through wire, and connected with serial server through network cable.
3. The electric spark adaptive control system based on fuzzy control as claimed in claim 1, wherein: the pulse circuit adopts a differential sampling circuit and a current sensor, the voltage detection value and the current detection value are subjected to digital-to-analog conversion through a high-speed AD chip, and the current gap state can be calculated in a controller according to the real-time voltage value and the real-time current value.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210461972.5A CN115401274A (en) | 2022-04-28 | 2022-04-28 | Electric spark self-adaptive control system based on fuzzy control |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210461972.5A CN115401274A (en) | 2022-04-28 | 2022-04-28 | Electric spark self-adaptive control system based on fuzzy control |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN115401274A true CN115401274A (en) | 2022-11-29 |
Family
ID=84158134
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210461972.5A Pending CN115401274A (en) | 2022-04-28 | 2022-04-28 | Electric spark self-adaptive control system based on fuzzy control |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115401274A (en) |
Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH10309630A (en) * | 1997-05-09 | 1998-11-24 | Sodick Co Ltd | Electric discharge machining control method and its device |
| CN1765572A (en) * | 2004-10-29 | 2006-05-03 | 大连理工大学 | Method for detecting discharge condition in tenuous electric spark process interval |
| CN102069245A (en) * | 2010-11-08 | 2011-05-25 | 大连理工大学 | Interval type-2 fuzzy logic-based two-order fuzzy control method for micro electrical discharge |
| CN103240474A (en) * | 2012-02-13 | 2013-08-14 | 严政 | Discharge gap control method for electric discharge machining unit |
| CN204035731U (en) * | 2014-07-01 | 2014-12-24 | 中州大学 | Wire two close cycles fuzzy self-adaptive control module in one |
| CN105195840A (en) * | 2015-09-14 | 2015-12-30 | 佛山市铬维科技有限公司 | Control method of electrical discharge machining power supply capable of realizing automatic boosting |
| CN107186295A (en) * | 2017-05-27 | 2017-09-22 | 南京理工大学 | A kind of energy control methods such as constant frequency of the fine electric spark pulse power |
| CN108213621A (en) * | 2017-12-13 | 2018-06-29 | 清华大学 | A kind of electrode gap control method for EDM Grinding |
| CN108380988A (en) * | 2018-01-30 | 2018-08-10 | 南京理工大学 | A kind of WEDM pulse power supply and its control method |
| CN207952846U (en) * | 2018-01-12 | 2018-10-12 | 西南交通大学 | A kind of numerical control electric spark pulse power |
| CN108723531A (en) * | 2018-07-06 | 2018-11-02 | 南京航空航天大学 | Between Wire EDM arteries and veins or the pulsewidth PID control constant current probability pulse power |
-
2022
- 2022-04-28 CN CN202210461972.5A patent/CN115401274A/en active Pending
Patent Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH10309630A (en) * | 1997-05-09 | 1998-11-24 | Sodick Co Ltd | Electric discharge machining control method and its device |
| CN1765572A (en) * | 2004-10-29 | 2006-05-03 | 大连理工大学 | Method for detecting discharge condition in tenuous electric spark process interval |
| CN102069245A (en) * | 2010-11-08 | 2011-05-25 | 大连理工大学 | Interval type-2 fuzzy logic-based two-order fuzzy control method for micro electrical discharge |
| CN103240474A (en) * | 2012-02-13 | 2013-08-14 | 严政 | Discharge gap control method for electric discharge machining unit |
| CN204035731U (en) * | 2014-07-01 | 2014-12-24 | 中州大学 | Wire two close cycles fuzzy self-adaptive control module in one |
| CN105195840A (en) * | 2015-09-14 | 2015-12-30 | 佛山市铬维科技有限公司 | Control method of electrical discharge machining power supply capable of realizing automatic boosting |
| CN107186295A (en) * | 2017-05-27 | 2017-09-22 | 南京理工大学 | A kind of energy control methods such as constant frequency of the fine electric spark pulse power |
| CN108213621A (en) * | 2017-12-13 | 2018-06-29 | 清华大学 | A kind of electrode gap control method for EDM Grinding |
| CN207952846U (en) * | 2018-01-12 | 2018-10-12 | 西南交通大学 | A kind of numerical control electric spark pulse power |
| CN108380988A (en) * | 2018-01-30 | 2018-08-10 | 南京理工大学 | A kind of WEDM pulse power supply and its control method |
| CN108723531A (en) * | 2018-07-06 | 2018-11-02 | 南京航空航天大学 | Between Wire EDM arteries and veins or the pulsewidth PID control constant current probability pulse power |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| EP3818608B1 (en) | Method for controlling a wind farm in order to damp subsynchronous oscillations | |
| CN106513879B (en) | A kind of spark discharge state recognition and detection method based on chaology | |
| CN110988633B (en) | Multifunctional monitoring method for self-adaptive adjustment of wire cut electrical discharge machining process | |
| CN109378867B (en) | Maximum transmission power control method for hybrid double-feed-in direct current transmission system | |
| CN103898621B (en) | Electrospinning based on many senses information mix together technology controls device and control method thereof | |
| CN110539054B (en) | Electric arc increase material stacking operation monitoring system | |
| CN108818310A (en) | A kind of online accurate control method of minute yardstick abrasive grain equating parameter | |
| CN104765403B (en) | Maximum power point of photovoltaic array tracking based on chaos optimization search | |
| CN205121296U (en) | Next quick -witted intelligent monitoring of beam -pumping unit integration system | |
| CN115401274A (en) | Electric spark self-adaptive control system based on fuzzy control | |
| CN112275728A (en) | Digital full-intelligent ultrasonic generator for pulse jet cleaning and stripping and automatic frequency locking method | |
| CN112763853B (en) | System for detecting and positioning short-circuit fault of alternating-current micro-grid in grid-connected mode and working method thereof | |
| CN116667537A (en) | Electric energy quality monitoring device | |
| CN109277657B (en) | Self-adaptive discharge control system and method for wire-moving linear cutting | |
| CN115308621A (en) | Multi-signal embeddable lithium ion battery electrochemical impedance spectrum testing device and method | |
| CN213670851U (en) | Digital full-intelligent ultrasonic generator for pulse jet cleaning and stripping | |
| CN205283451U (en) | Variable frequency speed device is trailed in single phase power threephase asynchronous machine load | |
| US11867740B2 (en) | Method and apparatus for identifying a grid fault | |
| CN114950701B (en) | Intelligent energy terminal, system and operation control method for industrial ball mill | |
| CN114236408A (en) | Controllable broadband impedance measuring method and device for lithium battery | |
| CN112953325A (en) | Brushless double-fed power generation system and control method thereof | |
| JPH08171430A (en) | Inverter device | |
| CN111458608A (en) | System and method for detecting and collecting discharge signals of electron gun | |
| CN212433315U (en) | Electron gun discharge signal detection and collection system | |
| CN1106327A (en) | Network quick feed control device for electric spark machine tool |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |