CN109558698B - Electric pulse auxiliary welding electric pulse waveform determining system based on data mining technology - Google Patents
Electric pulse auxiliary welding electric pulse waveform determining system based on data mining technology Download PDFInfo
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Abstract
The electric pulse auxiliary welding electric pulse waveform determining system based on the data mining technology comprises a grain size testing module, an upper computer system, a wireless transmission module, a lower computer system, an electric pulse generating circuit module and an electric pulse waveform collecting module; the upper computer system comprises an electric pulse waveform database module, an electric pulse waveform characteristic quantity acquisition module, an electric pulse waveform characteristic quantity database module, a grain size variation database module and an electric pulse waveform determination method module. The method has the advantages of being capable of determining proper electric pulse auxiliary welding electric pulse waveform and obtaining better experimental effect.
Description
Technical Field
The invention relates to the technical field of welding, in particular to an electric pulse auxiliary welding electric pulse waveform determining system based on a data mining technology.
Technical Field
Welding is an important material forming process and is widely applied to the fields of aerospace, ocean engineering, automobiles and the like. However, due to the action of high welding temperature, the microstructure of the welding seam area is coarse, thereby reducing the comprehensive performance of the welded workpiece, and how to refine the microstructure of the welding area of the welded workpiece has become an important research subject in the field of welding technology.
The electric pulse assisted welding technique can directly act on the solidification process, thereby achieving the purpose of controlling the solidification process at the beginning of material manufacture. The basic principle of generating high-energy electric pulse by capacitor energy storage is to charge and store energy to a capacitor and then discharge a load, thereby generating large pulse current. The characteristic quantity of the electric pulse waveform directly determines the energy injected into the metal solution, has important influence on the crystallization process, and if the action mechanism of the characteristic quantity of the electric pulse waveform on the crystallization process can be revealed, the proper electric pulse waveform can be selected on the basis to control the microstructure grain size of the solidified liquid alloy, thereby achieving the purpose of improving the comprehensive performance of the material. However, no literature has been published to report the action rule of the characteristic quantity of the electric pulse waveform on the grain size of the microstructure of the material, so that the process of determining the electric pulse waveform is more dependent on experience, the effect of the electric pulse auxiliary welding technology is not stable, and the popularization and application of the electric pulse auxiliary welding technology are limited. Therefore, it is necessary to research the action rule of the characteristic quantity of the electric pulse waveform on the grain size of the microstructure of the material, provide a basis for determining the electric pulse auxiliary welding electric pulse waveform, form a method for determining the electric pulse auxiliary welding electric pulse waveform, and construct an electric pulse auxiliary welding electric pulse waveform determination system based on the data mining technology on the basis.
Aiming at the problem that the action rule of the characteristic quantity of the electric pulse waveform on the grain size of the microstructure of the material is not clear, the invention provides an electric pulse auxiliary welding electric pulse waveform determining system based on a data mining technology, namely, a mass of electric pulse waveforms obtained in the experimental process and corresponding grain size data of the microstructure of the material are analyzed, the action rule of the characteristic quantity of the electric pulse waveform on the grain size of the microstructure of the material is revealed, a basis is provided for determining the electric pulse waveform on the basis, the electric pulse auxiliary welding electric pulse waveform determining system based on the data mining technology is constructed, and assistance is provided for popularization and application of the electric pulse auxiliary welding technology.
Disclosure of Invention
In order to solve the problem that the action rule of the characteristic quantity of the electric pulse waveform on the grain size of the microstructure of the material is not clear, the invention provides an electric pulse auxiliary welding electric pulse waveform determining system based on a data mining technology, namely, a mass of electric pulse waveforms obtained in the experimental process and corresponding grain size data of the microstructure of the material are analyzed, the action rule of the characteristic quantity of the electric pulse waveform on the grain size of the microstructure of the material is revealed, a basis is provided for determining the electric pulse waveform on the basis, and the electric pulse auxiliary welding electric pulse waveform determining system based on the data mining technology is constructed, so that the electric pulse auxiliary welding technology is promoted and applied.
The electric pulse auxiliary welding electric pulse waveform determining system based on the data mining technology comprises a grain size testing module, an upper computer system, a wireless transmission module, a lower computer system, an electric pulse generating circuit module and an electric pulse waveform collecting module; the upper computer system comprises an electric pulse waveform database module, an electric pulse waveform characteristic quantity acquisition module, an electric pulse waveform characteristic quantity database module, a grain size variation database module and an electric pulse waveform determination method module; the upper computer system is connected with the lower computer system through the wireless transmission module so as to control the electric pulse generating circuit module to generate electric pulses; the electric pulse waveform acquisition module acquires the electric pulse generated by the electric pulse generation circuit module and stores the electric pulse data into an electric pulse waveform database module in an upper computer system; the grain size testing module tests to obtain the grain sizes of the materials respectively when only welding and electric pulse auxiliary welding are carried out, and the grain size variation data of the materials are stored in a grain size variation database module in an upper computer system; the electric pulse waveform database module stores the electric pulse waveform acquired by the electric pulse waveform acquisition module; the electric pulse waveform characteristic quantity acquisition module acquires the characteristic quantity of the electric pulse waveform; the electric pulse waveform characteristic quantity database module stores the electric pulse waveform characteristic quantity; the electric pulse waveform determining method module stores the determining method of the electric pulse waveform.
The process of testing the grain size of the material by the grain size testing module in the invention is as follows: and (3) acquiring the grain sizes of the materials during only welding and electric pulse auxiliary welding by adopting a modern material testing and analyzing technology. During direct welding and electric pulse auxiliary welding, the welding process parameters are kept unchanged, and only the electric pulse waveform is changed to research the influence rule of the electric pulse waveform characteristic quantity on the grain size of the material; the grain size variation refers to the difference of the grain sizes of the materials when only welding and electric pulse auxiliary welding are carried out respectively.
Further, the electric pulse waveform characteristic quantity data stored in the electric pulse waveform characteristic quantity database module and the grain size variation data stored in the grain size variation database module have a one-to-one correspondence relationship. In the specific implementation process of the invention, during direct welding and electric pulse auxiliary welding, welding process parameters are kept unchanged, and only the waveform of the electric pulse is changed to study the influence of the characteristic quantity of the electric pulse waveform on the grain size of the material, namely, the electric pulse waveform stored in the electric pulse waveform database module has a one-to-one correspondence with the grain size variation data stored in the grain size variation database module, namely, the electric pulse waveform characteristic quantity data stored in the electric pulse waveform characteristic quantity database module also has a one-to-one correspondence with the grain size variation data stored in the grain size variation database module. After an electric pulse waveform is determined, electric pulse auxiliary welding is carried out on the material, after the electric pulse auxiliary welding process is finished, the grain size of the material is obtained through testing, the difference value of the grain size of the material when only welding and the electric pulse auxiliary welding are carried out respectively is obtained through calculation, meanwhile, the characteristic quantity of the electric pulse waveform at the moment is extracted, the electric pulse waveform characteristic quantity data and the grain size variation data are stored in an electric pulse waveform characteristic quantity database module and a grain size variation database module in an upper computer system respectively, the electric pulse waveform characteristic quantity data and the grain size variation data obtained in the mode have a one-to-one correspondence relation, and massive data are provided for the follow-up study of the action rule of the electric pulse waveform characteristic quantity on the grain size variation of the material.
Further, the waveform characteristic quantity of the electric pulse comprises a pulse peak value A, a pulse width d and a pulse rising rate k. The energy peak value of the first pulse of the electric pulse waveform is the largest, the effect on the microstructure in the material is the most obvious, and the influence rule of the characteristic quantity of the first pulse on the grain size of the microstructure in the material is mainly researched. The rate at which the pulses rise refers to how quickly the first pulse peaks, i.e., the slope of the pulse waveform. The rate k of rise of the pulses studied in the present invention is for the rate at which the first pulse rises to a peak.
Furthermore, the grain size of the material is expressed by the average line length of the grains.
Further, the electric pulse waveform determining method module comprises an electric pulse waveform determining first evaluation means storage module and an electric pulse waveform determining second evaluation means storage module.
Further, the storage module for determining the first evaluation means of the electric pulse waveform comprises an influence rule of a pulse peak value on the grain size variation, an influence rule of a pulse width on the grain size variation, an influence rule of a pulse rising rate on the grain size variation and a first evaluation means for determining the electric pulse auxiliary welding electric pulse waveform; the first evaluation means of the electric pulse auxiliary welding electric pulse waveform refers to that when the proper electric pulse auxiliary welding electric pulse waveform is determined, the electric pulse waveform characteristic quantity within the variation range of the electric pulse waveform characteristic quantity corresponding to the larger grain size variation is selected. When the electric pulse auxiliary welding is carried out on the material, the microstructure of the material can be thinned compared with the microstructure of the material when the material is directly welded, namely the microstructure of the material after the electric pulse auxiliary welding treatment is reduced compared with the microstructure of the material when the material is directly welded. In the welding process of the material, the pulse current acts on the solidification process of the material, the dendrite formed by the crystallization of the material is broken to form a new nucleation core, the size of the microstructure can be reduced, namely the purpose of refining grains is achieved, and therefore the purpose of improving the comprehensive performance of the material is achieved. The change rule of the grain size variation with the waveform characteristic quantity of each electric pulse is mainly disclosed, for example, the grain size variation is larger in what range of the waveform characteristic quantity of the electric pulse, for example, the grain size variation is smaller in what range of the waveform characteristic quantity of the electric pulse, and at the moment, when the proper electric pulse auxiliary welding electric pulse waveform is determined, the electric pulse waveform characteristic quantity in the variation range of the waveform characteristic quantity of the electric pulse corresponding to the larger grain size variation is selected.
Further, the storage module for determining the second evaluation means of the electric pulse waveform comprises a function model module between the grain size variation and the characteristic quantity of the electric pulse waveform, a partial derivative module for solving a single characteristic quantity of the function model, and a second evaluation means for determining the electric pulse auxiliary welding electric pulse waveform; the function model module is used for fitting the grain size variation data and the three electric pulse waveform characteristic quantity data to obtain a function model between the grain size variation and the three electric pulse waveform characteristic quantities; the partial derivative module is used for solving partial derivatives of a single characteristic quantity for the function model respectively, and the larger the partial derivative is, the larger the influence of the characteristic quantity on the grain size variation is shown to be; the second evaluation means for determining the electric pulse auxiliary welding electric pulse waveform means that the larger the partial derivative is, the larger the influence of the characteristic quantity on the grain size change quantity is shown, and the characteristic quantity with the large partial derivative is taken as a starting point when determining the proper electric pulse waveform.
Further, the method for determining the waveform of the electric pulse comprises the steps of firstly, taking the characteristic quantity with the largest influence degree on the grain size variation as a first consideration factor on the basis of the influence degree of the characteristic quantity of the waveform of the electric pulse determined by the second evaluation means on the grain size variation, and then further determining the selection range of the characteristic quantity according to the first evaluation means; secondly, on the basis of the influence degree of the electric pulse waveform characteristic quantity determined by the second evaluation means on the grain size variation, taking the characteristic quantity which has the influence degree on the grain size variation second to the first consideration as a second consideration factor, and then further determining the selection range of the characteristic quantity according to the first evaluation means; then, on the basis of the influence degree of the electric pulse waveform characteristic quantity determined by the second evaluation means on the grain size variation, the characteristic quantity with the minimum influence degree on the grain size variation is taken as a third consideration factor, and then the selection range of the characteristic quantity is further determined according to the first evaluation means; and finally, selecting specific characteristic quantity values in the selection range of the three characteristic quantities to obtain the required electric pulse waveform. And selecting specific characteristic quantity values in the selection ranges of the three characteristic quantities, adjusting parameters of the electric pulse generating circuit to obtain the required electric pulse waveform, and when the required electric pulse waveform cannot be obtained by adjusting the parameters of the electric pulse generating circuit, expanding the selection range of the characteristic quantity as a third consideration factor, and if the required electric pulse waveform cannot be obtained, expanding the selection range of the characteristic quantity as a second consideration factor to obtain the required electric pulse waveform. In addition, the selection range of the circuit parameters may be expanded by replacing the components of the electric pulse generating circuit, so that a desired electric pulse waveform can be obtained.
Specifically, the process of determining the electric pulse waveform by using the electric pulse auxiliary welding electric pulse waveform determination system based on the data mining technology provided by the invention comprises the following steps:
(1) And constructing an electric pulse auxiliary welding electric pulse waveform determining system based on a data mining technology. Constructing an electric pulse auxiliary welding electric pulse waveform determining system based on a data mining technology, wherein the electric pulse auxiliary welding electric pulse waveform determining system comprises a grain size testing module, an upper computer system, a wireless transmission module, a lower computer system, an electric pulse generating circuit module and an electric pulse waveform collecting module; the upper computer system comprises an electric pulse waveform database module, an electric pulse waveform characteristic quantity acquisition module, an electric pulse waveform characteristic quantity database module, a grain size variation database module and an electric pulse waveform determination method module.
(2) The electric pulse auxiliary welding electric pulse waveform based on the data mining technology determines the connection relation and the function of each module of the system. The upper computer system is connected with the lower computer system through the wireless transmission module so as to control the electric pulse generating circuit module to generate electric pulses; the electric pulse waveform acquisition module acquires electric pulses generated by the electric pulse generation circuit module and stores electric pulse data into an electric pulse waveform database module in an upper computer system; the grain size testing module tests to obtain the grain sizes of the materials respectively in welding and electric pulse auxiliary welding, and stores the grain size variation data of the materials into a grain size variation database module in an upper computer system; the electric pulse waveform database module stores the electric pulse waveforms acquired by the electric pulse waveform acquisition module; the electric pulse waveform characteristic quantity acquisition module acquires the characteristic quantity of an electric pulse waveform; the electric pulse waveform characteristic quantity database module stores electric pulse waveform characteristic quantities; the electric pulse waveform determining method module stores the determining method of the electric pulse waveform.
The invention has the following beneficial effects:
1. the electric pulse auxiliary welding electric pulse waveform determining system based on the data mining technology, which is provided by the invention, is based on mass data, can reveal the action rule of the electric pulse waveform characteristic quantity on the grain refinement degree, and the electric pulse waveform determined on the basis can obtain a relatively ideal grain refinement effect.
2. When the electric pulse auxiliary welding electric pulse waveform determining system based on the data mining technology provided by the invention is used for determining the electric pulse waveform, the electric pulse waveform is controlled by the upper computer system, so that the workload of operators is reduced, and the experimental efficiency is improved.
3. When the electric pulse auxiliary welding electric pulse waveform determining system based on the data mining technology is used for determining the electric pulse waveform, the upper computer system is connected with the lower computer system through the wireless transmission module, so that the electric pulse generating circuit module is controlled, and the safety of an electric pulse auxiliary welding experiment can be improved.
4. The electric pulse auxiliary welding electric pulse waveform determining system based on the data mining technology is based on mass data, and ensures that the action rule of the obtained electric pulse waveform characteristic quantity on the grain size variation is reliable, so that the electric pulse waveform determined by the system provided by the invention is effective in experiment, and better experiment effect can be obtained.
Drawings
FIG. 1 is a schematic diagram of an electric pulse assisted welding electric pulse waveform determination system based on a data mining technique.
Fig. 2 is a schematic diagram of modules included in the upper computer system.
FIG. 3 is a schematic diagram of a storage module for determining a first evaluation means by an electrical pulse waveform.
FIG. 4 is a schematic diagram of a storage module for determining a second evaluation means by an electrical pulse waveform.
Fig. 5 is a schematic diagram of the waveform characteristics of the electrical pulses.
Detailed Description
The invention is further illustrated with reference to the accompanying drawings:
the electric pulse auxiliary welding electric pulse waveform determining system based on the data mining technology comprises a grain size testing module, an upper computer system, a wireless transmission module, a lower computer system, an electric pulse generating circuit module and an electric pulse waveform collecting module; the upper computer system comprises an electric pulse waveform database module, an electric pulse waveform characteristic quantity acquisition module, an electric pulse waveform characteristic quantity database module, a grain size variation database module and an electric pulse waveform determination method module; the upper computer system is connected with the lower computer system through the wireless transmission module so as to control the electric pulse generating circuit module to generate electric pulses; the electric pulse waveform acquisition module acquires the electric pulse generated by the electric pulse generation circuit module and stores the electric pulse data into an electric pulse waveform database module in an upper computer system; the grain size testing module tests to obtain the grain sizes of the materials respectively when only welding and electric pulse auxiliary welding are carried out, and the grain size variation data of the materials are stored in a grain size variation database module in an upper computer system; the electric pulse waveform database module stores the electric pulse waveform acquired by the electric pulse waveform acquisition module; the electric pulse waveform characteristic quantity acquisition module acquires the characteristic quantity of the electric pulse waveform; the electric pulse waveform characteristic quantity database module stores the electric pulse waveform characteristic quantity; the electric pulse waveform determining method module stores the determining method of the electric pulse waveform.
The process of testing the grain size of the material by the grain size testing module in the invention is as follows: and (3) acquiring the grain sizes of the materials respectively in welding and electric pulse auxiliary welding by adopting a modern material testing and analyzing technology. During direct welding and electric pulse auxiliary welding, the welding process parameters are kept unchanged, and only the electric pulse waveform is changed to research the influence rule of the electric pulse waveform characteristic quantity on the grain size of the material; the grain size variation refers to the difference of the grain sizes of the materials when only welding and electric pulse auxiliary welding are carried out respectively.
Further, the electric pulse waveform characteristic quantity data stored in the electric pulse waveform characteristic quantity database module and the grain size variation data stored in the grain size variation database module have a one-to-one correspondence relationship. In the specific implementation process of the invention, during direct welding and electric pulse auxiliary welding, welding process parameters are kept unchanged, and only the waveform of the electric pulse is changed to study the influence of the characteristic quantity of the electric pulse waveform on the grain size of the material, namely, the electric pulse waveform stored in the electric pulse waveform database module has a one-to-one correspondence with the grain size variation data stored in the grain size variation database module, namely, the electric pulse waveform characteristic quantity data stored in the electric pulse waveform characteristic quantity database module also has a one-to-one correspondence with the grain size variation data stored in the grain size variation database module. After an electric pulse waveform is determined, electric pulse auxiliary welding is carried out on the material, after the electric pulse auxiliary welding process is finished, the grain size of the material is obtained through testing, the difference value of the grain size of the material when only welding and the grain size of the material when the electric pulse auxiliary welding is carried out is obtained through calculation, meanwhile, the characteristic quantity of the electric pulse waveform is extracted, the electric pulse waveform characteristic quantity data and the grain size variation data are stored in an electric pulse waveform characteristic quantity database module and a grain size variation database module in an upper computer system respectively, the electric pulse waveform characteristic quantity data and the grain size variation data obtained in the mode have a one-to-one correspondence relation, and massive data are provided for the follow-up research of the action rule of the electric pulse waveform characteristic quantity on the grain size variation of the material.
Further, the electric pulse waveform characteristic quantity comprises a pulse peak value A, a pulse width d and a pulse rising rate k. The energy peak value of the first pulse of the electric pulse waveform is the largest, the effect on the microstructure in the material is the most obvious, and the influence rule of the characteristic quantity of the first pulse on the grain size of the microstructure in the material is mainly researched. The rate at which the pulses rise refers to how quickly the first pulse peaks, i.e., the slope of the pulse waveform. The rate of rise k of the pulses studied in the present invention is for the rate at which the first pulse rises to a peak.
Further, the grain size of the material is expressed by the average line length of the grains.
Further, the electric pulse waveform determining method module comprises a first electric pulse waveform determining and evaluating means storage module and a second electric pulse waveform determining and evaluating means storage module.
Further, the storage module for determining the first evaluation means of the electric pulse waveform comprises an influence rule of a pulse peak value on the grain size variation, an influence rule of a pulse width on the grain size variation, an influence rule of a pulse rising rate on the grain size variation and a first evaluation means for determining the electric pulse auxiliary welding electric pulse waveform; the first evaluation means of the electric pulse auxiliary welding electric pulse waveform refers to that when the proper electric pulse auxiliary welding electric pulse waveform is determined, the electric pulse waveform characteristic quantity within the variation range of the electric pulse waveform characteristic quantity corresponding to the larger grain size variation is selected. When the electric pulse auxiliary welding is carried out on the material, the microstructure of the material can be thinned compared with the microstructure of the material when the material is directly welded, namely the microstructure of the material after the electric pulse auxiliary welding treatment is reduced compared with the microstructure of the material when the material is directly welded. In the welding process of the material, pulse current acts on the solidification process of the material, dendrite formed by material crystallization is broken to form a new nucleation core, the size of microstructure can be reduced, namely the purpose of refining grains is achieved, and therefore the purpose of improving the comprehensive performance of the material is achieved. The change rule of the grain size change amount along with the change of each electric pulse waveform characteristic quantity is mainly disclosed, for example, the grain size change amount is larger in what range of the electric pulse waveform characteristic quantity, for example, the grain size change amount is smaller in what range of the electric pulse waveform characteristic quantity, and at the moment, when the proper electric pulse auxiliary welding electric pulse waveform is determined, the electric pulse waveform characteristic quantity in the electric pulse waveform characteristic quantity change range corresponding to the larger grain size change amount is selected.
Further, the storage module for determining the second evaluation means of the electric pulse waveform comprises a function model module between the grain size variation and the characteristic quantity of the electric pulse waveform, a partial derivative module for solving a single characteristic quantity of the function model, and a second evaluation means for determining the electric pulse auxiliary welding electric pulse waveform; the function model module is used for fitting the grain size variation data and the three electric pulse waveform characteristic quantity data to obtain a function model between the grain size variation and the three electric pulse waveform characteristic quantities; the partial derivative module is used for solving partial derivatives of a single characteristic quantity for the function model respectively, and the larger the partial derivative is, the larger the influence of the characteristic quantity on the grain size variation is shown to be; the second evaluation means for determining the electric pulse auxiliary welding electric pulse waveform means that the larger the partial derivative is, the larger the influence of the characteristic quantity on the grain size change quantity is shown, and the characteristic quantity with the large partial derivative is taken as a starting point when determining the proper electric pulse waveform.
Further, the method for determining the waveform of the electric pulse comprises the steps of firstly, taking the characteristic quantity with the largest influence degree on the grain size variation as a first consideration factor on the basis of the influence degree of the characteristic quantity of the waveform of the electric pulse determined by the second evaluation means on the grain size variation, and then further determining the selection range of the characteristic quantity according to the first evaluation means; secondly, on the basis of the influence degree of the electric pulse waveform characteristic quantity determined by the second evaluation means on the grain size variation, taking the characteristic quantity which has the influence degree on the grain size variation second to the first consideration as a second consideration factor, and then further determining the selection range of the characteristic quantity according to the first evaluation means; then, on the basis of the influence degree of the electric pulse waveform characteristic quantity determined by the second evaluation means on the grain size variation, the characteristic quantity with the minimum influence degree on the grain size variation is taken as a third consideration factor, and then the selection range of the characteristic quantity is further determined according to the first evaluation means; and finally, selecting specific characteristic quantity values in the selection range of the three characteristic quantities to obtain the required electric pulse waveform. And selecting specific characteristic quantity values in the selection ranges of the three characteristic quantities, adjusting parameters of the electric pulse generating circuit to obtain the required electric pulse waveform, and when the required electric pulse waveform cannot be obtained by adjusting the parameters of the electric pulse generating circuit, expanding the selection range of the characteristic quantity as a third consideration factor, and if the required electric pulse waveform cannot be obtained, expanding the selection range of the characteristic quantity as a second consideration factor to obtain the required electric pulse waveform. In addition, the selection range of the circuit parameters may be expanded by replacing the components of the electric pulse generating circuit, so that a desired electric pulse waveform can be obtained.
Specifically, the process of determining the electric pulse waveform by the electric pulse auxiliary welding electric pulse waveform determination system based on the data mining technology provided by the invention comprises the following steps:
(1) And constructing an electric pulse auxiliary welding electric pulse waveform determining system based on a data mining technology. Constructing an electric pulse auxiliary welding electric pulse waveform determining system based on a data mining technology, wherein the electric pulse auxiliary welding electric pulse waveform determining system comprises a grain size testing module, an upper computer system, a wireless transmission module, a lower computer system, an electric pulse generating circuit module and an electric pulse waveform collecting module; the upper computer system comprises an electric pulse waveform database module, an electric pulse waveform characteristic quantity acquisition module, an electric pulse waveform characteristic quantity database module, a grain size variation database module and an electric pulse waveform determination method module.
(2) The electric pulse based on the data mining technology assists the welding electric pulse waveform to determine the connection relation and the function of each module of the system. The upper computer system is connected with the lower computer system through the wireless transmission module so as to control the electric pulse generating circuit module to generate electric pulses; the electric pulse waveform acquisition module acquires electric pulses generated by the electric pulse generation circuit module and stores electric pulse data into an electric pulse waveform database module in an upper computer system; the grain size testing module tests to obtain the grain sizes of the materials respectively when only welding and electric pulse auxiliary welding are carried out, and the grain size variation data of the materials are stored in a grain size variation database module in an upper computer system; the electric pulse waveform database module stores the electric pulse waveform collected by the electric pulse waveform collecting module; the electric pulse waveform characteristic quantity acquisition module acquires the characteristic quantity of an electric pulse waveform; the electric pulse waveform characteristic quantity database module stores electric pulse waveform characteristic quantities; the electric pulse waveform determining method module stores the determining method of the electric pulse waveform.
The embodiments described in this specification are merely illustrative of implementations of the inventive concept and the scope of the present invention should not be considered limited to the specific forms set forth in the embodiments but rather by the equivalents thereof as may occur to those skilled in the art upon consideration of the present inventive concept.
Claims (4)
1. The electric pulse auxiliary welding electric pulse waveform determining system based on the data mining technology comprises a grain size testing module, an upper computer system, a wireless transmission module, a lower computer system, an electric pulse generating circuit module and an electric pulse waveform collecting module; the upper computer system comprises an electric pulse waveform database module, an electric pulse waveform characteristic quantity acquisition module, an electric pulse waveform characteristic quantity database module, a grain size variation database module and an electric pulse waveform determination method module; the upper computer system is connected with the lower computer system through the wireless transmission module so as to control the electric pulse generating circuit module to generate electric pulses; the electric pulse waveform acquisition module acquires the electric pulse generated by the electric pulse generation circuit module and stores the electric pulse data into an electric pulse waveform database module in an upper computer system; the grain size testing module tests to obtain the grain sizes of the materials respectively in welding and electric pulse auxiliary welding, and stores the grain size variation data of the materials into a grain size variation database module in an upper computer system; the electric pulse waveform database module stores the electric pulse waveform acquired by the electric pulse waveform acquisition module; the electric pulse waveform characteristic quantity acquisition module acquires the characteristic quantity of the electric pulse waveform; the electric pulse waveform characteristic quantity database module stores the electric pulse waveform characteristic quantity; the electric pulse waveform determining method module stores the determining method of the electric pulse waveform;
the electric pulse waveform determining method module comprises an electric pulse waveform determining first evaluating means storage module and an electric pulse waveform determining second evaluating means storage module;
the storage module of the electric pulse waveform determination first evaluation means comprises an influence rule of a pulse peak value on grain size variation, an influence rule of a pulse width on grain size variation, an influence rule of a pulse rising rate on grain size variation and a first evaluation means for determining the electric pulse auxiliary welding electric pulse waveform; the first evaluation means of the electric pulse auxiliary welding electric pulse waveform refers to selecting the electric pulse waveform characteristic quantity within the electric pulse waveform characteristic quantity variation range corresponding to the larger grain size variation quantity when determining the proper electric pulse auxiliary welding electric pulse waveform;
the electric pulse waveform determination second evaluation means storage module comprises a function model module between grain size variation and electric pulse waveform characteristic quantity, a partial derivative module for solving single characteristic quantity of the function model and a second evaluation means for determining the electric pulse auxiliary welding electric pulse waveform; the function model module is used for fitting the grain size variation data and the three electric pulse waveform characteristic quantity data to obtain a function model between the grain size variation and the three electric pulse waveform characteristic quantities; the partial derivative module is used for respectively solving partial derivatives of single characteristic quantity on the function model, and the larger the partial derivatives are, the larger the influence of the characteristic quantity on the grain size variation is shown; the second evaluation means for determining the electric pulse auxiliary welding electric pulse waveform means that the larger the partial derivative is, the larger the influence of the characteristic quantity on the grain size variation is shown to be, and when a proper electric pulse waveform is determined, the characteristic quantity with the large partial derivative is firstly taken as a starting point;
firstly, based on the influence degree of the electric pulse waveform characteristic quantity determined by the second evaluation means on the grain size variation, taking the characteristic quantity with the maximum influence degree on the grain size variation as a first consideration factor, and then further determining the selection range of the characteristic quantity according to the first evaluation means; secondly, on the basis of the influence degree of the electric pulse waveform characteristic quantity determined by the second evaluation means on the grain size variation, taking the characteristic quantity which has the influence degree on the grain size variation second to the first consideration as a second consideration factor, and then further determining the selection range of the characteristic quantity according to the first evaluation means; then, on the basis of the influence degree of the electric pulse waveform characteristic quantity determined by the second evaluation means on the grain size variation, the characteristic quantity with the minimum influence degree on the grain size variation is taken as a third consideration factor, and then the selection range of the characteristic quantity is further determined according to the first evaluation means; and finally, selecting specific characteristic quantity values in the selection range of the three characteristic quantities to obtain the required electric pulse waveform.
2. The electric pulse assisted welding electric pulse waveform determining system based on the data mining technology as claimed in claim 1, wherein: the electric pulse waveform characteristic quantity data stored in the electric pulse waveform characteristic quantity database module and the grain size variation data stored in the grain size variation database module have a one-to-one correspondence relationship.
3. The electric pulse assisted welding electric pulse waveform determination system based on the data mining technology as claimed in claim 1, wherein: the waveform characteristic quantity of the electric pulse comprises a pulse peak value A, a pulse width d and a pulse rising rate k.
4. The electric pulse assisted welding electric pulse waveform determining system based on the data mining technology as claimed in claim 1, wherein: the grain size of the material is expressed by the average line length of the grains.
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| JPH08150515A (en) * | 1994-11-24 | 1996-06-11 | Sodick Co Ltd | Wire discharge finishing work method and power source for wire discharge finishing work |
| CN101421069A (en) * | 2006-04-13 | 2009-04-29 | 林肯环球公司 | Metal cored electrode for open root pass welding |
| CN102500901A (en) * | 2011-11-16 | 2012-06-20 | 上海交通大学 | Composite pulsation spot welding process and system |
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Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH08150515A (en) * | 1994-11-24 | 1996-06-11 | Sodick Co Ltd | Wire discharge finishing work method and power source for wire discharge finishing work |
| CN101421069A (en) * | 2006-04-13 | 2009-04-29 | 林肯环球公司 | Metal cored electrode for open root pass welding |
| CN102500901A (en) * | 2011-11-16 | 2012-06-20 | 上海交通大学 | Composite pulsation spot welding process and system |
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