CN116166073B - Power battery heat insulation cotton cutting temperature control system with learning function - Google Patents
Power battery heat insulation cotton cutting temperature control system with learning function Download PDFInfo
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- CN116166073B CN116166073B CN202310456927.5A CN202310456927A CN116166073B CN 116166073 B CN116166073 B CN 116166073B CN 202310456927 A CN202310456927 A CN 202310456927A CN 116166073 B CN116166073 B CN 116166073B
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- G—PHYSICS
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- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D23/00—Control of temperature
- G05D23/19—Control of temperature characterised by the use of electric means
- G05D23/20—Control of temperature characterised by the use of electric means with sensing elements having variation of electric or magnetic properties with change of temperature
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
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- Y02E60/10—Energy storage using batteries
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Abstract
The invention relates to the technical field of cutting temperature control of heat-insulating cotton of a power battery, in particular to a cutting temperature control system of heat-insulating cotton of a power battery with a learning function. The system comprises a data monitoring platform, an inferred relation calculation module and a data association degree simulation module. According to the invention, various data monitoring rules of the cutting process of the heat-insulating cotton of the power battery are established through the data monitoring platform, the laser temperature, the time spent by cutting work in the cutting process, the cutting effect and the thickness of the heat-insulating cotton of the power battery are monitored in real time, the relationship calculation module is deduced to combine various monitored data to obtain a relationship calculation formula, the data association degree simulation module is combined with the relationship calculation formula to determine the relationship between the thickness of the heat-insulating cotton of the power battery and various cutting data, the cutting data corresponding to the heat-insulating cotton of the power battery with different thicknesses are simulated in real time, the corresponding cutting data are provided for the heat-insulating cotton of the power battery with different thicknesses, and the autonomous learning function of the heat-insulating cotton cutting system of the battery is realized.
Description
Technical Field
The invention relates to the technical field of cutting temperature control of heat-insulating cotton of a power battery, in particular to a cutting temperature control system of heat-insulating cotton of a power battery with a learning function.
Background
Battery insulation wool is a porous asbestos product commonly used to protect batteries and other electronic and electrical appliances from moisture, excessive temperatures, or excessive low temperatures that could affect their performance. The asbestos product has good heat insulation performance and can resist cold and warm; the protective performance is excellent, and the battery and other electronic appliances can be effectively prevented from generating moisture, vapor, catalyst, oil dirt and the like; excellent fire resistance and can effectively inhibit fire.
In the process of processing battery heat insulation cotton, the battery heat insulation cotton needs to be cut for many times to adapt to different use occasions, most of the existing battery heat insulation cotton is cut through laser, a cutting path is instantly melted through the high temperature released by the laser, and the battery heat insulation cotton cutting work is realized.
In order to make corresponding cutting conditions for battery heat insulation cottons with different thicknesses, a power battery heat insulation cottons cutting temperature control system with a learning function is needed.
Disclosure of Invention
The invention aims to provide a power battery heat insulation cotton cutting temperature control system with a learning function so as to solve the problems in the background technology.
In order to achieve the above purpose, the power battery heat insulation cotton cutting temperature control system with a learning function is provided, and comprises a data monitoring platform, a real-time monitoring module, an inferred relation calculation module and a data association degree simulation module;
the data monitoring platform is used for establishing various data monitoring rules of the cutting process of the heat-insulating cotton of the power battery, monitoring the laser temperature in the cutting process, the time spent by the cutting work, the cutting effect and the thickness of the heat-insulating cotton of the power battery in real time, and obtaining various monitoring data;
the real-time monitoring module is provided with camera monitoring equipment and is used for monitoring the cutting effect and the thickness of the heat insulation cotton of the power battery to be cut in real time;
the output end of the data monitoring platform is connected with the input end of the inferred relation calculation module, and the inferred relation calculation module combines all monitored data to obtain a relation calculation formula:
；
wherein the method comprises the steps ofThe cutting effect of the heat insulation cotton of the power battery after cutting is +.>For the temperature during cutting, +.>The thickness of the heat insulation cotton for the power battery is->Is hardness coefficient, is related to heat insulation cotton material of power battery, < + >>Is the cutting time;
the output end of the inferred relation calculation module is connected with the input end of the data association degree simulation module, the data association degree simulation module is combined with a relation calculation formula to determine the relation between the thickness of the heat insulation cotton of the power battery and various cutting data, and cutting data corresponding to the heat insulation cotton of the power battery with different thicknesses are simulated in real time.
As a further improvement of the technical scheme, the data monitoring platform comprises a cutting temperature monitoring module, a cutting time monitoring module, a cutting effect identification module and a heat insulation film thickness monitoring module;
the cutting temperature monitoring module is provided with a temperature sensor and is used for monitoring the temperature of laser projected by the laser cutting head in real time;
the output end of the cutting temperature monitoring module is connected with the input end of the cutting time monitoring module, and the cutting time monitoring module identifies a cutting initial point and a cutting end point and determines cutting time;
the output end of the cutting time monitoring module is connected with the input end of the cutting effect identification module, the input end of the cutting effect identification module is connected with the output end of the real-time monitoring module, the cutting effect identification module identifies the number of defect points formed in the cut area, and the cutting effect is determined according to the number of the defect points;
the output end of the cutting effect identification module is connected with the input end of the heat insulation film thickness monitoring module, the input end of the heat insulation film thickness monitoring module is connected with the output end of the real-time monitoring module, and the heat insulation film thickness monitoring module is combined with camera monitoring equipment to determine the thickness of heat insulation cotton of the power battery which is required to be cut currently.
As a further improvement of the technical scheme, the cutting effect recognition module comprises a shooting residual defect point comparison unit and a residual defect point image database, wherein the residual defect point image database is used for pre-storing heat insulation cotton cutting residual defect point image data of each power battery, the output end of the residual defect point image database is connected with the input end of the shooting residual defect point comparison unit, and the shooting residual defect point comparison unit combines the residual defect point image data to compare residual defect point characteristics of each shooting image, so that the type of the residual defect point of the shooting image is determined.
As a further improvement of the technical scheme, the shooting residual point comparison unit adopts a characteristic point comparison algorithm, and the algorithm formula is as follows:
；
；
；
wherein the method comprises the steps ofFor a pre-stored set of feature points of the residual image, < >>To->Each feature point is a prestored incomplete image; />For the defect feature point set of the shooting image which needs to be compared currently, < >>To->For each feature point of the defect of the shooting image which needs to be compared currently, < >>Is a feature point comparison function,)>For the characteristic rate of coordination->For the coincidence characteristic rate threshold value, when the coincidence characteristic rate +>Less than the coincidence feature rate threshold->At the time, the feature point comparison function +.>The output is 0, which indicates that the defect of the current shooting image does not belong to the pre-stored defect, when the coincidence characteristic rate is +>Not less than the coincidence characteristic rate threshold +.>At the time, the feature point comparison function +.>The output is 1, which indicates that the defect of the current shot image belongs to the pre-stored defect.
As a further improvement of the technical scheme, the input end of the incomplete image database is connected with an incomplete supplementary recording unit, and the incomplete supplementary recording unit is used for carrying out the incomplete supplementary recording in real time.
As a further improvement of the technical scheme, the heat insulation film thickness monitoring module comprises a heat insulation film upper surface and lower surface determining unit and a heat insulation film thickness measuring unit, wherein the heat insulation film upper surface and lower surface determining unit is used for monitoring the roughness of the heat insulation film upper surface and lower surface and distinguishing the heat insulation film upper surface and lower surface, the output end of the heat insulation film upper surface and lower surface determining unit is connected with the input end of the heat insulation film thickness measuring unit, and the heat insulation film thickness measuring unit measures the heat insulation film thickness through the camera monitoring equipment according to the roughness of the heat insulation film upper surface and lower surface.
As a further improvement of the present technical solution, the method for measuring the thickness of the thermal insulation film by the thermal insulation film thickness measuring unit includes the steps of:
s1, regulating and controlling camera monitoring equipment, and capturing one surface of heat insulation cotton of a power battery;
s2, moving the camera monitoring equipment to enable the camera monitoring equipment to horizontally project to a heat insulation cotton capturing surface of the power battery;
s3, maintaining the horizontal position of the camera monitoring equipment, adjusting the angle of the camera monitoring equipment, and enabling the camera monitoring equipment to project to the other surface of the heat insulation cotton of the power battery;
s4, determining an angle adjustment value of the camera monitoring equipment, and calculating the thickness of the heat insulation film according to a trigonometric function.
As a further improvement of the technical scheme, the inferred relation calculation module comprises a forward and reverse influence determination unit and a rule integration summarizing unit, wherein the forward and reverse influence determination unit is used for determining forward influence conditions and reverse influence conditions for influencing cutting of heat insulation cotton of the power battery, the output end of the forward and reverse influence determination unit is connected with the input end of the rule integration summarizing unit, and the rule integration summarizing unit determines influence rules according to the forward influence conditions and the reverse influence conditions.
As a further improvement of the technical scheme, the input end of the forward and reverse influence determining unit is connected with an influence range planning unit, and the influence range planning unit is used for determining the influence range corresponding to each influence condition.
Compared with the prior art, the invention has the beneficial effects that:
1. in the power battery heat insulation cotton cutting temperature control system with the learning function, various data monitoring rules of the power battery heat insulation cotton cutting process are established through the data monitoring platform, the laser temperature in the cutting process, the time spent by cutting work, the cutting effect and the thickness of the cut power battery heat insulation cotton are monitored in real time, the relationship calculation module is inferred to combine various monitored data to obtain a relationship calculation formula, the data association degree simulation module is combined with the relationship calculation formula to determine the relationship between the thickness of the power battery heat insulation cotton and various cutting data, the cutting data corresponding to the power battery heat insulation cotton with different thicknesses are simulated in real time, the corresponding cutting data are provided for the power battery heat insulation cotton with different thicknesses, and the autonomous learning function of the battery heat insulation cotton cutting system is realized.
2. In the power battery heat insulation cotton cutting temperature control system with the learning function, forward influence conditions and reverse influence conditions for influencing the cutting of the power battery heat insulation cotton are determined through the forward and reverse influence determining unit, and then the rule integration summarizing unit determines influence rules according to the forward influence conditions and the reverse influence conditions so as to carry out cutting matching work of the power battery heat insulation cotton with different thicknesses in later period.
3. In the power battery heat insulation cotton cutting temperature control system with the learning function, the influence range corresponding to each influence condition is determined through the influence range planning unit, and the adaptive influence range is planned for each influence condition so as to carry out rule summarization in the later period.
Drawings
FIG. 1 is a schematic diagram of the overall structure of the present invention;
FIG. 2 is a schematic diagram of a cutting effect recognition module according to the present invention;
FIG. 3 is a schematic diagram of a thermal insulation film thickness monitoring module according to the present invention;
FIG. 4 is a schematic diagram of an inferred relationship calculation module according to the present invention.
The meaning of each reference sign in the figure is:
10. a cutting temperature monitoring module;
20. a cutting time monitoring module;
30. a cutting effect identification module; 310. shooting a residual point comparison unit; 320. a defect image database; 330. a defect repair unit;
40. a thermal insulation film thickness monitoring module; 410. a heat insulating film upper and lower surface determining unit; 420. a heat insulation film thickness measuring unit;
50. a real-time monitoring module;
60. an inferred relationship calculation module; 610. a forward/reverse influence determination unit; 620. a rule integration summarization unit; 630. an influence range planning unit;
70. and the data association degree simulation module.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
In the description of the present invention, it should be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", "clockwise", "counterclockwise", etc. indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings are merely for convenience in describing the present invention and simplifying the description, and do not indicate or imply that the apparatus or elements referred to must have a specific orientation, be configured and operated in a specific orientation, and thus should not be construed as limiting the present invention.
Referring to fig. 1-4, a power battery heat insulation cotton cutting temperature control system with learning function is provided, which comprises a data monitoring platform, a real-time monitoring module 50, an inferred relation calculation module 60 and a data association degree simulation module 70;
the data monitoring platform is used for establishing various data monitoring rules of the cutting process of the heat-insulating cotton of the power battery, monitoring the laser temperature in the cutting process, the time spent by the cutting work, the cutting effect and the thickness of the heat-insulating cotton of the power battery in real time, and obtaining various monitoring data;
the input end of the data monitoring platform and the real-time monitoring module 50 are provided with camera monitoring equipment, and the real-time monitoring module 50 monitors the cutting effect and the thickness of the heat insulation cotton of the cut power battery in real time;
the output end of the data monitoring platform is connected with the input end of the inferred relation calculation module 60, and the inferred relation calculation module 60 combines the monitored data items to obtain a relation calculation formula:
；
wherein the method comprises the steps ofThe cutting effect of the heat insulation cotton of the power battery after cutting is +.>For the temperature during cutting, +.>The thickness of the heat insulation cotton for the power battery is->Is hardness coefficient, is related to heat insulation cotton material of power battery, < + >>Is the cutting time;
the output end of the inferred relation calculation module 60 is connected with the input end of the data association degree simulation module 70, the data association degree simulation module 70 is combined with a relation calculation formula to determine the relation between the thickness of the heat insulation cotton of the power battery and various cutting data, and the cutting data corresponding to the heat insulation cotton of the power battery with different thicknesses are simulated in real time.
When the device is specifically used, in the process of cutting the heat-insulating cotton of the power battery, firstly, each data monitoring rule of the heat-insulating cotton of the power battery is established through the data monitoring platform, the laser temperature in the cutting process, the time spent by the cutting work, the cutting effect and the thickness of the heat-insulating cotton of the power battery are monitored in real time, each monitoring data is obtained, the real-time monitoring module 50 is provided with camera monitoring equipment, the cutting effect and the thickness of the heat-insulating cotton of the power battery are monitored in real time, an automatic data monitoring function is realized, the relationship calculation module 60 is inferred to combine each monitored data, a relationship calculation formula is obtained, the data association degree simulation module 70 is combined with the relationship calculation formula, the relationship between the thickness of the heat-insulating cotton of the power battery and each cutting data is determined, the cutting data corresponding to the heat-insulating cotton of the power battery with different thicknesses are simulated in real time, the corresponding cutting data is provided for the heat-insulating cotton of the power battery with different thicknesses, and the autonomous learning function of the heat-insulating cotton cutting system of the battery is realized.
In addition, the data monitoring platform comprises a cutting temperature monitoring module 10, a cutting time monitoring module 20, a cutting effect identification module 30 and a heat insulation film thickness monitoring module 40;
the cutting temperature monitoring module 10 is provided with a temperature sensor and monitors the temperature of laser projected by the laser cutting head in real time;
the output end of the cutting temperature monitoring module 10 is connected with the input end of the cutting time monitoring module 20, and the cutting time monitoring module 20 identifies the cutting initial point and the cutting end point and determines the cutting time;
the output end of the cutting time monitoring module 20 is connected with the input end of the cutting effect identification module 30, the input end of the cutting effect identification module 30 is connected with the output end of the real-time monitoring module 50, the cutting effect identification module 30 identifies the number of defect points formed in the cut area, and the cutting effect is determined according to the number of the defect points;
the output end of the cutting effect identification module 30 is connected with the input end of the heat insulation film thickness monitoring module 40, the input end of the heat insulation film thickness monitoring module 40 is connected with the output end of the real-time monitoring module 50, and the heat insulation film thickness monitoring module 40 is combined with camera monitoring equipment to determine the thickness of heat insulation cotton of the power battery which is required to be cut currently.
When the device is specifically used, in the process of monitoring the cutting data of the heat-insulating cotton of the power battery, the temperature sensor is configured through the cutting temperature monitoring module 10, the laser temperature projected by the laser cutting head is monitored in real time, the cutting time monitoring module 20 identifies the cutting initial point and the cutting end point, the cutting time is determined, the cutting effect identification module 30 identifies the number of defect points formed in the area after cutting, the cutting effect is determined according to the number of defect points, namely the number of position points with gaps in the cutting gap, then the thickness of the heat-insulating cotton of the power battery which is required to be cut is determined through the heat-insulating film thickness monitoring module 40 and the camera monitoring equipment, and the cutting data of each power battery heat-insulating cotton are recorded in real time for the inference of association degree in the later period.
The cutting effect recognition module 30 further includes a residual image data base 320 and a residual image data base 320, wherein the residual image data base 320 is used for pre-storing residual image data of each power battery heat insulation cotton cutting, the output end of the residual image data base 320 is connected with the input end of the residual image data comparing unit 310, and the residual image data comparing unit 310 combines the residual image data to compare the residual image characteristics of each photographed image, so as to determine the residual image type. In the process of cutting the heat-insulating cotton of the power battery, cutting defect point image data of each heat-insulating cotton of the power battery, namely cutting defect point image information which appears before, are prestored through a defect point image database 320, and then a shooting defect point comparison unit 310 combines the defect point image data, compares defect point characteristics of each shooting image, and determines the type of the defect point of the shooting image.
Still further, the shot residual defect comparing unit 310 adopts a feature point comparing algorithm, and the algorithm formula is as follows:
；
；
；
wherein the method comprises the steps ofFor a pre-stored set of feature points of the residual image, < >>To->Each feature point is a prestored incomplete image; />For the defect feature point set of the shooting image which needs to be compared currently, < >>To->For each feature point of the defect of the shooting image which needs to be compared currently, < >>Is a feature point comparison function,)>For the characteristic rate of coordination->For the coincidence characteristic rate threshold value, when the coincidence characteristic rate +>Less than the coincidence feature rate threshold->When the feature point comparison function output is 0, the defect of the current shooting image is not the pre-stored defect, and when the coincidence feature rate is +.>Not less than the coincidence characteristic rate threshold +.>At the time, the feature point comparison function +.>The output is 1, which indicates that the defect of the current shooting image belongs to the pre-storageIncomplete.
Since the defect occurrence type is related to the conditions such as the laser temperature, the thickness of the heat insulation cotton of the power battery, the cutting time and the like, when the conditions are changed, the defect type is also changed, specifically, the input end of the defect image database 320 is connected with the defect supplementary recording unit 330, the defect supplementary recording unit 330 is used for carrying out the defect supplementary recording in real time, and the defect supplementary recording is carried out through the defect supplementary recording unit 330, so that the defect image data is updated in real time.
In addition, the insulation film thickness monitoring module 40 includes an insulation film upper and lower determining unit 410 and an insulation film thickness measuring unit 420, the insulation film upper and lower determining unit 410 is used for monitoring the roughness of the upper and lower surfaces of the insulation film, the upper and lower surfaces of the insulation film are distinguished, the output end of the insulation film upper and lower determining unit 410 is connected with the input end of the insulation film thickness measuring unit 420, the insulation film thickness measuring unit 420 measures the insulation film thickness through the image pickup monitoring device according to the roughness of the upper and lower surfaces of the insulation film, in the insulation film thickness monitoring process, the roughness of the upper and lower surfaces of the insulation film is monitored through the insulation film upper and lower determining unit 410 due to the difference of the roughness of the upper and lower surfaces of the insulation film, then the insulation film thickness measuring unit 420 measures the insulation film thickness through the image pickup monitoring device according to the roughness of the upper and lower surfaces of the insulation film.
Further, the method for measuring the thickness of the insulation film by the insulation film thickness measuring unit 420 includes the steps of:
s1, regulating and controlling camera monitoring equipment, and capturing one surface of heat insulation cotton of a power battery;
s2, moving the camera monitoring equipment to enable the camera monitoring equipment to horizontally project to a heat insulation cotton capturing surface of the power battery;
s3, maintaining the horizontal position of the camera monitoring equipment, adjusting the angle of the camera monitoring equipment, and enabling the camera monitoring equipment to project to the other surface of the heat insulation cotton of the power battery;
s4, determining an angle adjustment value of the camera monitoring equipment, and calculating the thickness of the heat insulation film according to a trigonometric function.
Firstly, capturing one surface of heat insulation cotton of a power battery by regulating and controlling the image capturing monitoring equipment, moving the image capturing monitoring equipment at the moment, horizontally projecting the image capturing monitoring equipment to the capturing surface of the heat insulation cotton of the power battery, then keeping the horizontal position of the image capturing monitoring equipment, adjusting the angle of the image capturing monitoring equipment, enabling the image capturing monitoring equipment to project to the other surface of the heat insulation cotton of the power battery, forming a right triangle by the capturing path of the image capturing monitoring equipment twice and the side surface of the heat insulation cotton of the power battery at the moment, then determining the angle adjustment value of the image capturing monitoring equipment, and calculating the thickness of the heat insulation film according to the trigonometric function.
Since the conditions affecting the cutting operation of the heat insulation cotton of the power battery are different in the types of the effects, for example, the higher the temperature is, the higher the cutting efficiency is, the higher the trimming surface uniformity is, and the thickness of the heat insulation cotton of the power battery is inversely proportional to the cutting efficiency of the heat insulation cotton of the power battery, still further, the inferred relation calculating module 60 comprises a forward and reverse effect determining unit 610 and a rule integration summarizing unit 620, the forward and reverse effect determining unit 610 is used for determining the forward effect condition and the reverse effect condition affecting the cutting operation of the heat insulation cotton of the power battery, the output end of the forward and reverse effect determining unit 610 is connected with the input end of the rule integration summarizing unit 620, the rule integration summarizing unit 620 determines the effect rule according to the forward effect condition and the reverse effect condition, and then the rule integration summarizing unit 620 determines the effect rule according to the forward effect condition and the reverse effect condition, so that the cutting operation of the heat insulation cotton of the power battery with different thicknesses is matched.
In the actual monitoring process, the conditions affecting the cutting operation of the heat insulation cotton of the power battery are not completely positively or reversely influenced, but are positively or reversely influenced within a certain range, when the influence range is broken through, the influence type is changed, for example, the cutting temperature is positively influenced within a certain range, the cutting efficiency is higher as the temperature is higher, but once the temperature breaks through the influence range, the cutting surface temperature is too high to cause defects to increase and reversely influenced, in addition, the input end of the positive and negative influence determining unit 610 is connected with the influence range planning unit 630, the influence range planning unit 630 is used for determining the influence range corresponding to each influence condition, the influence range corresponding to each influence condition is determined through the influence range planning unit 630, and the adapted influence range is planned for each influence condition so as to regularly summarize the later period.
The foregoing has shown and described the basic principles, principal features and advantages of the invention. It will be understood by those skilled in the art that the present invention is not limited to the above-described embodiments, and that the above-described embodiments and descriptions are only preferred embodiments of the present invention, and are not intended to limit the invention, and that various changes and modifications may be made therein without departing from the spirit and scope of the invention as claimed. The scope of the invention is defined by the appended claims and equivalents thereof.
Claims (9)
1. Power battery thermal-insulated cotton temperature control system that cuts with study function, its characterized in that: the system comprises a data monitoring platform, a real-time monitoring module (50), an inferred relation calculation module (60) and a data association degree simulation module (70);
the data monitoring platform is used for establishing various data monitoring rules of the cutting process of the heat-insulating cotton of the power battery, monitoring the laser temperature in the cutting process, the time spent by the cutting work, the cutting effect and the thickness of the heat-insulating cotton of the power battery in real time, and obtaining various monitoring data;
the input end of the data monitoring platform and the real-time monitoring module (50), wherein the real-time monitoring module (50) is provided with camera monitoring equipment for monitoring the cutting effect and the thickness of the heat insulation cotton of the cut power battery in real time;
the output end of the data monitoring platform is connected with the input end of the inferred relation calculation module (60), and the inferred relation calculation module (60) combines all monitored data to obtain a relation calculation formula:
；
wherein the method comprises the steps ofThe cutting effect of the heat insulation cotton of the power battery after cutting is +.>For the temperature during cutting, +.>The thickness of the heat insulation cotton for the power battery is->Is the hardness coefficient, is related to the heat insulation cotton material of the power battery,is the cutting time;
the output end of the inferred relation calculation module (60) is connected with the input end of the data association degree simulation module (70), and the data association degree simulation module (70) is combined with a relation calculation formula to determine the relation between the thickness of the heat insulation cotton of the power battery and various cutting data, and the cutting data corresponding to the heat insulation cotton of the power battery with different thicknesses are simulated in real time.
2. The power battery heat insulation cotton cutting temperature control system with learning function according to claim 1, wherein: the data monitoring platform comprises a cutting temperature monitoring module (10), a cutting time monitoring module (20), a cutting effect identification module (30) and a heat insulation film thickness monitoring module (40);
the cutting temperature monitoring module (10) is provided with a temperature sensor and is used for monitoring the temperature of laser projected by the laser cutting head in real time;
the output end of the cutting temperature monitoring module (10) is connected with the input end of the cutting time monitoring module (20), and the cutting time monitoring module (20) identifies a cutting initial point and a cutting end point and determines cutting time;
the output end of the cutting time monitoring module (20) is connected with the input end of the cutting effect identification module (30), the input end of the cutting effect identification module (30) is connected with the output end of the real-time monitoring module (50), the cutting effect identification module (30) identifies the number of defect points formed in the cut area, and the cutting effect is determined according to the number of the defect points;
the output end of the cutting effect identification module (30) is connected with the input end of the heat insulation film thickness monitoring module (40), the input end of the heat insulation film thickness monitoring module (40) is connected with the output end of the real-time monitoring module (50), and the heat insulation film thickness monitoring module (40) is combined with camera monitoring equipment to determine the thickness of heat insulation cotton of the power battery which is required to be cut currently.
3. The power battery heat insulation cotton cutting temperature control system with learning function according to claim 2, wherein: the cutting effect identification module (30) comprises a shooting residual point comparison unit (310) and a residual point image database (320), wherein the residual point image database (320) is used for pre-storing heat insulation cotton cutting residual point image data of each power battery, the output end of the residual point image database (320) is connected with the input end of the shooting residual point comparison unit (310), and the shooting residual point comparison unit (310) combines the residual point image data to compare the residual point characteristics of each shooting image and determine the type of the residual point of the shooting image.
4. The power cell heat insulation cotton cutting temperature control system with learning function according to claim 3, wherein: the shooting residual point comparison unit (310) adopts a characteristic point comparison algorithm, and the algorithm formula is as follows:
；
；
；
wherein the method comprises the steps ofFor a pre-stored set of feature points of the residual image, < >>To->Each feature point is a prestored incomplete image;for the defect feature point set of the shooting image which needs to be compared currently, < >>To->For each feature point of the defect of the shooting image which needs to be compared currently, < >>Is a feature point comparison function,)>For the characteristic rate of coordination->For the coincidence characteristic rate threshold value, when the coincidence characteristic rate +>Less than the coincidence feature rate threshold->At the time, the feature point comparison function +.>The output is 0, which indicates that the defect of the current shooting image does not belong to the pre-stored defect, when the coincidence characteristic rate is +>Not less than the coincidence characteristic rate threshold +.>At the time, the feature point comparison function +.>The output is 1, which indicates that the defect of the current shot image belongs to the pre-stored defect.
5. The power cell heat insulation cotton cutting temperature control system with learning function according to claim 3, wherein: the input end of the incomplete image database (320) is connected with an incomplete supplementary recording unit (330), and the incomplete supplementary recording unit (330) is used for carrying out the incomplete supplementary recording in real time.
6. The power battery heat insulation cotton cutting temperature control system with learning function according to claim 2, wherein: the heat insulation film thickness monitoring module (40) comprises a heat insulation film upper and lower surface determining unit (410) and a heat insulation film thickness measuring unit (420), wherein the heat insulation film upper and lower surface determining unit (410) is used for monitoring the roughness of the upper and lower surfaces of the heat insulation film and distinguishing the upper and lower surfaces of the heat insulation film, the output end of the heat insulation film upper and lower surface determining unit (410) is connected with the input end of the heat insulation film thickness measuring unit (420), and the heat insulation film thickness measuring unit (420) measures the heat insulation film thickness through camera monitoring equipment according to the roughness of the upper and lower surfaces of the heat insulation film.
7. The power cell heat insulation cotton cutting temperature control system with learning function according to claim 6, wherein: the method for measuring the thickness of the heat insulation film by the heat insulation film thickness measuring unit (420) comprises the following steps:
s1, regulating and controlling camera monitoring equipment, and capturing one surface of heat insulation cotton of a power battery;
s2, moving the camera monitoring equipment to enable the camera monitoring equipment to horizontally project to a heat insulation cotton capturing surface of the power battery;
s3, maintaining the horizontal position of the camera monitoring equipment, adjusting the angle of the camera monitoring equipment, and enabling the camera monitoring equipment to project to the other surface of the heat insulation cotton of the power battery;
s4, determining an angle adjustment value of the camera monitoring equipment, and calculating the thickness of the heat insulation film according to a trigonometric function.
8. The power battery heat insulation cotton cutting temperature control system with learning function according to claim 1, wherein: the inference relation calculation module (60) comprises a forward and reverse influence determination unit (610) and a rule integration summarizing unit (620), wherein the forward and reverse influence determination unit (610) is used for determining a forward influence condition and a reverse influence condition for influencing the cutting of heat insulation cotton of the power battery, the output end of the forward and reverse influence determination unit (610) is connected with the input end of the rule integration summarizing unit (620), and the rule integration summarizing unit (620) determines an influence rule according to the forward influence condition and the reverse influence condition.
9. The power cell heat insulation cotton cutting temperature control system with learning function according to claim 8, wherein: the input end of the forward and reverse influence determining unit (610) is connected with an influence range planning unit (630), and the influence range planning unit (630) is used for determining the influence range corresponding to each influence condition.
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