CN116100790B - Full-automatic intelligent bottle blowing machine based on cloud platform - Google Patents
Full-automatic intelligent bottle blowing machine based on cloud platform Download PDFInfo
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- CN116100790B CN116100790B CN202310384972.4A CN202310384972A CN116100790B CN 116100790 B CN116100790 B CN 116100790B CN 202310384972 A CN202310384972 A CN 202310384972A CN 116100790 B CN116100790 B CN 116100790B
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B29—WORKING OF PLASTICS; WORKING OF SUBSTANCES IN A PLASTIC STATE IN GENERAL
- B29C—SHAPING OR JOINING OF PLASTICS; SHAPING OF MATERIAL IN A PLASTIC STATE, NOT OTHERWISE PROVIDED FOR; AFTER-TREATMENT OF THE SHAPED PRODUCTS, e.g. REPAIRING
- B29C49/00—Blow-moulding, i.e. blowing a preform or parison to a desired shape within a mould; Apparatus therefor
- B29C49/42—Component parts, details or accessories; Auxiliary operations
- B29C49/78—Measuring, controlling or regulating
- B29C49/783—Measuring, controlling or regulating blowing pressure
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B29—WORKING OF PLASTICS; WORKING OF SUBSTANCES IN A PLASTIC STATE IN GENERAL
- B29C—SHAPING OR JOINING OF PLASTICS; SHAPING OF MATERIAL IN A PLASTIC STATE, NOT OTHERWISE PROVIDED FOR; AFTER-TREATMENT OF THE SHAPED PRODUCTS, e.g. REPAIRING
- B29C49/00—Blow-moulding, i.e. blowing a preform or parison to a desired shape within a mould; Apparatus therefor
- B29C49/42—Component parts, details or accessories; Auxiliary operations
- B29C49/78—Measuring, controlling or regulating
- B29C49/786—Temperature
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B29—WORKING OF PLASTICS; WORKING OF SUBSTANCES IN A PLASTIC STATE IN GENERAL
- B29C—SHAPING OR JOINING OF PLASTICS; SHAPING OF MATERIAL IN A PLASTIC STATE, NOT OTHERWISE PROVIDED FOR; AFTER-TREATMENT OF THE SHAPED PRODUCTS, e.g. REPAIRING
- B29C49/00—Blow-moulding, i.e. blowing a preform or parison to a desired shape within a mould; Apparatus therefor
- B29C49/42—Component parts, details or accessories; Auxiliary operations
- B29C49/78—Measuring, controlling or regulating
- B29C49/80—Testing, e.g. for leaks
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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
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
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- Manufacturing & Machinery (AREA)
- Mechanical Engineering (AREA)
- Blow-Moulding Or Thermoforming Of Plastics Or The Like (AREA)
Abstract
The invention relates to the field of material forming, in particular to a full-automatic intelligent bottle blowing machine based on a cloud platform.
Description
Technical Field
The invention relates to the field of material forming, in particular to a full-automatic intelligent bottle blowing machine based on a cloud platform.
Background
Blow molding is a method of blowing hot-type blanks closed in a mold into hollow products by means of gas pressure, and plastic hollow containers are widely used in the industries of beverages, medicines, cosmetics, foods and chemical industry due to the characteristics of light weight, low cost, high safety and the like, so that the related technologies of automatic bottle blowing machines for manufacturing plastic hollow containers are also widely focused and studied.
Chinese patent publication No.: CN106346755a discloses a full-automatic bottle blowing machine, comprising a frame, a revolution chain which is provided with bottle blank seats and can do intermittent motion, a feeding device, a blank feeding mechanism, a preheating drying tunnel device, a blank withdrawing mechanism which transfers bottle blanks from the bottle blank seats on the revolution chain to a blank grabbing manipulator, a control device which enables all parts to act in coordination, and a bottle blowing mechanism arranged outside the revolution chain; the bottle blowing mechanism comprises a first bottle blowing mechanism and a second bottle blowing mechanism which are respectively positioned at two sides of the blank withdrawing mechanism; the distance between the bottle blowing stations of the two bottle blowing mechanisms and the blank withdrawing station of the blank withdrawing mechanism is equal; a slide bar is arranged between the blank returning mechanism and the two bottle blowing mechanisms, a first blank grabbing manipulator, a first bottle taking manipulator, a second blank grabbing manipulator and a second bottle taking manipulator are respectively arranged on the slide bar, and the distance between two adjacent manipulators on the slide bar is equal to the distance between a bottle blowing station and a blank returning station; the sliding bar is arranged on the sliding groove of the frame and is connected with a reciprocating driving device.
However, the prior art has the following problems,
in the prior art, the influence of the shape characteristics of the product to be manufactured on the blow molding process parameters is not considered, the existing blow molding machine cannot automatically adjust the process parameters according to the shape characteristics of the product to be manufactured, detection on the finished product to be manufactured is lacking, and the cloud platform is not combined to automatically store the process data in the production process and analyze the stored data to adjust the process parameters.
Disclosure of Invention
In order to solve the problems, the invention provides a full-automatic intelligent bottle blowing machine based on a cloud platform, which comprises:
the blow molding module comprises a parison making mechanism and a blow molding mechanism, wherein the parison making mechanism is used for making a parison, and the blow molding mechanism comprises a mold and a blowing unit so as to blow the parison;
the detection module comprises a photographing device for photographing the finished product;
the data processing module is respectively connected with the detection module and the blow molding module to control the heating temperature of the parison, control the inflation pressure of the blowing unit on the parison, control the heating temperature of the mold and receive the information sent by the detection module; the data processing module is internally provided with a cloud data exchange unit which is connected with a cloud data platform to complete data exchange with the cloud data platform;
the data processing module calculates a shape characteristic parameter E according to the standard contour information of the prefabricated product, compares the shape characteristic parameter E with a preset shape characteristic comparison parameter to judge whether the technological parameter needs to be adjusted, judges whether a finished product has quality problems according to a finished product image shot by the shooting device, stores production data corresponding to the finished product into a data set, and uploads the data to a cloud data platform;
and the data processing module is used for calling a data pool in the cloud data platform, dividing a data set stored in the data pool into a plurality of data sets, calculating a process parameter average value corresponding to the data sets, matching the data sets according to a shape characteristic parameter E corresponding to the standard profile information of the prefabricated product, calling the process parameter average value corresponding to the matched data sets, comparing the process parameter average value with the adjusted process parameter, and judging whether the adjusted process parameter needs to be corrected.
Specifically, the data processing module calculates a shape characteristic parameter E according to a formula (1) according to stored standard contour information of the prefabricated product,
in the formula (1), S represents the total area of the standard contour of the preform, S0 represents the preset contour area contrast value, D represents the maximum width of the standard contour of the preform, D represents the average width of the standard contour of the preform, and D0 represents the preset width difference contrast value.
Further, the data processing module determines whether the process parameters need to be adjusted according to the comparison of the shape characteristic parameters E and preset shape characteristic comparison parameters, wherein,
when E is more than or equal to E2, the data processing module determines that the process parameters need to be adjusted, adjusts the heating temperature of the embryo to be Ts ', sets Ts' =Ts+ts×E/E2, adjusts the inflation pressure to be P0', sets P0' =P0+p0×E/E2, adjusts the heating temperature of the mould to be Tm ', and sets Tm' =Tm+tm×E/E2;
when E1 is less than or equal to E2, the data processing module determines that the process parameters are not required to be adjusted, maintains the preset standard embryo heating temperature Ts, maintains the preset standard inflation pressure p0 and maintains the preset standard heating temperature Tm;
when E < E1, the data processing module determines that the process parameters need to be adjusted, adjusts the heating temperature of the embryo to be Ts ', sets Ts' =Ts-ts×E1/E, adjusts the inflation pressure to be P0', sets P0' =P0-P0×E1/E, adjusts the heating temperature of the mould to be Tm ', and sets Tm' =Tm-tm×E1/E;
wherein ts represents a preset embryo temperature adjustment parameter, p0 represents a preset inflation pressure adjustment parameter, tm represents a preset mold temperature adjustment parameter, E1 represents a preset first shape characteristic comparison parameter, and E2 represents a preset second shape characteristic comparison parameter.
Further, the detection module detects the quality of the finished product, the finished product image is shot by the shooting device and sent to the data processing module, the data processing module judges whether the finished product has quality problems according to the finished product image, wherein,
the data processing module extracts the finished product contour in the finished product image, compares the finished product contour with the standard contour of the prefabricated product, calculates the offset G according to the formula (2),
when the formula (2) is calculated, a coordinate system is established, a finished product contour and a prefabricated product standard contour are established in the coordinate system, the centers of the finished product contour and the prefabricated product standard contour are both coordinate origins, S represents the total area of the prefabricated product standard contour, sg represents the total area of the finished product contour, and S0 represents the area of the superposition area of the finished product contour and the prefabricated product standard contour;
and when G is more than G0, the data processing module judges that the finished product has quality problems, and G0 represents a preset offset parameter comparison value.
Further, the data processing module stores production data corresponding to a finished product with quality problems to the same data set and uploads the data to the cloud data platform, wherein the production data comprises a process parameter, an offset G and a shape characteristic parameter E corresponding to a standard contour of the prefabricated product, and the process parameter comprises a corresponding embryo heating temperature, an inflation air pressure and a mold heating temperature during processing of the finished product.
Further, a plurality of data pools are arranged in the cloud data platform, association relations are established between the data pools and the data intervals, the data intervals associated with the data pools are different, after the cloud data platform receives the data sets, the offset G in the data sets is matched with the data intervals, if the offset G belongs to any data interval, the cloud data platform stores the data sets to the data pools with association relations with the data intervals, and the cloud data platform records the number of the data sets stored in the data pools.
Further, the data processing module judges whether to call the corresponding data pool according to the number N of the data sets in the data pool every preset time period T, wherein,
the data processing module determines the lower limit Gm of the data interval with the association relation in each data pool, compares the lower limit Gm of the data interval with the preset interval comparison parameters,
when Gm is more than or equal to G02 and N is more than N1, the data processing module calls a corresponding data pool;
when G01 is less than or equal to Gm < G02 and N is more than N2, the data processing module calls a corresponding data pool;
when Gm is smaller than G01 and N is larger than N3, the data processing module calls a corresponding data pool;
wherein G01 represents a preset first interval comparison parameter, G02 represents a preset second interval comparison parameter, G0 < G01 < G02, N1 represents a preset first number comparison value, N2 represents a preset second number comparison value, N3 represents a preset third number comparison value, and N3 > N2 > N1.
Further, a data storage unit is arranged in the data processing module, the data processing module extracts the data set in the called data pool, stores the data set in the data storage unit, divides the data set stored in the data storage unit, wherein,
the data processing module is internally provided with a characteristic parameter interval, the characteristic parameter interval is divided into a plurality of subintervals, the length of each subinterval is the same, the interval lower limit of the characteristic parameter interval is 0, the interval upper limit is E3, E3 is a preset interval upper limit, and E3 is more than E2;
the data processing module compares the shape characteristic parameter E in the data set with each subinterval, divides the data set of which the corresponding shape characteristic parameter E belongs to the same subinterval into the same data group,
the data processing module calculates the average value of the process parameters corresponding to each data set, wherein the data processing module calls the process parameters stored in all data sets in the corresponding data set, and calculates the average value Tsr of the embryo heating temperature, the average value PEr of the inflation pressure and the average value Tmr of the mold heating temperature respectively.
Further, the data processing module matches the data set according to the shape characteristic parameter E corresponding to the standard contour information of the prefabricated product, and calls the process parameter average value corresponding to the matched data set to compare with the adjusted process parameter, and judges whether the adjusted process parameter needs to be corrected or not, wherein,
comparing the shape characteristic parameter E with each subinterval, if the shape characteristic parameter E belongs to any subinterval, the data processing module judges that the standard contour information of the prefabricated product is matched with the data set corresponding to the subinterval, and comparing the average value of each process parameter corresponding to the data set with each currently determined process parameter,
when the TS '-Tsr is less than Ts0, the data processing module judges that the adjusted process parameters need to be corrected, increases the TS' by TS1,
when P0'-PEr is less than pe0, the data processing module judges that the adjusted process parameters need to be corrected, increases P0' by P01,
when Tm '-Tmr is smaller than Tm0, the data processing module judges that the adjusted process parameters need to be corrected, increases Tm' by Tm1,
wherein Ts1 represents a preset parison temperature correction parameter, P01 represents a preset inflation pressure adjustment parameter correction parameter, tm1 represents a preset mold temperature correction parameter, ts0 represents a preset parison temperature comparison parameter, pe0 represents a preset inflation pressure comparison parameter, tm0 represents a preset mold temperature comparison parameter.
Further, the data processing module is also connected with an external display screen so as to receive the data sent by the data processing module and display corresponding content.
Compared with the prior art, the method has the advantages that the blow molding module, the detection module and the data processing module are arranged, the data processing module calculates the shape characteristic parameters according to the standard outline information of the prefabricated product, the shape characteristic parameters are used as the reference to adjust the technological parameters of the blow molding process, the detection module detects and calculates the offset to judge the product with quality problems, the cloud data platform uploads the production data of the product with quality problems to the cloud data platform, the cloud data platform divides and stores the production data into different data pools according to the different product offsets with quality, the data processing module calls the data of the cloud data platform, divides the data set in the data pools, corrects the adjusted technological parameters after the technological parameter average value is determined, considers the influence of the shape characteristic on the blow molding process, automatically adjusts the technological parameters, ensures the quality of the blow molding finished product, ensures the reliability of the blow molding process, improves the quality of the finished product, analyzes the product production data with quality problems, corrects the parameters after the technological parameter adjustment, avoids the quality products, and improves the quality of the finished product.
In particular, the invention calculates the shape characteristic parameter E through the size of the standard contour area of the prefabricated product, the maximum width of the standard contour of the prefabricated product and the average width of the standard contour of the prefabricated product, in the practical situation, the size of the blow molding prefabricated product and the stretching degree of the side stretching area have great influence on the blow molding process, especially the blow molding product with the large side stretching area is easy to generate uneven blow molding thickness or the situation that blow molding is not in place in the position.
In particular, the data processing module correspondingly adjusts the blow molding process through the shape characteristic parameter E, adjusts the heating temperature of the embryo, adjusts the heating temperature of the mould and adjusts the inflation pressure, so that the process can be automatically adjusted when blow molding a blow molding product with a special shape, the adjustment is reliable, the accuracy is high, and the reliability of the blow molding process and the quality rate of a finished product are further improved.
In particular, the data processing module performs quality detection on the finished product by acquiring the image information, uploads production data corresponding to the finished product with quality problems to the cloud data platform, and the cloud data platform stores a large amount of production data corresponding to the finished product with quality problems, so that data analysis is convenient, an existing blow molding process control mode is automatically corrected based on the data analysis, and a large amount of production data samples through the cloud data platform provide support for data processing, so that the process adjustment can be performed later, the data processing mode is more reliable, and the accuracy of the blow molding process is further improved.
In particular, the cloud data platform stores production data into different data pools according to the deviation amount corresponding to the finished product with quality problems, the data processing module calls the data of the cloud data platform regularly, the size of the sample capacity is judged during call, only the data pool with the sample capacity conforming to the standard is called, so that the reference data is more reliable, the data processing module stores the called data set into the data storage unit, divides the data set into different data sets according to the size of the shape characteristic parameter E to calculate corresponding process parameter average values, and when the process parameters are corrected subsequently, the shape characteristic parameter E corresponding to the standard contour information of the prefabricated product is matched with the interval corresponding to the data sets when the data sets are divided, so that the process parameter data with high similarity to the standard contour information of the prefabricated product can be matched, the matched data is the production data corresponding to the finished product with quality problems, the adjusted process parameters are corrected by taking the sample capacity as the standard, the repeated occurrence of the quality problems is avoided, the precision of the process parameters is improved, and the quality of the finished product is improved.
Drawings
FIG. 1 is a schematic diagram of a full-automatic intelligent bottle blowing machine based on a cloud platform according to an embodiment of the invention;
FIG. 2 is a standard outline schematic of a preform according to an embodiment of the invention;
in the figure, 1: data processing module, 2: detection module, 3: blow molding mechanism, 4: embryo preparation mechanism, 5: and a cloud data platform.
Detailed Description
In order that the objects and advantages of the invention will become more apparent, the invention will be further described with reference to the following examples; it should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
Preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are merely for explaining the technical principles of the present invention, and are not intended to limit the scope of the present invention.
It should be noted that, in the description of the present invention, terms such as "upper," "lower," "left," "right," "inner," "outer," and the like indicate directions or positional relationships based on the directions or positional relationships shown in the drawings, which are merely for convenience of description, and do not indicate or imply that the apparatus or elements must have a specific orientation, be constructed and operated in a specific orientation, and thus should not be construed as limiting the present invention.
Furthermore, it should be noted that, in the description of the present invention, unless explicitly specified and limited otherwise, the terms "mounted," "connected," and "connected" are to be construed broadly, and may be either fixedly connected, detachably connected, or integrally connected, for example; can be mechanically or electrically connected; can be directly connected or indirectly connected through an intermediate medium, and can be communication between two elements. The specific meaning of the above terms in the present invention can be understood by those skilled in the art according to the specific circumstances.
Referring to fig. 1, which is a schematic structural diagram of a full-automatic intelligent bottle blowing machine based on a cloud platform according to an embodiment of the present invention, the full-automatic intelligent bottle blowing machine based on the cloud platform includes:
a blow molding module comprising a parison making mechanism 4 and a blow molding mechanism 3, wherein the parison making mechanism 4 is used for making a parison, and the blow molding mechanism 3 comprises a mold and a blowing unit so as to blow the parison put into the mold;
the detection module 2 comprises a photographing device for photographing the finished product;
the data processing module 1 is respectively connected with the detection module 2 and the blow molding module to control the heating temperature of the parison, control the inflation pressure of the blowing unit on the parison, control the heating temperature of the mold and receive the information sent by the detection module 2; the data processing module 1 is also internally provided with a cloud data exchange unit which is connected with the cloud data platform 5 to complete data exchange with the cloud data platform 5;
the data processing module 1 calculates a shape characteristic parameter E according to the standard contour information of the prefabricated product, compares the shape characteristic parameter E with a preset shape characteristic comparison parameter to judge whether the technological parameter needs to be adjusted, judges whether a finished product has quality problems according to a finished product image shot by a shooting device, stores production data corresponding to the finished product into a data set, and uploads the data to the cloud data platform 5;
and the data processing module 1 calls a data pool in the cloud data platform 5, divides a data set stored in the data pool into a plurality of data sets, calculates a process parameter average value corresponding to the data sets, matches the data sets according to a shape characteristic parameter E corresponding to the standard profile information of the prefabricated product, calls the process parameter average value corresponding to the matched data sets, compares the process parameter average value with the adjusted process parameter, and judges whether the adjusted process parameter needs to be corrected.
Specifically, the invention is not specifically limited to the structure of the blow molding module, and is a mature prior art, and the technical scheme of the invention is not influenced, in the prior art, a bottle blowing machine usually comprises a parison making mechanism, a mold and a blowing unit, the manufactured parison is placed into the mold and then blown through the blowing unit, in the invention, the parison making mechanism 4 only needs to make the parison and control the temperature of the parison, the mold only needs to have a heating function, the blow molding mechanism 3 only needs to blow the parison, the connection relation among the three is not limited, and the whole blow molding step only needs to be completed, which is the prior art, and the description is omitted here.
For a particular configuration, one skilled in the art may make substitutions and modifications in accordance with the prior art.
Specifically, the data processing module 1 may be an external computer, and only needs to complete data processing and data exchange.
Specifically, the cloud data platform 5 is not limited to a specific structure, and only needs to have a data storage function, and can receive data sent by the data processing modules 1 of a plurality of bottle blowing machines and send the data to the data processing modules 1.
Referring specifically to fig. 2, the data processing module 1 calculates a shape characteristic parameter E according to equation (1) based on stored preform standard profile information,
in the formula (1), S represents the total area of the standard contour of the preform, S0 represents the preset contour area contrast value, S0 is larger than 20cm, D represents the maximum width of the standard contour of the preform, D represents the average width of the standard contour of the preform, D0 represents the preset width difference contrast value, and 0 < D0.
Specifically, the invention calculates the shape characteristic parameter E through the size of the standard contour area of the prefabricated product, the maximum width of the standard contour of the prefabricated product and the average width of the standard contour of the prefabricated product, in the practical situation, the size of the blow molding prefabricated product and the stretching degree of the side stretching area have great influence on the blow molding process, especially the blow molding product with the large side stretching area is easy to generate uneven blow molding thickness or the situation that blow molding is not in place in the position.
Specifically, the data processing module 1 determines whether the process parameter needs to be adjusted according to the comparison between the shape characteristic parameter E and a preset shape characteristic comparison parameter, wherein,
when E is more than or equal to E2, the data processing module 1 determines that the process parameters need to be adjusted, adjusts the heating temperature of the embryo to be Ts ', sets Ts' =Ts+ts×E/E2, adjusts the inflation pressure to be P0', sets P0' =P0+p0×E/E2, adjusts the heating temperature of the mould to be Tm ', and sets Tm' =Tm+tm×E/E2;
when E1 is less than or equal to E2, the data processing module 1 determines that the process parameters are not required to be adjusted, maintains the preset standard embryo heating temperature Ts, maintains the preset standard inflation pressure p0 and maintains the preset standard heating temperature Tm;
when E < E1, the data processing module 1 determines that the process parameters need to be adjusted, adjusts the embryo heating temperature to Ts ', sets Ts' =ts-ts×e1/E, adjusts the inflation pressure to P0', sets P0' =p0-p0×e1/E, adjusts the mold heating temperature to Tm ', and sets Tm' =tm-tm×e1/E;
wherein, 150 ℃ is less than 350 ℃, P0 is less than 1.2Mpa,10 ℃ is less than Tm is less than 200 ℃, ts represents a preset embryo temperature adjustment parameter, 30 ℃ is less than Ts is less than 70 ℃, P0 represents a preset inflation pressure adjustment parameter, 0.1Mpa is less than P0 is less than 0.5Mpa, tm represents a preset mould temperature adjustment parameter, tm is less than 40 ℃, E1 represents a preset first shape characteristic comparison parameter, E2 represents a preset second shape characteristic comparison parameter, and 0 < E1 < E2 < 4.
Specifically, the detection module 2 performs quality detection on the finished product, a finished product image is shot through a shooting device and sent to the data processing module 1, and the data processing module 1 determines whether the finished product has quality problems according to the finished product image, wherein,
the data processing module 1 extracts the finished product contour in the finished product image, compares the finished product contour with the standard contour of the prefabricated product, calculates the offset G according to the formula (2),
when the formula (2) is calculated, a coordinate system is established, a finished product contour and a prefabricated product standard contour are established in the coordinate system, the centers of the finished product contour and the prefabricated product standard contour are both coordinate origins, S represents the total area of the prefabricated product standard contour, sg represents the total area of the finished product contour, S0 represents the area of the overlapping area of the finished product contour and the prefabricated product standard contour,
when G > G0, the data processing module 1 judges that the finished product has quality problems, G0 represents a preset offset parameter comparison value, and G0 > 0.05.
Specifically, the data processing module 1 stores production data corresponding to a finished product with quality problems into the same data set, and uploads the data to the cloud data platform 5, wherein the production data comprises a process parameter, an offset G and a shape characteristic parameter E corresponding to a standard contour of the prefabricated product, and the process parameter comprises a corresponding embryo heating temperature, an inflation air pressure and a mold heating temperature during processing of the finished product.
Specifically, a plurality of data pools are disposed in the cloud data platform 5, an association relationship is established between the data pools and the data intervals, the data intervals associated with the data pools are different, after the cloud data platform 5 receives the data sets, the offset G in the data sets is matched with the data intervals, if the offset G belongs to any data interval, the cloud data platform 5 stores the data sets to the data pools having the association relationship with the data intervals, and the cloud data platform 5 records the number of the data sets stored in the data pools.
Specifically, the data processing module 1 of the invention performs quality detection on the finished product by acquiring the image information, uploads production data corresponding to the finished product with quality problems to the cloud data platform 5, and the cloud data platform 5 stores a large amount of production data corresponding to the finished product with quality problems, so that data analysis is convenient, an existing blow molding process control mode is automatically corrected based on the data analysis, and a large amount of production data samples of the cloud data platform 5 provide support for data processing, so that the process adjustment can be performed later, the data processing mode is more reliable, and the accuracy of the blow molding process is further improved.
Specifically, the data processing module 1 determines whether to call a corresponding data pool according to the number N of data sets in the data pool every preset time period T, wherein,
the data processing module 1 determines the lower limit Gm of the data interval with the association relation in each data pool, compares the lower limit Gm of the data interval with the preset interval comparison parameters,
when Gm is more than or equal to G02 and N is more than N1, the data processing module 1 calls a corresponding data pool;
when G01 is less than or equal to Gm < G02 and N is more than N2, the data processing module 1 calls a corresponding data pool;
when Gm is smaller than G01 and N is larger than N3, the data processing module 1 calls a corresponding data pool;
wherein G01 represents a preset first interval comparison parameter, G02 represents a preset second interval comparison parameter, G0 is more than 0.05 and less than G01 and less than G02, N1 represents a preset first quantity comparison value, N2 represents a preset second quantity comparison value, N3 represents a preset third quantity comparison value, and N3 is more than N2 and more than N1 is more than 0.
Specifically, a data storage unit is disposed in the data processing module 1, the data processing module 1 extracts a data set in the called data pool, stores the data set in the data storage unit, and divides the data set stored in the data storage unit, wherein,
the data processing module 1 is internally provided with a characteristic parameter interval, the characteristic parameter interval is divided into a plurality of subintervals, the length of each subinterval is the same, the interval lower limit of the characteristic parameter interval is 0, the interval upper limit is E3, E3 is a preset interval upper limit, and E3 is more than E2;
the data processing module 1 compares the shape characteristic parameter E in the data set with each subinterval, divides the data set of which the corresponding shape characteristic parameter E belongs to the same subinterval into the same data group,
the data processing module 1 calculates the average value of the process parameters corresponding to each data set, wherein the data processing module invokes the process parameters stored in all data sets in the corresponding data set, and calculates the average value Tsr of the embryo heating temperature, the average value PEr of the inflation pressure and the average value Tmr of the mold heating temperature respectively.
Specifically, the data processing module 1 matches the data set according to the shape characteristic parameter E corresponding to the standard contour information of the preform, and calls the process parameter average value corresponding to the matched data set to compare with the adjusted process parameter, and determines whether the adjusted process parameter needs to be corrected, wherein,
comparing the shape characteristic parameter E with each subinterval, if the shape characteristic parameter E belongs to any subinterval, the data processing module 1 judges that the standard profile information of the prefabricated product is matched with the data set corresponding to the subinterval, and comparing the average value of each process parameter corresponding to the data set with each process parameter which is determined currently,
when the TS '-Tsr is less than Ts0, the data processing module 1 judges that the adjusted process parameters need to be corrected, increases the TS' by TS1,
when P0'-PEr is smaller than pe0, the data processing module 1 judges that the adjusted process parameters need to be corrected, increases P0' by P01,
when Tm '-Tmr is smaller than Tm0, the data processing module 1 judges that the adjusted process parameters need to be corrected, increases Tm' by Tm1,
wherein, ts1 represents a preset embryo temperature correction parameter, 15 ℃ is less than Ts1 and less than 35 ℃, P01 represents a preset inflation pressure adjustment parameter correction parameter, P01 is less than 0.3mpa, tm1 represents a preset mould temperature correction parameter, tm1 is less than 20 ℃, ts0 represents a preset embryo temperature comparison parameter, ts0 is less than 150 ℃, pe0 represents a preset inflation pressure comparison parameter pe0 is less than 0.5mpa, tm0 represents a preset mould temperature comparison parameter, tm0 is less than 100 ℃.
Specifically, the cloud data platform 5 stores production data into different data pools according to the deviation amount corresponding to the finished product with quality problems, the data processing module 1 calls the data of the cloud data platform 5 regularly, judges the size of the sample capacity during call, calls only the data pool with the sample capacity meeting the standard, so that the reference data is more reliable, the data processing module 1 stores the called data set into the data storage unit, divides the data set into different data sets according to the size of the shape characteristic parameter E to calculate the corresponding process parameter average value, and matches the shape characteristic parameter E corresponding to the standard contour information of the prefabricated product with the interval corresponding to the division of the data sets when the process parameter is corrected, so that the process parameter data with high similarity to the standard contour information of the prefabricated product can be matched, the matched data is the production data corresponding to the finished product with quality problems, the adjusted process parameter is corrected based on the data, the repeated occurrence of the quality problems is avoided, the precision of the process parameter is improved, and the quality of the finished product is improved.
Specifically, the data processing module 1 is further connected to an external display screen, so as to receive the data sent by the data processing module and display the corresponding content.
Thus far, the technical solution of the present invention has been described in connection with the preferred embodiments shown in the drawings, but it is easily understood by those skilled in the art that the scope of protection of the present invention is not limited to these specific embodiments. Equivalent modifications and substitutions for related technical features may be made by those skilled in the art without departing from the principles of the present invention, and such modifications and substitutions will be within the scope of the present invention.
Claims (2)
1. Full-automatic intelligent bottle blowing machine based on cloud platform, its characterized in that includes:
the blow molding module comprises a parison making mechanism and a blow molding mechanism, wherein the parison making mechanism is used for making a parison, and the blow molding mechanism comprises a mold and a blowing unit so as to blow the parison;
the detection module comprises a photographing device for photographing the finished product;
the data processing module is respectively connected with the detection module and the blow molding module to control the heating temperature of the parison, control the inflation pressure of the blowing unit on the parison, control the heating temperature of the mold and receive the information sent by the detection module; the data processing module is internally provided with a cloud data exchange unit which is connected with a cloud data platform to complete data exchange with the cloud data platform;
the data processing module calculates a shape characteristic parameter E according to the standard contour information of the prefabricated product, compares the shape characteristic parameter E with a preset shape characteristic comparison parameter to judge whether the technological parameter needs to be adjusted, judges whether a finished product has quality problems according to a finished product image shot by the shooting device, stores production data corresponding to the finished product into a data set, and uploads the data to a cloud data platform;
the data processing module is used for calling a data pool in the cloud data platform, dividing a data set stored in the data pool into a plurality of data sets, calculating a process parameter average value corresponding to the data sets, matching the data sets according to a shape characteristic parameter E corresponding to the standard profile information of the prefabricated product, calling the process parameter average value corresponding to the matched data sets, comparing the process parameter average value with the adjusted process parameter, and judging whether the adjusted process parameter needs to be corrected;
the data processing module calculates a shape characteristic parameter E according to a formula (1) according to the stored standard contour information of the prefabricated product,
in the formula (1), S represents the total area of the standard contour of the preform, S0 represents the preset contour area contrast value, D represents the maximum width of the standard contour of the preform, D represents the average width of the standard contour of the preform, and D0 represents the preset width difference contrast value;
the data processing module judges whether the process parameters need to be adjusted according to the comparison of the shape characteristic parameters E and preset shape characteristic comparison parameters, wherein,
when E is more than or equal to E2, the data processing module determines that the process parameters need to be adjusted, adjusts the heating temperature of the embryo to be Ts ', sets Ts' =Ts+ts×E/E2, adjusts the inflation pressure to be P0', sets P0' =P0+p0×E/E2, adjusts the heating temperature of the mould to be Tm ', and sets Tm' =Tm+tm×E/E2;
when E1 is less than or equal to E2, the data processing module determines that the process parameters are not required to be adjusted, maintains the preset standard embryo heating temperature Ts, maintains the preset standard inflation pressure p0 and maintains the preset standard heating temperature Tm;
when E < E1, the data processing module determines that the process parameters need to be adjusted, adjusts the heating temperature of the embryo to be Ts ', sets Ts' =Ts-ts×E1/E, adjusts the inflation pressure to be P0', sets P0' =P0-P0×E1/E, adjusts the heating temperature of the mould to be Tm ', and sets Tm' =Tm-tm×E1/E;
wherein ts represents a preset embryo temperature adjustment parameter, p0 represents a preset inflation pressure adjustment parameter, tm represents a preset mold temperature adjustment parameter, E1 represents a preset first shape characteristic comparison parameter, and E2 represents a preset second shape characteristic comparison parameter;
the detection module detects the quality of the finished product, the finished product image is shot by the shooting device and sent to the data processing module, the data processing module judges whether the finished product has quality problems according to the finished product image, wherein,
the data processing module extracts the finished product contour in the finished product image, compares the finished product contour with the standard contour of the prefabricated product, calculates the offset G according to the formula (2),
when the formula (2) is calculated, a coordinate system is established, a finished product contour and a prefabricated product standard contour are established in the coordinate system, the centers of the finished product contour and the prefabricated product standard contour are both coordinate origins, S represents the total area of the prefabricated product standard contour, sg represents the total area of the finished product contour, and S0 represents the area of the superposition area of the finished product contour and the prefabricated product standard contour;
when G is more than G0, the data processing module judges that the finished product has quality problems, and G0 represents a preset offset parameter comparison value;
the data processing module stores production data corresponding to a finished product with quality problems into the same data set and uploads the data to a cloud data platform, wherein the production data comprises a technological parameter, an offset G and a shape characteristic parameter E corresponding to a standard contour of the prefabricated product, and the technological parameter comprises a corresponding embryo heating temperature, an inflation pressure and a mold heating temperature when the finished product is processed;
the cloud data platform is provided with a plurality of data pools, wherein the data pools are in association with data intervals, the data intervals associated with the data pools are different, after receiving the data sets, the cloud data platform matches the offset G in the data sets with the data intervals, if the offset G belongs to any data interval, the cloud data platform stores the data sets to the data pools in association with the data intervals, and the cloud data platform records the number of the data sets stored in the data pools;
the data processing module judges whether to call the corresponding data pool or not according to the number N of the data sets in the data pool every preset time period T, wherein,
the data processing module determines the lower limit Gm of the data interval with the association relation in each data pool, compares the lower limit Gm of the data interval with the preset interval comparison parameters,
when Gm is more than or equal to G02 and N is more than N1, the data processing module calls a corresponding data pool;
when G01 is less than or equal to Gm < G02 and N is more than N2, the data processing module calls a corresponding data pool;
when Gm is smaller than G01 and N is larger than N3, the data processing module calls a corresponding data pool;
wherein G01 represents a preset first interval comparison parameter, G02 represents a preset second interval comparison parameter, G0 < G01 < G02, N1 represents a preset first number comparison value, N2 represents a preset second number comparison value, N3 represents a preset third number comparison value, and N3 > N2 > N1;
the data processing module is internally provided with a data storage unit, extracts the data set in the called data pool, stores the data set into the data storage unit, divides the data set stored in the data storage unit, wherein,
the data processing module is internally provided with a characteristic parameter interval, the characteristic parameter interval is divided into a plurality of subintervals, the length of each subinterval is the same, the interval lower limit of the characteristic parameter interval is 0, the interval upper limit is E3, E3 is a preset interval upper limit, and E3 is more than E2;
the data processing module compares the shape characteristic parameter E in the data set with each subinterval, divides the data set of which the corresponding shape characteristic parameter E belongs to the same subinterval into the same data group,
the data processing module respectively calculates the average value of the process parameters corresponding to each data set, wherein the data processing module calls the process parameters stored in all data sets in the corresponding data set, and respectively calculates the average value Tsr of the embryo heating temperature, the average value PEr of the inflation pressure and the average value Tmr of the mold heating temperature;
the data processing module matches the data set according to the shape characteristic parameter E corresponding to the standard contour information of the prefabricated product, and calls the process parameter average value corresponding to the matched data set to compare with the adjusted process parameter, and judges whether the adjusted process parameter needs to be corrected or not, wherein,
comparing the shape characteristic parameter E with each subinterval, if the shape characteristic parameter E belongs to any subinterval, the data processing module judges that the standard contour information of the prefabricated product is matched with the data set corresponding to the subinterval, and comparing the average value of each process parameter corresponding to the data set with each currently determined process parameter,
when the TS '-Tsr is less than Ts0, the data processing module judges that the adjusted process parameters need to be corrected, increases the TS' by TS1,
when P0'-PEr is less than pe0, the data processing module judges that the adjusted process parameters need to be corrected, increases P0' by P01,
when Tm '-Tmr is smaller than Tm0, the data processing module judges that the adjusted process parameters need to be corrected, increases Tm' by Tm1,
wherein Ts1 represents a preset parison temperature correction parameter, P01 represents a preset inflation pressure adjustment parameter correction parameter, tm1 represents a preset mold temperature correction parameter, ts0 represents a preset parison temperature comparison parameter, pe0 represents a preset inflation pressure comparison parameter, tm0 represents a preset mold temperature comparison parameter.
2. The cloud platform-based full-automatic intelligent bottle blowing machine according to claim 1, wherein the data processing module is further connected with an external display screen to receive data sent by the data processing module and display corresponding contents.
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| US6620352B1 (en) * | 2000-07-27 | 2003-09-16 | Ball Corporation | Automated material distribution control for stretch blow molded articles |
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| US6620352B1 (en) * | 2000-07-27 | 2003-09-16 | Ball Corporation | Automated material distribution control for stretch blow molded articles |
| CN115284580A (en) * | 2022-10-08 | 2022-11-04 | 张家港市联鑫塑料机械有限公司 | Injection blow molding intelligent manufacturing system based on remote monitoring |
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