CN114993224A - Intelligent coating thickness measurement control system and method applied to BIM (building information modeling) of Internet of things - Google Patents
Intelligent coating thickness measurement control system and method applied to BIM (building information modeling) of Internet of things Download PDFInfo
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- CN114993224A CN114993224A CN202210543234.5A CN202210543234A CN114993224A CN 114993224 A CN114993224 A CN 114993224A CN 202210543234 A CN202210543234 A CN 202210543234A CN 114993224 A CN114993224 A CN 114993224A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B21/00—Measuring arrangements or details thereof, where the measuring technique is not covered by the other groups of this subclass, unspecified or not relevant
- G01B21/02—Measuring arrangements or details thereof, where the measuring technique is not covered by the other groups of this subclass, unspecified or not relevant for measuring length, width, or thickness
- G01B21/08—Measuring arrangements or details thereof, where the measuring technique is not covered by the other groups of this subclass, unspecified or not relevant for measuring length, width, or thickness for measuring thickness
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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
- Y02P90/30—Computing systems specially adapted for manufacturing
Abstract
The invention discloses an intelligent coating thickness measuring method applied to BIM of the Internet of things, which comprises the following steps: grouping products which finish spraying in the same batch according to standard production duration; judging whether the product coating is in a ready state, if so, extracting the products to be detected according to an extraction ratio for each group of products to obtain thickness data of the product coating to be detected, obtaining the coating qualification rate of each group of products according to the obtained coating thickness data, and if the coating qualification rate of each group of products is not less than the set qualification rate, determining that the product coating in the same batch is qualified; if the grouped coating is unqualified, extracting the groups with the coating qualification rate smaller than the set qualification rate, respectively obtaining the coating thickness data of each product in the groups, if the grouped coating thickness qualification rate is not smaller than the set qualification rate and the coating thickness uniformity is unqualified, judging that the spraying equipment is in failure, and if the grouped coating thickness qualification rate is smaller than the set qualification rate and the coating thickness uniformity is qualified, setting the failure for the coating thickness.
Description
Technical Field
The invention relates to coating measurement, in particular to a coating thickness intelligent measurement control system and method applied to the BIM of the Internet of things.
Background
The good external insulation state of the high-voltage transmission line is an important guarantee for the safe operation of the power system. Since the last 90 s of the century, composite insulation materials have been used in large quantities in power systems, so that the pollution flashover resistance of external insulation equipment is remarkably improved. The composite insulating material is mainly used for manufacturing composite insulators, various composite insulating coatings, various sleeves and the like.
The composite insulating paint is coated on the surface of an insulator by methods of brushing, spraying and the like, so that the purpose of isolating the insulator from the external environment is achieved. The composite insulating paint has excellent hydrophobicity and hydrophobic migration, and when the paint is coated on the surfaces of glass and ceramic insulators, the original hydrophilic surface can be changed into a hydrophobic surface, and the surface pollution also has hydrophobicity, so that the generation and development of leakage current and local electric arc are inhibited, and the pollution flashover voltage of the insulator is obviously improved.
In order to ensure that the composite insulating paint has good anti-pollution flashover performance, the coating quality of the composite insulating paint is very important, and the coating thickness of the composite insulating paint in the electric power industry standard has a definite requirement, generally 0.3-0.5 mm. In practice, however, the conditions of irregular spraying, poor coating surface quality, unsatisfactory thickness or non-uniform spraying thickness are quite severe. With the increase of the operation time, the problems caused by the uneven performance of the composite insulating coating are highlighted, and due to the fact that the coating thickness is uneven and is too small at partial positions, the hydrophobicity is reduced, the aging is caused to fall off, and the safety of electric power transmission is affected. In addition, after long-term operation, the coating of the composite insulating paint is influenced by various conditions such as operation conditions, high electric field intensity, high temperature and humidity, acid rain and the like, and the thickness of the coating changes to show nonuniformity, even peeling and pulverization, so that the operation performance of the coating is influenced, and the safety of power transmission is further influenced. Therefore, the method has strong practical significance for monitoring the construction quality of the power line and monitoring the insulation state of the line in the measurement of the coating thickness of the composite insulating coating.
Disclosure of Invention
The invention aims to overcome the defects of the prior art, and the intelligent coating thickness measuring method applied to the BIM of the Internet of things comprises the following steps:
firstly, grouping products which are sprayed in the same batch according to standard production time;
step two, judging whether the product coating is in a ready state, and if so, entering a step three;
extracting products to be detected according to the extraction ratio for each group of products to obtain thickness data of the coating of the products to be detected, obtaining the coating pass percent of each group of products according to the obtained coating thickness data, and if the pass percent of each group of coatings is not less than the set pass percent, determining that the coatings of the products in the same batch are qualified; if the grouped coating is unqualified, entering a step four;
and step four, extracting the groups with the coating qualification rate smaller than the set qualification rate, respectively acquiring the coating thickness data of each product in the groups, obtaining the grouped coating thickness qualification rate and the grouped product coating thickness uniformity of the grouped products according to the coating thickness data of all the products in the groups, judging that the spraying equipment fails if the grouped coating thickness qualification rate is not smaller than the set qualification rate and the coating thickness uniformity is unqualified, and setting the faults for the coating thickness if the grouped coating thickness qualification rate is smaller than the set qualification rate and the coating thickness uniformity is qualified.
Further, the extraction of the products to be detected is carried out on each group of products according to the extraction ratio, the coating thickness data of the coating of the products to be detected is obtained, and the coating qualification rate of each group of products is obtained according to the obtained coating thickness data, and the method comprises the following steps:
selecting products in the same batch for testing; dividing the production time length T of the same batch of products into n test periods according to the unit production time length T; selecting a test product for testing the products in each test period according to a set proportion gamma;
respectively testing the product qualification rate of the test products in each test period to obtain the qualification rate of the products in the same batch, wherein the qualification rate of the products adopts the following formula:
wherein a is i Is the number of test products in the ith test cycle, b i Testing the number of products for the fault in the ith test period;
the qualification rate beta of the products in the same batch is as follows:
wherein omega is the total number of products in the same batch;
if the qualified rate beta is less than or equal to the set qualified rate, the batch of products is qualified; while adding beta in the batch i Products corresponding to more than or equal to beta are subjected to fault product elimination, so that the qualified rate is beta i ＜β；
And if the qualified rate beta is greater than the set qualified rate, the batch of products is unqualified.
Further, the judging whether the product coating is in a ready state comprises the following steps: and measuring the water content of the coating, wherein if the water content of the coating is within a set coating water content threshold range, the coating is in a ready state, and if not, the coating is in an unsettled state.
Further, the standard production time is the time required for spraying one product.
Further, the coating is qualified as follows: and if the coating thickness and the coating thickness uniformity of the product are qualified, the product is qualified, and if not, the product is unqualified.
Further, in the fourth step, the grouped coating thickness qualified rate and the grouped product coating thickness uniformity of the grouped products are obtained according to the coating thickness data of all the products in the group, and the method comprises the following steps: adopting a five-point sampling method, collecting coating thickness data of five points on a product spraying surface, if the coating thickness data of the five points are all in the coating thickness qualified threshold range, determining that the product is qualified in thickness, and if not, determining that the product is not qualified; if the deviation of the coating thickness of the five points and the set standard thickness is within the set deviation threshold value, the coating thickness uniformity of the product is qualified, otherwise, the coating thickness uniformity of the product is unqualified.
Further, the deviation of the coating thickness from the set standard thickness is calculated by the following formula:
x is set standard thickness data, and X is coating thickness data collected by sampling points of a five-point sampling method.
The intelligent coating thickness measurement control system applied to the BIM of the Internet of things comprises a data processing module, a thickness data measurement device, a data storage device, a product data server, a parameter setting device, a communication device, a display module, a thickness measurement control device and a coating thickness qualification rate testing device;
the data storage device, the product data server, the parameter setting device, the communication device, the display module, the thickness measurement control device and the coating thickness qualified rate testing device are respectively connected with the data processing module; the coating thickness qualification rate testing device is used for obtaining the coating thickness uniformity of a tested product according to the collected thickness data of the product, and comparing the coating thickness uniformity of the tested product with the set coating thickness uniformity to obtain whether the tested product is qualified or not
Preferably, the thickness data measuring device comprises a standard product measuring device and a special-shaped product measuring device; the standard product measuring device and the special product measuring device are respectively connected with the data processor.
Preferably, the parameter setting device comprises a coating thickness setting module and a coating thickness uniformity setting module; the coating thickness setting module and the coating thickness uniformity setting module are respectively connected with the data processor.
The invention has the beneficial effects that: by the technical scheme provided by the invention, the thickness of the coating can be rapidly measured, and unqualified products of the coating can be screened out.
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FIG. 1 is a schematic flow chart of an intelligent coating thickness measuring method applied to the BIM of the Internet of things;
fig. 2 is a schematic diagram of an intelligent coating thickness measurement control system applied to the BIM of the internet of things.
Detailed Description
The technical solutions of the present invention are further described in detail below with reference to the accompanying drawings, but the scope of the present invention is not limited to the following.
For the purpose of making the object, technical solution and advantages of the present invention more apparent, the present invention will be further described in detail with reference to the accompanying drawings and embodiments. It should be understood that the detailed description and specific examples, while indicating embodiments of the invention, are given by way of illustration only, not by way of limitation, i.e., the embodiments described are intended as a selection of the best mode contemplated for carrying out the invention, not as a full mode. The components of embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations.
Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present invention without making any creative effort, shall fall within the protection scope of the present invention. It is noted that relational terms such as "first" and "second," and the like, may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions.
Furthermore, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The features and properties of the present invention are described in further detail below with reference to examples.
As shown in fig. 1, the intelligent coating thickness measuring method applied to the BIM of the internet of things comprises the following steps:
firstly, grouping products which are sprayed in the same batch according to standard production time;
step two, judging whether the product coating is in a ready state, and entering step three if the product coating is in the ready state;
extracting products to be detected according to the extraction ratio for each group of products to obtain thickness data of the coating of the products to be detected, obtaining the coating pass percent of each group of products according to the obtained coating thickness data, and if the pass percent of each group of coatings is not less than the set pass percent, determining that the coatings of the products in the same batch are qualified; if the grouped coating is unqualified, entering a step four;
and step four, extracting the groups with the coating qualification rate smaller than the set qualification rate, respectively acquiring the coating thickness data of each product in the groups, obtaining the grouped coating thickness qualification rate and the grouped product coating thickness uniformity of the grouped products according to the coating thickness data of all the products in the groups, judging that the spraying equipment fails if the grouped coating thickness qualification rate is not smaller than the set qualification rate and the coating thickness uniformity is unqualified, and setting the faults for the coating thickness if the grouped coating thickness qualification rate is smaller than the set qualification rate and the coating thickness uniformity is qualified.
The method comprises the following steps of extracting products to be detected according to an extraction ratio for each group of products to obtain coating thickness data of the coating of the products to be detected, and obtaining the coating qualification rate of each group of products according to the obtained coating thickness data, wherein the method comprises the following steps:
selecting products in the same batch for testing; dividing the production time length T of the same batch of products into n test periods according to the unit production time length T; selecting a test product for testing the products in each test period according to a set proportion gamma;
respectively testing the product qualification rate of the test products in each test period to obtain the qualification rate of the products in the same batch, wherein the qualification rate of the products adopts the following formula:
wherein a is i Is the number of test products in the ith test cycle, b i Testing the number of products for the fault in the ith test period;
the qualification rate beta of the products in the same batch is as follows:
wherein omega is the total number of products in the same batch;
if the qualification rate beta is less than or equal to the set qualification rate, the batch of products is qualified; while adding beta in the batch i Products corresponding to more than or equal to beta are subjected to fault product elimination, so that the qualification rate beta is increased i ＜β；
And if the qualified rate beta is greater than the set qualified rate, the batch of products is unqualified.
The method for judging whether the product coating is in a ready state comprises the following steps: and measuring the water content of the coating, wherein if the water content of the coating is within a set coating water content threshold value range, the coating is in a ready state, and if not, the coating is in an unsettled state.
The standard production time is the time required for finishing one product by spraying.
The qualified coating is as follows: and if the coating thickness and the coating thickness uniformity of the product are qualified, the product is qualified, and if not, the product is unqualified.
In the fourth step, the grouped coating thickness qualified rate and the grouped product coating thickness uniformity of the grouped products are obtained according to the coating thickness data of all the products in the group, and the method comprises the following steps: adopting a five-point sampling method, collecting coating thickness data of five points on a product spraying surface, wherein if the coating thickness data of the five points are all in the range of coating thickness qualified threshold values, the product is qualified in thickness, and if not, the product is not qualified in thickness; if the deviation of the coating thickness of the five points and the set standard thickness is within the set deviation threshold value, the coating thickness uniformity of the product is qualified, otherwise, the coating thickness uniformity of the product is unqualified.
The deviation of the coating thickness from the set standard thickness adopts the following formula:
x is the set standard thickness data, and X is the coating thickness data collected by the sampling points of the five-point sampling method.
The intelligent coating thickness measurement control system applied to the BIM of the Internet of things comprises a data processing module, a thickness data measurement device, a data storage device, a product data server, a parameter setting device, a communication device, a display module, a thickness measurement control device and a coating thickness qualified rate testing device;
the data storage device, the product data server, the parameter setting device, the communication device, the display module, the thickness measurement control device and the coating thickness qualified rate testing device are respectively connected with the data processing module; the coating thickness qualification rate testing device is used for obtaining the coating thickness uniformity of a tested product according to the collected thickness data of the product, and comparing the coating thickness uniformity of the tested product with the set coating thickness uniformity to obtain whether the tested product is qualified or not
The thickness data measuring device comprises a standard product measuring device and a special product measuring device; the standard product measuring device and the special product measuring device are respectively connected with the data processor.
The parameter setting device comprises a coating thickness setting module and a coating thickness uniformity setting module; the coating thickness setting module and the coating thickness uniformity setting module are respectively connected with the data processor.
The foregoing is illustrative of the preferred embodiments of this invention, and it is to be understood that the invention is not limited to the precise form disclosed herein and that various other combinations, modifications, and environments may be resorted to, falling within the scope of the concept as disclosed herein, either as described above or as apparent to those skilled in the relevant art. And that modifications and variations may be effected by those skilled in the art without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (10)
1. The intelligent coating thickness measuring method applied to the BIM of the Internet of things is characterized by comprising the following steps:
firstly, grouping products which are sprayed in the same batch according to standard production time;
step two, judging whether the product coating is in a ready state, and if so, entering a step three;
extracting the products to be detected according to the extraction ratio for each group of products to obtain thickness data of the coating of the products to be detected, obtaining the coating qualification rate of each group of products according to the obtained thickness data of the coating, and if the qualification rate of each group of products is not less than the set qualification rate, the coating of the products in the same batch is qualified; if the grouped coating is unqualified, entering a step four;
and step four, extracting the groups with the coating qualification rate smaller than the set qualification rate, respectively acquiring the coating thickness data of each product in the groups, obtaining the grouped coating thickness qualification rate and the grouped product coating thickness uniformity of the grouped products according to the coating thickness data of all the products in the groups, judging that the spraying equipment fails if the grouped coating thickness qualification rate is not smaller than the set qualification rate and the coating thickness uniformity is unqualified, and setting the faults for the coating thickness if the grouped coating thickness qualification rate is smaller than the set qualification rate and the coating thickness uniformity is qualified.
2. The intelligent measuring method for the coating thickness of the BIM applied to the Internet of things as claimed in claim 1, wherein each group of products is extracted according to an extraction ratio to obtain the coating thickness data of the coating of the product to be measured, and the coating pass percent of each group of products is obtained according to the obtained coating thickness data, and the method comprises the following steps:
selecting products in the same batch for testing; dividing the production time length T of the same batch of products into n test periods according to the unit production time length T; selecting a test product for testing the products in each test period according to a set proportion gamma;
respectively testing the product qualification rate of the test products in each test period to obtain the qualification rate of the products in the same batch, wherein the qualification rate of the products adopts the following formula:
wherein a is i Is the number of test products in the ith test cycle, b i Testing the number of products for the fault in the ith test period;
the qualification rate beta of the products in the same batch is as follows:
wherein omega is the total number of products in the same batch;
if the qualification rate beta is less than or equal to the set qualification rate, the batch of products is qualified; while adding beta in the batch i Products corresponding to more than or equal to beta are subjected to fault product elimination, so that the qualification rate beta is increased i ＜β；
And if the qualified rate beta is greater than the set qualified rate, the batch of products is unqualified.
3. The intelligent coating thickness measuring method applied to the BIM of the Internet of things as claimed in claim 2, wherein the step of judging whether the product coating is in a ready state comprises the following steps: and measuring the water content of the coating, wherein if the water content of the coating is within a set coating water content threshold range, the coating is in a ready state, and if not, the coating is in an unsettled state.
4. The intelligent measuring method for the coating thickness of the BIM of the Internet of things as claimed in claim 3, wherein the standard production time is the time required for completing one product by spraying.
5. The intelligent measuring method for the coating thickness of the BIM of the Internet of things according to claim 4, wherein the coating is qualified as follows: and if the coating thickness and the coating thickness uniformity of the product are qualified, the product is qualified, and if not, the product is unqualified.
6. The intelligent measuring method for the coating thickness of the BIM of the Internet of things as claimed in claim 5, wherein in the fourth step, the grouped coating thickness qualified rate and the grouped product coating thickness uniformity of the grouped products are obtained according to the coating thickness data of all the products in the group, and the method comprises the following processes: adopting a five-point sampling method, collecting coating thickness data of five points on a product spraying surface, wherein if the coating thickness data of the five points are all in the range of coating thickness qualified threshold values, the product is qualified in thickness, and if not, the product is not qualified in thickness; if the deviation of the coating thickness of the five points and the set standard thickness is within the set deviation threshold value, the coating thickness uniformity of the product is qualified, otherwise, the coating thickness uniformity of the product is unqualified.
7. The intelligent measuring method for the coating thickness of the BIM of the Internet of things as claimed in claim 6, wherein the deviation between the coating thickness and the set standard thickness adopts the following formula:
x is the set standard thickness data, and X is the coating thickness data collected by the sampling points of the five-point sampling method.
8. The intelligent coating thickness measurement control system applied to the BIM of the Internet of things and applying the intelligent coating thickness measurement method applied to the BIM of the Internet of things as claimed in any one of claims 1 to 7 is characterized by comprising a data processing module, a thickness data measurement device, a data storage device, a product data server, a parameter setting device, a communication device, a display module, a thickness measurement control device and a coating thickness qualification rate testing device;
the data storage device, the product data server, the parameter setting device, the communication device, the display module, the thickness measurement control device and the coating thickness qualified rate testing device are respectively connected with the data processing module; the coating thickness qualification rate testing device is used for obtaining the coating thickness uniformity of a tested product according to the collected thickness data of the product, and comparing the coating thickness uniformity of the tested product with the set coating thickness uniformity to obtain whether the tested product is qualified.
9. The intelligent measuring and control system for the coating thickness of the BIM in the Internet of things as claimed in claim 8, wherein the thickness data measuring device comprises a standard product measuring device and a special product measuring device; the standard product measuring device and the special product measuring device are respectively connected with the data processor.
10. The intelligent coating thickness measurement and control system applied to the BIM of the Internet of things as claimed in claim 8, wherein the parameter setting device comprises a coating thickness setting module and a coating thickness uniformity setting module; the coating thickness setting module and the coating thickness uniformity setting module are respectively connected with the data processor.
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| CN202210543234.5A CN114993224A (en) | 2022-05-13 | 2022-05-13 | Intelligent coating thickness measurement control system and method applied to BIM (building information modeling) of Internet of things |
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| CN202210543234.5A CN114993224A (en) | 2022-05-13 | 2022-05-13 | Intelligent coating thickness measurement control system and method applied to BIM (building information modeling) of Internet of things |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115914063A (en) * | 2023-02-17 | 2023-04-04 | 四川景诺电子有限公司 | Intelligent terminal automatic testing method and system based on 5G communication |
| CN117073602A (en) * | 2023-08-25 | 2023-11-17 | 广州兰泰仪器有限公司 | Intelligent thickness measuring method and system for coating |
-
2022
- 2022-05-13 CN CN202210543234.5A patent/CN114993224A/en not_active Withdrawn
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115914063A (en) * | 2023-02-17 | 2023-04-04 | 四川景诺电子有限公司 | Intelligent terminal automatic testing method and system based on 5G communication |
| CN117073602A (en) * | 2023-08-25 | 2023-11-17 | 广州兰泰仪器有限公司 | Intelligent thickness measuring method and system for coating |
| CN117073602B (en) * | 2023-08-25 | 2024-03-22 | 广州兰泰仪器有限公司 | Intelligent thickness measuring method and system for coating |
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Application publication date: 20220902 |