CN110611793A - Supply chain information acquisition and data analysis method and device based on industrial vision - Google Patents
Supply chain information acquisition and data analysis method and device based on industrial vision Download PDFInfo
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Abstract
The invention discloses a supply chain information acquisition and data analysis method and device based on industrial vision, wherein the method comprises the following steps: carrying out optical CCD sensing identification on the industrial supply chain based on optical acquisition equipment to form recordable optical visual images or picture information; storing the optical visual image or picture information in a designated position of a cloud server; reading optical visual image or picture information stored in a cloud server based on a preset time threshold value to perform visual feature extraction processing, and acquiring visual feature information; analyzing and judging the visual characteristic information based on an artificial intelligence analysis algorithm, and outputting a judgment result to a corresponding database; and when the judgment result is abnormal, generating abnormal reminding information based on the judgment result with the abnormality and feeding back the abnormal reminding information. In the implementation of the invention, the monitoring and early warning of various abnormal information of the industrial supply chain are realized.
Description
Technical Field
The invention relates to the technical field of industrial internet, in particular to a supply chain information acquisition and data analysis method and device based on industrial vision.
Background
With the gradual implementation of the ERP/DCS system in the upstream and downstream enterprises of the chemical supply chain industry, an industrial internet prototype facing the whole chemical supply chain gradually appears. The implementation difficulty of the industrial internet is mainly raised in two aspects: a) and (4) safety acquisition problem. How to realize effective collection of data under the condition of ensuring the safety of an enterprise information system. The safety of the enterprise information system means that in the daily operation and maintenance process of an enterprise, a production process, a financial system, a sales client system and the like are not generally provided with an information solution by a single supplier, so how to design a data exchange mechanism without physical contact in various information systems to complete data safety collection is a difficult point to be solved urgently. b) Heterogeneous collection problem. The information bus and the storage processing mode of the industrial department need to be pertinently optimized according to the industrial characteristics, so that the number of common industrial information buses is dozens, the number of information systems is hundreds, and the number of industrial information combinations generated by the information buses and the storage processing mode can reach tens of thousands. Therefore, a unified information acquisition and data processing device is needed, which can realize a unified data acquisition process aiming at various heterogeneous industrial environments and solve the implementation difficulty of serious fragmentation of an enterprise information system.
Disclosure of Invention
The invention aims to overcome the defects of the prior art, and provides a supply chain information acquisition and data analysis method and device based on industrial vision, which can be used for monitoring and early warning various abnormal information of an industrial supply chain.
In order to solve at least one technical problem, an embodiment of the present invention provides a supply chain information collection and data analysis method based on industrial vision, where the method includes:
carrying out optical CCD sensing identification on the industrial supply chain based on optical acquisition equipment to form recordable optical visual images or picture information;
storing the optical visual image or picture information in a designated position of a cloud server, wherein the stored files are named in a time sequence;
reading the optical visual image or picture information stored in the cloud server based on a preset time threshold value to perform visual feature extraction processing, and acquiring visual feature information;
analyzing and judging the visual characteristic information based on an artificial intelligence analysis algorithm, and outputting a judgment result to a corresponding database; and the number of the first and second groups,
and when the judgment result is abnormal, generating abnormal reminding information based on the judgment result with the abnormality and feeding back the abnormal reminding information.
Optionally, the optical CCD sensing and identifying for the industrial supply chain based on the optical collecting device includes:
fixing the optical acquisition equipment based on a mechanical constraint device, so that the optical acquisition equipment provides a fixed angle when carrying out optical CCD sensing identification;
and adopting optical auxiliary processing based on the current environmental information of the industrial supply chain, and carrying out optical CCD sensing identification on the industrial supply chain based on an optical acquisition device after the optical auxiliary processing.
Optionally, the current environment information based on the industrial supply chain adopts optical auxiliary processing, including:
performing optical enhancement auxiliary processing in a specific environment before performing optical CCD sensing identification on industrial supply based on optical auxiliary hardware integrated on the optical acquisition equipment; and the number of the first and second groups,
the optical acquisition equipment is connected with a visual terminal on the basis of a data line, and performs automatic focusing and automatic exposure processing before performing optical CCD sensing identification on industrial supply on the basis of optical auxiliary software on the visual terminal; and the number of the first and second groups,
and the visual terminal carries out fine adjustment processing on the angle and the position acquired by the optical acquisition equipment based on picture preview.
Optionally, the optical CCD sensing recognition based on the optical acquisition device is performed on the industrial supply chain, further including:
the optical acquisition equipment converts the optical information into an electric signal by utilizing optical CCD sensing; and the number of the first and second groups,
recording the characteristic processing of the electric signal, and carrying out noise reduction processing on various noises in the process of replacing;
the optical CCD sensing carries out information sensing without physical contact, physical exchange or contact with a visual target system is not needed, and intervention on the operation flow of the visual target system is not needed.
Optionally, after the forming the recordable optical visual image or the picture information, the method further includes:
the visual terminal stores the optical visual image or picture information and transmits the stored optical visual image or picture information to the cloud server based on the transmitting terminal according to a preset timing time threshold.
Optionally, the storing the optical visual image or the picture information in a designated location of a cloud server includes:
and after receiving the optical visual image or picture information, the cloud server continuously stores the optical visual image or picture information in a designated position based on preset industrialization requirements and different storage time requirements.
Optionally, the reading of the optical visual image or picture information stored in the cloud server based on a preset time threshold value is performed to perform visual feature extraction processing, including:
carrying out feature extraction processing on optical visual images or picture information according to a preset time threshold value by an artificial intelligence algorithm based on various industrial vision to obtain first extraction features;
tensor analysis is carried out on the optical visual image or picture information stored in the cloud server and read within a preset time threshold, learning enhancement processing of all characteristics of the optical visual image or picture information is achieved, and an enhancement result is obtained;
calling a feature extraction algorithm in the remote algorithm library to analyze and extract various data features of the enhanced result in the industrial environment to obtain a second extraction feature;
and aiming at different industrial visual scenes, a unified artificial intelligence feature extraction algorithm is adopted to perform supervised learning on the first extraction feature and the second extraction feature, and various industrial visual features are automatically generated.
Optionally, the analyzing, distinguishing and processing the visual characteristic information based on the artificial intelligence analysis algorithm includes:
and analyzing and judging the visual characteristic information by using a static or dynamic artificial intelligence decision algorithm based on a preset working criterion.
Optionally, the method further includes:
mapping the optical visual image or picture information based on a preset mapping rule;
the output object generated by the mapping rule is the only output, and irreversible mapping output is carried out through a hash structure; there is no unique one-to-one mapping relationship between the mapped original data and the output object.
In addition, the embodiment of the invention also provides a supply chain information acquisition and data analysis device based on industrial vision, which comprises:
the information acquisition module: the system is used for carrying out optical CCD sensing identification on the industrial supply chain based on an optical acquisition device to form recordable optical visual images or picture information;
an information storage module: the system comprises a cloud server, a storage module, a display module and a display module, wherein the cloud server is used for storing optical visual images or picture information in a designated position of the cloud server, and stored files are named in a time sequence;
the visual feature extraction module: the system comprises a cloud server and a server, wherein the cloud server is used for reading optical visual images or picture information stored in the cloud server based on a preset time threshold value to perform visual feature extraction processing so as to acquire visual feature information;
the analysis, judgment and reminding module comprises: the system is used for analyzing and judging the visual characteristic information based on an artificial intelligence analysis algorithm and outputting a judgment result to a corresponding database; and when the judgment result is abnormal, generating abnormal reminding information based on the judgment result with the abnormality and feeding back the abnormal reminding information.
In the embodiment of the invention, the characteristic of no physical contact of industrial vision is fully utilized, so that the safety production condition in the chemical and chemical field can be comprehensively met, and the information safety of the links such as an enterprise financial system, a sales system, a production system and the like can be comprehensively protected; processing the image information in an artificial intelligence mode to realize monitoring and warning of various abnormal information; by adopting a mapping mode, irreversible mapping of the enterprise image information to the characteristic parameters can be completed, and the third party monitoring of the abnormal state is realized while the data privacy of the enterprise supply chain is protected.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a schematic flow chart of a method for industrial vision based supply chain information collection and data analysis in an embodiment of the invention;
FIG. 2 is a schematic structural component diagram of an industrial vision-based supply chain information collection and data analysis device according to an embodiment of the present invention;
fig. 3 is a schematic structural composition diagram of an industrial vision-based supply chain information collection and data analysis system according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Examples
Referring to fig. 1, fig. 1 is a schematic flow chart illustrating a supply chain information collection and data analysis method based on industrial vision according to an embodiment of the present invention.
As shown in fig. 1, a supply chain information collection and data analysis method based on industrial vision includes:
s11: carrying out optical CCD sensing identification on the industrial supply chain based on optical acquisition equipment to form recordable optical visual images or picture information;
in the specific implementation process of the present invention, the optical CCD sensing recognition of the industrial supply chain based on the optical acquisition device includes: fixing the optical acquisition equipment based on a mechanical constraint device, so that the optical acquisition equipment provides a fixed angle when carrying out optical CCD sensing identification; and adopting optical auxiliary processing based on the current environmental information of the industrial supply chain, and carrying out optical CCD sensing identification on the industrial supply chain based on an optical acquisition device after the optical auxiliary processing.
Further, the current environment information based on the industrial supply chain adopts optical auxiliary processing, including: performing optical enhancement auxiliary processing in a specific environment before performing optical CCD sensing identification on industrial supply based on optical auxiliary hardware integrated on the optical acquisition equipment; the optical acquisition equipment is connected with a visual terminal on the basis of a data line, and performs automatic focusing and automatic exposure processing before performing optical CCD sensing identification on industrial supply on the basis of optical auxiliary software on the visual terminal; and the visual terminal carries out fine adjustment processing on the angle and the position acquired by the optical acquisition equipment based on picture preview.
Further, the optical CCD sensing identification of the industrial supply chain based on the optical acquisition equipment further comprises: the optical acquisition equipment converts the optical information into an electric signal by utilizing optical CCD sensing; recording the characteristic processing of the electric signal, and carrying out noise reduction processing on various noises in the process of replacing; the optical CCD sensing carries out information sensing without physical contact, physical exchange or contact with a visual target system is not needed, and intervention on the operation flow of the visual target system is not needed.
Specifically, an optical CCD sensor is integrated on the optical acquisition device, and the optical CCD sensor is used to perform optical CCD sensing recognition on the information on the industrial supply chain, and to form a recordable optical visual image or picture information on the optical acquisition device.
For the fixation of the optical acquisition equipment, the optical acquisition equipment is fixed by utilizing a mechanical constraint device, so that the optical acquisition equipment cannot change the angle and the position due to non-human factors when carrying out optical CCD sensing identification, and a fixed angle is provided.
Environmental information on the industrial supply chain changes along with time, so that the optical CCD sensing identification of the industrial supply chain by the optical acquisition equipment needs to be assisted by corresponding software or hardware.
Wherein, the optics auxiliary hardware of hardware part is mainly used for when producing the change according to the light environment of the industry supply chain that optical acquisition equipment needs to gather, for all kinds of industry visual light source reinforcing, wherein includes: light intensity enhancement, specific spectrum enhancement, variable light intensity control and the like; and the optical assist hardware is integrated with the optical acquisition device; the optical auxiliary software of the software part is that an optical acquisition device is connected to a visual terminal through a data line or other connection relations, the visual terminal is provided with corresponding optical auxiliary software, and the optical auxiliary software controls the optical acquisition device to carry out automatic focusing and automatic exposure processing before optical CCD sensing identification based on the connection relation; and the angle and the position acquired by the optical acquisition equipment can be subjected to fine adjustment processing by previewing the optical visual image or the picture information acquired by the optical acquisition equipment through a visual terminal.
The optical acquisition equipment converts optical information into an electric signal by using an integrated optical CCD sensor; recording the characteristics of the electric signal, and then carrying out noise reduction treatment on various noises in the process of replacing; the optical CCD sensing carries out information sensing without physical contact, physical exchange or contact with a visual target system is not needed, and intervention on the operation flow of the visual target system is not needed.
S12: storing the optical visual image or picture information in a designated position of a cloud server, wherein the stored files are named in a time sequence;
in the implementation process of the present invention, after the forming the recordable optical visual image or the picture information, the method further comprises: the visual terminal stores the optical visual image or picture information and transmits the stored optical visual image or picture information to the cloud server based on the transmitting terminal according to a preset timing time threshold.
Further, the storing the optical visual image or picture information in a specified location of a cloud server includes: and after receiving the optical visual image or picture information, the cloud server continuously stores the optical visual image or picture information in a designated position based on preset industrialization requirements and different storage time requirements.
Specifically, the visualization terminal is connected with the optical acquisition device and used for storing optical visual images or picture information acquired by the optical acquisition device; and then, the transmitting end of the visual terminal is used for transmitting the stored optical visual image or picture information to a cloud server according to a preset timing time threshold.
After receiving the optical visual image or picture information, the cloud server continuously stores the optical visual image or picture information in a designated position according to preset industrialization requirements and different storage time requirements; wherein the stored files are named in chronological order.
S13: reading the optical visual image or picture information stored in the cloud server based on a preset time threshold value to perform visual feature extraction processing, and acquiring visual feature information;
in a specific implementation process of the present invention, the reading of the optical visual image or picture information stored in the cloud server based on a preset time threshold to perform visual feature extraction processing includes: carrying out feature extraction processing on optical visual images or picture information according to a preset time threshold value by an artificial intelligence algorithm based on various industrial vision to obtain first extraction features; tensor analysis is carried out on the optical visual image or picture information stored in the cloud server and read within a preset time threshold, learning enhancement processing of all characteristics of the optical visual image or picture information is achieved, and an enhancement result is obtained; calling a feature extraction algorithm in the remote algorithm library to analyze and extract various data features of the enhanced result in the industrial environment to obtain a second extraction feature; and aiming at different industrial visual scenes, a unified artificial intelligence feature extraction algorithm is adopted to perform supervised learning on the first extraction feature and the second extraction feature, and various industrial visual features are automatically generated.
Specifically, the artificial intelligence algorithms for various industrial vision include a neural network algorithm, a machine learning algorithm and the like, which are not limited herein; the algorithms read the optical visual image or picture information stored in the cloud server once per preset time threshold value to perform feature extraction processing, so as to obtain a first extraction feature.
Tensor analysis is carried out according to the optical visual image or picture information which is read within a preset time threshold and stored in the cloud server, so that learning enhancement processing of all characteristics of the optical visual image or picture information is achieved, and an enhancement result is obtained; then calling a feature extraction algorithm in a remote algorithm library to perform various data feature analysis and extraction on the enhanced result in the industrial environment so as to obtain a second extraction feature; because the industrial visual scene has multiple modes, the first extraction characteristic and the second extraction characteristic are supervised and learned by adopting a unified artificial intelligence extraction algorithm to automatically generate various industrial visual characteristics for different industrial visual scenes.
The preset time threshold may be 10S after the optical visual image or picture information exists in the cloud server, and the preset time threshold is generally not less than 10S; to prevent conflicts from occurring in the storage of data.
S14: analyzing and judging the visual characteristic information based on an artificial intelligence analysis algorithm, and outputting a judgment result to a corresponding database; and the number of the first and second groups,
in a specific implementation process of the present invention, the analyzing, distinguishing and processing the visual characteristic information based on the artificial intelligence analysis algorithm includes: and analyzing and judging the visual characteristic information by using a static or dynamic artificial intelligence decision algorithm based on a preset working criterion.
Specifically, according to a preset working criterion, statically or dynamically decomposing a relevant decision algorithm and calculating a decision result of the relevant decision algorithm; the related decision algorithm is an artificial intelligent decision algorithm, such as a Bayesian decision algorithm and the like; and after the decision judgment result is obtained, outputting the decision judgment result to a corresponding database for corresponding storage.
S15: and when the judgment result is abnormal, generating abnormal reminding information based on the judgment result with the abnormality and feeding back the abnormal reminding information.
In the specific implementation process of the invention, when the decision-making discrimination result is abnormal, the decision-making discrimination result is automatically output according to the extraction rule of the abnormal characteristic, and the abnormal reminding information is generated and fed back by combining the corresponding database and the abnormal decision-making discrimination result; therefore, the decision process can be corrected, adjusted and optimized in an external interaction mode; and when external interaction exists, carrying out irreversible encryption protection on the interacted data and keeping the running characteristics of the interacted data.
In this embodiment, the method further includes: mapping the optical visual image or picture information based on a preset mapping rule; the output object generated by the mapping rule is the only output, and irreversible mapping output is carried out through a hash structure; there is no unique one-to-one mapping relationship between the mapped original data and the output object.
Specifically, raw data of the map, raw collected data from industrial vision (optical visual image or picture information), or input data of any other industrial department; the mapping object of the mapping can be mapped to the output object through a preset mapping rule; the output object generated by the mapping rule only has unique output, and the irreversible mapping effect is realized through the structure of hash and the like; the mapping relation between the mapped original data and the output objects does not exist uniquely and correspondingly; the mapping process can be fused with decentralized data file storage formats such as a block chain and the like, so that a decentralized data management mode is realized.
In the embodiment of the invention, the characteristic of no physical contact of industrial vision is fully utilized, so that the safety production condition in the chemical and chemical field can be comprehensively met, and the information safety of the links such as an enterprise financial system, a sales system, a production system and the like can be comprehensively protected; processing the image information in an artificial intelligence mode to realize monitoring and warning of various abnormal information; by adopting a mapping mode, irreversible mapping of the enterprise image information to the characteristic parameters can be completed, and the third party monitoring of the abnormal state is realized while the data privacy of the enterprise supply chain is protected.
Examples
Referring to fig. 2, fig. 2 is a schematic structural composition diagram of an industrial vision-based supply chain information collection and data analysis device according to an embodiment of the present invention.
As shown in fig. 2, an industrial vision-based supply chain information collecting and data analyzing apparatus includes:
the information acquisition module 21: the system is used for carrying out optical CCD sensing identification on the industrial supply chain based on an optical acquisition device to form recordable optical visual images or picture information;
in the specific implementation process of the present invention, the optical CCD sensing recognition of the industrial supply chain based on the optical acquisition device includes: fixing the optical acquisition equipment based on a mechanical constraint device, so that the optical acquisition equipment provides a fixed angle when carrying out optical CCD sensing identification; and adopting optical auxiliary processing based on the current environmental information of the industrial supply chain, and carrying out optical CCD sensing identification on the industrial supply chain based on an optical acquisition device after the optical auxiliary processing.
Further, the current environment information based on the industrial supply chain adopts optical auxiliary processing, including: performing optical enhancement auxiliary processing in a specific environment before performing optical CCD sensing identification on industrial supply based on optical auxiliary hardware integrated on the optical acquisition equipment; the optical acquisition equipment is connected with a visual terminal on the basis of a data line, and performs automatic focusing and automatic exposure processing before performing optical CCD sensing identification on industrial supply on the basis of optical auxiliary software on the visual terminal; and the visual terminal carries out fine adjustment processing on the angle and the position acquired by the optical acquisition equipment based on picture preview.
Further, the optical CCD sensing identification of the industrial supply chain based on the optical acquisition equipment further comprises: the optical acquisition equipment converts the optical information into an electric signal by utilizing optical CCD sensing; recording the characteristic processing of the electric signal, and carrying out noise reduction processing on various noises in the process of replacing; the optical CCD sensing carries out information sensing without physical contact, physical exchange or contact with a visual target system is not needed, and intervention on the operation flow of the visual target system is not needed.
Specifically, an optical CCD sensor is integrated on the optical acquisition device, and the optical CCD sensor is used to perform optical CCD sensing recognition on the information on the industrial supply chain, and to form a recordable optical visual image or picture information on the optical acquisition device.
For the fixation of the optical acquisition equipment, the optical acquisition equipment is fixed by utilizing a mechanical constraint device, so that the optical acquisition equipment cannot change the angle and the position due to non-human factors when carrying out optical CCD sensing identification, and a fixed angle is provided.
Environmental information on the industrial supply chain changes along with time, so that the optical CCD sensing identification of the industrial supply chain by the optical acquisition equipment needs to be assisted by corresponding software or hardware.
Wherein, the optics auxiliary hardware of hardware part is mainly used for when producing the change according to the light environment of the industry supply chain that optical acquisition equipment needs to gather, for all kinds of industry visual light source reinforcing, wherein includes: light intensity enhancement, specific spectrum enhancement, variable light intensity control and the like; and the optical assist hardware is integrated with the optical acquisition device; the optical auxiliary software of the software part is that an optical acquisition device is connected to a visual terminal through a data line or other connection relations, the visual terminal is provided with corresponding optical auxiliary software, and the optical auxiliary software controls the optical acquisition device to carry out automatic focusing and automatic exposure processing before optical CCD sensing identification based on the connection relation; and the angle and the position acquired by the optical acquisition equipment can be subjected to fine adjustment processing by previewing the optical visual image or the picture information acquired by the optical acquisition equipment through a visual terminal.
The optical acquisition equipment converts optical information into an electric signal by using an integrated optical CCD sensor; recording the characteristics of the electric signal, and then carrying out noise reduction treatment on various noises in the process of replacing; the optical CCD sensing carries out information sensing without physical contact, physical exchange or contact with a visual target system is not needed, and intervention on the operation flow of the visual target system is not needed.
The information storage module 22: the system comprises a cloud server, a storage module, a display module and a display module, wherein the cloud server is used for storing optical visual images or picture information in a designated position of the cloud server, and stored files are named in a time sequence;
in the implementation process of the present invention, after the forming the recordable optical visual image or the picture information, the method further comprises: the visual terminal stores the optical visual image or picture information and transmits the stored optical visual image or picture information to the cloud server based on the transmitting terminal according to a preset timing time threshold.
Further, the storing the optical visual image or picture information in a specified location of a cloud server includes: and after receiving the optical visual image or picture information, the cloud server continuously stores the optical visual image or picture information in a designated position based on preset industrialization requirements and different storage time requirements.
Specifically, the visualization terminal is connected with the optical acquisition device and used for storing optical visual images or picture information acquired by the optical acquisition device; and then, the transmitting end of the visual terminal is used for transmitting the stored optical visual image or picture information to a cloud server according to a preset timing time threshold.
After receiving the optical visual image or picture information, the cloud server continuously stores the optical visual image or picture information in a designated position according to preset industrialization requirements and different storage time requirements; wherein the stored files are named in chronological order.
The visual feature extraction module 23: the system comprises a cloud server and a server, wherein the cloud server is used for reading optical visual images or picture information stored in the cloud server based on a preset time threshold value to perform visual feature extraction processing so as to acquire visual feature information;
in a specific implementation process of the present invention, the reading of the optical visual image or picture information stored in the cloud server based on a preset time threshold to perform visual feature extraction processing includes: carrying out feature extraction processing on optical visual images or picture information according to a preset time threshold value by an artificial intelligence algorithm based on various industrial vision to obtain first extraction features; tensor analysis is carried out on the optical visual image or picture information stored in the cloud server and read within a preset time threshold, learning enhancement processing of all characteristics of the optical visual image or picture information is achieved, and an enhancement result is obtained; calling a feature extraction algorithm in the remote algorithm library to analyze and extract various data features of the enhanced result in the industrial environment to obtain a second extraction feature; and aiming at different industrial visual scenes, a unified artificial intelligence feature extraction algorithm is adopted to perform supervised learning on the first extraction feature and the second extraction feature, and various industrial visual features are automatically generated.
Specifically, the artificial intelligence algorithms for various industrial vision include a neural network algorithm, a machine learning algorithm and the like, which are not limited herein; the algorithms read the optical visual image or picture information stored in the cloud server once per preset time threshold value to perform feature extraction processing, so as to obtain a first extraction feature.
Tensor analysis is carried out according to the optical visual image or picture information which is read within a preset time threshold and stored in the cloud server, so that learning enhancement processing of all characteristics of the optical visual image or picture information is achieved, and an enhancement result is obtained; then calling a feature extraction algorithm in a remote algorithm library to perform various data feature analysis and extraction on the enhanced result in the industrial environment so as to obtain a second extraction feature; because the industrial visual scene has multiple modes, the first extraction characteristic and the second extraction characteristic are supervised and learned by adopting a unified artificial intelligence extraction algorithm to automatically generate various industrial visual characteristics for different industrial visual scenes.
The preset time threshold may be 10S after the optical visual image or picture information exists in the cloud server, and the preset time threshold is generally not less than 10S; to prevent conflicts from occurring in the storage of data.
The analysis, judgment and reminding module 24: the system is used for analyzing and judging the visual characteristic information based on an artificial intelligence analysis algorithm and outputting a judgment result to a corresponding database; and when the judgment result is abnormal, generating abnormal reminding information based on the judgment result with the abnormality and feeding back the abnormal reminding information.
In a specific implementation process of the present invention, the analyzing, distinguishing and processing the visual characteristic information based on the artificial intelligence analysis algorithm includes: and analyzing and judging the visual characteristic information by using a static or dynamic artificial intelligence decision algorithm based on a preset working criterion.
Specifically, according to a preset working criterion, statically or dynamically decomposing a relevant decision algorithm and calculating a decision result of the relevant decision algorithm; the related decision algorithm is an artificial intelligent decision algorithm, such as a Bayesian decision algorithm and the like; and after the decision judgment result is obtained, outputting the decision judgment result to a corresponding database for corresponding storage.
In the specific implementation process of the invention, when the decision-making discrimination result is abnormal, the decision-making discrimination result is automatically output according to the extraction rule of the abnormal characteristic, and the abnormal reminding information is generated and fed back by combining the corresponding database and the abnormal decision-making discrimination result; therefore, the decision process can be corrected, adjusted and optimized in an external interaction mode; and when external interaction exists, carrying out irreversible encryption protection on the interacted data and keeping the running characteristics of the interacted data.
In this embodiment, the method further includes: mapping the optical visual image or picture information based on a preset mapping rule; the output object generated by the mapping rule is the only output, and irreversible mapping output is carried out through a hash structure; there is no unique one-to-one mapping relationship between the mapped original data and the output object.
Specifically, raw data of the map, raw collected data from industrial vision (optical visual image or picture information), or input data of any other industrial department; the mapping object of the mapping can be mapped to the output object through a preset mapping rule; the output object generated by the mapping rule only has unique output, and the irreversible mapping effect is realized through the structure of hash and the like; the mapping relation between the mapped original data and the output objects does not exist uniquely and correspondingly; the mapping process can be fused with decentralized data file storage formats such as a block chain and the like, so that a decentralized data management mode is realized.
In the embodiment of the invention, the characteristic of no physical contact of industrial vision is fully utilized, so that the safety production condition in the chemical and chemical field can be comprehensively met, and the information safety of the links such as an enterprise financial system, a sales system, a production system and the like can be comprehensively protected; processing the image information in an artificial intelligence mode to realize monitoring and warning of various abnormal information; by adopting a mapping mode, irreversible mapping of the enterprise image information to the characteristic parameters can be completed, and the third party monitoring of the abnormal state is realized while the data privacy of the enterprise supply chain is protected.
Examples
Referring to fig. 3, fig. 3 is a schematic structural diagram of an industrial vision-based supply chain information collection and data analysis system according to an embodiment of the present invention,
as shown in fig. 3, a supply chain information collection and data analysis system based on industrial vision includes an optical collection device 31, a visualization terminal 32, and a cloud server 33; wherein, the system user realizes the supply chain information collection and data analysis method implemented by the embodiment.
For a detailed implementation of the system, please refer to the embodiments listed in the market, which are not described herein.
Those skilled in the art will appreciate that all or part of the steps in the methods of the above embodiments may be implemented by associated hardware instructed by a program, which may be stored in a computer-readable storage medium, and the storage medium may include: a Read Only Memory (ROM), a Random Access Memory (RAM), a magnetic or optical disk, or the like.
In addition, the supply chain information acquisition and data analysis method and device based on industrial vision provided by the embodiment of the invention are described in detail, a specific embodiment is adopted herein to explain the principle and the implementation of the invention, and the description of the embodiment is only used for helping to understand the method and the core idea of the invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present invention.
Claims (10)
1. A supply chain information collection and data analysis method based on industrial vision, the method comprising:
carrying out optical CCD sensing identification on the industrial supply chain based on optical acquisition equipment to form recordable optical visual images or picture information;
storing the optical visual image or picture information in a designated position of a cloud server, wherein the stored files are named in a time sequence;
reading the optical visual image or picture information stored in the cloud server based on a preset time threshold value to perform visual feature extraction processing, and acquiring visual feature information;
analyzing and judging the visual characteristic information based on an artificial intelligence analysis algorithm, and outputting a judgment result to a corresponding database; and the number of the first and second groups,
and when the judgment result is abnormal, generating abnormal reminding information based on the judgment result with the abnormality and feeding back the abnormal reminding information.
2. The supply chain information collection and data analysis method according to claim 1, wherein the optical collection device-based optical CCD sensing identification of the industrial supply chain comprises:
fixing the optical acquisition equipment based on a mechanical constraint device, so that the optical acquisition equipment provides a fixed angle when carrying out optical CCD sensing identification;
and adopting optical auxiliary processing based on the current environmental information of the industrial supply chain, and carrying out optical CCD sensing identification on the industrial supply chain based on an optical acquisition device after the optical auxiliary processing.
3. The supply chain information collection and data analysis method of claim 2, wherein the optically assisted processing is applied based on the current environmental information of the industrial supply chain, comprising:
performing optical enhancement auxiliary processing in a specific environment before performing optical CCD sensing identification on industrial supply based on optical auxiliary hardware integrated on the optical acquisition equipment; and the number of the first and second groups,
the optical acquisition equipment is connected with a visual terminal on the basis of a data line, and performs automatic focusing and automatic exposure processing before performing optical CCD sensing identification on industrial supply on the basis of optical auxiliary software on the visual terminal; and the number of the first and second groups,
and the visual terminal carries out fine adjustment processing on the angle and the position acquired by the optical acquisition equipment based on picture preview.
4. The supply chain information collection and data analysis method of claim 1, wherein the optical collection device based optical CCD sensing identification of the industrial supply chain further comprises:
the optical acquisition equipment converts the optical information into an electric signal by utilizing optical CCD sensing; and the number of the first and second groups,
carrying out recording electric signal characteristic processing, and carrying out noise reduction processing on various noises in the process of replacing;
the optical CCD sensing carries out information sensing without physical contact, physical exchange or contact with a visual target system is not needed, and intervention on the operation flow of the visual target system is not needed.
5. The supply chain information collection and data analysis method of claim 1, wherein after forming the recordable optical visual image or picture information, further comprising:
the visual terminal stores the optical visual image or picture information and transmits the stored optical visual image or picture information to the cloud server based on the transmitting terminal according to a preset timing time threshold.
6. The supply chain information collection and data analysis method of claim 1, wherein the storing the optical visual image or picture information in a cloud server designated location comprises:
and after receiving the optical visual image or picture information, the cloud server continuously stores the optical visual image or picture information in a designated position based on preset industrialization requirements and different storage time requirements.
7. The supply chain information collection and data analysis method according to claim 1, wherein the reading the optical visual image or picture information stored in the cloud server based on a preset time threshold for performing a visual feature extraction process comprises:
carrying out feature extraction processing on optical visual images or picture information according to a preset time threshold value by an artificial intelligence algorithm based on various industrial vision to obtain first extraction features;
tensor analysis is carried out on the optical visual image or picture information stored in the cloud server and read within a preset time threshold, learning enhancement processing of all characteristics of the optical visual image or picture information is achieved, and an enhancement result is obtained;
calling a feature extraction algorithm in the remote algorithm library to analyze and extract various data features of the enhanced result in the industrial environment to obtain a second extraction feature;
and aiming at different industrial visual scenes, a unified artificial intelligence feature extraction algorithm is adopted to perform supervised learning on the first extraction feature and the second extraction feature, and various industrial visual features are automatically generated.
8. The supply chain information collection and data analysis method according to claim 1, wherein the analyzing and distinguishing process of the visual characteristic information based on the artificial intelligence analysis algorithm comprises:
and analyzing and judging the visual characteristic information by using a static or dynamic artificial intelligence decision algorithm based on a preset working criterion.
9. The supply chain information collection and data analysis method of claim 1, further comprising:
mapping the optical visual image or picture information based on a preset mapping rule;
the output object generated by the mapping rule is the only output, and irreversible mapping output is carried out through a hash structure; there is no unique one-to-one mapping relationship between the mapped original data and the output object.
10. An industrial vision based supply chain information collection and data analysis device, the device comprising:
the information acquisition module: the system is used for carrying out optical CCD sensing identification on the industrial supply chain based on an optical acquisition device to form recordable optical visual images or picture information;
an information storage module: the system comprises a cloud server, a storage module, a display module and a display module, wherein the cloud server is used for storing optical visual images or picture information in a designated position of the cloud server, and stored files are named in a time sequence;
the visual feature extraction module: the system comprises a cloud server and a server, wherein the cloud server is used for reading optical visual images or picture information stored in the cloud server based on a preset time threshold value to perform visual feature extraction processing so as to acquire visual feature information;
the analysis, judgment and reminding module comprises: the system is used for analyzing and judging the visual characteristic information based on an artificial intelligence analysis algorithm and outputting a judgment result to a corresponding database; and when the judgment result is abnormal, generating abnormal reminding information based on the judgment result with the abnormality and feeding back the abnormal reminding information.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111260212A (en) * | 2020-01-14 | 2020-06-09 | 江苏古卓科技有限公司 | Supply chain cooperative behavior analysis method for product design evolution |
| CN112801959A (en) * | 2021-01-18 | 2021-05-14 | 华南理工大学 | Auxiliary assembly system based on visual feature recognition |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20170035317A1 (en) * | 2014-04-17 | 2017-02-09 | The Regents Of The University Of California | Portable brain activity sensing platform for assessment of visual field deficits |
| CN109002018A (en) * | 2018-07-17 | 2018-12-14 | 许雄轩 | The safe acquisition system of industrial control data and acquisition method based on image recognition |
| CN109376613A (en) * | 2018-09-29 | 2019-02-22 | 东莞中国科学院云计算产业技术创新与育成中心 | Video brainpower watch and control system based on big data and depth learning technology |
| CN109445388A (en) * | 2018-10-29 | 2019-03-08 | 黄莹 | Industrial control system data analysis processing device and method based on image recognition |
| CN109460829A (en) * | 2018-11-05 | 2019-03-12 | 常熟理工学院 | Based on the intelligent monitoring method and platform under big data processing and cloud transmission |
-
2019
- 2019-08-30 CN CN201910818187.9A patent/CN110611793B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20170035317A1 (en) * | 2014-04-17 | 2017-02-09 | The Regents Of The University Of California | Portable brain activity sensing platform for assessment of visual field deficits |
| CN109002018A (en) * | 2018-07-17 | 2018-12-14 | 许雄轩 | The safe acquisition system of industrial control data and acquisition method based on image recognition |
| CN109376613A (en) * | 2018-09-29 | 2019-02-22 | 东莞中国科学院云计算产业技术创新与育成中心 | Video brainpower watch and control system based on big data and depth learning technology |
| CN109445388A (en) * | 2018-10-29 | 2019-03-08 | 黄莹 | Industrial control system data analysis processing device and method based on image recognition |
| CN109460829A (en) * | 2018-11-05 | 2019-03-12 | 常熟理工学院 | Based on the intelligent monitoring method and platform under big data processing and cloud transmission |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111260212A (en) * | 2020-01-14 | 2020-06-09 | 江苏古卓科技有限公司 | Supply chain cooperative behavior analysis method for product design evolution |
| CN111260212B (en) * | 2020-01-14 | 2023-04-28 | 江苏古卓科技有限公司 | Product design evolution-oriented supply chain collaborative behavior analysis method |
| CN112801959A (en) * | 2021-01-18 | 2021-05-14 | 华南理工大学 | Auxiliary assembly system based on visual feature recognition |
| CN112801959B (en) * | 2021-01-18 | 2023-08-22 | 华南理工大学 | Auxiliary assembly system based on visual feature recognition |
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