A safety quality control system based on image monitoring

Abstract

The present invention discloses a safety quality control system based on image monitoring, including: platform architecture: including four levels: user layer, edge layer, platform layer and data layer, the user layer is responsible for interacting with users, providing a visual interface and an operation interface, the edge layer is responsible for data collection, preprocessing and real-time analysis, the platform layer is responsible for data storage, model training and service provision functions, and the data layer is responsible for building a product quality big data system to provide data support for the platform. The safety quality control system for field operations provided by the present invention has significant technical characteristics and innovations, and can achieve quality control of the entire process and life cycle of field operation products. Through the application of this system, the speed and accuracy of field operation quality inspection can be improved, the cost of quality inspection can be reduced, product quality can be improved, and product bidding, procurement and quality traceability can be supported.

Description

Technical Field

[0001] The present invention relates to the technical field of manufacturing industry, and in particular to a safety quality control system based on image monitoring. Background Art

[0002] Manufacturing refers to the industry that uses certain resources (materials, energy, equipment, tools, funds, technology, information and manpower, etc.) to transform them into large-scale tools, industrial products and consumer products that can be used and utilized by people through the manufacturing process according to market requirements. This definition covers the entire process from raw material extraction to the delivery of final products and services to end users, and involves a series of activities such as design, raw material procurement, warehousing and transportation, order processing, batch production, quality control, factory guarantee and distribution.

[0003] Manufacturing industry plays a vital role in the national economy, and its role is mainly reflected in the following aspects: Engine of economic growth: Manufacturing is the main driving force of economic growth, promoting sustained and healthy economic development through technological innovation and industrial upgrading. Providing employment opportunities: Manufacturing is a labor-intensive industry. It provides employment opportunities for a large number of workers, which is conducive to social stability and improvement of people's livelihood. Promote technological innovation: Manufacturing is an important field of technological innovation. It promotes scientific and technological progress and industrial upgrading through the research and development of new products, new processes and new technologies. At the same time, manufacturing is also an important carrier for the transformation of technological innovation results, transforming scientific research results into actual productivity. Enhance international competitiveness: A strong manufacturing industry is an important manifestation of a country's international competitiveness. By improving product quality, reducing costs, and enhancing brand influence, the country's position and voice in the global industrial chain can be enhanced. Ensure national security: Manufacturing plays an important role in national defense security, energy security, food security, etc. By independently manufacturing key equipment and components, we can reduce dependence on external markets and enhance national security and stability.

[0004] However, when the existing technology is actually used, with the rapid development of the manufacturing industry and the intensification of market competition, product quality has become an important part of the core competitiveness of enterprises. However, traditional quality control methods have problems such as slow detection speed, low accuracy, and narrow coverage, which makes it difficult to meet the demand of modern manufacturing industry for high-quality products. Summary of the invention

[0005] The purpose of the present invention is to provide a safety quality control system based on image monitoring to solve the problem raised in the above background technology that with the rapid development of the manufacturing industry and the intensification of market competition, product quality has become an important part of the core competitiveness of enterprises. However, traditional quality control methods have problems such as slow detection speed, low accuracy, and narrow coverage, which makes it difficult to meet the demand for high-quality products in modern manufacturing.

[0006] To achieve the above object, the present invention provides the following technical solutions: Platform architecture: It includes four layers: user layer, edge layer, platform layer and data layer. The user layer is responsible for interacting with users and providing visual interfaces and operation interfaces. The edge layer is responsible for data collection, preprocessing and real-time analysis. The platform layer is responsible for data storage, model training and service provision functions. The data layer is responsible for building a product quality big data system and providing data support for the platform. Data collection and storage: Through sensors and camera equipment deployed on the production line, various data in the production process are collected in real time; Data modeling and services: Use big data technology and machine learning algorithms to clean, integrate, analyze and model the collected data to build a product quality big data system; Quality control service system: Based on AI industrial visual image technology, we build a comprehensive quality control service system for pre-prevention, in-process monitoring and post-event tracing; Edge computing and real-time analysis: Deploy intelligent algorithms and models at the edge to achieve real-time analysis and processing of data; Algorithm model and training: Provide a complete set of algorithm models and training systems to support users to customize algorithm models according to actual needs, and perform training and optimization.

[0007] Preferably, the data collection and storage also includes images, videos, temperature and pressure, and these data are stored in a database in the cloud or at the edge.

[0008] Preferably, the data modeling and services can also provide users with data query, data analysis and data visualization services to help users better understand product quality status.

[0009] Preferably, the quality control service system also monitors abnormal conditions in the production process in real time, issues early warning signals in a timely manner, and takes corresponding measures to intervene to ensure that product quality meets standards.

[0010] Preferably, the edge computing and real-time analysis can also reduce data transmission delay and bandwidth occupancy through edge computing technology, thereby improving the real-time performance and response speed of the system.

[0011] Preferably, the algorithm model and training also have the ability to update the model online and continuously evolve to adapt to the ever-changing production environment and product quality requirements.

[0012] Compared with the prior art, the present invention has the following beneficial effects: The present invention improves the speed and accuracy of quality inspection: By utilizing AI industrial visual imaging technology, rapid inspection and accurate judgment of product quality can be achieved, thereby improving the speed and accuracy of quality inspection. Reduce quality inspection costs: Through automated and intelligent quality inspection methods, manual intervention and inspection costs can be reduced, thereby improving production efficiency. Improve product quality: Through full-process and full-life cycle quality control, product quality problems can be discovered and resolved in a timely manner, thereby improving product quality and competitiveness. Support product bidding, procurement and quality traceability: Provide bidding and procurement units and product users with quality archives and quality traceability support for product quality compliance, thereby enhancing product reputation and market competitiveness; The present invention also integrates AI industrial visual imaging technology: using advanced AI industrial visual imaging technology, rapid detection and accurate judgment of product quality can be achieved. Edge computing and real-time analysis: deploying intelligent algorithms and models at the edge to achieve real-time analysis and processing of data, and improve the real-time and response speed of the system. Big data technology support: building a product quality big data system to provide users with data query, data analysis, data visualization and other services. All-round quality control services: providing all-round quality control services including pre-prevention, in-process monitoring, and post-event traceability to ensure that product quality meets standards. Online model update and continuous evolution: the system has the ability to update and continuously evolve the model online to adapt to the ever-changing production environment and product quality requirements. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 The present invention is a schematic diagram of a security quality control system based on image monitoring. DETAILED DESCRIPTION

[0014] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0015] See also Figure 1 The present invention provides a technical solution: comprising: Platform architecture: It includes four layers: user layer, edge layer, platform layer and data layer. The user layer is responsible for interacting with users and providing visual interfaces and operation interfaces; the edge layer is responsible for data collection, preprocessing and real-time analysis; the platform layer is responsible for data storage, model training, service provision and other functions; the data layer is responsible for building a product quality big data system to provide data support for the platform.

[0016] Data collection and storage: Through sensors, cameras and other equipment deployed on the production line, various types of data in the production process are collected in real time, including images, videos, temperature, pressure, etc., and stored in the cloud or edge database.

[0017] Data modeling and services: Using big data technology and machine learning algorithms, we clean, integrate, analyze and model the collected data to build a product quality big data system. The system can provide users with data query, data analysis, data visualization and other services to help users better understand product quality status.

[0018] Quality control service system: Based on AI industrial visual image technology, we build a comprehensive quality control service system with pre-prevention, in-process monitoring, and post-event traceability. By real-time monitoring of abnormal conditions in the production process, early warning signals are issued in a timely manner, and corresponding measures are taken to intervene to ensure that product quality meets standards.

[0019] Edge computing and real-time analysis: Deploy intelligent algorithms and models at the edge to achieve real-time analysis and processing of data. Edge computing technology can reduce data transmission delays and bandwidth usage, and improve the real-time performance and response speed of the system.

[0020] Algorithm model and training: Provide a complete set of algorithm model and training system, support users to customize algorithm model according to actual needs, and conduct training and optimization. At the same time, the system also has the ability to update and continuously evolve the model online to adapt to the ever-changing production environment and product quality requirements.

[0021] The safety and quality control system provided by the present invention can be widely used in various fields of manufacturing, such as automobile manufacturing, machinery manufacturing, electronic manufacturing, etc. Through the application of this platform, the following results can be achieved: Improve the speed and accuracy of quality inspection: AI industrial visual image technology can be used to quickly detect and accurately judge product quality, improving the speed and accuracy of quality inspection. Reduce quality inspection costs: Through automated and intelligent quality inspection methods, manual intervention and inspection costs can be reduced, and production efficiency can be improved. Improve product quality: Through full-process and full-life cycle quality control, product quality problems can be discovered and resolved in a timely manner, improving product quality and competitiveness. Support product bidding, procurement and quality traceability: Provide quality files and quality traceability support for product quality compliance for bidding and procurement units and product users, and enhance product reputation and market competitiveness.

[0022] Technical features and innovations: Integrated AI industrial visual imaging technology: Utilize advanced AI industrial visual imaging technology to achieve rapid detection and accurate judgment of product quality. Edge computing and real-time analysis: Deploy intelligent algorithms and models at the edge to achieve real-time analysis and processing of data, and improve the real-time performance and response speed of the system. Big data technology support: Build a product quality big data system to provide users with data query, data analysis, data visualization and other services. All-round quality control services: Provide all-round quality control services including pre-prevention, in-process monitoring, and post-event traceability to ensure that product quality meets standards. Online model update and continuous evolution: The system has the ability to update and continuously evolve the model online to adapt to the ever-changing production environment and product quality requirements.

[0023] The present invention is further described below in conjunction with specific embodiments: Example

[0024] This embodiment provides a safety quality control system for automobile on-site operations. The system includes four layers: user layer, edge layer, platform layer and data layer. Among them, the user layer provides a visual interface and an operation interface; the edge layer is deployed on the automobile production line and is responsible for data collection, preprocessing and real-time analysis; the platform layer is responsible for data storage, model training, service provision and other functions; the data layer builds an automobile product quality big data system. In the specific implementation process, firstly, data acquisition equipment such as sensors and cameras, as well as infrastructure such as edge computing equipment and cloud servers are deployed on the automobile production line. Then, a set of intelligent quality control platform software based on cloud computing and big data technology is developed, including core components such as data acquisition module, data storage module, data analysis module, quality control service module, etc. Finally, the hardware equipment and software system are integrated and debugged to ensure that the components can communicate and collaborate normally. Through the application of this platform, real-time collection and analysis of various types of data in the automobile production process can be realized, and product quality problems can be discovered and solved in a timely manner. At the same time, it can also provide quality archives and quality traceability support for product quality compliance for bidding and procurement units and product users. Example

[0025] This embodiment provides a safety and quality control system for mechanical on-site operations. The system also includes four levels: user layer, edge layer, platform layer, and data layer. In the specific implementation process, firstly, data acquisition equipment such as sensors and cameras, as well as infrastructure such as edge computing devices and cloud servers are deployed on the mechanical manufacturing production line. Then, a set of intelligent quality control platform software based on cloud computing and big data technology is developed. Finally, the hardware equipment and software system are integrated and debugged. Through the application of this platform, real-time collection and analysis of various types of data in the mechanical manufacturing process can be realized, and product quality problems can be discovered and solved in time. At the same time, it can also provide decision-making support for product quality optimization and improvement for mechanical manufacturing enterprises. Example

[0026] This embodiment provides a safety quality control system for electronic field operations. The system also includes four levels: user layer, edge layer, platform layer, and data layer. In the specific implementation process, firstly, data acquisition equipment such as sensors and cameras, as well as infrastructure such as edge computing devices and cloud servers are deployed on the electronic manufacturing production line. Then, a set of intelligent quality control platform software based on cloud computing and big data technology is developed. Finally, the hardware equipment and software system are integrated and debugged. Through the application of this platform, real-time collection and analysis of various types of data in the electronic manufacturing process can be realized, and product quality problems can be discovered and solved in time. At the same time, technical support for product quality control and optimization can also be provided to electronic manufacturing companies.

[0027] In summary, the safety quality control system for field operations provided by the present invention has significant technical features and innovations, and can achieve quality control of the entire process and life cycle of field operation products. Through the application of this system, the speed and accuracy of quality inspection can be improved, the cost of quality inspection can be reduced, the product quality can be improved, and the bidding, procurement and quality traceability of products can be supported. Therefore, the present invention has broad application prospects and market value.

[0028] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0029] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A safety quality control system based on image monitoring, characterized in that: include: Platform architecture: It includes four layers: user layer, edge layer, platform layer and data layer. The user layer is responsible for interacting with users and providing visual interfaces and operation interfaces. The edge layer is responsible for data collection, preprocessing and real-time analysis. The platform layer is responsible for data storage, model training and service provision functions. The data layer is responsible for building a product quality big data system and providing data support for the platform. Data collection and storage: Through sensors and camera equipment deployed on the production line, various data in the production process are collected in real time; Data modeling and services: Use big data technology and machine learning algorithms to clean, integrate, analyze and model the collected data to build a product quality big data system; Quality control service system: Based on AI industrial visual image technology, we build a comprehensive quality control service system for pre-prevention, in-process monitoring and post-event tracing; Edge computing and real-time analysis: Deploy intelligent algorithms and models at the edge to achieve real-time analysis and processing of data; Algorithm model and training: Provide a complete set of algorithm models and training systems to support users to customize algorithm models according to actual needs, and perform training and optimization.

2. The safety quality control system based on image monitoring according to claim 1 is characterized in that: The data collection and storage also includes images, videos, temperature and pressure, and the data are stored in a database in the cloud or at the edge.

3. A safety quality control system based on image monitoring according to claim 2, characterized in that: The data modeling and services can also provide users with data query, data analysis and data visualization services to help users better understand product quality status.

4. The safety quality control system based on image monitoring according to claim 3 is characterized in that: The quality control service system also monitors abnormal situations in the production process in real time, issues early warning signals in a timely manner, and takes corresponding measures to intervene to ensure that product quality meets the standards.

5. The safety quality control system based on image monitoring according to claim 4 is characterized in that: The edge computing and real-time analysis can also reduce data transmission delays and bandwidth occupancy through edge computing technology, and improve the real-time performance and response speed of the system.

6. The safety quality control system based on image monitoring according to claim 5 is characterized in that: The algorithm model and training also have the ability to update the model online and continuously evolve to adapt to the ever-changing production environment and product quality requirements.

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