Online monitoring control system for Internet of Things manufacturing

Abstract

The utility model discloses an on-line monitoring control system for Internet of Things manufacturing, which relates to the technical field of on-line monitoring control, and comprises a sensing layer, a network layer, a platform layer and an application layer, the sensing layer is used for acquiring production parameters, equipment states and environmental data in the manufacturing process, the network layer is used for realizing protocol conversion and network transmission of sensing layer data, and the platform layer is used for applying the data to the platform layer. By arranging the production parameter acquisition module, the equipment state acquisition module and the environment monitoring acquisition module of the sensing layer, comprehensive acquisition of production parameters, equipment states and environment data in the manufacturing process is realized, and rich and accurate data support is provided for monitoring and control of the manufacturing process; the problem of data intercommunication between different protocol devices is solved through the data protocol conversion module of the network layer, seamless connection of heterogeneous devices is achieved, stable and efficient transmission of data is guaranteed through the network communication management module, and the reliability of the system is guaranteed.

Description

Technical Field

[0001] This utility model relates to the field of online monitoring and control technology, and in particular to an online monitoring and control system for Internet of Things (IoT) manufacturing. Background Technology

[0002] The Internet of Things (IoT) manufacturing online monitoring and control system is an intelligent system based on IoT technology. It is used to monitor, collect, analyze and optimize equipment, environmental and production data in the manufacturing process in real time. Its core objective is to improve production efficiency, ensure quality, reduce energy consumption and achieve predictive maintenance through data-driven approaches.

[0003] However, existing technologies and traditional manufacturing monitoring and control methods have many shortcomings, such as low efficiency of manual monitoring, incomplete data collection, and inflexible equipment control. Although some IoT-based manufacturing monitoring and control systems have emerged, these systems still have certain deficiencies in terms of the comprehensiveness of data collection, the efficiency of data processing, the intelligence of equipment management, and the convenience of human-machine interaction. For example, existing systems may not be able to simultaneously collect production parameters, equipment status, and environmental data during the production process, resulting in insufficient monitoring of the manufacturing process; during data transmission, there may be difficulties in data interoperability between devices with different protocols; the analysis and utilization of historical data are insufficient, making it difficult to achieve predictive maintenance of equipment and optimization of production processes; and the human-machine interface is not intuitive and convenient enough, hindering operators from real-time monitoring of production status and remote control. Utility Model Content

[0004] The purpose of this invention is to address the problems of incomplete manufacturing process monitoring, low data processing efficiency, insufficient intelligent equipment management, and inconvenient human-machine interaction in existing technologies, and to propose an online monitoring and control system for Internet of Things manufacturing.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: an online monitoring and control system for Internet of Things manufacturing, comprising a sensing layer, a network layer, a platform layer, and an application layer. The sensing layer is used to collect production parameters, equipment status, and environmental data during the manufacturing process. The network layer is used to realize protocol conversion and network transmission of the data from the sensing layer. The platform layer is used to process, analyze, and manage the data transmitted from the sensing layer. The application layer is used to realize real-time monitoring and remote control of the manufacturing process.

[0006] Preferably, the sensing layer includes a production parameter acquisition module, an equipment status acquisition module, and an environmental monitoring acquisition module. The production parameter acquisition module includes a temperature sensor, a pressure sensor, and a flow sensor to acquire production parameters such as temperature, pressure, and material flow during the manufacturing process. The equipment status acquisition module includes a vibration sensor, a current sensor, and a voltage sensor to acquire equipment status data such as vibration frequency, current, and voltage. The environmental monitoring acquisition module includes a temperature and humidity sensor and an air quality sensor to acquire environmental data such as temperature, humidity, and air quality in the production environment.

[0007] Preferably, the network layer includes a data protocol conversion module and a network communication management module. The data protocol conversion module is used to convert data from different protocols in the perception layer into data in a unified format, and the network communication management module is used to manage network transmission.

[0008] Preferably, the platform layer includes a real-time data processing module, a historical data analysis module, an equipment lifecycle management module, a system configuration management module, and a data security encryption module. The real-time data processing module is used to clean, filter, and preprocess the real-time collected data. The historical data analysis module is used to perform in-depth mining and analysis of historical data. The equipment lifecycle management module is used to manage the entire lifecycle of equipment from procurement to scrapping. The system configuration management module is used to manage the system parameters and configurations. The data security encryption module is used to encrypt the data to ensure data security.

[0009] Preferably, the application layer includes a 3D visualization monitoring module and a mobile terminal control module. The 3D visualization monitoring module is used to display real-time data of the manufacturing process and equipment status in a 3D visualization manner, and the mobile terminal control module is used to realize remote control and monitoring of production equipment through mobile terminal devices.

[0010] Preferably, the temperature sensor, pressure sensor, flow sensor, vibration sensor, current sensor, voltage sensor, temperature and humidity sensor, and air quality sensor are all connected to the network layer via wired or wireless means.

[0011] Preferably, the data protocol conversion module supports the conversion of Bluetooth communication protocols, and the network communication management module includes network devices such as routers and switches, used to build wired or wireless networks.

[0012] Compared with the prior art, the advantages and positive effects of this utility model are as follows:

[0013] 1. In this utility model, by setting up a production parameter acquisition module, an equipment status acquisition module, and an environmental monitoring acquisition module in the perception layer, comprehensive acquisition of production parameters, equipment status, and environmental data during the manufacturing process is achieved, providing rich and accurate data support for the monitoring and control of the manufacturing process. The data protocol conversion module in the network layer solves the data interoperability problem between devices with different protocols, realizing seamless connection of heterogeneous devices. The network communication management module ensures stable and efficient data transmission, ensuring the reliability of the system.

[0014] 2. In this utility model, through the historical data analysis module and equipment lifecycle management module at the platform layer, data mining and machine learning technologies are used to realize predictive maintenance of equipment and optimization of production processes, thereby improving equipment utilization and production efficiency and reducing production costs. The three-dimensional visualization monitoring module and mobile terminal control module at the application layer provide an intuitive and convenient human-machine interface, allowing operators to monitor production status in real time and perform remote control, thus improving the convenience and flexibility of production management. Attached Figure Description

[0015] Figure 1 This utility model presents a modular block diagram of an online monitoring and control system for Internet of Things manufacturing.

[0016] Legend: 1. Perception Layer; 11. Production Parameter Acquisition Module; 12. Equipment Status Acquisition Module; 13. Environmental Monitoring Acquisition Module; 2. Network Layer; 21. Data Protocol Conversion Module; 22. Network Communication Management Module; 3. Platform Layer; 31. Real-time Data Processing Module; 32. Historical Data Analysis Module; 33. Equipment Lifecycle Management Module; 34. System Configuration Management Module; 35. Data Security Encryption Module; 4. Application Layer; 41. 3D Visualization Monitoring Module; 42. Mobile Terminal Control Module. Detailed Implementation

[0017] To better understand the above-mentioned objectives, features, and advantages of this utility model, the present utility model will be further described below with reference to the accompanying drawings and embodiments. It should be noted that, unless otherwise specified, the embodiments and features described in these embodiments can be combined with each other.

[0018] Many specific details are set forth in the following description in order to provide a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Therefore, the present invention is not limited to the specific embodiments disclosed in the following specification.

[0019] Example: Figure 1As shown, this utility model provides an online monitoring and control system for Internet of Things (IoT) manufacturing, which includes a perception layer 1, a network layer 2, a platform layer 3, and an application layer 4.

[0020] In the perception layer 1, the production parameter acquisition module 11 is equipped with temperature sensors, pressure sensors, and flow sensors. On the production equipment in a manufacturing workshop, the temperature sensor is installed on the surface of the heating furnace to collect the temperature of the heating furnace in real time. The pressure sensor is installed on the compressed air pipeline to collect the pressure in the pipeline. The flow sensor is installed on the material conveying pipeline to collect the flow rate of the material. The equipment status acquisition module 12 is equipped with vibration sensors, current sensors, and voltage sensors. The vibration sensor is fixed on the bearing seat of the motor to collect the vibration frequency of the motor. The current sensor and voltage sensor are installed in the power distribution cabinet of the equipment to collect the current and voltage of the equipment. The environmental monitoring acquisition module 13 is equipped with temperature and humidity sensors and air quality sensors in the workshop to collect temperature, humidity and air quality data of the workshop, respectively.

[0021] In network layer 2, the data protocol conversion module 21 adopts an industrial-grade gateway, which supports the conversion of multiple communication protocols and converts the different protocol data output by the sensors in the perception layer 1 into unified TCP / IP protocol data. The network communication management module 22 consists of an industrial switch and a wireless router, which builds wired and wireless networks in the workshop and realizes stable data transmission.

[0022] In platform layer 3, the real-time data processing module 31 cleans and filters the real-time data transmitted from the sensing layer 1 to remove abnormal data. The historical data analysis module 32 analyzes the stored historical data, such as analyzing the vibration data of the equipment through machine learning algorithms to predict equipment failures. The equipment lifecycle management module 33 establishes a file for each piece of equipment, recording the basic information and maintenance records of the equipment, and formulates maintenance plans based on the equipment's operating data. The system configuration management module 34 provides a graphical configuration interface, allowing operators to easily set the calibration parameters and alarm thresholds of the sensors. The data security encryption module 35 encrypts the transmitted and stored data to ensure data security.

[0023] In application layer 4, the 3D visualization monitoring module 41 constructs a 3D virtual scene based on the actual layout of the workshop, and displays the real-time collected data in the 3D scene. Operators can intuitively see the operating status and production data of the equipment through a computer or a large screen. The mobile terminal control module 42 has developed a mobile APP, which allows operators to remotely control the start and stop of the equipment, adjust the parameters of the equipment, and receive alarm information from the equipment through their mobile phones.

[0024] The sensors in the perception layer 1 are connected to the network layer 2 via wireless transmission. For example, the temperature sensor and vibration sensor have built-in wireless communication modules and transmit data to the gateway of the network layer 2 via the ZigBee protocol. The gateway of the network layer 2 converts the wireless data into wired network data and transmits it to the platform layer 3 for processing.

[0025] At platform layer 3, the historical data analysis module 32 analyzes the historical fault data of a certain type of equipment and establishes a fault prediction model. When the real-time operating data of the equipment approaches the fault threshold, the system will issue an early warning to remind maintenance personnel to check and maintain the equipment, thereby reducing the downtime of the equipment.

[0026] The mobile control module 42 of application layer 4 supports offline operation. When the mobile device is offline, the operator can view the production data and equipment status before going offline. When the device reconnects to the network, the data will be automatically synchronized to the system.

[0027] The usage and working principle of this device are as follows: When using this device, firstly, deploy various sensors in the sensing layer 1 according to the actual situation of the manufacturing workshop, install the sensors in appropriate locations, and connect them to the network layer 2 via wired or wireless means. The data protocol conversion module 21 of the network layer 2 converts the sensor data into a unified format and transmits it to the platform layer 3 through the network communication management module 22. The platform layer 3 processes, analyzes, and manages the data. The application layer 4 obtains data from the platform layer 3 and displays real-time data and equipment status through the three-dimensional visualization monitoring module 41. Operators can remotely control the equipment through the mobile terminal control module 42.

[0028] Sensors in the perception layer 1 collect production parameters, equipment status, and environmental data in real time and transmit the data to the network layer 2. The network layer 2 performs protocol conversion and network transmission, sending the data to the platform layer 3. The platform layer 3 processes and analyzes the data to generate useful information, such as equipment status assessment and production trend prediction. The application layer 4 displays this information to the operators in an intuitive way and receives control commands from the operators. The actuators in the network layer 2 and perception layer 1 are used to control the equipment.

[0029] The above description is merely a preferred embodiment of the present utility model and is not intended to limit the present utility model in any other way. Any person skilled in the art may make changes or modifications to the above-disclosed technical content to create equivalent embodiments for application in other fields. However, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present utility model without departing from the technical solution of the present utility model shall still fall within the protection scope of the technical solution of the present utility model.

Claims

1. An online monitoring and control system for Internet of Things (IoT) manufacturing, characterized in that: An online monitoring and control system for Internet of Things manufacturing is characterized by comprising a perception layer (1), a network layer (2), a platform layer (3), and an application layer (4). The perception layer (1) is used to collect production parameters, equipment status, and environmental data during the manufacturing process. The network layer (2) is used to realize protocol conversion and network transmission of data from the perception layer (1). The platform layer (3) is used to process, analyze, and manage the data transmitted from the perception layer (1). The application layer (4) is used to realize real-time monitoring and remote control of the manufacturing process.

2. The online monitoring and control system for Internet of Things manufacturing according to claim 1, characterized in that: The sensing layer (1) includes a production parameter acquisition module (11), an equipment status acquisition module (12), and an environmental monitoring acquisition module (13). The production parameter acquisition module (11) includes a temperature sensor, a pressure sensor, and a flow sensor, which are used to acquire production parameters such as temperature, pressure, and material flow during the manufacturing process. The equipment status acquisition module (12) includes a vibration sensor, a current sensor, and a voltage sensor, which are used to acquire equipment status data such as vibration frequency, current, and voltage of the equipment. The environmental monitoring acquisition module (13) includes a temperature and humidity sensor and an air quality sensor, which are used to acquire environmental data such as temperature, humidity, and air quality of the production environment.

3. The online monitoring and control system for Internet of Things manufacturing according to claim 1, characterized in that: The network layer (2) includes a data protocol conversion module (21) and a network communication management module (22). The data protocol conversion module (21) is used to convert data from different protocols of the perception layer (1) into data in a unified format. The network communication management module (22) is used to manage network transmission.

4. The online monitoring and control system for Internet of Things manufacturing according to claim 1, characterized in that: The platform layer (3) includes a real-time data processing module (31), a historical data analysis module (32), an equipment lifecycle management module (33), a system configuration management module (34), and a data security encryption module (35). The real-time data processing module (31) is used to clean, filter, and preprocess the data collected in real time. The historical data analysis module (32) is used to perform in-depth mining and analysis of historical data. The equipment lifecycle management module (33) is used to manage the entire lifecycle of equipment from procurement to scrapping. The system configuration management module (34) is used to manage the parameters and configuration of the system. The data security encryption module (35) is used to encrypt the data to ensure data security.

5. The online monitoring and control system for Internet of Things manufacturing according to claim 1, characterized in that: The application layer (4) includes a three-dimensional visualization monitoring module (41) and a mobile terminal control module (42). The three-dimensional visualization monitoring module (41) is used to display real-time data of the manufacturing process and equipment status in a three-dimensional visualization manner. The mobile terminal control module (42) is used to realize remote control and monitoring of production equipment through mobile terminal devices.

6. The online monitoring and control system for Internet of Things manufacturing according to claim 1, characterized in that: Temperature sensors, pressure sensors, flow sensors, vibration sensors, current sensors, voltage sensors, temperature and humidity sensors, and air quality sensors are all connected to the network layer (2) via wired or wireless means.

7. The online monitoring and control system for Internet of Things manufacturing according to claim 1, characterized in that: The data protocol conversion module (21) supports the conversion of Bluetooth communication protocols, and the network communication management module (22) includes network devices such as routers and switches, which are used to build wired or wireless networks.

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