Corrugated paper product production early warning system and method based on wireless internet of things

Abstract

The invention discloses a corrugated paper product production early warning system and method based on the wireless Internet of Things, and the system comprises data collection modules which are disposed at a plurality of positions of a corrugated paper product production line, and are used for collecting the environment data, equipment data and product data of the production line in real time, the data acquisition module transmits the acquired data to the cloud server through the LoRa Internet of Things gateway; the data analysis module is configured in the cloud server and is used for analyzing the acquired real-time data, identifying an abnormal state in the data and sending alarm information to the abnormity early warning module through the wireless Internet of Things when the abnormal state is detected; and the abnormity early warning module is configured at an intelligent terminal of a production control center and / or a worker, and is used for carrying out early warning after receiving the alarm information.

Description

Technical Field

[0001] The present invention relates to the technical field of corrugated paper product production, and in particular to a corrugated paper product production early warning system and method based on wireless Internet of Things. Background Art

[0002] With the development of industrial automation and Internet of Things technology, the production of corrugated paper products is gradually transforming towards intelligence. However, due to the complexity of the production process and the great influence of environmental factors such as temperature and humidity, the traditional corrugated paper production management method is difficult to monitor and warn of production anomalies in a timely manner, resulting in low production efficiency, unstable product quality, and even serious consequences such as production shutdown. Therefore, there is an urgent need for an intelligent early warning system based on the Internet of Things to monitor key parameters in the production process in real time and detect abnormalities in a timely manner to improve production efficiency and product quality. Summary of the invention

[0003] In order to solve the problems raised in the above background technology, the technical solution adopted by the present invention is:

[0004] A corrugated paper product production early warning system based on wireless Internet of Things, comprising:

[0005] The data acquisition module is set at multiple locations of the corrugated paper product production line to collect environmental data, equipment data and product data of the production line in real time, and the data acquisition module transmits the collected data to the cloud server through the LoRa Internet of Things gateway;

[0006] The data analysis module is configured in the cloud server and is used to analyze the acquired real-time data, identify abnormal conditions in the data, and send alarm information to the abnormal warning module through the wireless Internet of Things when an abnormal condition is detected;

[0007] The abnormal warning module is configured in the production control center and / or the staff's smart terminal to issue an early warning after receiving the alarm information.

[0008] Preferably, the data acquisition module includes a temperature and humidity sensor, the model of the temperature and humidity sensor is HTG3500, and the environmental data includes environmental temperature data and humidity data acquired by the temperature and humidity sensor.

[0009] Preferably, the data acquisition module includes multiple types of equipment status monitoring sensors, and the equipment data is the operating data of the production equipment in the production line, including the working temperature data of each production equipment, the pressure data of the paper press and the gluing machine, the current and voltage data of the motor in each production equipment, the operating speed data of the conveyor belt, and also includes the operating time and fault records of each production equipment.

[0010] Preferably, the data acquisition module includes a 5g camera and a tension sensor, the tension sensor adopts an RB series tension detector, and the product data includes image data of corrugated paper obtained by taking a photo with the 5g camera, and also includes tension data of corrugated paper obtained by collecting the tension sensor.

[0011] Another aspect of the present invention provides a method for early warning of corrugated paper product production based on wireless Internet of Things, comprising the following steps:

[0012] S1. Real-time collection of environmental data, equipment data and product data at multiple locations of the corrugated paper production line;

[0013] S2, transmit the collected data to the cloud server through the LoRa IoT gateway;

[0014] S3. In the cloud server, the acquired real-time data is analyzed and abnormal conditions in the data are identified;

[0015] S4. When an abnormal state is identified, the alarm information is sent to the corresponding smart terminal and / or production control center through the wireless Internet of Things for abnormal warning.

[0016] Preferably, in step S1, the environmental data includes environmental temperature data and humidity data collected by a temperature and humidity sensor;

[0017] In step S3, the collected environmental data is compared with a preset threshold to determine whether there is an abnormal state in the data.

[0018] Preferably, in step S1, the equipment data is the operation data of the production equipment in the production line;

[0019] In step S3, the collected device data is compared with a preset threshold to determine whether there is an abnormal state in the data.

[0020] Preferably, in step S1, the product data includes tension data of the corrugated paper collected by a tension sensor;

[0021] In step S3, the collected tension data is compared with a preset threshold value to determine whether there is an abnormal state in the data.

[0022] Preferably, in step S1, the product data includes image data of corrugated paper captured by a 5g camera.

[0023] Preferably, in step S3, it is determined whether the image data is in an abnormal state by specifically performing the following steps:

[0024] First, the collected image is denoised using a Gaussian filter. The calculation formula of the Gaussian filter used is:

[0025]

[0026] Where (x, y) represents the input two-dimensional image, and the parameter σ is used to control the smoothness of the Gaussian filter;

[0027] Then, based on the image segmentation model, the feature area that needs to be detected is separated from the image. The loss function of the image segmentation model adopts Dice loss, which is expressed as:

[0028]

[0029] Among them, A and B represent the segmentation results predicted by the model and the actual segmentation results respectively;

[0030] Finally, the segmented feature area image is compared with the preset template image for matching, and whether the feature area is abnormal is determined based on the matching result.

[0031] In this way, it is possible to determine whether the corrugated paper products have defects such as damage, cracks, and bubbles.

[0032] Compared with the prior art, the wireless Internet of Things-based corrugated paper product production early warning system provided by the present invention utilizes Internet of Things technology to realize real-time monitoring of environmental data, equipment data and product data in the corrugated paper production process; the system can automatically identify and warn of abnormal situations in production, reducing the workload of manual monitoring; it improves the reliability of the production process and the quality stability of the product, reduces production costs and the risk of shutdown, and is conducive to improving production efficiency and product quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 The present invention provides a schematic diagram of a corrugated paper product production early warning system based on wireless Internet of Things;

[0034] Figure 2 A schematic flow chart of a method for early warning production of corrugated paper products based on wireless Internet of Things provided by the present invention. DETAILED DESCRIPTION

[0035] In order to make the technical means, creative features, objectives and effects achieved by the present invention easy to understand, the following further describes how the present invention is implemented in conjunction with the accompanying drawings and specific implementation methods.

[0036] Reference Figure 1As shown, the present invention provides a corrugated paper product production early warning system based on wireless Internet of Things, including: a data acquisition module 1, which is arranged at multiple positions of the corrugated paper product production line, and is used to collect environmental data, equipment data and product data of the production line in real time, and the data acquisition module 1 transmits the collected data to a cloud server through a LoRa (Long Range Radio) Internet of Things gateway; a data analysis module 2, which is configured in the cloud server, is used to analyze the acquired real-time data, identify abnormal states in the data, and when an abnormal state is detected, send alarm information to an abnormal early warning module 3 through the wireless Internet of Things; the abnormal early warning module 3 is configured in the production control center and / or the staff's smart terminal, and is used to issue an early warning after receiving the alarm information.

[0037] In a specific embodiment, the data acquisition module 1 includes a temperature and humidity sensor, the model of the temperature and humidity sensor is HTG3500, and the environmental data includes environmental temperature data and humidity data collected by the temperature and humidity sensor.

[0038] The data acquisition module 1 includes multiple types of equipment status monitoring sensors, and the equipment data is the operating data of the production equipment in the production line, including the working temperature data of each production equipment, the pressure data of the paper press and the gluing machine, the current and voltage data of the motor in each production equipment, the operating speed data of the conveyor belt, and also includes the operating time and fault records of each production equipment.

[0039] The data acquisition module 1 includes a 5g camera and a tension sensor. The tension sensor adopts an RB series tension detector. The product data includes image data of corrugated paper obtained by taking a photo with the 5g camera, and tension data of corrugated paper obtained by collecting the tension sensor.

[0040] Reference Figure 2 As shown, another aspect of the present invention provides a corrugated paper product production early warning method based on wireless Internet of Things, comprising the following steps:

[0041] S1. Real-time collection of environmental data, equipment data and product data at multiple locations of the corrugated paper production line;

[0042] S2, transmit the collected data to the cloud server through the LoRa IoT gateway;

[0043] S3. In the cloud server, the acquired real-time data is analyzed and abnormal conditions in the data are identified;

[0044] S4. When an abnormal state is identified, the alarm information is sent to the corresponding smart terminal and / or production control center through the wireless Internet of Things for abnormal warning.

[0045] In a specific embodiment, in step S1, the environmental data includes environmental temperature data and humidity data collected by temperature and humidity sensors; in step S3, by comparing the collected environmental data with a preset threshold, it is determined whether there is an abnormal state in the data.

[0046] In this embodiment, the overall ambient temperature of the production workshop is controlled between 15 and 27°C by presetting the temperature threshold and cooperating with the air conditioning equipment. If the workshop temperature is too high, the corrugated paper will consume more energy during the growth process, and the air drying time will be prolonged, resulting in a decrease in the quality of the corrugated paper; if the workshop temperature is too low, the corrugated paper will not grow normally, resulting in insufficient hardness, easy breakage and other problems.

[0047] In addition, by presetting the humidity threshold, and using humidifiers, dehumidifiers and other equipment, the overall relative humidity of the production workshop is controlled between 45% and 65% RH. Within this humidity range, the paper can maintain good flatness and strength, which is conducive to the smooth progress of subsequent processing such as printing, cutting and folding. At the same time, appropriate humidity can also prevent the paper from over-shrinking in a dry environment or over-expanding in a humid environment, thereby avoiding product deformation and cracking.

[0048] The temperature threshold is set according to different locations of the production line. For example, the base paper of corrugated paper needs to be controlled at 70-90°C after preheating; and the ambient temperature of the final corrugated paper product storage area should be controlled at

[0049] Furthermore, in step S1, the equipment data is the operation data of the production equipment in the production line; in step S3, by comparing the collected equipment data with a preset threshold, it is determined whether there is an abnormal state in the data.

[0050] Further, in step S1, the product data includes tension data of the corrugated paper collected by a tension sensor; in step S3, by comparing the collected tension data with a preset threshold, it is determined whether there is an abnormal state in the data.

[0051] Furthermore, in step S1, the product data includes image data of corrugated paper captured by a 5G camera. In step S3, the image data is judged to be abnormal by the following steps:

[0052] First, the collected image is denoised using a Gaussian filter. The calculation formula of the Gaussian filter used is:

[0053]

[0054] Where (x, y) represents the input two-dimensional image, and the parameter σ is used to control the smoothness of the Gaussian filter;

[0055] Then, based on the image segmentation model, the feature area that needs to be detected is separated from the image. The loss function of the image segmentation model adopts Dice loss, which is expressed as:

[0056]

[0057] Among them, A and B represent the segmentation results predicted by the model and the actual segmentation results respectively;

[0058] Finally, the segmented feature area image is compared with the preset template image for matching degree, and whether the feature area is abnormal is determined based on the matching result.

[0059] In summary, it can be seen that compared with the prior art, the wireless Internet of Things-based corrugated paper product production early warning system provided by the present invention utilizes Internet of Things technology to realize real-time monitoring of environmental data, equipment data and product data in the corrugated paper production process; the system can automatically identify and warn of abnormal situations in production, reducing the workload of manual monitoring; it improves the reliability of the production process and the quality stability of the product, reduces production costs and the risk of shutdown, and is conducive to improving production efficiency and product quality.

[0060] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the purpose and scope of the technical solution of the present invention, which should be included in the scope of the claims of the present invention.

Claims

1. A corrugated paper product production early warning system based on wireless Internet of Things, characterized in that: include: A data acquisition module (1) is arranged at multiple locations of a corrugated paper product production line and is used to collect environmental data, equipment data and product data of the production line in real time, and the data acquisition module (1) transmits the collected data to a cloud server via a LoRa Internet of Things gateway; A data analysis module (2) is configured in a cloud server and is used to analyze the acquired real-time data, identify abnormal conditions in the data, and send alarm information to the abnormal warning module (3) via a wireless Internet of Things when an abnormal condition is detected; The abnormal warning module (3) is configured in the production control center and / or the intelligent terminal of the staff, and is used to issue a warning after receiving the alarm information.

2. The corrugated paper product production early warning system based on wireless Internet of Things according to claim 1 is characterized in that: The data acquisition module (1) comprises a temperature and humidity sensor, the model of which is HTG3500, and the environmental data comprises environmental temperature data and humidity data acquired by the temperature and humidity sensor.

3. The corrugated paper product production early warning system based on wireless Internet of Things according to claim 1 is characterized in that: The data acquisition module (1) includes multiple types of equipment status monitoring sensors, and the equipment data is the operating data of the production equipment in the production line, including the operating temperature data of each production equipment, the pressure data of the paper press and the gluing machine, the current and voltage data of the motor in each production equipment, the operating speed data of the conveyor belt, and also includes the operating time and fault records of each production equipment.

4. The corrugated paper product production early warning system based on wireless Internet of Things according to claim 1 is characterized in that: The data acquisition module (1) comprises a 5G camera, a temperature transmitter and a tension sensor, wherein the tension sensor adopts an RB series tension detector, and the product data comprises image data of the corrugated paper obtained by taking a picture with the 5G camera, and also comprises tension data of the corrugated paper obtained by collecting the tension sensor.

5. A corrugated paper product production early warning method based on wireless Internet of Things, characterized in that: The steps include: S1. Real-time collection of environmental data, equipment data and product data at multiple locations of the corrugated paper production line; S2, transmit the collected data to the cloud server through the LoRa IoT gateway; S3. In the cloud server, the acquired real-time data is analyzed and abnormal conditions in the data are identified; S4. When an abnormal state is identified, the alarm information is sent to the corresponding smart terminal and / or production control center through the wireless Internet of Things for abnormal warning.

6. The method for early warning of corrugated paper product production based on wireless Internet of Things according to claim 5 is characterized in that: In step S1, the environmental data includes environmental temperature data and humidity data collected by a temperature and humidity sensor; In step S3, the collected environmental data is compared with a preset threshold to determine whether there is an abnormal state in the data.

7. The method for early warning of corrugated paper product production based on wireless Internet of Things according to claim 5 is characterized in that: In step S1, the equipment data is the operation data of the production equipment in the production line; In step S3, the collected device data is compared with a preset threshold to determine whether there is an abnormal state in the data.

8. The method for early warning of corrugated paper product production based on wireless Internet of Things according to claim 5 is characterized in that: In step S1, the product data includes tension data of the corrugated paper collected by a tension sensor; In step S3, the collected tension data is compared with a preset threshold value to determine whether there is an abnormal state in the data.

9. The method for early warning of corrugated paper product production based on wireless Internet of Things according to claim 1, characterized in that: In step S1, the product data includes image data of corrugated paper captured by a 5g camera.

10. The method for early warning of corrugated paper product production based on wireless Internet of Things according to claim 9, characterized in that: In step S3, it is determined whether the image data is in an abnormal state by specifically performing the following steps: First, the collected image is denoised using a Gaussian filter. The calculation formula of the Gaussian filter used is: Where (x, y) represents the input two-dimensional image, and the parameter σ is used to control the smoothness of the Gaussian filter; Then, based on the image segmentation model, the feature area that needs to be detected is separated from the image. The loss function of the image segmentation model adopts Dice loss, which is expressed as: Among them, A and B represent the segmentation results predicted by the model and the actual segmentation results respectively; Finally, the segmented feature area image is compared with the preset template image for matching degree, and whether the feature area is abnormal is determined based on the matching result.

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