A method and system for detecting and identifying the drying stage of online dryness in a spray coating production line

Abstract

The present application relates to the technical field of insulation board spraying and drying, and particularly discloses a method and system for detecting and identifying the drying degree of an online drying stage of a spraying production line, which comprises the following steps: S1: during the drying stage of the insulation board spraying production line, a plurality of detection points are arranged along the length direction of the production line, and each detection point is equipped with an infrared thermal imager with high precision and a wide field of view; S2: the temperature data of the surface of the insulation board at each detection point is acquired in real time by means of the non-contact measurement mode of the infrared thermal imager. The present application adopts the non-contact temperature measurement mode of the infrared camera, thereby avoiding direct contact with the insulation board and causing no damage to the insulation board or affecting the performance of the insulation board. The infrared camera can capture and display the temperature distribution of the surface of the insulation board in real time, so that the worker can quickly understand the drying progress and effect. By arranging a plurality of detection points, the overall drying process can be comprehensively monitored, and the drying degree of each region can meet the requirements.

Description

Technical Field

[0001] This invention belongs to the field of thermal insulation board spraying and drying technology, specifically relating to a method and system for online detection and identification of drying stage in a spraying production line. Background Technology

[0002] Online drying testing during the drying stage of a spray coating production line is a crucial step in ensuring product quality and production efficiency. Real-time monitoring of temperature changes and drying levels of insulation boards or other spray-coated products during the drying process ensures that the products achieve the expected drying effect. By analyzing the test data, the parameters of the drying equipment can be adjusted in a timely manner to optimize the drying process and improve production efficiency and product quality.

[0003] However, in existing technologies, single-point temperature measuring devices are generally used. These devices (such as thermocouples and resistance temperature detectors) can usually only measure the temperature of one point. If only single-point temperature measuring devices are used on the insulation board spraying production line, it may be impossible to capture the temperature distribution of the entire insulation board surface, resulting in a detection blind spot. Therefore, a method and system for online drying degree detection and identification in the drying stage of the spraying production line is proposed. Summary of the Invention

[0004] The purpose of this invention is to provide a method and system for online drying degree detection and identification in a spraying production line, in order to solve the problem that the commonly used single-point temperature measuring equipment (such as thermocouples, resistance temperature detectors, etc.) can usually only measure the temperature of one point. In the insulation board spraying production line, if only single-point temperature measuring equipment is used, it may not be possible to capture the temperature distribution of the entire insulation board surface, thus creating a detection blind spot.

[0005] To achieve the above objectives, the present invention provides the following technical solution:

[0006] A method for detecting and identifying the drying stage of an online coating production line, comprising:

[0007] S1: During the drying stage of the insulation board spraying production line, multiple detection points are set along the length of the production line, and each detection point is equipped with a high-precision, wide-field infrared thermal imager. The infrared thermal imager has the function of automatically adjusting the focal length, exposure time and infrared sensitivity to adapt to insulation boards of different sizes, shapes and surface characteristics, and captures and records the temperature distribution image of the insulation board surface in real time. At the same time, the infrared thermal imager is also equipped with a dustproof, waterproof and high-temperature resistant shell to ensure stable operation in harsh environments.

[0008] S2: The temperature data of the insulation board surface at each detection point is acquired in real time through the non-contact measurement method of infrared thermal imager, and the temperature data is converted into a dryness index using advanced image processing algorithms and machine learning models. This index reflects the degree of moisture evaporation and heat distribution on the surface of the insulation board, while taking into account the influence of external factors such as ambient temperature, humidity, airflow speed, insulation board material and coating type.

[0009] S3: Compare the obtained dryness index with the preset dryness standard range; this standard range is preset based on factors such as the material, thickness, coating type, required dryness degree and production process requirements of the insulation board, and can be dynamically adjusted and optimized according to actual production conditions and historical data;

[0010] S4: If the dryness index of the insulation board at any detection point fails to meet the preset standard range, the alarm system will be triggered immediately, displaying the specific non-conforming location and dryness index, and the parameters of the drying equipment will be automatically adjusted through the control system, such as heating temperature, wind speed, drying time, internal pressure of the drying chamber, and air circulation mode, to optimize the drying effect. At the same time, the non-conforming data will be recorded and analyzed, including the non-conforming location, dryness index, parameters before and after adjustment, and adjustment effect, for subsequent quality improvement and process optimization.

[0011] S5: After adjusting the parameters, continue to monitor the dryness index of the insulation board until the index of all detection points meets the preset standard range, ensuring that the insulation board reaches the predetermined dryness level. Record and analyze the adjusted drying effect data, including the trend of the dryness index, energy consumption, and production efficiency, to evaluate and optimize the adjustment strategy.

[0012] By setting up the above technical solution, the present invention uses an infrared thermal imager to measure moisture using the principle of near-infrared light absorption, embeds an online moisture detector into the production line, and achieves continuous production process control by combining it with the transmission mechanism, thus ensuring the stability of panel dryness.

[0013] By receiving and processing reflected light, and utilizing an embedded high-performance micro digital signal processing chip for data processing, storage, and display, moisture content can be measured quickly and accurately. During use, the sensor monitors the moisture content of the product in real time, transmitting the detected data to a computer, enabling real-time, continuous, and accurate monitoring of moisture levels. By determining the moisture content, the dryness of the board material can be assessed, and boards that do not meet the required dryness level can be dried again.

[0014] In the online drying stage of the insulation board spraying production line, using multiple detection points and setting up an infrared camera at each detection point has the following advantages:

[0015] The infrared camera uses a non-contact temperature measurement method, which avoids direct contact with the insulation board, thus preventing any damage to the insulation board or affecting its performance.

[0016] Infrared cameras can capture and display the temperature distribution on the surface of the insulation board in real time, enabling staff to quickly understand the drying progress and effect; by setting up multiple detection points, comprehensive monitoring of the entire drying process can be achieved, ensuring that the dryness of each area meets the requirements;

[0017] Infrared cameras have high sensitivity and can accurately capture minute temperature changes, thereby improving detection accuracy; setting up multiple detection points can further reduce errors and improve overall detection precision.

[0018] The infrared camera has an area array temperature measurement function, which can cover a large detection area and ensure that each detection point can be fully monitored; by adjusting the camera parameters, it is also possible to monitor insulation boards of different sizes and shapes.

[0019] A method for detecting and identifying the drying stage of an online drying process in a spray coating production line, further comprising the following steps:

[0020] A1: After the drying stage, the surface quality of the insulation board is inspected using a machine vision system combined with deep learning algorithms and image recognition technology. The system automatically identifies and marks defects or flaws such as cracks, bubbles, uneven coating, color difference, scratches, and contamination. It also provides the severity and location information of the defects, as well as possible repair suggestions.

[0021] A2: If defects or flaws are found during quality inspection, the relevant information will be automatically fed back to the control system, the production line will be suspended, and an audible and visual alarm and SMS or email notification will be triggered. This will allow operators to conduct manual re-inspection or take other remedial measures. At the same time, defect data, including defect type, location, quantity, and repair measures, will be recorded and analyzed for subsequent quality improvement and process optimization.

[0022] A method for detecting and identifying the drying stage of an online drying process in a spray coating production line, further comprising the following steps:

[0023] C1: Before the insulation board enters the drying stage, the weight, thickness, and appearance quality of the sprayed insulation board are measured using a weighing sensor, thickness measuring device, and image recognition technology to determine the thickness, uniformity, and appearance quality of the sprayed coating. At the same time, a laser rangefinder or 3D scanner is used to accurately measure the size and shape of the insulation board to ensure the accuracy and consistency of the spraying and drying process.

[0024] C2: If the coating weight, thickness, appearance quality, or dimensions do not meet the preset standards, the parameters of the coating equipment will be automatically adjusted, such as the coating speed, coating pressure, coating volume, nozzle type and layout, and coating path, to ensure that the coating quality meets the requirements. At the same time, the adjusted coating effect data will be recorded and analyzed, including the coating thickness distribution, uniformity, appearance quality, and energy consumption, to evaluate and optimize the adjustment strategy.

[0025] A detection system for online drying stage detection and identification in a spray coating production line is characterized by comprising a spray coating equipment, a drying equipment, a high-precision infrared thermal imager detection system, a machine vision quality inspection system, an intelligent control system, a data storage and analysis system, and a human-machine interface. The detection system includes multiple high-precision, wide-field-of-view infrared thermal imagers, respectively positioned at different locations on the drying equipment, for real-time detection and recording of temperature distribution images on the surface of the insulation board. The machine vision quality inspection system, combining deep learning algorithms and image recognition technology, is used to perform surface quality inspection on the insulation board after the drying stage. The intelligent control system is connected to the detection system and the quality inspection system, for receiving detection data and quality inspection results, and for adjusting parameters of the spray coating equipment and the drying equipment according to preset logic. The data storage and analysis system stores and analyzes detection data, quality inspection results, effect data of adjustment strategies, and production line operation data, providing support for production line quality improvement, process optimization, and equipment maintenance. The human-machine interface displays real-time production status, alarm information, adjustment strategies, and historical data, facilitating operator monitoring and management of the production line.

[0026] Compared with the prior art, the beneficial effects of the present invention are:

[0027] This invention uses an infrared camera for non-contact temperature measurement, avoiding direct contact with the insulation board and thus preventing any damage or impact on its performance. The infrared camera can capture and display the temperature distribution on the surface of the insulation board in real time, allowing staff to quickly understand the drying progress and effect. By setting multiple detection points, comprehensive monitoring of the entire drying process can be achieved, ensuring that the dryness of each area meets the requirements. Attached Figure Description

[0028] Figure 1 This is a flowchart of the steps of the present invention;

[0029] Figure 2 This is a flowchart of the steps following the drying and testing in this invention;

[0030] Figure 3 This is a flowchart of the steps before drying and testing in this invention. Detailed Implementation

[0031] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention. Example

[0032] like Figure 1 As shown, a method for detecting and identifying the drying stage of an online coating production line includes:

[0033] S1: During the drying stage of the insulation board spraying production line, multiple detection points are set along the length of the production line, and each detection point is equipped with a high-precision, wide-field infrared thermal imager. The infrared thermal imager has the function of automatically adjusting the focal length, exposure time and infrared sensitivity to adapt to insulation boards of different sizes, shapes and surface characteristics, and captures and records the temperature distribution image of the insulation board surface in real time. At the same time, the infrared thermal imager is also equipped with a dustproof, waterproof and high-temperature resistant shell to ensure stable operation in harsh environments.

[0034] S2: The temperature data of the insulation board surface at each detection point is acquired in real time through the non-contact measurement method of infrared thermal imager, and the temperature data is converted into a dryness index using advanced image processing algorithms and machine learning models. This index reflects the degree of moisture evaporation and heat distribution on the surface of the insulation board, while taking into account the influence of external factors such as ambient temperature, humidity, airflow speed, insulation board material and coating type.

[0035] S3: Compare the obtained dryness index with the preset dryness standard range; this standard range is preset based on factors such as the material, thickness, coating type, required dryness degree and production process requirements of the insulation board, and can be dynamically adjusted and optimized according to actual production conditions and historical data;

[0036] S4: If the dryness index of the insulation board at any detection point fails to meet the preset standard range, the alarm system will be triggered immediately, displaying the specific non-conforming location and dryness index, and the parameters of the drying equipment will be automatically adjusted through the control system, such as heating temperature, wind speed, drying time, internal pressure of the drying chamber, and air circulation mode, to optimize the drying effect. At the same time, the non-conforming data will be recorded and analyzed, including the non-conforming location, dryness index, parameters before and after adjustment, and adjustment effect, for subsequent quality improvement and process optimization.

[0037] S5: After adjusting the parameters, continue to monitor the dryness index of the insulation board until the index of all detection points meets the preset standard range, ensuring that the insulation board reaches the predetermined dryness level. Record and analyze the adjusted drying effect data, including the trend of the dryness index, energy consumption, and production efficiency, to evaluate and optimize the adjustment strategy.

[0038] By setting up the above technical solution, the present invention uses an infrared thermal imager to measure moisture using the principle of near-infrared light absorption, embeds an online moisture detector into the production line, and achieves continuous production process control by combining it with the transmission mechanism, thus ensuring the stability of panel dryness.

[0039] By receiving and processing reflected light, and utilizing an embedded high-performance micro digital signal processing chip for data processing, storage, and display, moisture content can be measured quickly and accurately. During use, the sensor monitors the moisture content of the product in real time, transmitting the detected data to a computer, enabling real-time, continuous, and accurate monitoring of moisture levels. By determining the moisture content, the dryness of the board material can be assessed, and boards that do not meet the required dryness level can be dried again.

[0040] In the drying stage of the online drying process of the insulation board spraying production line, using multiple detection points and setting up an infrared camera at each detection point has the following advantages:

[0041] The infrared camera uses a non-contact temperature measurement method, which avoids direct contact with the insulation board, thus preventing any damage to the insulation board or affecting its performance.

[0042] Infrared cameras can capture and display the temperature distribution on the surface of the insulation board in real time, enabling staff to quickly understand the drying progress and effect; by setting up multiple detection points, comprehensive monitoring of the entire drying process can be achieved, ensuring that the dryness of each area meets the requirements;

[0043] Infrared cameras have high sensitivity and can accurately capture minute temperature changes, thereby improving detection accuracy; setting up multiple detection points can further reduce errors and improve overall detection precision.

[0044] The infrared camera has an area array temperature measurement function, which can cover a large detection area and ensure that each detection point can be fully monitored; by adjusting the camera parameters, it is also possible to monitor insulation boards of different sizes and shapes. Example

[0045] A method for detecting and identifying the drying stage of an online drying process in a spray coating production line, further comprising the following steps:

[0046] A1: After the drying stage, the surface quality of the insulation board is inspected using a machine vision system combined with deep learning algorithms and image recognition technology. The system automatically identifies and marks defects or flaws such as cracks, bubbles, uneven coating, color difference, scratches, and contamination. It also provides the severity and location information of the defects, as well as possible repair suggestions.

[0047] A2: If defects or flaws are found during quality inspection, the relevant information will be automatically fed back to the control system, the production line will be suspended, and an audible and visual alarm and SMS or email notification will be triggered. This will allow operators to conduct manual re-inspection or take other remedial measures. At the same time, defect data, including defect type, location, quantity, and repair measures, will be recorded and analyzed for subsequent quality improvement and process optimization. Example

[0048] A method for detecting and identifying the drying stage of an online drying process in a spray coating production line, further comprising the following steps:

[0049] C1: Before the insulation board enters the drying stage, the weight, thickness, and appearance quality of the sprayed insulation board are measured using a weighing sensor, thickness measuring device, and image recognition technology to determine the thickness, uniformity, and appearance quality of the sprayed coating. At the same time, a laser rangefinder or 3D scanner is used to accurately measure the size and shape of the insulation board to ensure the accuracy and consistency of the spraying and drying process.

[0050] C2: If the coating weight, thickness, appearance quality, or dimensions do not meet the preset standards, the parameters of the coating equipment will be automatically adjusted, such as the coating speed, coating pressure, coating volume, nozzle type and layout, and coating path, to ensure that the coating quality meets the requirements. At the same time, the adjusted coating effect data will be recorded and analyzed, including the coating thickness distribution, uniformity, appearance quality, and energy consumption, to evaluate and optimize the adjustment strategy.

[0051] A detection system for online drying stage detection and identification in a spray coating production line is characterized by comprising a spray coating equipment, a drying equipment, a high-precision infrared thermal imager detection system, a machine vision quality inspection system, an intelligent control system, a data storage and analysis system, and a human-machine interface. The detection system includes multiple high-precision, wide-field-of-view infrared thermal imagers, respectively positioned at different locations on the drying equipment, for real-time detection and recording of temperature distribution images on the surface of the insulation board. The machine vision quality inspection system, combining deep learning algorithms and image recognition technology, is used to perform surface quality inspection on the insulation board after the drying stage. The intelligent control system is connected to the detection system and the quality inspection system, for receiving detection data and quality inspection results, and for adjusting parameters of the spray coating equipment and the drying equipment according to preset logic. The data storage and analysis system stores and analyzes detection data, quality inspection results, effect data of adjustment strategies, and production line operation data, providing support for production line quality improvement, process optimization, and equipment maintenance. The human-machine interface displays real-time production status, alarm information, adjustment strategies, and historical data, facilitating operator monitoring and management of the production line.

[0052] Furthermore, this design is applied to the detection and identification of the online drying stage of the insulation board spraying production line. The infrared camera adopts a non-contact temperature measurement method, avoiding direct contact with the insulation board, thus preventing any damage to the insulation board or affecting its performance. The infrared camera can capture and display the temperature distribution on the surface of the insulation board in real time, enabling workers to quickly understand the drying progress and effect. By setting multiple detection points, comprehensive monitoring of the entire drying process can be achieved, ensuring that the dryness of each area meets the requirements.

[0053] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for detecting and identifying the drying stage of an online drying process in a spray coating production line, characterized in that, include: S1: During the drying stage of the insulation board spraying production line, multiple detection points are set along the length of the production line, and each detection point is equipped with a high-precision, wide-field infrared thermal imager. S2: The temperature data of the insulation board surface at each detection point is acquired in real time through the non-contact measurement method of infrared thermal imager, and the temperature data is converted into a dryness index using advanced image processing algorithms and machine learning models. S3: Compare the obtained dryness index with the preset dryness standard range; S4: If the dryness index of the insulation board at any detection point does not meet the preset standard range, the alarm system will be triggered immediately, displaying the specific non-conforming location and dryness index, and the parameters of the drying equipment will be automatically adjusted through the control system. S5: After adjusting the parameters, continue to monitor the dryness index of the insulation board until all the indicators at the test points meet the preset standard range, ensuring that the insulation board reaches the predetermined dryness level, and record and analyze the adjusted drying effect data. The temperature data of the insulation board surface includes ambient temperature, humidity and airflow speed, and the dryness index is used to reflect the degree of moisture evaporation and heat distribution on the insulation board surface. The parameters of the drying equipment are heating temperature, wind speed, drying time, internal pressure of the drying chamber, and air circulation mode; The drying effect data indicators include the trend of the dryness index, energy consumption, and production efficiency. Also includes: C1: Before the insulation board enters the drying stage, the weight, thickness and appearance quality of the sprayed insulation board are measured using a weighing sensor, thickness measuring device and image recognition technology. At the same time, the size and shape of the insulation board are accurately measured using a laser rangefinder or 3D scanner. C2: If the coating weight, thickness, appearance quality, or dimensions do not meet the preset standards, the parameters of the coating equipment will be automatically adjusted, and the adjusted coating effect data will be recorded and analyzed.

2. The method for detecting and identifying the drying stage of an online drying production line according to claim 1, characterized in that: The infrared thermal imager has the function of automatically adjusting the focal length, exposure time and infrared sensitivity, and is equipped with a dustproof, waterproof and high temperature resistant outer shell.

3. The method for detecting and identifying the drying stage of an online drying production line according to claim 1, characterized in that: The dryness standard range includes the material, thickness, coating type, required dryness level, and production process requirements of the insulation board.

4. A method for detecting and identifying the drying stage of an online drying process in a spray coating production line according to any one of claims 1-3, characterized in that, It also includes: A1: After the drying stage, the surface quality of the insulation board is inspected using a machine vision system combined with deep learning algorithms and image recognition technology, and defects or flaws are automatically identified and marked. A2: If defects or flaws are found during quality inspection, the relevant information will be automatically fed back to the control system, the production line will be suspended, and an audible and visual alarm and SMS or email notification will be triggered. At the same time, the defect data will be recorded and analyzed.

5. The method for detecting and identifying the drying stage of an online drying production line according to claim 4, characterized in that: The marked defects or flaws include cracks, bubbles, uneven coating, color difference, scratches, and contamination. The recorded and analyzed defect data includes defect type, location, quantity, and repair measures.

6. A detection system employing the online drying stage detection and identification method for a spray coating production line according to any one of claims 1-5, characterized in that, It includes spraying equipment, drying equipment, high-precision infrared thermal imager detection system, machine vision quality inspection system, intelligent control system, data storage and analysis system, and human-machine interface.

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