Intelligent monitoring, regulating and controlling method and system for setting machine

Abstract

The embodiment of the invention discloses an intelligent monitoring, regulating and controlling method and system for a setting machine. The method comprises the following steps: acquiring corresponding data acquired by a sensor arranged at a specified position of a setting machine, wherein the data comprises at least one of cloth cover temperature, humidity in a drying oven, fabric moisture content, fabric gram weight, fabric thickness, fabric breadth, fabric tension, drying oven air pressure, drying oven particulate matter concentration, filter screen pollution degree and fabric defects; and adjusting regulation and control parameters corresponding to the setting machine according to the data. By implementing the method provided by the embodiment of the invention, various parameters in the production process can be quantified, manual experience judgment is replaced, the qualified rate of the fabric quality is improved, the production energy consumption is reduced, and the yield is improved.

Description

Technical Field

[0001] This invention relates to a method for monitoring a stenter, and more specifically to an intelligent monitoring and control method and system for a stenter. Background Technology

[0002] In the textile industry, finishing processes are crucial steps in improving fabric performance and appearance, and the stenter is the core equipment in this process. The purpose of finishing is to improve the fabric's hand feel, appearance, durability, and endow it with specific functional characteristics through a series of treatments, such as stretching and drying. The stenter plays a vital role in this process. The stenter's workflow is as follows: The fabric undergoes pretreatment through a water tank or spray device at the front of the stenter. This step aims to increase the fabric's moisture content, providing the necessary humid environment for subsequent processing steps and ensuring uniform treatment in subsequent operations. Inside the stenter, the fabric is stretched by a stretching device, which helps to smooth the fabric's texture, resulting in a more uniform appearance and better dimensional stability after setting. Finally, the fabric undergoes high-temperature drying in an oven. Drying not only removes excess moisture from the fabric but also helps to set the fabric's shape and size.

[0003] Currently, the operation of most setting machines relies heavily on worker experience. During debugging and operation, workers adjust equipment parameters based on intuition and experience to ensure the fabric meets the expected quality standards. However, the production process of setting machines often lacks a comprehensive intelligent monitoring system. Workers can only adjust the equipment using single parameters, such as oven temperature, which prevents other important variables in the production process, such as humidity, fabric thickness, and weight, from being monitored and adjusted in real time. Due to the lack of intelligent monitoring of the entire setting machine production process, workers cannot fully understand the state of the fabric throughout the processing. In this situation, the control and adjustment of the production process depend entirely on worker experience rather than data-driven real-time feedback. Currently, the final judgment of fabric quality mainly relies on manual inspection at the setting machine exit. This manual inspection method can lead to quality fluctuations and is difficult to achieve in terms of consistency and comprehensiveness.

[0004] Therefore, it is necessary to design a new method that quantifies various parameters of the production process, replaces manual experience-based judgment, improves the fabric quality pass rate, reduces production energy consumption, and increases output. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of the prior art and provide an intelligent monitoring and control method and system for stenter machines.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: an intelligent monitoring and control method for a stenter, comprising:

[0007] The sensor located at a specified position on the setting machine collects corresponding data, including at least one of the following: fabric surface temperature, humidity in the oven, fabric moisture content, fabric weight, fabric thickness, fabric width, fabric tension, oven air pressure, oven particulate matter concentration, filter contamination level, and fabric defects.

[0008] Adjust the control parameters of the setting machine according to the data.

[0009] The further technical solution is as follows: the sensor includes at least one of the following: a fabric surface temperature sensor installed in the oven of the setting machine; a high temperature and humidity sensor installed inside the oven of the setting machine; a moisture content sensor and a moisture content consistency sensor installed between the feeding device and the inlet of the setting machine; a weight sensor and a thickness sensor installed at the outlet of the setting machine; a wind pressure sensor installed on the oven; a smoke sensor installed at the inlet and outlet of the oven of the setting machine; a transmittance sensor installed on the filter screen of the oven of the setting machine; a defect detection device installed at the outlet of the setting machine; a tension sensor installed at the inlet of the setting machine; and a width sensor installed at the outlet of the setting machine.

[0010] The further technical solution is as follows: adjusting the control parameters corresponding to the setting machine according to the data includes:

[0011] The machine speed, setting temperature and setting time are calculated based on the curve corresponding to the fabric temperature, fabric humidity and oven temperature and humidity and oven length. The fabric temperature is compared with the setting temperature and the setting time is compared with the set time conditions to obtain the first comparison result.

[0012] If the first comparison result is that the fabric temperature has not reached the setting temperature, then the oven temperature is adjusted; if the setting time does not meet the set time condition, then the machine speed is adjusted.

[0013] The further technical solution is as follows: adjusting the control parameters corresponding to the setting machine according to the data includes:

[0014] The humidity range is calculated using simulation technology based on the humidity of the oven, and the humidity of the oven is controlled by adjusting the air volume of the exhaust fan.

[0015] The further technical solution is as follows: adjusting the control parameters corresponding to the setting machine according to the data includes:

[0016] A moisture content sensor is used to monitor the moisture content and distribution of the fabric, and the feeding device is adjusted according to the set value to control the overall moisture content and auxiliary agent content of the fabric.

[0017] The further technical solution is as follows: adjusting the control parameters corresponding to the setting machine according to the data includes:

[0018] The fabric weight data is monitored in real time by a weight sensor, and the fabric weight is controlled by adjusting the overfeed and stretching.

[0019] The further technical solution is as follows: adjusting the control parameters corresponding to the setting machine according to the data includes:

[0020] Fabric thickness data is monitored in real time using a thickness sensor, and the fabric thickness is controlled by adjusting overfeed and stretching.

[0021] The further technical solution is as follows: adjusting the control parameters corresponding to the setting machine according to the data includes:

[0022] Set a wind pressure threshold and adjust the exhaust fan to keep the data collected by the wind pressure sensor below the wind pressure threshold in order to maintain the negative pressure state of the oven.

[0023] The further technical solution is as follows: adjusting the control parameters corresponding to the setting machine according to the data includes:

[0024] Set a particulate matter concentration threshold and adjust the exhaust fan to keep the data collected by the smoke sensor below the particulate matter concentration threshold;

[0025] The step of adjusting the control parameters corresponding to the setting machine based on the data further includes:

[0026] The intensity of transmitted light through the filter is monitored by a transmittance sensor. When the light intensity is lower than a set threshold, the filter is cleaned and replaced.

[0027] The step of adjusting the control parameters corresponding to the setting machine based on the data further includes:

[0028] The defect detection device uses image recognition technology to detect defects on the fabric based on the data collected, and evaluates whether the fabric's production quality is up to standard based on the set defect rate, defect size, and shape.

[0029] The present invention also provides an intelligent monitoring and control system for the aforementioned setting machine, comprising a control unit and sensors. The control unit is used to acquire data collected by sensors located at designated positions on the setting machine. The data includes at least one of the following: fabric surface temperature, humidity inside the oven, fabric moisture content, fabric weight, fabric thickness, fabric width, fabric tension, oven air pressure, oven particulate matter concentration, filter contamination level, and fabric defects. The control unit adjusts the corresponding control parameters of the setting machine based on the data. The sensors include at least one of the following: fabric surface temperature sensor located in the setting machine oven; high temperature and humidity sensor located inside the setting machine oven; moisture content sensor and moisture content consistency sensor located between the feeding device and the fabric inlet of the setting machine; weight sensor and thickness sensor located at the outlet of the setting machine; air pressure sensor located on the oven; smoke sensor located at the inlet and outlet of the setting machine oven; transmittance sensor located on the filter screen of the setting machine oven; defect detection device located at the outlet of the setting machine; tension sensor located at the inlet of the setting machine; and width sensor located at the outlet of the setting machine.

[0030] The advantages of this invention compared to existing technologies are as follows: This invention collects data at designated locations on the setting machine using sensors, including fabric surface temperature, oven humidity, fabric moisture content, fabric weight, fabric thickness, oven air pressure, particulate matter concentration, filter transmittance, and fabric defects. The control system analyzes this data and compares it with set standards. If the data does not meet the standards, the system automatically adjusts the setting machine's control parameters. This adjustment ensures the setting machine operates at its optimal state to maintain fabric quality; it quantifies various parameters of the production process, replaces manual experience-based judgment, improves the fabric quality pass rate, reduces production energy consumption, and increases output.

[0031] The present invention will be further described below with reference to the accompanying drawings and specific embodiments. Attached Figure Description

[0032] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0033] Figure 1 A flowchart illustrating the intelligent monitoring and control method for a stenter provided in an embodiment of the present invention;

[0034] Figure 2 A schematic diagram showing the shaping temperature and oven length provided for an embodiment of the present invention;

[0035] Figure 3This is a schematic block diagram of an intelligent monitoring and control system for a stenter provided in an embodiment of the present invention;

[0036] Figure 4 This is a schematic diagram illustrating the installation of the sensor provided in an embodiment of the present invention. Detailed Implementation

[0037] 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, not all, of the embodiments of the present invention. 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.

[0038] It should be understood that, when used in this specification and the appended claims, the terms "comprising" and "including" indicate the presence of the described features, integrals, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0039] It should also be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the invention. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0040] It should also be further understood that the term "and / or" as used in this specification and the appended claims refers to any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0041] Please see Figure 1 , Figure 1 This is a schematic flowchart illustrating the intelligent monitoring and control method for a stenter provided in this embodiment of the invention. This intelligent monitoring and control method for a stenter is applied to a controller, combining sensors to monitor the products produced by the stenter. By installing multiple sensors, intelligent monitoring of the entire production process of the stenter is achieved, quantifying traditional manual experience, improving the fabric quality pass rate, reducing production energy consumption, and increasing output. The system framework includes a controller and sensors. The controller receives feedback data from the sensors and controls the operation of the stenter through calculation and analysis. After the sensors are installed, they operate in real time. The controller analyzes the data and compares it with a set feedback threshold. If the threshold is not reached, the controller issues a command to adjust the control parameters of the stenter to ensure that the stenter's operating state remains within the set feedback threshold range.

[0042] Figure 1This is a flowchart illustrating the intelligent monitoring and control method for a stenter provided in an embodiment of the present invention. Figure 1 As shown, the method includes the following steps S110 to S120.

[0043] S110. Acquire corresponding data from sensors set at designated locations on the setting machine. The data includes at least one of the following: fabric surface temperature, humidity inside the oven, fabric moisture content, fabric weight, fabric thickness, fabric width, fabric tension, oven air pressure, oven particulate matter concentration, filter contamination level, and fabric defects.

[0044] In this embodiment, the sensors include at least one of the following: a fabric surface temperature sensor installed in the setting machine oven; a high temperature and humidity sensor installed inside the setting machine oven; a moisture content sensor and a moisture content consistency sensor installed between the feeding device and the fabric inlet of the setting machine; a weight sensor and a thickness sensor installed at the outlet of the setting machine; an air pressure sensor installed on the oven; a smoke sensor installed at the inlet and outlet of the setting machine oven; a transmittance sensor installed on the filter screen of the setting machine oven; a defect detection device installed at the outlet of the setting machine; a tension sensor installed at the inlet of the setting machine; and a width sensor installed at the outlet of the setting machine.

[0045] S120. Adjust the control parameters corresponding to the setting machine according to the data.

[0046] In one embodiment, step S120 described above may include the following steps:

[0047] The setting temperature and setting time are calculated based on the distribution curve of the fabric temperature, the machine speed and the length of the oven. The fabric temperature is compared with the setting temperature and the setting time is compared with the set time conditions to obtain the first comparison result.

[0048] If the first comparison result is that the fabric temperature has not reached the setting temperature, then the oven temperature is adjusted; if the setting time does not meet the set time condition, then the machine speed is adjusted.

[0049] In this embodiment, the first comparison result refers to the result obtained by comparing the fabric temperature with the setting temperature and the setting time with the set time conditions.

[0050] Specifically, the required setting temperature and setting time are calculated based on the fabric temperature profile, machine speed, and oven length. These calculations are based on the actually measured fabric temperature profile, combined with machine speed and oven length, to determine the ideal setting conditions for the fabric.

[0051] The actual measured fabric temperature is compared with the calculated setting temperature; the actual setting time is compared with the preset time conditions; through these comparisons, a first comparison result is obtained.

[0052] If the first comparison result shows that the fabric temperature has not reached the required setting temperature, the oven temperature needs to be adjusted to make the fabric temperature reach the required setting temperature; speed adjustment: if the setting time does not meet the preset time conditions, the speed needs to be adjusted to ensure that the fabric stays in the oven for the set setting time.

[0053] The adjustment process involves installing fabric surface temperature sensors at the top of each oven section to monitor the fabric surface temperature in real time. During the fabric heat setting process, the fabric surface temperature needs to reach a predetermined setting temperature and be maintained at that temperature for a certain period of time. The fabric surface temperature curve fed back by the sensors, along with the machine speed and oven length, are used to calculate the actual setting temperature and setting time of the fabric. Figure 2 As shown; when the fabric temperature does not reach the set setting temperature, the system will automatically adjust the oven temperature; when the setting time does not meet the set threshold, the system will adjust the machine speed to ensure that the fabric is set within the specified time.

[0054] Through these steps, the system can precisely control the fabric setting process, ensuring that the fabric reaches the ideal quality standards during the heat setting process.

[0055] In one embodiment, step S120 described above may include:

[0056] The humidity range is calculated using simulation technology based on the humidity of the oven, and the humidity of the oven is controlled by adjusting the air volume of the exhaust fan.

[0057] Specifically, a high-temperature humidity sensor is installed in the middle of the setting machine to monitor the humidity level inside the oven in real time. Through simulation calculations of the impact of oven humidity on energy consumption, it was found that when the oven humidity is increased to 20%, the relative energy consumption can be significantly reduced by about 80%. Based on this finding, the system sets the control range of oven humidity between 20% and 30%.

[0058] To achieve this humidity control range, the following measures are adopted:

[0059] A high-temperature humidity sensor is installed in the middle of the setting machine to detect and record the humidity data inside the oven in real time.

[0060] Based on simulation calculations, the target humidity threshold for the drying oven is set between 20% and 30%. This humidity range is considered to effectively reduce energy consumption while maintaining the fabric's setting quality.

[0061] To maintain the oven humidity within a set range, the system controls the humidity level by adjusting the airflow of the exhaust fan. Specific operations include:

[0062] Increase exhaust fan airflow: If the humidity exceeds the set upper limit, the system will increase the exhaust fan airflow to promote the removal of moisture and thus reduce humidity.

[0063] Reduce exhaust fan airflow: If the humidity is below the set lower limit, the system will reduce the exhaust fan airflow to reduce the amount of moisture discharged and maintain an appropriate humidity level.

[0064] In this way, the system can dynamically adjust the humidity of the oven to ensure that it is always within the optimal control range, thereby achieving a significant improvement in energy efficiency and optimizing the fabric setting process.

[0065] In one embodiment, step S120 described above may include:

[0066] A moisture content sensor is used to monitor the moisture content and distribution of the fabric, and the feeding device is adjusted according to the set value to control the overall moisture content and auxiliary agent content of the fabric.

[0067] Specifically, moisture content sensors are installed between the rear end of the feeding device (such as a water tank or spray equipment) and the fabric inlet of the setting machine. These sensors are responsible for monitoring the moisture content and its distribution of the fabric across its entire width in real time. Based on the moisture content data acquired by the sensors and the set target values, the overall moisture content of the fabric and the concentration of auxiliaries are controlled by adjusting the operation of the feeding device.

[0068] The specific operations include:

[0069] A moisture content sensor is installed at an appropriate position between the rear end of the feeding device and the fabric inlet of the setting machine to ensure accurate monitoring and recording of the fabric's moisture content throughout its width.

[0070] The sensor provides real-time feedback on the fabric's moisture content and compares this data with a preset target value. The target value is set based on the fabric type and production requirements.

[0071] Based on the monitored moisture content data and set values, the overall moisture content of the fabric is controlled by adjusting the feeding device. This includes:

[0072] The solution used in the feeding device is a mixture of auxiliaries and water. The ratio of auxiliaries to water is adjusted according to the required moisture content to achieve the desired fabric moisture content and auxiliary content. The feeding rate and method of the feeding device are varied to ensure the fabric absorbs the appropriate amount of auxiliaries and water evenly, thereby controlling the overall moisture content.

[0073] In this way, the system can adjust and optimize the moisture content and auxiliary agent content of the fabric in real time to ensure consistency and quality during the fabric processing.

[0074] In one embodiment, step S120 described above may include:

[0075] The fabric weight data is monitored in real time by a weight sensor, and the fabric weight is controlled by adjusting the overfeed and stretching.

[0076] In this embodiment, a weight sensor is installed at the exit position of the setting machine to monitor the weight data of the fabric after setting in real time. Weight is one of the key indicators for evaluating fabric quality. The weight of the fabric is controlled by adjusting the overfeed and stretching of the setting machine.

[0077] The specific steps are as follows:

[0078] A weight sensor is installed at the exit of the setting machine to accurately measure the actual weight of the fabric after setting. The sensor provides real-time data, enabling timely monitoring of the fabric's quality during production.

[0079] The real-time monitored weight data is compared with the target value. The target value is set according to the fabric specifications and quality requirements.

[0080] Overfeed refers to the amount of fabric fed into the setting machine. When the overfeed of the setting machine increases, the amount of fabric entering the machine increases, which usually leads to an increase in fabric weight because the fabric is compressed more tightly during the setting process.

[0081] Conversely, when the overfeed is reduced, the amount of fabric input decreases, and the weight per square meter also decreases.

[0082] Tensioning refers to the degree to which a fabric is stretched in a setting machine. As the tensioning of the setting machine increases, the fabric becomes thinner during the stretching process, and its weight decreases.

[0083] Conversely, when the stretch is reduced, the fabric is less stretched and the weight per square meter increases.

[0084] Based on real-time weight data, adjust the overfeed and stretching to achieve the desired weight value. This can be achieved by adjusting the operating settings of the stenter.

[0085] In this way, the setting machine can automatically or manually adjust its operating parameters based on real-time weight data, thereby ensuring that the fabric weight meets the expected standard. This adjustment helps maintain fabric consistency and quality, meeting production requirements.

[0086] In one embodiment, step S120 described above may include:

[0087] Fabric thickness data is monitored in real time using a thickness sensor, and the fabric thickness is controlled by adjusting overfeed and stretching.

[0088] In this embodiment, a thickness sensor is installed at the exit position of the setting machine to monitor the thickness data of the fabric after setting in real time; thickness is one of the key indicators for evaluating fabric quality. The fabric thickness is controlled by adjusting the overfeed and stretching of the setting machine.

[0089] The specific steps are as follows:

[0090] A thickness sensor is installed at the exit of the setting machine to measure the fabric thickness in real time. The data provided by the sensor is used to ensure that the fabric thickness meets production standards.

[0091] The thickness data monitored in real time is compared with the target value, and adjustments are made as needed.

[0092] Overfeed refers to the amount of fabric fed into the setting machine. Increasing the overfeed means more fabric is fed into the setting machine, which usually results in an increase in fabric thickness. This is because the fabric is compressed more during the setting process.

[0093] Conversely, reducing the overfeed decreases the amount of fabric entering the fabric and reduces its thickness.

[0094] Tensioning refers to the degree to which a fabric is stretched in a setting machine. As the tensioning of the setting machine increases, the fabric becomes thinner as it is stretched, thus reducing its thickness.

[0095] Conversely, reducing the stretching decreases the fabric's stretch and increases its thickness.

[0096] Based on real-time thickness data, adjust the overfeed and stretching to achieve the desired fabric thickness. These adjustments are made by operating the settings of the setting machine to ensure that the fabric thickness meets the expected standards.

[0097] This monitoring and adjustment method helps ensure the consistency of fabric thickness and quality, meeting production requirements.

[0098] In one embodiment, step S120 described above may include:

[0099] Set a wind pressure threshold and adjust the exhaust fan to keep the data collected by the wind pressure sensor below the wind pressure threshold in order to maintain the negative pressure state of the oven.

[0100] In this embodiment, wind pressure sensors are installed in the first and last sections of the oven to monitor and control the wind pressure inside the oven. A wind pressure threshold is set, and the exhaust fan is adjusted to ensure that the wind pressure value measured by the wind pressure sensor is always below this threshold, thereby maintaining the setting machine in a negative pressure state.

[0101] The specific steps are as follows:

[0102] Wind pressure sensors are installed inside the first and last sections of the oven. These sensors are responsible for measuring the wind pressure level in these areas in real time.

[0103] Based on production requirements and equipment specifications, set an appropriate air pressure threshold. This threshold represents the maximum permissible air pressure value, ensuring a negative pressure environment inside the oven.

[0104] The wind pressure sensor measures the wind pressure inside the oven in real time and feeds the data back to the control system.

[0105] When the measured value approaches or exceeds the set wind pressure threshold, the control system will automatically adjust the operating status of the exhaust fan.

[0106] Increase exhaust volume: If the sensor detects that the air pressure value is close to or exceeds the threshold, the system will increase the exhaust volume of the exhaust fan to reduce the air pressure inside the oven and make it lower than the set threshold.

[0107] Reduce exhaust volume: If the air pressure value is lower than the threshold, the system will reduce the exhaust volume of the exhaust fan to keep the air pressure within an appropriate range.

[0108] By continuously adjusting the operating status of the exhaust fan, the air pressure inside the oven is kept at a negative pressure level, i.e., below the set air pressure threshold. This helps ensure the normal operation of the setting machine and avoids problems caused by excessively high air pressure.

[0109] This method ensures that the oven maintains the required negative pressure, thereby stabilizing the quality and efficiency of the setting process.

[0110] In one embodiment, step S120 described above may include:

[0111] Set a particulate matter concentration threshold and adjust the exhaust fan to keep the data collected by the smoke sensor below the particulate matter concentration threshold.

[0112] In this embodiment, smoke sensors are installed at the inlet and outlet of the first and last sections of the oven to monitor the concentration of smoke particles. A threshold for the concentration of smoke particles is set, and the exhaust fan is adjusted to ensure that the concentration value measured by the smoke sensors is below this threshold, thereby ensuring that the smoke inside the setting machine can be effectively removed.

[0113] The specific steps are as follows:

[0114] Smoke sensors are installed at the inlet and outlet of the oven to monitor the concentration of smoke particles in real time.

[0115] Based on operational requirements and equipment standards, set an appropriate smoke particulate matter concentration threshold. This threshold represents the maximum permissible smoke concentration, ensuring that the smoke inside the oven does not exceed this level.

[0116] The smoke sensor continuously monitors the concentration of smoke particles at the inlet and outlet and transmits the data to the control system.

[0117] Increase ventilation: When the sensor detects that the smoke concentration is close to or exceeds the set threshold, the control system will instruct the exhaust fan to increase the ventilation to accelerate the removal of smoke and reduce the concentration.

[0118] Reduce exhaust volume: If the smoke concentration is below the threshold, the system will appropriately reduce the exhaust volume to maintain stable system operation and prevent excessive exhaust.

[0119] By adjusting the operation of the exhaust fan, the concentration measured by the smoke sensor is ensured to remain below the set threshold. This effectively removes smoke from inside the setting machine, maintaining clean air and ensuring normal equipment operation.

[0120] This control method ensures that the smoke concentration inside the oven is kept at a safe level, avoiding the impact of smoke on the equipment and production process.

[0121] In one embodiment, step S120 described above may include:

[0122] The intensity of transmitted light through the filter is monitored by a transmittance sensor. When the light intensity is lower than a set threshold, the filter is cleaned and replaced.

[0123] In this embodiment, a transmittance sensor is installed on the filter screen of each oven section to detect the intensity of transmitted light. A threshold is set based on the light intensity; when the light intensity falls below this threshold, the system will prompt that the filter screen needs to be cleaned or replaced.

[0124] The specific operating steps are as follows:

[0125] A transmittance sensor is installed at the filter location in each section of the oven. The transmittance sensor is used to measure the light intensity passing through the filter to evaluate the filter's light transmission performance.

[0126] Based on the filter's design and operating standards, a light intensity threshold is set. This threshold represents the light intensity level the filter should have when it is clean.

[0127] The transmittance sensor will continuously monitor the light intensity transmitted through the filter and transmit the data in real time to the control system.

[0128] The control system compares the real-time light intensity with a set light intensity threshold. When the detected light intensity is lower than the threshold, it indicates that the filter may have accumulated a lot of dirt, resulting in reduced light transmittance.

[0129] When the light intensity is lower than the set threshold, the system will issue an alarm or prompt, informing the operator that the filter needs to be cleaned or replaced.

[0130] As instructed, operators should clean the filter screen promptly to remove accumulated dirt, or replace the filter screen when necessary to maintain its effective filtration performance.

[0131] This method ensures that the filter is always in optimal working condition, avoiding impact on the oven's performance and efficiency due to filter clogging.

[0132] In one embodiment, step S120 described above may include:

[0133] The defect detection device uses image recognition technology to detect defects on the fabric based on the data collected, and evaluates whether the fabric's production quality is up to standard based on the set defect rate, defect size, and shape.

[0134] In this embodiment, a defect detection device is installed at the exit end of the setting machine to inspect for defects on the fabric using image recognition technology. Users can evaluate the production quality of the fabric based on set criteria, such as defect rate, defect size, and shape.

[0135] The specific operating steps are as follows:

[0136] An image recognition device is installed at the exit end of the stenter. This typically includes a high-resolution camera and an associated computer vision system to capture and analyze images of the fabric.

[0137] Users set defect detection standards according to production requirements, including the allowable defect rate (the proportion of defective areas to the total area), the size of defects, and the shape of defects.

[0138] The inspection equipment continuously monitors the fabric exiting the setting machine, capturing images of the fabric using a camera. The frequency and resolution of image capture should be high enough to ensure that even minute defects can be clearly identified.

[0139] The device uses image recognition algorithms to analyze fabric images and identify potential defects. The system then compares the detected defects with user-defined standards.

[0140] Based on the number, size, and shape of the detected defects, the system assesses whether the fabric meets the set quality standards. If the defect rate, size, or shape exceeds the allowable range, the system will issue an alarm or generate a report indicating that further processing is required.

[0141] Based on the evaluation results, users decide whether to treat the fabric, such as adjusting the production process, modifying equipment settings, or reproducing it, to ensure that the quality of the final product meets the requirements.

[0142] This method uses precise image recognition technology to help ensure the quality of fabrics and prevent defects in the production process from affecting the final product.

[0143] In this embodiment, after the system and sensors are fully installed, all sensors will operate synchronously during normal operation. The control system will collect data from these sensors in real time and perform calculations and analyses to derive corresponding feedback parameters. If these feedback parameters have not yet reached a preset threshold, the system will issue adjustment commands to the setting machine to adjust the relevant parameters to ensure that the setting machine's operating status remains within the set threshold range. This allows for real-time adjustment of the setting machine's operation to maintain stable product quality.

[0144] In this embodiment, data is collected at designated locations on the setting machine using sensors, including a high-temperature humidity sensor to measure the humidity of the oven, a smoke sensor to measure the particle size of smoke around the oven, a wind pressure sensor to measure the wind pressure inside the oven, a weight sensor to measure the weight of the fabric, a moisture content sensor to measure the moisture content of the fabric, a thickness sensor to measure the thickness of the fabric, a width sensor to measure the width of the fabric, a fabric surface temperature sensor to measure the surface temperature of the fabric inside the oven, a tension sensor to measure the tension of the fabric, a transmittance sensor to measure the pore blockage of the filter screen inside the oven, and a defect sensor to measure defects on the surface of the fabric.

[0145] Specifically, by installing various sensors at designated locations on the setting machine to collect critical data, efficiency and quality control in the fabric production process are ensured. The following is a detailed explanation of the function of each sensor and its data processing:

[0146] High-temperature humidity sensor: This sensor monitors the humidity inside the oven in real time and automatically adjusts the speed of the exhaust fan based on the measured data to ensure that the oven maintains the optimal humidity level. This process not only helps reduce excessive heat loss but also prevents positive pressure caused by the deceleration of the exhaust fan, thus avoiding the overflow of oil fumes from the oven inlet and outlet, which could cause environmental pollution. Through intelligent analysis of multiple sets of data, the system can flexibly adjust the dehumidification settings while meeting emission standards, achieving automatic energy saving.

[0147] Weight, moisture content, thickness, and width sensors: These sensors work together to inspect the quality of the fabric. They measure key parameters such as weight, moisture content, thickness, and width, which directly affect the fabric's quality. After measurement, the system compares the results with user-defined thresholds. If the fabric is found to be substandard, the system automatically adjusts the oven speed, humidity, temperature, and exhaust fan speed to ensure the final product meets quality standards.

[0148] Fabric surface temperature sensor: This sensor monitors temperature changes on the fabric surface to determine the drying and setting status of the fabric at different locations in the drying oven. Based on the temperature data, the system can automatically adjust the oven temperature and speed to optimize the drying effect. This adjustment process is based on fabric quality indicators to ensure the accuracy and effectiveness of the operation.

[0149] Tension sensor: By monitoring the tension of the fabric, this sensor can determine the quality status of the fabric. When linked with a width sensor, the system reduces tension when the width is too large and increases tension when the width is too small. This dynamic adjustment helps maintain the stability of the fabric during processing, ensuring its quality.

[0150] Transmittance sensor: This sensor monitors the cleanliness of the oven's interior and determines the degree of filter clogging. Severe filter clogging affects airflow and fabric drying efficiency. Therefore, when the sensor detects filter clogging, the system promptly alerts the user to clean it to maintain a good working environment.

[0151] Defect Sensor: This sensor is used to identify flaws and defects on the fabric surface and is an important basis for assessing fabric quality. When too many defects are detected, the system will alert the user to stop production for inspection to prevent continued production from causing serious quality problems.

[0152] In summary, through the coordinated operation of the various sensors mentioned above, this invention can achieve precise monitoring and automatic adjustment of various parameters during the fabric production process, thereby improving production efficiency, ensuring product quality, and reducing resource waste.

[0153] The aforementioned intelligent monitoring and control method for the setting machine collects data at designated locations on the machine using sensors. This data includes fabric surface temperature, oven humidity, fabric moisture content, fabric weight, fabric thickness, oven air pressure, particulate matter concentration, filter transmittance, and fabric defects. The control system analyzes this data and compares it to set standards. If the data does not meet the standards, the system automatically adjusts the setting machine's control parameters. This adjustment ensures the setting machine operates at its optimal state to maintain fabric quality. It quantifies various parameters of the production process, replaces manual judgment based on experience, improves the fabric quality pass rate, reduces energy consumption, and increases output.

[0154] Figure 3 This is a schematic block diagram of an intelligent monitoring and control system 200 for a stenter machine provided in an embodiment of the present invention. Figure 3 As shown, corresponding to the above-described intelligent monitoring and control method for stenter machines, the present invention also provides an intelligent monitoring and control system 200 for stenter machines. This intelligent monitoring and control system 200 includes a unit for executing the above-described intelligent monitoring and control method for stenter machines. Specifically, please refer to... Figure 4The intelligent monitoring and control system 200 for the stenter includes a control unit 201 and a sensor 202.

[0155] The control unit 201 is used to acquire corresponding data collected by the sensor 202 set at a designated position on the setting machine. The data includes at least one of the following: fabric surface temperature, humidity in the oven, fabric moisture content, fabric weight, fabric thickness, fabric width, fabric tension, oven air pressure, oven particulate matter concentration, filter contamination level, and fabric defects. The control unit 201 adjusts the corresponding control parameters of the setting machine according to the data.

[0156] like Figure 4 As shown, the sensor 202 includes a fabric surface temperature sensor 202 installed in the setting machine oven, a high temperature and humidity sensor 202 installed inside the setting machine oven, a moisture content sensor 202 and a moisture content consistency sensor installed between the feeding device and the fabric inlet of the setting machine, a weight sensor 202 and a thickness sensor 202 installed at the outlet of the setting machine, a wind pressure sensor 202 installed on the oven, a smoke sensor 202 installed at the inlet and outlet of the setting machine oven, a transmittance sensor 202 installed on the filter screen of the setting machine oven, and a defect detection device installed at the outlet of the setting machine.

[0157] It should be noted that those skilled in the art can clearly understand that the specific implementation process of the above-mentioned intelligent monitoring and control system 200 for the stenter and each unit can be referred to the corresponding description in the foregoing method embodiments. For the sake of convenience and brevity, it will not be repeated here.

[0158] In the embodiments provided by this invention, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the system embodiments described above are merely illustrative. For example, the division of each unit is only a logical functional division, and there may be other division methods in actual implementation. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed.

[0159] The steps in the method of this invention can be adjusted, merged, or reduced in order according to actual needs. The units in the system of this invention can be merged, divided, or reduced according to actual needs. Furthermore, the functional units in the various embodiments of this invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0160] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, a terminal, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention.

[0161] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in the present invention, and these modifications or substitutions should all be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for intelligent monitoring and control of a setting machine, characterized in that, include: The sensor located at a specified position on the setting machine collects corresponding data, including at least one of the following: fabric surface temperature, humidity in the oven, fabric moisture content, fabric weight, fabric thickness, fabric width, fabric tension, oven air pressure, oven particulate matter concentration, filter contamination level, and fabric defects. Adjust the control parameters of the setting machine according to the data.

2. The setting machine intelligent monitoring and regulating method according to claim 1, characterized in that, The sensors include at least one of the following: a fabric surface temperature sensor installed in the setting machine oven; a high temperature and humidity sensor installed inside the setting machine oven; a moisture content sensor and a moisture content consistency sensor installed between the feeding device and the fabric inlet of the setting machine; a weight sensor and a thickness sensor installed at the outlet of the setting machine; an air pressure sensor installed on the oven; a smoke sensor installed at the inlet and outlet of the setting machine oven; a transmittance sensor installed on the filter screen of the setting machine oven; a defect detection device installed at the outlet of the setting machine; a tension sensor installed at the inlet of the setting machine; and a width sensor installed at the outlet of the setting machine.

3. The intelligent monitoring and control method for a stenter according to claim 2, characterized in that, The step of adjusting the control parameters corresponding to the setting machine based on the data includes: The machine speed, setting temperature and setting time are calculated based on the curve corresponding to the fabric temperature, fabric humidity and oven temperature and humidity and oven length. The fabric temperature is compared with the setting temperature and the setting time is compared with the set time conditions to obtain the first comparison result. If the first comparison result is that the fabric temperature has not reached the setting temperature, then the oven temperature is adjusted; if the setting time does not meet the set time condition, then the machine speed is adjusted.

4. The intelligent monitoring and control method for a stenter according to claim 2, characterized in that, The step of adjusting the control parameters corresponding to the setting machine based on the data includes: The humidity range is calculated using simulation technology based on the humidity of the oven, and the humidity of the oven is controlled by adjusting the air volume of the exhaust fan.

5. The intelligent monitoring and control method for a stenter according to claim 2, characterized in that, The step of adjusting the control parameters corresponding to the setting machine based on the data includes: A moisture content sensor is used to monitor the moisture content and distribution of the fabric, and the feeding device is adjusted according to the set value to control the overall moisture content and auxiliary agent content of the fabric.

6. The intelligent monitoring and control method for a stenter according to claim 2, characterized in that, The step of adjusting the control parameters corresponding to the setting machine based on the data includes: The fabric weight data is monitored in real time by a weight sensor, and the fabric weight is controlled by adjusting the overfeed and stretching.

7. The intelligent monitoring and control method for a stenter according to claim 2, characterized in that, The step of adjusting the control parameters corresponding to the setting machine based on the data includes: Fabric thickness data is monitored in real time using a thickness sensor, and the fabric thickness is controlled by adjusting overfeed and stretching.

8. The intelligent monitoring and control method for a stenter according to claim 2, characterized in that, The step of adjusting the control parameters corresponding to the setting machine based on the data includes: Set a wind pressure threshold and adjust the exhaust fan to keep the data collected by the wind pressure sensor below the wind pressure threshold in order to maintain the negative pressure state of the oven.

9. The intelligent monitoring and control method for a stenter according to claim 2, characterized in that, The step of adjusting the control parameters corresponding to the setting machine based on the data includes: Set a particulate matter concentration threshold and adjust the exhaust fan to keep the data collected by the smoke sensor below the particulate matter concentration threshold; The step of adjusting the control parameters corresponding to the setting machine based on the data further includes: The intensity of transmitted light through the filter is monitored by a transmittance sensor. When the light intensity is lower than a set threshold, the filter is cleaned and replaced. The step of adjusting the control parameters corresponding to the setting machine based on the data further includes: The defect detection device uses image recognition technology to detect defects on the fabric based on the data collected, and evaluates whether the fabric's production quality is up to standard based on the set defect rate, defect size, and shape.

10. A system applied to the intelligent monitoring and control method for a stenter as described in any one of claims 1 to 9, characterized in that, The system includes a control unit and sensors. The control unit is used to acquire data collected by sensors located at designated positions on the setting machine. The data includes at least one of the following: fabric surface temperature, humidity inside the oven, fabric moisture content, fabric weight, fabric thickness, fabric width, fabric tension, oven air pressure, oven particulate matter concentration, filter contamination level, and fabric defects. The control unit adjusts the corresponding control parameters of the setting machine based on the data. The sensors include at least one of the following: fabric surface temperature sensor located in the setting machine oven; high temperature and humidity sensor located inside the setting machine oven; moisture content sensor and moisture content consistency sensor located between the feeding device and the fabric inlet of the setting machine; weight sensor and thickness sensor located at the outlet of the setting machine; air pressure sensor located on the oven; smoke sensor located at the inlet and outlet of the setting machine oven; transmittance sensor located on the filter screen of the setting machine oven; defect detection device located at the outlet of the setting machine; tension sensor located at the inlet of the setting machine; and width sensor located at the outlet of the setting machine.

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