Tarpaulin preparation system based on multiple intelligent sensors

Abstract

The invention relates to the field of tarpaulin preparation, in particular to a tarpaulin preparation system based on multiple intelligent sensors. The data acquisition module is used for acquiring base cloth state parameters and motor state parameters for tarpaulin preparation; a data analysis module is used for analyzing a base cloth control characterization value according to the base cloth state parameters and the motor state parameters; whether the tarpaulin preparation system meets the standard or not is evaluated through a standard evaluation module on the basis of the base cloth control characterization value; the compensation control module is used for determining the reason that the tarpaulin preparation system does not meet the standard; and adjusting production line acceleration or starting current loop compensation. According to the invention, through the deployed multiple intelligent sensors, relevant parameters for showing the states of the base cloth and the motor are respectively collected, accurate data analysis is carried out, whether the tarpaulin preparation system meets the standard is evaluated, and targeted adjustment is carried out according to the reason that the tarpaulin preparation system does not meet the standard, so that the accuracy of the tarpaulin preparation system in the coating link is remarkably improved.

Description

Technical Field

[0001] This invention relates to the field of tarpaulin manufacturing, and more particularly to a tarpaulin manufacturing system based on multiple intelligent sensors. Background Technology

[0002] With the continuous improvement of industrial automation, the tarpaulin industry has increasingly higher requirements for the intelligence and precision of its manufacturing systems. Existing tarpaulin manufacturing systems mostly rely on fixed control strategies for production adjustments. However, because the production process often involves complex state information, fixed control strategies are insufficient to cope with dynamic changes during production, affecting the quality and efficiency of tarpaulin manufacturing. Therefore, there is an urgent need to develop a tarpaulin manufacturing system that can integrate multi-source data and achieve precise analysis and effective compensation control.

[0003] Patent application publication number CN113914108B discloses a tarpaulin and its preparation method. This invention discloses a tarpaulin comprising a base fabric and a coating, with the base fabric and coating material integrally arranged on the upper and lower sides. The preparation method of the coating material is as follows: S1: Preparation of the base material; S2: Base fabric contact agent; S3: Adding the base fabric contact agent to the base material at a weight ratio of 1:5, then adding 20-30% bentonite agent and 10-20% hydrophobic microparticles (total weight of the base material), stirring at 100-500 r / min for 20-30 min, and obtaining the coating material after stirring. The coating material of this invention is prepared by combining the base material with the base fabric contact agent, bentonite agent, and hydrophobic microparticles. Combined with the operation of the coating material in vertical coating and high-temperature curing slurry, the adhesion strength of the coating is improved. Simultaneously, naphthenate has excellent hydrophobic properties, and its ratio with the raw materials enhances the hydrophobic properties of the product.

[0004] Therefore, the invention has the following problems: This invention does not take into account the inertia fluctuations caused by the dynamic changes in the unwinding roll diameter in the tarpaulin preparation system, or the low precision of the system in the coating process caused by the uneven tension of the base fabric due to the speed feedback delay of the tarpaulin preparation motor. Summary of the Invention

[0005] To address this, the present invention provides a tarpaulin preparation system based on multiple intelligent sensors, which overcomes the problems in the prior art where dynamic changes in the unwinding roll diameter cause inertia fluctuations and uneven base fabric tension due to motor speed feedback delays in tarpaulin preparation systems, resulting in low accuracy in the coating process.

[0006] To achieve the above objectives, the present invention provides a tarpaulin manufacturing system based on multiple intelligent sensors, comprising: The data acquisition module is used to collect the status parameters of the base fabric used for tarpaulin preparation during the historical period, as well as the status parameters of the motor used for tarpaulin preparation during the historical period. A data analysis module, which is connected to the data acquisition module, is used to analyze the control characterization values ​​of the base fabric used for tarpaulin preparation based on the base fabric state parameters and motor state parameters. A standard evaluation module, connected to the data analysis module, is used to obtain the base fabric control characterization value analyzed by the data analysis module, and to evaluate whether the tarpaulin preparation system meets the standard based on the difference between the base fabric control characterization value and a predetermined base fabric control characterization value threshold. The compensation control module is connected to the data acquisition module, the data analysis module, and the standard evaluation module, respectively. It is used to determine the reason why the tarpaulin preparation system does not meet the standard when the tarpaulin preparation system does not meet the standard, based on the roll diameter of the base fabric state parameter or the motor current of the motor state parameter; and to determine the adjustment of the production line acceleration or the initiation of current loop compensation based on the reason for the non-compliance. The base fabric state parameters include roll diameter and base fabric tension, and the motor state parameters include motor current and motor angular velocity.

[0007] Furthermore, the data analysis module is used to determine the base fabric control characterization value based on the first base fabric control factor and the second base fabric control factor, wherein the first base fabric control factor and the second base fabric control factor are calculated by the base fabric state characterization value and the motor state characterization value, respectively. The base fabric state characterization value is calculated by the roll diameter and the base fabric tension, and the motor state characterization value is calculated by the motor current and the motor angular velocity.

[0008] Furthermore, the standard evaluation module evaluates whether the tarpaulin preparation system meets the standard based on the difference between the base fabric control characterization value and a predetermined difference threshold, wherein the difference between the base fabric control characterization value and the predetermined base fabric control characterization value threshold are calculated.

[0009] Furthermore, the compensation control module determines that the reason why the tarpaulin preparation system does not meet the standard is due to abnormal roll diameter change, based on the rate of change of the roll diameter.

[0010] Furthermore, the compensation control module determines that the reason why the tarpaulin preparation system does not meet the standard is that the drive control motor does not respond in a timely manner, based on the variance of the motor current.

[0011] Furthermore, the compensation control module determines the proportion of adjusting the production line acceleration based on the rate of change of the roll diameter and the rate of change threshold.

[0012] Furthermore, the compensation control module determines the current loop compensation based on the inertia compensation torque, wherein the inertia compensation torque is calculated by the motor angular velocity and the roll diameter.

[0013] Furthermore, the compensation control module is used to trigger the data acquisition module to update the base fabric state parameters and motor state parameters after adjusting the production line acceleration or after completing current loop compensation.

[0014] Furthermore, the data analysis module is used to respond to the updated base fabric control characterization value, and the standard evaluation module re-evaluates whether the tarpaulin preparation system meets the standard based on the updated base fabric control characterization value.

[0015] Furthermore, the compensation control module is used to initiate mechanical calibration if the tarpaulin preparation system fails to meet the standards during the secondary evaluation.

[0016] Compared with existing technologies, the beneficial effects of this invention are that it provides a tarpaulin manufacturing system based on multiple intelligent sensors. A data acquisition module collects base fabric state parameters, including roll diameter and base fabric tension, over a historical period using multiple intelligent sensors; and collects motor state parameters, including motor current and motor angular velocity, over a historical period. A data analysis module, connected to the data acquisition module, analyzes the acquired roll diameter and base fabric tension to derive base fabric state characterization values, and then analyzes these values ​​to derive a first base fabric control factor; it also analyzes the acquired motor current and motor angular velocity to derive a motor state characterization value, and then analyzes these values ​​to derive a second base fabric control factor; finally, it analyzes the first and second base fabric control factors to obtain a base fabric control characterization value. A standard evaluation module, connected to the data analysis module, acquires the base fabric control characterization value analyzed by the data analysis module, and evaluates whether the tarpaulin manufacturing system meets the standard based on the difference between the base fabric control characterization value and a predetermined base fabric control characterization value threshold. The compensation control module, connected to the data acquisition module, data analysis module, and standard evaluation module, analyzes the roll diameter and motor current when the tarpaulin preparation system fails to meet standards. This analysis determines whether the non-compliance is due to abnormal roll diameter changes or untimely motor response. Based on the cause of the non-compliance, adjustments are made to the production line acceleration or current loop compensation is activated. This invention utilizes multiple intelligent sensors to collect and display relevant parameters of the base fabric and motor status. Through multi-module collaborative operation, precise data analysis is performed to assess whether the tarpaulin preparation system meets standards. The reasons for non-compliance are then analyzed, and adjustments are made to the production line acceleration or current loop compensation is activated, significantly improving the accuracy of the tarpaulin preparation system in the coating process.

[0017] In particular, the data acquisition module deploys multiple intelligent sensors to collect data on the roll diameter and base fabric tension, as well as the motor current and angular velocity over historical periods. This constructs a database covering historical periods, enabling the identification of trends in the collected data and providing predictive data for subsequent compensation, thus offering a comprehensive dynamic profile of the system's operating conditions. The data analysis module analyzes the collected data to obtain base fabric control characterization values, providing fused characterization data for subsequent analysis. This overcomes the limitations of traditional single-parameter thresholds and improves the sensitivity of detecting abnormal system states.

[0018] In particular, through the standard evaluation module, based on the comparison between the base fabric control characterization value and the base fabric control characterization value threshold, the system accurately evaluates whether the current tarpaulin preparation system meets the standard, realizing intelligent diagnosis of the status of the tarpaulin preparation system, thereby enabling real-time monitoring and evaluation of the system's accuracy.

[0019] In particular, when the tarpaulin preparation system fails to meet standards, the compensation control module analyzes the roll diameter and motor current to determine if the non-compliance is due to abnormal roll diameter changes or untimely response of the drive control motor. Based on the cause of the non-compliance, it determines whether to adjust the production line acceleration or activate current loop compensation. The cause of the non-compliance is determined by the roll diameter change rate, or by the variance of the motor current. When the non-compliance is due to abnormal roll diameter changes, the adjustment ratio of the production line acceleration is determined by the roll diameter change rate and its threshold. When the non-compliance is due to untimely response of the drive control motor, the inertia compensation torque is calculated using the motor angular velocity and roll diameter, and current loop compensation is determined based on the inertia compensation torque. After adjusting the production line acceleration or completing current compensation, the data acquisition module updates the base fabric state parameters and motor state parameters. The data analysis module updates the base fabric control characterization value, and the standard evaluation module re-evaluates whether the tarpaulin preparation system meets the standards based on the updated base fabric control characterization value. If the secondary evaluation of the tarpaulin fabrication system fails to meet the standards, mechanical calibration is initiated. In cases where the tarpaulin fabrication system does not meet the standards, intelligent attribution and targeted compensation can precisely address the influencing sources, significantly improving the accuracy of the multi-intelligent sensor-based tarpaulin fabrication system. Attached Figure Description

[0020] Figure 1 This is a structural block diagram of the tarpaulin manufacturing system based on multiple intelligent sensors according to an embodiment of the present invention; Figure 2 This invention provides a logic diagram for evaluating whether a tarpaulin preparation system conforms to standards. Figure 3A logic diagram for determining the reasons for non-compliance with standards in an embodiment of the present invention; Figure 4 The embodiments of the present invention determine the logic diagram for adjusting the production line acceleration or enabling current loop compensation based on the reasons for non-compliance with standards. Detailed Implementation

[0021] In order to make the objects and advantages of the present invention more clearly understood, the present invention is further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0022] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0023] Please see Figure 1 , Figure 2 , Figure 3 as well as Figure 4 The diagram shown is a structural block diagram of a tarpaulin preparation system based on multiple intelligent sensors according to an embodiment of the present invention; a logic decision diagram for evaluating whether the tarpaulin preparation system conforms to standards according to an embodiment of the present invention; a logic decision diagram for determining the reasons for non-compliance with standards according to an embodiment of the present invention; and a logic decision diagram for determining whether to adjust the production line acceleration or enable current loop compensation based on the reasons for non-compliance with standards according to an embodiment of the present invention.

[0024] This invention provides a tarpaulin manufacturing system based on multiple intelligent sensors, comprising: The data acquisition module is used to collect the status parameters of the base fabric used for tarpaulin preparation during the historical period, as well as the status parameters of the motor used for tarpaulin preparation during the historical period. A data analysis module, which is connected to the data acquisition module, is used to analyze the control characterization values ​​of the base fabric used for tarpaulin preparation based on the base fabric state parameters and motor state parameters. A standard evaluation module, connected to the data analysis module, is used to obtain the base fabric control characterization value analyzed by the data analysis module, and to evaluate whether the tarpaulin preparation system meets the standard based on the difference between the base fabric control characterization value and a predetermined base fabric control characterization value threshold. The compensation control module is connected to the data acquisition module, the data analysis module, and the standard evaluation module, respectively. It is used to determine the reason why the tarpaulin preparation system does not meet the standard when the tarpaulin preparation system does not meet the standard, based on the roll diameter of the base fabric state parameter or the motor current of the motor state parameter; and to determine the adjustment of the production line acceleration or the start-up current loop compensation based on the reason for the non-compliance. The base fabric state parameters include roll diameter and base fabric tension, and the motor state parameters include motor current and motor angular velocity.

[0025] In this embodiment, a data acquisition module collects base fabric state parameters, including roll diameter and base fabric tension, over a historical period using multiple intelligent sensors; and collects motor state parameters, including motor current and motor angular velocity, over a historical period. A data analysis module, connected to the data acquisition module, analyzes the acquired roll diameter and base fabric tension to derive base fabric state characterization values, and then analyzes these values ​​to derive a first base fabric control factor. Similarly, it analyzes the acquired motor current and motor angular velocity to derive a motor state characterization value, and then analyzes these values ​​to derive a second base fabric control factor. Finally, it analyzes the first and second base fabric control factors to obtain a base fabric control characterization value. A standard evaluation module, connected to the data analysis module, acquires the base fabric control characterization value analyzed by the data analysis module. Based on the difference between the base fabric control characterization value and a predetermined base fabric control characterization value threshold, it evaluates whether the tarpaulin fabric manufacturing system meets the standard. The compensation control module, connected to the data acquisition module, data analysis module, and standard evaluation module, analyzes the roll diameter and motor current when the tarpaulin preparation system fails to meet standards. This analysis determines whether the non-compliance is due to abnormal roll diameter changes or untimely motor response. Based on the cause of the non-compliance, adjustments are made to the production line acceleration or current loop compensation is activated. This invention utilizes multiple intelligent sensors to collect and display relevant parameters of the base fabric and motor status. Through multi-module collaborative operation, precise data analysis is performed to assess whether the tarpaulin preparation system meets standards. The reasons for non-compliance are then analyzed, and adjustments are made to the production line acceleration or current loop compensation is activated, significantly improving the accuracy of the tarpaulin preparation system in the coating process.

[0026] In this embodiment, the roll diameter data is obtained by a laser rangefinder; the base fabric tension data is obtained by an S-type tension sensor; the motor current data is obtained by a closed-loop Hall current sensor; and the motor angular velocity data is obtained by a 23-bit absolute encoder.

[0027] Specifically, the data analysis module is used to determine the base fabric control characterization value based on the first base fabric control factor and the second base fabric control factor. The first base fabric control factor and the second base fabric control factor are calculated by the base fabric state characterization value and the motor state characterization value, respectively. The base fabric state characterization value is calculated by the roll diameter and the base fabric tension, and the motor state characterization value is calculated by the motor current and the motor angular velocity.

[0028] In this embodiment, the process of analyzing the base fabric control characterization value based on the base fabric state parameters and motor state parameters includes: obtaining the roll diameter and base fabric tension within a historical period; calculating the base fabric state characterization value, which is obtained by summing the ratio of the roll diameter to a predetermined roll diameter threshold within a single period with the ratio of the base fabric tension to a predetermined base fabric tension threshold; obtaining the motor current and motor angular velocity within a historical period; calculating the motor state characterization value, which is obtained by summing the ratio of the motor current to a predetermined motor current threshold within a single period with the ratio of the motor angular velocity to a predetermined motor angular velocity threshold; determining the ratio of the base fabric state characterization value within a single period to a predetermined base fabric state characterization value threshold as a first base fabric control factor; determining the ratio of the motor state characterization value within a single period to a predetermined motor state characterization value threshold as a second base fabric control factor; and summing the first base fabric control factor and the second base fabric control factor to obtain the base fabric control characterization value. All of the above thresholds adopt a dynamic adaptive threshold generation mechanism and are the average values ​​of the corresponding data of the system being in a standard state for three consecutive months within the historical period.

[0029] Specifically, the standard evaluation module evaluates whether the tarpaulin preparation system meets the standard based on the difference between the base fabric control characterization value and a predetermined difference threshold. The difference between the base fabric control characterization value and the predetermined base fabric control characterization value threshold is calculated.

[0030] In this embodiment, the absolute value of the difference between the base fabric control characterization value and a predetermined base fabric control characterization value threshold is calculated. The absolute value of the difference is compared with the threshold. If the absolute value of the difference is greater than the threshold, the tarpaulin manufacturing system is assessed as non-compliant; if the absolute value of the difference is less than or equal to the threshold, the tarpaulin manufacturing system is assessed as compliant. The base fabric control characterization value threshold is generated using a dynamic adaptive threshold generation mechanism, which is the average base fabric control characterization value of the system in a compliant state over three consecutive months within a historical period. The difference threshold is pre-obtained and is 0.2 times the base fabric control characterization value threshold.

[0031] Specifically, the compensation control module determines that the reason why the tarpaulin preparation system does not meet the standard is due to abnormal changes in roll diameter, based on the rate of change of the roll diameter.

[0032] In this embodiment, the roll diameter change rate of a single cycle and the previous cycle is calculated and compared with a predetermined roll diameter change rate threshold. If the roll diameter change rate is greater than the roll diameter change rate threshold, the reason why the tarpaulin manufacturing system does not meet the standard is determined to be abnormal roll diameter change. The roll diameter change rate threshold adopts a dynamic adaptive threshold generation mechanism, which is the average roll diameter change rate of the system in a standard-compliant state over three consecutive months within a historical cycle.

[0033] Specifically, the compensation control module determines that the reason why the tarpaulin preparation system does not meet the standard is that the drive control motor does not respond in a timely manner, based on the variance of the motor current.

[0034] In this embodiment, the variance of the motor current within a single cycle is calculated and compared with a predetermined variance threshold for the motor current. If the variance is greater than the variance threshold, it is determined that the reason the tarpaulin manufacturing system does not meet the standard is due to untimely response of the drive control motor. The variance threshold is generated using a dynamic adaptive threshold generation mechanism, which is the average variance of the system's compliance with the standard over three consecutive months within a historical period.

[0035] Specifically, the compensation control module determines the proportion of adjusting the production line acceleration based on the rate of change of the roll diameter and the rate of change threshold.

[0036] In this embodiment, when it is determined that the reason why the tarpaulin preparation system does not meet the standard is due to abnormal roll diameter changes, the roll diameter change rate is obtained, the ratio of the roll diameter change rate to the change rate threshold is calculated, and the ratio is determined as the proportion for adjusting the production line acceleration.

[0037] Specifically, the compensation control module determines the current loop compensation based on the inertia compensation torque, wherein the inertia compensation torque is calculated by the motor angular velocity and the roll diameter.

[0038] In this embodiment, when it is determined that the reason the tarpaulin preparation system does not meet the standard is due to the untimely response of the drive control motor, the motor angular velocity within a single cycle is obtained, and the motor angular acceleration is calculated; the roll diameter within a single cycle is obtained, and the moment of inertia is calculated. Based on the product of the motor angular acceleration and the moment of inertia, the inertia compensation torque is calculated. The inertia compensation torque is divided by the torque constant to obtain the current loop compensation amount. The torque constant is obtained by consulting the corresponding motor's datasheet. It is understood that the formulas for calculating the motor angular velocity and the moment of inertia are existing technologies and will not be elaborated further.

[0039] Specifically, the compensation control module is used to trigger the data acquisition module to update the base fabric state parameters and motor state parameters after adjusting the production line acceleration or after completing current loop compensation.

[0040] Specifically, the data analysis module is used to respond to the updated base fabric control characterization value, and the standard evaluation module re-evaluates whether the tarpaulin preparation system meets the standard based on the updated base fabric control characterization value.

[0041] Specifically, the compensation control module is used to initiate mechanical calibration if the tarpaulin preparation system fails to meet the standards during the secondary evaluation.

[0042] In this embodiment, if the tarpaulin preparation system still does not meet the standard after a second evaluation, the guide roller tilt angle is measured using a laser interferometer and compared with a guide roller tilt angle threshold. If the tilt angle is greater than the threshold, the guide roller tilt angle is adjusted to the value corresponding to the threshold. The guide roller tilt angle threshold is pre-obtained and is the average of the guide roller tilt angles of the system when it was in a standard-compliant state over three consecutive months within a historical period.

[0043] Thus far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art may make equivalent changes or substitutions to the relevant technical features, and the technical solutions after such changes or substitutions will fall within the scope of protection of the present invention.

Claims

1. A tarpaulin manufacturing system based on multiple intelligent sensors, characterized in that, include: The data acquisition module is used to collect the status parameters of the base fabric used for tarpaulin preparation during the historical period, as well as the status parameters of the motor used for tarpaulin preparation during the historical period. A data analysis module, which is connected to the data acquisition module, is used to analyze the control characterization values ​​of the base fabric used for tarpaulin preparation based on the base fabric state parameters and motor state parameters. A standard evaluation module, connected to the data analysis module, is used to obtain the base fabric control characterization value analyzed by the data analysis module, and to evaluate whether the tarpaulin preparation system meets the standard based on the difference between the base fabric control characterization value and a predetermined base fabric control characterization value threshold. The compensation control module is connected to the data acquisition module, the data analysis module, and the standard evaluation module, respectively. It is used to determine the reason why the tarpaulin preparation system does not meet the standard when the tarpaulin preparation system does not meet the standard, based on the roll diameter of the base fabric state parameter or the motor current of the motor state parameter; and to determine the adjustment of the production line acceleration or the start-up current loop compensation based on the reason for the non-compliance. The base fabric state parameters include roll diameter and base fabric tension, and the motor state parameters include motor current and motor angular velocity.

2. The tarpaulin manufacturing system based on multiple intelligent sensors according to claim 1, characterized in that, The data analysis module is used to determine the base fabric control characterization value based on the first base fabric control factor and the second base fabric control factor. The first base fabric control factor and the second base fabric control factor are calculated by the base fabric state characterization value and the motor state characterization value, respectively. The base fabric state characterization value is calculated by the roll diameter and the base fabric tension, and the motor state characterization value is calculated by the motor current and the motor angular velocity.

3. The tarpaulin manufacturing system based on multiple intelligent sensors according to claim 1, characterized in that, The standard evaluation module evaluates whether the tarpaulin preparation system meets the standard based on the difference between the base fabric control characterization value and a predetermined difference threshold. The difference between the base fabric control characterization value and the predetermined base fabric control characterization value threshold are calculated.

4. The tarpaulin manufacturing system based on multiple intelligent sensors according to claim 3, characterized in that, The compensation control module determines that the reason the tarpaulin preparation system does not meet the standard is due to abnormal roll diameter changes, based on the rate of change in the roll diameter.

5. The tarpaulin manufacturing system based on multiple intelligent sensors according to claim 3, characterized in that, The compensation control module determines that the reason why the tarpaulin preparation system does not meet the standard is that the drive control motor does not respond in a timely manner, based on the variance of the motor current.

6. The tarpaulin manufacturing system based on multiple intelligent sensors according to claim 4, characterized in that, The compensation control module determines the proportion of the production line acceleration to be adjusted based on the rate of change of the roll diameter and the rate of change threshold.

7. The tarpaulin manufacturing system based on multiple intelligent sensors according to claim 5, characterized in that, The compensation control module determines the current loop compensation based on the inertia compensation torque, wherein the inertia compensation torque is calculated by the motor angular velocity and the roll diameter.

8. The tarpaulin manufacturing system based on multiple intelligent sensors according to claim 7, characterized in that, The compensation control module is used to trigger the data acquisition module to update the base fabric state parameters and motor state parameters after adjusting the production line acceleration or after completing current loop compensation.

9. The tarpaulin manufacturing system based on multiple intelligent sensors according to claim 8, characterized in that, The data analysis module is used to respond to the updated base fabric control characterization value, and the standard evaluation module re-evaluates whether the tarpaulin preparation system meets the standard based on the updated base fabric control characterization value.

10. The tarpaulin manufacturing system based on multiple intelligent sensors according to claim 9, characterized in that, The compensation control module is used to initiate mechanical calibration if the tarpaulin preparation system fails to meet the standards during the secondary evaluation.

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