Self-adaptive regulation and control method and system for processing parameters of sunshade net raw materials
By acquiring parameter response values during the processing of shading net raw materials, forming a response value sequence, determining whether preset fluctuation or risk conditions are met, and generating new parameter adjustment values, the problem of unsuitable parameter control in shading net production is solved, and high precision and stable production of shading net raw materials is achieved.
Patent Information
- Application Number
- CN202511378903.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-09-25
- Publication Date
- 2026-01-16
AI Technical Summary
The existing shade net production process has poor control adaptability and cannot automatically detect changes in raw material batches and adaptively adjust processing parameters, resulting in poor product quality consistency and significant performance differences between batches.
By acquiring parameter response values during the processing of shade net raw materials, forming a response value sequence, determining whether preset fluctuation or risk conditions are met, generating new parameter adjustment values, and achieving adaptive parameter control, including closed-loop feedback and forward-looking risk identification.
It improves the accuracy and stability of the performance indicators of shade net raw materials, ensures the long-term stability and safety of the production process, avoids risks caused by lack of effective monitoring, and has the ability to predict performance inflection points.
Smart Images
Figure CN121348730A_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of shade net production technology, specifically relating to an adaptive control method and system for processing parameters of shade net raw materials. Background Technology
[0002] With the continuous advancement of polymer processing technology, functional polymer products are playing an increasingly crucial role in modern agriculture, construction, and industrial protection.
[0003] The existing shade net production process has poor control adaptability and relies heavily on manual experience. For example, the production process often adopts a mode based on fixed formulas or manual adjustments by operators. When raw material batches are changed or new types of raw materials are used, their physicochemical properties will fluctuate. However, the existing methods cannot automatically detect these changes and adaptively adjust the processing parameters, resulting in poor product quality consistency and significant performance differences between batches. Summary of the Invention
[0004] This invention provides an adaptive control method for the processing parameters of shading net raw materials to solve the problems existing in the prior art.
[0005] To achieve the above-mentioned objectives, the technical solution adopted by the present invention is as follows: This invention provides an adaptive control method for processing parameters of shading net raw materials, characterized in that it includes: Obtain the parameter response values generated during the processing of shade net raw materials, and form a response value sequence based on the parameter response values; When the response value sequence is detected to meet the preset fluctuation conditions, parameter adjustment is performed; when the response value sequence does not meet the fluctuation conditions, the risk identification process is initiated. The step of forming the response value sequence includes: performing performance tests on the shading net raw material processed with modified adjustable parameters to obtain parameter response values; The parameter response values and their associated parameter adjustment values are recorded as key nodes to form a key node set; the response value sequence is composed of the parameter response values in the key node set in chronological order.
[0006] In a preferred embodiment, the parameter adjustment steps include: using the parameter adjustment value that triggers the fluctuation condition as a feedback signal, and generating a new parameter adjustment value based on the feedback signal; and correcting the adjustable parameters used for processing the shading net raw materials according to the new parameter adjustment value.
[0007] In a preferred embodiment, generating a new parameter adjustment value includes: reading the current set value of the adjustable parameter and a preset maximum fluctuation range, generating a fluctuation coefficient based on the maximum fluctuation range, and performing an arithmetic operation between the current set value and the fluctuation coefficient to generate a new parameter adjustment value.
[0008] In a preferred embodiment, the risk identification process includes: continuously monitoring parameter response values to determine whether risk conditions are met; and when risk conditions are met, regenerating parameter adjustment values.
[0009] In a preferred embodiment, determining whether the risk condition is met includes: counting the number of times the statistical response value difference is continuously less than or equal to a preset fluctuation benchmark value, in order to obtain a continuous stable number; When the number of consecutive stable states is greater than or equal to the preset continuity judgment standard, the parameter adjustment value associated with the last critical node corresponding to the consecutive stable state is marked as the test starting point, and the risk test procedure is started. The test results obtained from the risk testing procedure are compared with the preset risk judgment threshold to determine whether the risk conditions are met.
[0010] In a preferred embodiment, determining whether the preset fluctuation condition is met includes: calculating the difference between the parameter response values of two adjacent key nodes arranged in chronological order in the response value sequence to obtain the response value difference; comparing the response value difference with the preset fluctuation benchmark value; and determining that the fluctuation condition is met when the response value difference is greater than the fluctuation benchmark value.
[0011] In a preferred embodiment, the method further includes: monitoring the changing trend of the response value sequence; when the change node of the response value sequence from monotonically increasing to decreasing is identified, setting a prediction period, obtaining the parameter response value corresponding to the end of the prediction period as an alarm parameter, and issuing a warning signal to the control system based on the alarm parameter.
[0012] This invention also provides an adaptive control system for processing parameters of shading net raw materials, used to implement any of the above-described adaptive control methods for processing parameters of shading net raw materials, comprising: The monitoring unit acquires parameter response values generated during the processing of shading net raw materials, forms a response value sequence, and determines whether preset fluctuation conditions or risk conditions are met based on the response value sequence in order to generate a trigger signal. The decision-making unit, in response to the trigger signal generated by the monitoring unit, when the trigger signal indicates that the fluctuation condition is met, uses the parameter adjustment value that triggered the fluctuation condition as a feedback signal to generate a new parameter adjustment value, or... When the trigger signal indicates that the fluctuation conditions are not met, the risk identification process is initiated, and when the monitoring unit determines that the risk conditions are met, the parameter adjustment value is regenerated. The execution unit receives new or regenerated parameter adjustment values generated by the decision unit and corrects the adjustable parameters used for processing shading net raw materials based on these parameter adjustment values.
[0013] In a preferred embodiment, the monitoring unit is used to calculate the difference between the parameter response values of two adjacent key nodes arranged in chronological order in the response value sequence, to obtain the response value difference, and The difference in response values is compared with a preset fluctuation benchmark value to determine whether the fluctuation conditions are met.
[0014] In a preferred embodiment, the decision-making unit instructs the monitoring unit to count the number of continuous stable states when the risk identification process is initiated; when the number of continuous stable states received from the monitoring unit is greater than or equal to the preset continuity judgment standard, the parameter adjustment value associated with the last key node corresponding to the continuous stable state is marked as the test starting point, and the risk test program is initiated; wherein, the result of the risk test program is used by the monitoring unit to determine whether the risk conditions are met.
[0015] Beneficial effects This invention acquires parameter response values during the processing of shading net raw materials, forms a response value sequence, and uses the parameter adjustment values that trigger fluctuations in the response value sequence as feedback signals to generate new parameter adjustment values. This constructs a closed-loop control logic based on parameter response values, enabling adaptive parameter control based on real-time changes in the performance indicators of the shading net raw materials. This overcomes the shortcomings of existing technologies that rely on static experience values, resulting in low parameter matching and unstable product performance, and improves the accuracy and stability of the final performance indicators of the shading net raw materials.
[0016] This invention performs parameter control by determining whether the response value sequence meets preset fluctuation conditions. When the response value sequence meets the fluctuation conditions, the parameter adaptive control system performs parameter control; when the response value sequence does not meet the fluctuation conditions, a risk identification process is initiated. Through continuous monitoring, it is determined whether the risk conditions are met, and when they are met, the parameter adjustment values are regenerated. This approach balances the agility of dynamic adjustment with the reliability of stable operation, avoiding the risks accumulated due to a lack of effective monitoring when the process is stable, and ensuring the long-term stability and safety of the entire shading net raw material processing process.
[0017] This invention identifies change nodes representing inflection points in product performance by monitoring the changing trends of response value sequences. After these change nodes, a prediction period is set to obtain alarm parameters, and finally, an early warning signal is sent to the control system. This gives the parameter adaptive control system the ability to predict product performance inflection points and can issue early warning signals before performance indicators reach their peak and are about to decline. Attached Figure Description
[0018] Figure 1 This is a flowchart illustrating an adaptive control method for processing parameters of shading net raw materials according to the present invention. Detailed Implementation
[0019] Example 1 This embodiment provides an adaptive control method for processing parameters of shade net raw materials. This method achieves precise control of the production process through closed-loop feedback and forward-looking risk identification. The specific steps are as follows: The system acquires parameter response values generated during the processing of shade net raw materials and forms a response value sequence based on these values. When the response value sequence meets the preset fluctuation conditions, parameter adjustment is performed. When the response value sequence does not meet the fluctuation conditions, a risk identification process is initiated. The steps for forming the response value sequence include: performing performance tests on the shading net raw material processed with modified adjustable parameters to obtain parameter response values, recording the parameter response values and associated parameter adjustment values as key nodes to form a set of key nodes, and the response value sequence being composed of the parameter response values in the set of key nodes in chronological order.
[0020] This application uses a sensor network interface with the shading net raw material processing equipment to collect and monitor parameters in real time. These monitoring parameters are adjustable parameters in the production process and are key process settings that affect the final performance of the raw materials. In this embodiment, they are specifically the temperature parameters of each temperature zone of the extruder, the pressure parameters of the melt pump, and the flow rate parameters corresponding to the screw speed that directly affects the polymer melt output. The initial settings of these parameters constitute the basis of the control process.
[0021] Specifically, the parameter adjustment steps include: using the parameter adjustment value that triggers the fluctuation condition as a feedback signal, and generating a new parameter adjustment value based on the feedback signal; and correcting the adjustable parameters used for processing the shading net raw materials according to the new parameter adjustment value.
[0022] The step of generating a parameter adjustment value based on the initial set value of the monitored parameters involves the system reading the current set value of the monitored parameters and a preset maximum fluctuation range to constrain the boundaries of parameter adjustment. For example, the temperature is ±5 degrees Celsius and the pressure is ±0.5 MPa. A fluctuation coefficient is generated based on this maximum fluctuation range, such as a random number or a value in a predetermined sequence within the range [-1, 1]. The current set value is then arithmetically calculated with this fluctuation coefficient to generate a new parameter value as the parameter adjustment value. This ensures that the magnitude and direction of the adjustment are controlled.
[0023] Specifically, regarding the step of correcting the monitoring parameters based on the parameter adjustment values, after applying the new parameter adjustment values, a stabilization period judgment mechanism is introduced. The stabilization period judgment mechanism refers to the control logic that, after applying the new parameter adjustments, determines whether the equipment running time has reached a preset duration threshold to confirm that the production process has reached a stable state.
[0024] The steps for forming the response value sequence include: performing performance tests on the shading net raw material processed with modified adjustable parameters to obtain parameter response values, recording the parameter response values and associated parameter adjustment values as key nodes to form a set of key nodes; the response value sequence is composed of the parameter response values in the set of key nodes in chronological order.
[0025] Specifically, the initial setting value of the monitoring parameter is defined as the base point, which serves as the starting reference point for calculating the adjustment duration. After applying the correction magnitude, the system begins to calculate the adjustment duration that has elapsed since the base point was set. This adjustment duration is compared with a preset duration threshold, such as 300 seconds. This threshold is determined based on the thermal inertia of the production equipment and the time required for stable material flow.
[0026] If the adjustment duration does not exceed the duration threshold, the device state is considered unstable. Based on the current corrected parameter value and the correction magnitude, a new corrected parameter value will be generated iteratively until the adjustment duration exceeds the duration threshold. When the duration condition is met, the corrected parameter value at this moment is determined as the parameter adjustment value, and the parameter response value is obtained. The parameter response value refers to the quantitative result obtained by performing performance testing on the raw material sample produced by applying a specific parameter adjustment value, such as tensile strength or light transmittance.
[0027] For each determined parameter adjustment value, the production line generates a corresponding shading net raw material sample. This sample is sent to the quality inspection station and undergoes performance testing using standardized testing equipment. For example, a tensile testing machine is used to measure its tensile strength, or a transmittance meter is used to measure its optical performance. The quantified test results are defined as the parameter response value and associated with the corresponding parameter adjustment value, and are recorded together as key nodes. As the process progresses, the steps of generating the parameter adjustment value, correcting the monitoring parameters, and recording the key nodes are repeated to obtain a time-series-based set of key nodes.
[0028] In this embodiment of the application, the system analyzes the set of key nodes in the time series, specifically, it analyzes the response value sequence composed of the response values of each parameter to determine whether it meets the preset fluctuation conditions.
[0029] Specifically, all the key nodes in the time-series key node set are arranged in chronological order. The difference between the parameter response values of every two adjacent key nodes in the chronological order is calculated to obtain the response value difference. It is then determined whether the change of adjacent data points in the response value sequence reaches a significant level. For example, if the tensile strengths of two adjacent nodes are 15.2 MPa and 15.5 MPa, respectively, the response value difference is 0.3 MPa. The absolute value of the response value difference is compared with a preset fluctuation benchmark value, such as 0.5 MPa.
[0030] In this application, if the absolute value of the difference in response values is greater than the fluctuation benchmark value, it is determined that the response value sequence meets the preset fluctuation condition. If the response value sequence meets the fluctuation condition, it indicates that the recent parameter adjustment has had a significant impact on the product performance. The parameter adjustment value that triggered this fluctuation is used as a feedback signal, and the feedback signal is used to guide the control system to generate a new parameter adjustment value.
[0031] If the response value sequence does not meet the fluctuation condition, it indicates that the current parameter adjustment has not caused significant performance changes and the process is relatively stable. The risk identification process will be initiated. The risk identification process aims to proactively detect potential process risks. The process first counts the number of consecutive response value differences that do not meet the fluctuation condition to obtain a continuous stable number.
[0032] The system then determines whether the number of consecutive stable events is greater than or equal to the set continuity criterion, such as 10 times. If the criterion is met, the system will set the parameter adjustment value corresponding to the last critical node in the consecutive stable sequence as the test starting point. Based on this test starting point, the system will start a risk test program, such as applying a preset probing disturbance and observing the test results. The test results, such as the rate of decrease in the raw material melt index, will be used to determine whether the risk conditions are met.
[0033] Specifically, the test result is compared with a preset risk assessment threshold, such as a melt index decrease rate greater than 15%. If the test result is greater than or equal to the risk assessment threshold, the risk condition is determined to be met, and the system will immediately instruct the parameter generation unit to regenerate the parameter adjustment value. If the test result is less than the risk assessment threshold, the risk condition is determined not to be met, and subsequent processing will continue using the parameter adjustment value that triggered the risk test procedure.
[0034] The method described in this embodiment also includes an alarm mechanism. The alarm mechanism refers to a system function that issues early warnings by analyzing the overall trend of the response value sequence, especially identifying the inflection point of decline after the performance peak. The system will continuously monitor the overall change trend of the response value sequence and specifically identify the change node where the response value sequence changes from a monotonically increasing state to a decreasing state.
[0035] For example, when the tensile strength sequence shows 15.1, 15.3, 15.5, and 15.4, the node with a value of 15.5 is the changing node. After identifying the changing node, the system sets a prediction period, for example, observing the next two key nodes. At the end of the prediction period, the system obtains the corresponding parameter response value and uses this parameter response value as an alarm parameter. If the alarm parameter confirms a downward trend in performance, the system will send a warning signal to the control system based on the alarm parameter, prompting the operator that the process parameter may have reached or exceeded the optimal point.
[0036] Through the above steps, this application achieves closed-loop control of dynamic acquisition, precise correction and risk assessment of various processing parameters. Through continuous data analysis and real-time execution mechanism, it ensures the stability of the shading net raw material processing process, product consistency and the safety of the production system.
[0037] Example 2 This embodiment provides an adaptive control system for processing parameters of shading net raw materials, which can be applied to the aforementioned adaptive control method for processing parameters of shading net raw materials, and constructs a fully automated management platform from parameter acquisition and performance determination to feedback control. The system includes the following units: The parameter acquisition unit acquires the adjustable parameters of the shading net raw material processing as monitoring parameters. The monitoring parameters include temperature parameters, pressure parameters, and flow rate parameters. This unit monitors the real-time processing status through a sensor network interface with the production equipment.
[0038] The parameter generation unit generates parameter adjustment values based on the initial or current settings of the monitored parameters. When a generation command is received, the unit generates new parameter adjustment values according to the system's preset parameter adjustment range and the current settings.
[0039] The process execution unit corrects the monitoring parameters based on the parameter adjustment values and controls the processing to generate the shade net raw material. This unit applies the parameter adjustment values generated by the parameter generation unit to the processing equipment, so that the control loop in the production process can operate in a closed loop.
[0040] The data recording unit receives parameter response values obtained by performing performance tests on the shade net raw materials, and records the parameter adjustment values and parameter response values as key nodes to form a time-series set of key nodes. This unit is also responsible for collecting performance test data of the samples, such as tensile properties and light transmittance performance indicators, and managing such test results as parameter response values in a unified manner.
[0041] The trend analysis unit analyzes the response value sequence in the key node set of time series and determines whether the response value sequence meets the fluctuation conditions. This unit analyzes the changing trend of parameter response values to determine whether parameter adjustments have triggered changes that meet the fluctuation conditions. This unit is also responsible for monitoring the nodes where the response value sequence changes from increasing to decreasing to support alarm functions.
[0042] When the trend analysis unit determines that the fluctuation conditions are met, the control decision unit will trigger the parameter adjustment value of the fluctuation conditions as a feedback signal, and instruct the parameter generation unit to generate a new parameter adjustment value. When the determination result is that the fluctuation conditions are not met, the unit will initiate a risk identification process. When the risk conditions are met, the instruction parameter generation unit will regenerate the parameter adjustment value. If the evaluation result of the risk identification process is that no adjustment is needed, the original setting value will be maintained. If the trend analysis unit identifies a change node and confirms a performance decline trend, the unit will also send an early warning signal to the control system.
[0043] This application is applicable to the automated environment of precise control and dynamic response in industrial shading net production lines. It can realize multi-parameter parallel monitoring and trend analysis, support cross-cycle performance superposition analysis and error control mechanism, and has the ability to identify risks and make adaptive adjustments under the closed-loop control architecture. Through the three-in-one approach of continuous data acquisition, dynamic decision-making and automatic optimization, this application can effectively improve the real-time performance, accuracy and safety of parameter control during the processing of shading net raw materials, thereby continuously ensuring product quality and equipment operation stability.
[0044] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.
Claims
1. A sunshade net raw material processing parameter self-adaptive regulation method, characterized in that, The method comprises the following steps: Obtaining parameter response values generated in the processing of the sunshade net raw material, and forming a response value sequence based on the parameter response values; When it is monitored that the response value sequence meets a preset fluctuation condition, parameter adjustment is performed, and when the response value sequence does not meet the fluctuation condition, a risk identification process is started; The step of forming the response value sequence comprises: performing performance testing on the sunshade net raw material processed by using the adjusted adjustable parameter to obtain the parameter response value; recording the parameter response value and the parameter adjustment value associated therewith as a key node to form a key node set; and the response value sequence is composed of each parameter response value in the key node set in chronological order.
2. The self-adaptive control method for processing parameters of a solar screen raw material according to claim 1, characterized in that, The step of parameter adjustment comprises: taking the parameter adjustment value triggering the fluctuation condition as a feedback signal, and generating a new parameter adjustment value based on the feedback signal; and adjusting the adjustable parameter used for processing the sunshade net raw material according to the new parameter adjustment value.
3. The self-adaptive control method of processing parameters of sunshade net raw materials according to claim 2, characterized in that, Generating a new parameter adjustment value comprises: reading the current setting value of the adjustable parameter and a preset maximum floating range; generating a floating coefficient based on the maximum floating range; and performing arithmetic operation on the current setting value and the floating coefficient to generate a new parameter adjustment value.
4. The self-adaptive control method for processing parameters of sunshade net raw materials according to claim 1, characterized in that, The risk identification process comprises: continuously monitoring the parameter response value to determine whether a risk condition is met; and re-generating the parameter adjustment value when the risk condition is met.
5. The self-adaptive control method of processing parameters of sunshade net raw materials according to claim 4, characterized in that, Determining whether the risk condition is met comprises: counting the number of continuous stable quantities in which the response value difference is less than or equal to a preset fluctuation reference value, to obtain the continuous stable quantity; When the continuous stable quantity is greater than or equal to a preset continuity judgment standard, the parameter adjustment value associated with the last key node corresponding to the continuous stable state is marked as a test starting point, and a risk test program is started; The test result obtained by the risk test program is compared with a preset risk judgment threshold to determine whether the risk condition is met.
6. The self-adaptive control method of processing parameters of sunshade net raw materials according to claim 1, characterized in that, Determining whether the preset fluctuation condition is met comprises: calculating the difference between the parameter response values of two adjacent key nodes arranged in chronological order in the response value sequence to obtain a response value difference, comparing the response value difference with a preset fluctuation reference value, and determining that the fluctuation condition is met when the response value difference is greater than the fluctuation reference value.
7. The sunshade net raw material processing parameter self-adaptive regulation and control method according to claim 1, characterized in that, Further comprising: Monitoring the change trend of the response value sequence, and when a change node is identified in which the response value sequence changes from monotonic increase to decrease, setting a prediction period, obtaining the parameter response value corresponding to the end of the prediction period as an alarm parameter, and sending a warning signal to the control system based on the alarm parameter.
8. A sunshade net raw material processing parameter adaptive regulation system, characterized in that, A sunshade net raw material processing parameter self-adaptive adjustment method according to any one of claims 1-7, comprising: A monitoring unit obtains parameter response values generated in the processing of the sunshade net raw material, forms a response value sequence, and determines whether a preset fluctuation condition or a risk condition is met based on the response value sequence to generate a trigger signal; A decision unit responds to the trigger signal generated by the monitoring unit, takes the parameter adjustment value triggering the fluctuation condition as a feedback signal to generate a new parameter adjustment value when the trigger signal indicates that the fluctuation condition is met, or When the trigger signal indicates that the fluctuation condition is not met, a risk identification process is started, and the parameter adjustment value is re-generated when the monitoring unit determines that the risk condition is met; The execution unit receives the new or regenerated parameter adjustment value generated by the decision unit, and corrects the adjustable parameter for processing the sunshade net raw material according to the parameter adjustment value.
9. The sunshade net raw material processing parameter self-adaptive regulation and control system according to claim 8, characterized in that, The monitoring unit is configured to calculate a difference between parameter response values of two adjacent key nodes arranged in time sequence in the response value sequence to obtain a response value difference, and The response value difference is compared with a preset fluctuation reference value to determine whether a fluctuation condition is met.
10. The sunshade net raw material processing parameter self-adaptive regulation and control system according to claim 8, characterized in that, The decision unit is configured to instruct the monitoring unit to count a continuous stable number when starting a risk identification process, and to mark a parameter adjustment value associated with a last key node corresponding to the continuous stable state as a test starting point and start a risk test procedure when the continuous stable number received from the monitoring unit is greater than or equal to a preset continuity judgment standard. The result of the risk test procedure is used by the monitoring unit to determine whether a risk condition is met.