Control method and system for automatically adjusting parameters of fine cotton blending unit

Abstract

The invention provides a control method and system for automatically adjusting parameters of a fine cotton blending unit, and the method is characterized in that the method comprises the following steps: (1) presetting the total weight W of weighing units and the preset weights of four weighing units on main control equipment, and calculating the average loading time of each hopper; and (2) obtaining an error value and an error rate between the preset weight and the actual weight, and an error value between the average loading time and the actual loading time, and obtaining a proportionality coefficient and an integral coefficient of an outer ring and a proportionality coefficient of an inner ring in the cascade system by adopting a control rule of a fuzzy self-adaptive cascade PID (Proportion Integration Differentiation) algorithm. (3) repeatedly calculating the second weighing weight and the bucket loading time according to the data in the step (2); and (4) repeating the step (2) and the step (3) according to the data of the step (3), calculating the next weighing weight and the hopper loading time, and repeating the steps in sequence. Parameters are automatically adjusted in the production process, the quality and yield of produced products are guaranteed, and manual adjustment is not needed in the whole process.

Description

Technical Field

[0001] This invention belongs to the field of textile machinery technology, specifically a control method and system for automatic adjustment of parameters of a fine cotton blending machine. Background Technology

[0002] The demand for blended yarns is increasing in the textile market. Often, it's necessary to uniformly mix two or more raw materials in a specific ratio to improve yarn quality. Ensuring uniform mixing while meeting production demands requires high-precision and high-speed weighing of fine blending machines.

[0003] In the cotton feeding process of the fine cotton blending unit, there is a problem that improving the weighing accuracy results in low production efficiency, while improving the production efficiency makes it difficult to guarantee the weighing accuracy. Moreover, manual adjustments based on experience are often required, which involves a large amount of manual work and makes it difficult to guarantee both weighing accuracy and production efficiency.

[0004] In view of the above-mentioned shortcomings, there is an urgent need to design a control method and system for automatic adjustment of parameters of a fine cotton blending unit, which can not only ensure weighing accuracy and improve production efficiency, but also eliminate the need for manual adjustment throughout the process. Summary of the Invention

[0005] To address the aforementioned problems in the prior art, this invention provides a control method and system for automatic parameter adjustment of a fine cotton blending unit. This eliminates the need for manual adjustment, enabling automatic parameter adjustment and improving weighing accuracy and production efficiency.

[0006] The objective of this invention is achieved through the following technical solution: A control method for automatically adjusting parameters of a fine cotton blending machine, characterized in that the control method includes the following steps: Step 1: First, preset the total weight W of the weighing units and the ratio A:B:C:D of the four weighing units on the main control device. The four weighing units will then obtain the preset weight according to the different ratios. , , , If the hourly output requirement of the subsequent stage is preset to P, then the average loading time for each bucket can be obtained based on the total weight W of the weighing unit. ; Step 2: Obtain the error value and error rate between the preset weight and the actual weight, the error value between the average loading time and the actual loading time, and use the control rules of the fuzzy adaptive cascade PID algorithm to obtain the proportional coefficient, integral coefficient of the outer loop and the proportional coefficient of the inner loop in the cascade system. Step 3: Based on the preset weight, actual weight, average loading time, actual loading time, proportional coefficient, and integral coefficient, repeat the calculation of the second weighing weight and loading time. Step 4: Replace the initial preset weighing weight and loading time with the second weighing weight and loading time, repeat steps 2 to 3, calculate the next weighing weight and loading time, and repeat in this cycle.

[0007] Improvement to the above technical solution: In step 2, the fuzzy adaptive cascaded PID algorithm includes outer loop control and inner loop control, with outer loop control as the main controller and inner loop control as the secondary controller.

[0008] Further improvement to the above technical solution: The main controller is a fuzzy adaptive PI control, with error and error change rate as inputs, and the universe of discourse of both is set to [-6, 6].

[0009] Further improvement to the above technical solution: Set a fuzzy set of error, error change rate, proportional coefficient and integral coefficient, and obtain the proportional coefficient and integral coefficient subset according to the subset to which the error and error change rate belong.

[0010] Further improvements to the above technical solution: The fuzzy set includes three positive and negative array subsets with zero as the dividing point, namely negative large, negative medium, negative small, zero, positive small, positive medium, and positive large.

[0011] A further improvement to the above technical solution: the secondary controller is a P-controller, using the output of the outer-loop fuzzy adaptive PID controller as the input signal.

[0012] A further improvement to the above technical solution: the proportional coefficient in the secondary controller is obtained by using the critical proportionality method.

[0013] Further improvements to the above technical solution: In step 3, during the calculation of the second weighing process, the zeroing time of material removal and the stabilization time after the weighing is completed are also obtained.

[0014] Further improvement to the above technical solution: The control method adopts a fuzzy adaptive cascaded PID algorithm. In the fuzzy adaptive cascaded PID algorithm, the zeroing time of material removal is taken as the integration start point and the end of weighing stability judgment is taken as the integration end point.

[0015] This invention discloses an automatic parameter adjustment system for a fine cotton blending machine using the aforementioned automatic parameter adjustment control method. The system includes a main control unit and four weighing units. The main control unit includes a control box, characterized in that a switch and a main control PLC are housed inside the control box, and a touchscreen is installed outside the control box to interact with the main control PLC. The PLCs in the four weighing units interact with the main control PLC via network cables.

[0016] Improvement to the above technical solution: The main control PLC includes a preset module, an adaptive module, and a calculation module. The preset module is used to preset the total weight W of the weighing unit and the ratio A:B:C:D of the four weighing unit devices. The preset weight is obtained by the four weighing unit devices according to different ratios. , , , If the hourly output requirement of the subsequent stage is preset to P, then the average loading time for each bucket can be obtained based on the total weight W of the weighing unit. The system obtains the error value and error rate between the preset weight and the actual weight, and the error value between the average loading time and the actual loading time. The adaptive module uses the control rules of the fuzzy adaptive cascade PID algorithm to obtain the proportional coefficient, integral coefficient, and inner proportional coefficient of the outer loop in the cascade system. The calculation module is used to repeatedly calculate the second weighing weight and loading time based on the preset weight, actual weight, average loading time, actual loading time, proportional coefficient, and integral coefficient. The second weighing weight and loading time replace the first preset weighing weight and loading time to calculate the next weighing weight and loading time, and this process is repeated.

[0017] Compared with the prior art, the present invention has the following advantages and positive effects: This invention eliminates the need for manual adjustments, ensuring that the fine cotton blending unit automatically adjusts parameters during production, thereby improving weighing accuracy and production efficiency, and guaranteeing the quality and quantity of the produced products. Attached Figure Description

[0018] Figure 1 This is a schematic diagram of the automatic parameter adjustment system for a fine cotton blending unit according to the present invention; Figure 2 This is a block diagram of the main control PLC in the automatic parameter adjustment system of a fine cotton blending unit according to the present invention. Detailed Implementation

[0019] The present invention will now be described in further detail with reference to the accompanying drawings.

[0020] See Figure 1 , Figure 2 An embodiment of the control method for automatic adjustment of parameters of a fine cotton blending unit provided by the present invention includes the following steps: Step 1: First, preset the total weight W of the weighing units and the ratio A:B:C:D of the four weighing units on the main control device. The four weighing units will then obtain the preset weight according to the different ratios. , , , If the hourly output requirement of the subsequent stage is preset to P, then the average loading time for each bucket can be obtained based on the total weight W of the weighing unit. .

[0021] Specifically, in this example, a switch and a main control PLC are placed inside the control box of the main control equipment. A touch screen is installed outside the control box to interact with the main control PLC. The PLCs of the four weighing units interact with the PLC of the main control equipment via network cables. The preset total weight W of the weighing units, and the ratio of the four weighing units being A:B:C:D, then the preset weights of weighing units 1# to 4# are... , , , They are respectively: ; ; ; ; Let the actual weighing weights be respectively , , , .

[0022] Let P be the hourly output requirement of the subsequent stage, and W be the total weight of the weighing unit. Then, the average loading time per bucket is... for: .

[0023] In this step, the fuzzy adaptive cascaded PID algorithm uses an outer loop to control the weighing weight and an inner loop to control the loading time. In the outer loop control, the weighing error is set to... The rate of change of weighing error is The proportionality coefficient is The integral coefficient is Weighing error and rate of change of weighing error As input, and set the universe of discourse for both to [-6, 6]. Set the weighing error. Rate of change of weighing error proportionality coefficient Integral coefficient The fuzzy set, and based on the weighing error and rate of change of weighing error To obtain the scaling factor from the subset to which it belongs. and integral coefficient The fuzzy set contains three symmetrical positive and negative subsets with zero as the dividing point: negative large, negative medium, negative small, zero, positive small, positive medium, and positive large.

[0024] Specifically, the fuzzy set is {NB, NM, NS, ZO, PS, PM, PB}, where NB represents negative large, NM represents negative medium, NS represents negative small, ZO represents zero, PS represents positive small, PM represents positive medium, and PB represents positive large. The proportional coefficient... The determination method is shown in Table 1, and the integral coefficients are as follows. The determination method is shown in Table 2.

[0025] Table 1

[0026] Table 2

[0027] In inner-loop control, the critical proportional gain method is used. The proportional gain is gradually increased from 0 until a sustained, stable, constant-amplitude oscillation first appears. At this point, the gain adjustment is stopped, and the critical gain at this time is recorded. Then the proportionality coefficient of the inner ring .

[0028] Step 3: Based on the preset weight, actual weight, average loading time, actual loading time, proportional coefficient, and integral coefficient, repeat the calculation of the second weighing weight and loading time.

[0029] In this step, during the calculation of the second feed weight value of the weighing hopper, the zeroing end time of the material removal from the weighing hopper is also obtained. And the time for determining the end of the weighing process for materials in the weighing hopper. In fact, it's a battle of time In addition to the fuzzy algorithm mentioned in the preceding steps, a cascaded PID algorithm is also used, that is, the zeroing end time of material removal from the weighing hopper is taken as the integration start time, and the stability judgment end time of the weighing of material in the weighing hopper is taken as the integration end time.

[0030] Combining the cascaded PID algorithm, taking weighing unit #1 as an example, the second feeding... The calculation method is as follows: ; Step 4: Replace the initial preset weighing weight and loading time with the second weighing weight and loading time, repeat steps 2 to 3, calculate the next weighing weight and loading time, and repeat in this cycle.

[0031] Specifically, let the nth feed value be... The preset feed value for the (n-1)th time is The actual feed value for the (n-1)th time is The actual fighting time for the (n-1)th battle is ,but By using this method for cyclical calculation, the fine cotton blending unit can automatically adjust parameters during the production process, ensuring the quality and quantity of the produced products.

[0032] See Figure 1 , Figure 2 An embodiment of the automatic parameter adjustment system for a fine cotton blending machine using the above-described automatic parameter adjustment control method includes a main control device and four weighing units (including weighing unit 1, weighing unit 2, weighing unit 3, and weighing unit 4, as shown in the figure). Figure 1 As shown, the main control device includes a control box, inside which a switch and a main control PLC are placed. A touch screen is installed on the outside of the control box to interact with the main control PLC. The PLCs of the four weighing unit devices interact with the main control PLC via network cables.

[0033] Specifically, the aforementioned main control PLC includes a preset module, an adaptive module, and a calculation module. The preset module is used to preset the total weight W of the weighing unit and the ratio A:B:C:D of the four weighing unit devices. The preset weight is obtained by the four weighing unit devices according to different ratios. , , , If the hourly output requirement of the subsequent stage is preset to P, then the average loading time for each bucket can be obtained based on the total weight W of the weighing unit. The system obtains the error value and error rate between the preset weight and the actual weight, as well as the error value between the average loading time and the actual loading time. The adaptive module uses a fuzzy adaptive cascade PID algorithm to obtain the proportional coefficient, integral coefficient, and inner proportional coefficient of the outer loop in the cascade system. The calculation module is used to repeatedly calculate the second weighing weight and loading time based on the preset weight, actual weight, average loading time, actual loading time, proportional coefficient, and integral coefficient; using the second weighing weight and loading time to replace the first preset weighing weight and loading time, it calculates the next weighing weight and loading time, and repeats this cycle. Figure 2 As shown, the data from the preset module is sent to the adaptive module, which then sends the data to the calculation module, which performs calculations based on the received data.

[0034] Of course, the above description is not intended to limit the present invention, and the present invention is not limited to the examples given above. Any changes, modifications, additions or substitutions made by those skilled in the art within the scope of the present invention should also fall within the protection scope of the present invention.

Claims

1. A control method for automatic adjustment of parameters of a fine cotton blending unit, characterized in that, The control method includes the following steps: Step 1: First, preset the total weight W of the weighing units and the ratio A:B:C:D of the four weighing units on the main control device. The four weighing units will then obtain the preset weight according to the different ratios. , , , If the hourly output requirement of the subsequent stage is preset to P, then the average loading time for each bucket can be obtained based on the total weight W of the weighing unit. ; Step 2: Obtain the error value and error rate between the preset weight and the actual weight, the error value between the average loading time and the actual loading time, and use the control rules of the fuzzy adaptive cascade PID algorithm to obtain the proportional coefficient, integral coefficient of the outer loop and the proportional coefficient of the inner loop in the cascade system. Step 3: Based on the preset weight, actual weight, average loading time, actual loading time, proportional coefficient, and integral coefficient, repeat the calculation of the second weighing weight and loading time. Step 4: Replace the initial preset weighing weight and loading time with the second weighing weight and loading time, repeat steps 2 to 3, calculate the next weighing weight and loading time, and repeat in this cycle.

2. The control method for automatic adjustment of parameters of a fine cotton blending unit according to claim 1, characterized in that, In step 2, the fuzzy adaptive cascaded PID algorithm includes outer loop control and inner loop control, with the outer loop control as the main controller and the inner loop control as the secondary controller.

3. The control method for automatic adjustment of parameters of a fine cotton blending unit according to claim 2, characterized in that, The main controller is a fuzzy adaptive PI controller, with error and error change rate as inputs, and both are set to have a universe of discourse of [-6, 6].

4. The control method for automatic adjustment of parameters of a fine cotton blending unit according to any one of claims 1-3, characterized in that, Define a fuzzy set of error, error rate of change, proportional coefficient, and integral coefficient, and obtain the subsets of proportional coefficient and integral coefficient based on the subsets to which the error and error rate of change belong.

5. The control method for automatic adjustment of parameters of a fine cotton blending unit according to any one of claims 1-3, characterized in that, The fuzzy set includes three positive and negative subsets with zero as the dividing point: negative large, negative medium, negative small, zero, positive small, positive medium, and positive large.

6. The control method for automatic adjustment of parameters of a fine cotton blending unit according to claim 2 or 3, characterized in that, The secondary controller is a P-controller, using the output of the outer-loop fuzzy adaptive PID controller as the input signal; the proportional coefficient in the secondary controller is obtained using the critical proportionality method.

7. The control method for automatic adjustment of parameters of a fine cotton blending unit according to claim 2 or 3, characterized in that, In step 3, during the calculation of the second weighing process, the zeroing time of material removal and the stabilization time after weighing are also obtained.

8. The control method for automatic adjustment of parameters of a fine cotton blending unit according to claim 2 or 3, characterized in that, The control method adopts a fuzzy adaptive cascaded PID algorithm, in which the zeroing time of material removal is taken as the integration start point and the end of weighing stability judgment is taken as the integration end point.

9. An automatic parameter adjustment system for a fine cotton blending machine using the automatic parameter adjustment control method for any one of claims 1-8, comprising a main control device and four weighing unit devices, wherein the main control device includes a control box, characterized in that, The main control device contains a switch and a main control PLC inside its control box. A touch screen is installed outside the control box to interact with the main control PLC. The PLCs of the four weighing unit devices interact with the main control PLC via network cables.

10. The automatic parameter adjustment system for a fine cotton blending unit according to claim 9, characterized in that, The main control PLC includes a preset module, an adaptive module, and a calculation module. The preset module is used to preset the total weight W of the weighing unit and the ratio A:B:C:D of the four weighing unit devices. The preset weight is obtained by the four weighing unit devices according to different ratios. , , , If the hourly output requirement of the subsequent stage is preset to P, then the average loading time for each bucket can be obtained based on the total weight W of the weighing unit. ; The system obtains the error value and error rate between the preset weight and the actual weight, and the error value between the average loading time and the actual loading time. The adaptive module uses the control rules of the fuzzy adaptive cascade PID algorithm to obtain the proportional coefficient, integral coefficient, and inner proportional coefficient of the outer loop in the cascade system. The calculation module is used to repeatedly calculate the second weighing weight and loading time based on the preset weight, actual weight, average loading time, actual loading time, proportional coefficient, and integral coefficient. The second weighing weight and loading time are used to replace the first preset weighing weight and loading time to calculate the next weighing weight and loading time, and this process is repeated.

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