Control method for reciprocating bale plucker

Abstract

The invention discloses a control method for a reciprocating bale plucker, which comprises the following steps of: constructing a target function according to an error between target pressure and real-time pressure of a rear-stage multi-bin cotton blender machine, and solving an optimal solution of the target function. And in combination with the optimal solution and the target function under the optimal solution, based on the operation efficiency of the reciprocating bale plucker and the error between the real-time pressure and the target pressure of the rear-stage multi-bin cotton blender, the descending depth value and the walking speed value at the current moment are calculated, so that the descending depth value and the walking speed value can be automatically adjusted according to the actual operation condition. Compared with the mode that the grabbing depth and the walking speed are adjusted according to manual experience, the reciprocating bale plucker achieves frequent grabbing and less grabbing, the cotton supply pressure of the multi-bin cotton mixing machine is stable, and the defects caused by manual adjustment according to experience are overcome.

Description

Technical Field

[0001] The invention belongs to the technical field of textiles, and in particular relates to a control method for a reciprocating cotton plucking machine. Background Art

[0002] The reciprocating plucker grabs cotton through reciprocating motion, and the parameters that need to be controlled include grabbing depth and travel speed. If the grabbing depth and travel speed are set too large, the reciprocating plucker will grab large pieces, which is easy to squeeze the beater; if the grabbing depth and travel speed are set too small, it will cause insufficient cotton supply in the subsequent multi-bin cotton mixer. In the existing technology, the grabbing depth and travel speed are adjusted manually based on experience, which is difficult to ensure the stability and continuity of cotton supply. Summary of the invention

[0003] The purpose of the present invention is to provide a control method for a reciprocating cotton plucking machine, which calculates the descent depth value and walking speed value at the next moment based on the operating efficiency of the reciprocating cotton plucking machine, the real-time pressure of the subsequent multi-bin cotton mixing machine and the target pressure, so that the cotton supply pressure of the multi-bin cotton mixing machine is stable, thereby achieving the technical effect of improving the refined production of the reciprocating cotton plucking machine and improving work efficiency.

[0004] The present invention is implemented by the following technical solutions:

[0005] A control method for a reciprocating plucking machine is proposed, comprising:

[0006] S1, obtaining the operating efficiency of the reciprocating plucker, the real-time pressure and target pressure of the subsequent multi-bin mixer, and calculating the error between the target pressure and the real-time pressure;

[0007] S2, constructing an objective function based on the error between the target pressure and the real-time pressure to find the optimal solution;

[0008] S3, calculating the descending depth value and the walking speed value of the reciprocating plucking machine at the current moment according to the operating efficiency of the reciprocating plucking machine, the error between the target pressure and the real-time pressure, and the obtained optimal solution;

[0009] S4, replacing the previous moment value with the descent depth value and the travel speed value of the reciprocating cotton plucker at the current moment, and repeating steps S1 to S3 to calculate the descent depth value and the travel speed value of the reciprocating cotton plucker at the next moment;

[0010] Repeat steps S1 to S4 until the exit control is satisfied.

[0011] In some embodiments of the present invention, the step S2 of using a genetic algorithm to find the optimal solution includes:

[0012] Obtain the basic parameters of the reciprocating plucker and initialize the genetic algorithm;

[0013] Establish a fitness function to evaluate the fitness of individuals;

[0014] Calculate the fitness probability of the individual, and calculate the crossover probability and mutation probability based on the fitness probability;

[0015] Use crossover probability and mutation probability to perform crossover and mutation operations to generate new populations, and eliminate individuals with fitness below the average;

[0016] Determine whether the stopping condition is met, output the optimal result when the stopping condition is met, and return to the crossover and mutation operations when the stopping condition is not met.

[0017] In some embodiments of the present invention, the fitness function established is:

[0018] ;

[0019] Where a is the proportional coefficient, and its value range is [0, 0.0084]; is the error between the target pressure and the real-time pressure at time t, and its value range is [0, 600]; b is the integral coefficient, and its value range is [0, 10].

[0020] In some embodiments of the present invention, the crossover probability is:

[0021] ;

[0022] The mutation probability is:

[0023] ;

[0024] in, for The constant between is the maximum fitness value, is the minimum fitness value, is the average fitness value, It is the one with higher fitness among the two parents before the crossover operation.

[0025] In some embodiments of the present invention, after the genetic algorithm in step S2, the values ​​of a and b under the optimal solution are obtained according to the output optimal result.

[0026] In some embodiments of the present invention, in step S3, the values ​​of parameters a and b are automatically adjusted according to the operating efficiency of the reciprocating plucking machine:

[0027] ; ;

[0028] in It is the operating efficiency of the reciprocating plucking machine, which is calculated by the ratio of the running time of the travel motor per unit time to the unit time, and the value range is [0, 100%].

[0029] In some embodiments of the present invention, in step S3, the descending depth value of the reciprocating plucking machine at the current moment is , the walking speed value is .

[0030] Compared with the prior art, the advantages and positive effects of the present invention are as follows: in the control method for the reciprocating cotton plucking machine proposed in the present invention, an objective function is constructed according to the error between the target pressure and the real-time pressure of the rear-stage multi-bin cotton mixing machine to obtain its optimal solution. In combination with the optimal solution and the objective function under the optimal solution, based on the operating efficiency of the reciprocating cotton plucking machine, the error between the real-time pressure and the target pressure of the rear-stage multi-bin cotton mixing machine, the descent depth value and the walking speed value at the current moment are calculated, so that the descent depth value and the walking speed value can be automatically adjusted according to the actual operating conditions. Compared with the method of adjusting the grasping depth value and the walking speed value based on manual experience, the method adopted by the present invention enables the reciprocating cotton plucking machine to grasp more and grasp less, and stabilizes the cotton supply pressure of the multi-bin cotton mixing machine, thereby solving the disadvantages brought about by manual adjustment based on experience.

[0031] Other features and advantages of the present invention will become more apparent after reading the detailed description of the embodiments of the present invention in conjunction with the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0033] Figure 1 The following is a schematic diagram of the steps of the control method for the reciprocating cotton plucking machine proposed in the present invention. DETAILED DESCRIPTION

[0034] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0035] In the description of the present invention, it should be understood that the terms "center", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating the orientation or position relationship are based on the orientation or position relationship shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present invention.

[0036] In the description of the present invention, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected" and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0037] The terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features. In the description of the present invention, unless otherwise specified, "plurality" means two or more.

[0038] The present invention aims to provide a control method for a cotton plucking machine, comprising:

[0039] Step S1: obtaining the operating efficiency of the reciprocating plucking machine, the real-time pressure and the target pressure of the subsequent multi-bin mixing machine, and calculating the error between the target pressure and the real-time pressure.

[0040] In the embodiment of the present invention, the operating efficiency of the reciprocating plucking machine is It is calculated based on the ratio of the running time of the walking motor per unit time to the unit time.

[0041] Real-time pressure of the subsequent multi-bin blender It is obtained through a pressure sensor, which usually outputs current. It is installed above the cotton inlet pipe of the multi-bin cotton mixer. When raw materials enter the multi-bin cotton mixer, the pressure in the cotton bin will change accordingly. The pressure sensor will generate a current signal, which will be processed by the system processor and generate a pressure value corresponding to the current signal.

[0042] The target pressure is Indicates the error between the target pressure and the real-time pressure .

[0043] Step S2: construct an objective function based on the error between the target pressure and the real-time pressure to find the optimal solution.

[0044] The constructed objective function is:

[0045] ;

[0046] Where a is the proportional coefficient, and its value range is [0, 0.0084]; is the error between the target pressure and the real-time pressure at time t, and its value range is [0, 600]; b is the integral coefficient, and its value range is [0, 10].

[0047] According to the fitness value, the probability of each individual being selected is:

[0048] ;

[0049] That is, the larger the fitness value, the greater the probability of being selected, and M is the individual number.

[0050] In the embodiment of the present invention, in order to prevent the algorithm from falling into a local optimal solution and enable the algorithm to better realize the search for the global optimal solution, adaptive crossover and mutation probability are used to improve the search capability, and the crossover probability is:

[0051] ;

[0052] The mutation probability is:

[0053] ;

[0054] in, for The constant between is the maximum fitness value, is the minimum fitness value, is the average fitness value, It is the one with higher fitness among the two parents before the crossover operation.

[0055] The specific steps of genetic algorithm include:

[0056] 1. Genetic algorithm initialization.

[0057] Including setting the evolutionary generations and randomly generating the initial population.

[0058] 2. Calculate the fitness of each individual in the group.

[0059] The fitness function mentioned above is used to calculate the fitness of each individual.

[0060] 3. Calculate the individual’s fitness probability.

[0061] 4. Calculate the crossover probability and mutation probability based on the fitness probability.

[0062] The crossover probability and mutation probability formula given above are used for calculation.

[0063] 5. Use crossover probability and mutation probability to perform crossover and mutation operations to generate new populations, and eliminate individuals with fitness below the average.

[0064] 6. Determine whether the stopping condition is met, output the optimal result when the stopping condition is met, and return to the crossover and mutation operations when the stopping condition is not met.

[0065] Step S3: Calculate the descent depth value and the travel speed value of the reciprocating cotton plucking machine at the current moment according to the operating efficiency of the reciprocating cotton plucking machine, the error between the target pressure and the real-time pressure, and the optimal solution obtained.

[0066] a and b are the values ​​of the optimal solution obtained in step S2. The values ​​of parameters a and b are automatically adjusted according to the operating efficiency of the reciprocating plucking machine:

[0067] ;

[0068] ;

[0069] in It is the operating efficiency of the reciprocating plucking machine, which is calculated by the ratio of the running time of the travel motor per unit time to the unit time, and the value range is [0, 100%]. and are the adjusted values ​​of a and b.

[0070] In this step, the current descent depth of the reciprocating plucking machine is , the walking speed value is For safety reasons, the maximum descent depth is set to 5 and the maximum walking speed is set to 30.

[0071] Step S4: Replace the previous moment's value with the current moment's descent depth value and travel speed value of the reciprocating cotton plucking machine, repeat steps S1 to S3, calculate the next moment's descent depth value and travel speed value of the reciprocating cotton plucking machine, and cycle in sequence.

[0072] In this step, the reciprocating plucking machine updates the descent depth value and the travel speed value of the previous moment according to the calculated descent depth value and the travel speed value every 5 minutes (a number of moments are set at intervals of 5 minutes).

[0073] It should be noted that, in the specific implementation process, the above-mentioned control part can be implemented by a hardware processor executing computer execution instructions in software form stored in the memory, which will not be elaborated here, and the programs corresponding to the actions performed by the above-mentioned control circuit can be stored in the computer-readable storage medium of the system in software form, so that the processor can call and execute the operations corresponding to the above-mentioned modules.

[0074] The computer-readable storage medium mentioned above may include volatile memory, such as random access memory; may also include non-volatile memory, such as read-only memory, flash memory, hard disk or solid-state drive; may also include a combination of the above types of memory.

[0075] The processor mentioned above may also be a general term for multiple processing elements. For example, the processor may be a central processing unit, or other general-purpose processors, digital signal processors, application-specific integrated circuits, field programmable gate arrays or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc., or may be a dedicated processor.

[0076] It should be pointed out that the above description is not a limitation of the present invention, and the present invention is not limited to the above examples. Changes, modifications, additions or substitutions made by ordinary technicians in this technical field within the essential scope of the present invention should also fall within the protection scope of the present invention.

Claims

1. A control method for a reciprocating plucking machine, characterized in that: include: S1, obtaining the operating efficiency of the reciprocating plucker, the real-time pressure and target pressure of the subsequent multi-bin mixer, and calculating the error between the target pressure and the real-time pressure; S2, constructing an objective function based on the error between the target pressure and the real-time pressure to find the optimal solution; S3, calculating the descending depth value and the walking speed value of the reciprocating plucking machine at the current moment according to the operating efficiency of the reciprocating plucking machine, the error between the target pressure and the real-time pressure, and the obtained optimal solution; S4, replacing the previous moment value with the descent depth value and the travel speed value of the reciprocating cotton plucker at the current moment, and repeating steps S1 to S3 to calculate the descent depth value and the travel speed value of the reciprocating cotton plucker at the next moment; Repeat steps S1 to S4 until the exit control is satisfied.

2. The control method for a reciprocating plucking machine according to claim 1, characterized in that: The step S2 of using a genetic algorithm to find the optimal solution includes: Obtain the basic parameters of the reciprocating plucker and initialize the genetic algorithm; Establish a fitness function to evaluate the fitness of individuals; Calculate the fitness probability of the individual, and calculate the crossover probability and mutation probability based on the fitness probability; Use crossover probability and mutation probability to perform crossover and mutation operations to generate new populations, and eliminate individuals with fitness below the average; Determine whether the stopping condition is met, output the optimal result when the stopping condition is met, and return to the crossover and mutation operations when the stopping condition is not met.

3. The control method for a reciprocating plucking machine according to claim 2, characterized in that: The fitness function established is: ； Among them, a is the proportional coefficient, and its value range is [0, 0.0084]; is the error between the target pressure and the real-time pressure at time t, and its value range is [0, 600]; b is the integral coefficient, and its value range is [0, 10].

4. The control method for a reciprocating plucking machine according to claim 2, characterized in that: The crossover probability is: ； The mutation probability is: ； in, for The constant between is the maximum fitness value, is the minimum fitness value, is the average fitness value, It is the one with higher fitness among the two parents before the crossover operation.

5. The control method for a reciprocating plucking machine according to claim 3, characterized in that: After the genetic algorithm in step S2, the a and b values ​​under the optimal solution are obtained according to the output optimal result.

6. The control method for a reciprocating plucking machine according to claim 5, characterized in that: In step S3, the values ​​of parameters a and b are automatically adjusted according to the operating efficiency of the reciprocating plucking machine: ； ； in It is the operating efficiency of the reciprocating plucking machine, which is calculated by the ratio of the running time of the travel motor per unit time to the unit time, and the value range is [0, 100%].

7. The control method for a reciprocating plucking machine according to claim 5, characterized in that: In step S3, the current descending depth of the reciprocating plucking machine is , the walking speed value is .

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