A method and device for automatically adjusting the speed of a scutching machine

Abstract

The application provides a method and device for automatically adjusting the feeding speed of a fine cleaning cotton machine. The target pressure value and real-time pressure value of the fine cleaning cotton machine after feeding are obtained, and the error between the target pressure value and the actual pressure value is obtained. According to the error between the target pressure value and the actual pressure value, the improved particle swarm algorithm is used to calculate the proportional coefficient and the integral coefficient. According to the target pressure value, the real-time pressure value, the proportional coefficient and the integral coefficient, the PID algorithm is used to calculate the feeding speed of the fine cleaning cotton machine at the next moment. The feeding speed at the next moment is used to replace the feeding speed at the previous moment, and the above three steps are repeated to calculate the feeding speed of the fine cleaning cotton machine at the next moment, and the cycle is repeated in turn. The application introduces the particle swarm control method to optimize the PID parameters on the basis of using the PID control. When the pressure fluctuates, the appropriate PID parameters can be quickly found to adjust the feeding speed, the pressure of the conveying pipeline of the fine cleaning cotton machine is stabilized, and the quality of the sliver generated by the carding machine is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of fine cotton cleaning machines, and in particular to a method and a device for automatically adjusting the cotton feeding speed of a fine cotton cleaning machine. Background Art

[0002] The blowing and carding system is widely used in spinning systems. In the conventional spinning process, several carding machines are placed behind the blower. The pressure in the duct above the card directly affects the quality of the resulting sliver. Excessive pressure can easily block the duct, while too little pressure can prevent the card from dropping cotton. Frequent pressure fluctuations can also cause unstable slivers. Ensuring constant and robust pressure throughout the spinning process requires the blower to automatically adjust its feed speed based on the number of carding machines in operation and production.

[0003] The feed speed of the fine cleaner is controlled by the feed motor. The current feeding process presents several issues: The number of cards in operation and their output fluctuate constantly throughout the feeding process, causing pressure fluctuations in the cotton feed pipeline. Furthermore, the fine cleaner's feed speed doesn't change quickly enough. These issues lead to an error between the target and actual pressure values ​​of the fine cleaner, causing pressure fluctuations that impact sliver quality in the card. Summary of the Invention

[0004] In view of the deficiencies in the prior art, the present invention provides a method and device for automatically adjusting the cotton feeding speed of a fine cotton cleaner, so as to achieve pressure stability in the cotton conveying pipeline of the fine cotton cleaner.

[0005] In a first aspect, the present invention provides a method for automatically adjusting the feeding speed of a fine cotton cleaning machine, comprising:

[0006] S1. Obtaining a target pressure value of the fine cotton cleaner and a real-time pressure value after feeding cotton, and obtaining an error between the target pressure value and the actual pressure value;

[0007] S2. Based on the error between the target pressure value and the actual pressure value, the improved particle swarm algorithm is used to calculate the proportional coefficient and the integral coefficient. The calculation process is as follows:

[0008] Taking the minimum error as the objective function, it is specifically expressed as:

[0009]

[0010] Particles update their speed and position according to the following rules:

[0011]

[0012] x ij (t+1)=x ij (t)+vij (t+1)

[0013] Among them, v ij (t+1) is the velocity of the i-th particle in the j-th dimension at time t+1, η is the inertia weight, v ij (t) is the velocity of the i-th particle in the j-th dimension at time t, c1 and c2 are learning factors, let c1 = c2 = 2, r1(t) and r2(t) are random numbers between [0, 1], p ij (t) is the individual extreme value of the i-th particle in the j-th dimension at time t, p gj (t) is the global extreme value of the i-th particle in the j-th dimension at time t, x ij (t) is the position of the i-th particle in the j-th dimension at time t, x ij (t+1) is the position of the i-th particle in the j-th dimension at time t+1;

[0014] η is the inertia weight, and its value will be adjusted with the number of iterations. The specific expression is as follows:

[0015]

[0016] Where n is the current number of iterations and N is the maximum number of iterations;

[0017] The proportionality coefficient K p and the integral coefficient K i Composition particle code string [K p K i ], the global extreme value obtained in the first dimension is K p The value of the second dimension is the global extreme value of K i The value of

[0018] S3. Calculate the cotton feeding speed of the fine cotton cleaning machine at the next moment using the PID algorithm based on the target pressure value, the real-time pressure value, the proportional coefficient, and the integral coefficient. The calculation formula is as follows:

[0019]

[0020] Among them, FV n is the cotton feeding speed at the next moment, TP0 is the target pressure value, AP n-1 is the current actual pressure value, t1 is the time to obtain the current actual pressure value, and t2 is the time to reach the target pressure;

[0021] S4. Replace the cotton feeding speed at the previous moment with the cotton feeding speed at the next moment, repeat steps S1 to S3, calculate the cotton feeding speed of the fine cotton cleaner at the next moment, and repeat the cycle in sequence.

[0022] In a second aspect, the present invention provides a device for automatically adjusting the feeding speed of a fine cotton cleaning machine, comprising:

[0023] An acquisition module is used to obtain the target pressure value of the fine cotton cleaning machine and the real-time pressure value after cotton feeding, and to obtain the error between the target pressure value and the actual pressure value;

[0024] The proportional coefficient and integral coefficient calculation module is used to calculate the proportional coefficient and integral coefficient based on the error between the target pressure value and the actual pressure value using the improved particle swarm algorithm. The calculation process is as follows:

[0025] Taking the minimum error as the objective function, it is specifically expressed as:

[0026]

[0027] Particles update their speed and position according to the following rules:

[0028]

[0029] x ij (t+1)=x ij (t)+v ij (t+1)

[0030] Among them, v ij (t+1) is the velocity of the i-th particle in the j-th dimension at time t+1, η is the inertia weight, v ij (t) is the velocity of the i-th particle in the j-th dimension at time t, c1 and c2 are learning factors, let c1 = c2 = 2, r1(t) and r2(t) are random numbers between [0, 1], p ij (t) is the individual extreme value of the i-th particle in the j-th dimension at time t, p gj (t) is the global extreme value of the i-th particle in the j-th dimension at time t, x ij (t) is the position of the i-th particle in the j-th dimension at time t, x ij (t+1) is the position of the i-th particle in the j-th dimension at time t+1;

[0031] η is the inertia weight, and its value will be adjusted with the number of iterations. The specific expression is as follows:

[0032]

[0033] Where n is the current number of iterations and N is the maximum number of iterations;

[0034] The proportionality coefficient K p and the integral coefficient K i Composition particle code string [K p K i ], the global extreme value obtained in the first dimension is K p The value of the second dimension is the global extreme value of Ki The value of

[0035] The cotton feeding speed calculation module is used to calculate the cotton feeding speed of the fine cotton cleaning machine at the next moment based on the target pressure value, real-time pressure value, proportional coefficient and integral coefficient using the PID algorithm. The calculation formula is as follows:

[0036]

[0037] Among them, FV n is the cotton feeding speed at the next moment, TP0 is the target pressure value, AP n-1 is the current actual pressure value, t1 is the time to obtain the current actual pressure value, and t2 is the time to reach the target pressure;

[0038] The assignment module is used to replace the cotton feeding speed at the previous moment with the cotton feeding speed at the next moment.

[0039] Compared with the prior art, the present invention provides the following beneficial effects:

[0040] On the basis of using PID control, the present invention also introduces a particle swarm control method to optimize PID parameters. When the pressure fluctuates, it can quickly find suitable PID parameters to adjust the cotton feeding speed, thereby achieving stable pressure in the cotton conveying pipeline of the fine cotton cleaning machine and improving the quality of the cotton strips generated by the carding machine. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0042] Figure 1 A schematic flow chart of a method for automatically adjusting the feeding speed of a fine cotton cleaning machine provided in an embodiment of the present disclosure;

[0043] Figure 2 This is a structural schematic diagram of an automatic cotton feeding speed adjustment device for a fine cotton cleaning machine provided in an embodiment of the present disclosure. DETAILED DESCRIPTION

[0044] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. 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 making creative efforts are within the scope of protection of the present invention.

[0045] Figure 1 This is a flow chart of a method for automatically adjusting the feeding speed of a fine cotton cleaning machine provided by an embodiment of the present disclosure. Figure 1 As shown, the embodiment of the present disclosure provides a method for automatically adjusting the feeding speed of a fine cotton cleaning machine, comprising:

[0046] S1. Obtaining a target pressure value of the fine cotton cleaner and a real-time pressure value after feeding cotton, and obtaining an error between the target pressure value and the actual pressure value;

[0047] In this step, the cotton cleaner's pressure sensor uses a current-type sensor to accurately measure the pressure in the cotton conveying pipe. When raw material enters the cotton conveying pipe, the space it occupies is transmitted through the air pipe device to the pressure sensor. The pressure sensor generates a 4-20mA current signal. After internal processing by the PLC, it generates a pressure value corresponding to the current signal.

[0048] S2. Based on the error between the target pressure value and the actual pressure value, the improved particle swarm algorithm is used to calculate the proportional coefficient and the integral coefficient. The calculation process is as follows:

[0049] Taking the minimum error as the objective function, it is specifically expressed as:

[0050]

[0051] Particles update their speed and position according to the following rules:

[0052]

[0053] x ij (t+1)=x ij (t)+v ij (t+1)

[0054] Among them, v ij (t+1) is the velocity of the i-th particle in the j-th dimension at time t+1, η is the inertia weight, v ij (t) is the velocity of the i-th particle in the j-th dimension at time t, c1 and c2 are learning factors, let c1 = c2 = 2, r1(t) and r2(t) are random numbers between [0, 1], p ij (t) is the individual extreme value of the i-th particle in the j-th dimension at time t, p gj (t) is the global extreme value of the i-th particle in the j-th dimension at time t, x ij (t) is the position of the i-th particle in the j-th dimension at time t, x ij (t+1) is the position of the i-th particle in the j-th dimension at time t+1;

[0055] η is the inertia weight, and its value will be adjusted with the number of iterations. The specific expression is as follows:

[0056]

[0057] Where n is the current number of iterations and N is the maximum number of iterations;

[0058] The proportionality coefficient K p and the integral coefficient K i Composition particle code string [K p K i ], the global extreme value obtained in the first dimension is K p The value of the second dimension is the global extreme value of K i The value of

[0059] S3. Calculate the cotton feeding speed of the fine cotton cleaning machine at the next moment using the PID algorithm based on the target pressure value, the real-time pressure value, the proportional coefficient, and the integral coefficient. The calculation formula is as follows:

[0060]

[0061] Among them, FV n is the cotton feeding speed at the next moment, TP0 is the target pressure value, AP n-1 is the current actual pressure value, t1 is the time to obtain the current actual pressure value, and t2 is the time to reach the target pressure;

[0062] In this step, the PID algorithm is used to calculate the cotton feeding speed process of the fine cotton cleaner at the next moment, and the time when the fine cotton cleaner obtains the current actual pressure value is used as the integration starting point, and the time when the pressure reaches the target pressure is used as the integration end point.

[0063] S4. Replace the cotton feeding speed at the previous moment with the cotton feeding speed at the next moment, repeat steps S1 to S3, calculate the cotton feeding speed of the cotton cleaner at the next moment, and repeat the process in sequence until the actual pressure value is infinitely close to the target pressure value.

[0064] Corresponding to the automatic adjustment method of the feeding speed of the fine cotton cleaning machine in the above embodiment, Figure 2 This is a schematic diagram of the structure of an automatic cotton feeding speed adjustment device for a fine cotton cleaning machine provided by an embodiment of the present disclosure. For the sake of convenience, only the parts related to the embodiment of the present disclosure are shown. Figure 2 The automatic adjustment device for feeding speed of the fine cotton cleaning machine comprises:

[0065] Acquisition module 1, acquires the target pressure value of the fine cotton cleaning machine and the real-time pressure value after cotton feeding, and acquires the error between the target pressure value and the actual pressure value;

[0066] The proportional coefficient and integral coefficient calculation module 2 is used to calculate the proportional coefficient and integral coefficient based on the error between the target pressure value and the actual pressure value using the improved particle swarm algorithm. The calculation process is as follows:

[0067] Taking the minimum error as the objective function, it is specifically expressed as:

[0068]

[0069] Particles update their speed and position according to the following rules:

[0070]

[0071] x ij (t+1)=x ij (t)+v ij (t+1)

[0072] Among them, v ij (t+1) is the velocity of the i-th particle in the j-th dimension at time t+1, η is the inertia weight, v ij (t) is the velocity of the i-th particle in the j-th dimension at time t, c1 and c2 are learning factors, let c1 = c2 = 2, r1(t) and r2(t) are random numbers between [0, 1], p ij (t) is the individual extreme value of the i-th particle in the j-th dimension at time t, p gj (t) is the global extreme value of the i-th particle in the j-th dimension at time t, x ij (t) is the position of the i-th particle in the j-th dimension at time t, x ij (t+1) is the position of the i-th particle in the j-th dimension at time t+1;

[0073] η is the inertia weight, and its value will be adjusted with the number of iterations. The specific expression is as follows:

[0074]

[0075] Where n is the current number of iterations and N is the maximum number of iterations;

[0076] The proportionality factor K p and the integral coefficient K i Composition particle code string [K p K i ], the global extreme value obtained in the first dimension is K p The value of the second dimension is the global extreme value of K i The value of

[0077] The cotton feeding speed calculation module 3 is used for calculating the cotton feeding speed of the next moment of the lint cleaner according to the target pressure value, the real-time pressure value, the proportional coefficient and the integral coefficient by using the PID algorithm, and the calculation formula is as follows:

[0078]

[0079] Wherein, FV n is the cotton feeding speed of the next moment, TP0 is the target pressure value, AP n-1 is the current actual pressure value, t1 is the time for obtaining the current actual pressure value, and t2 is the time for reaching the target pressure.

[0080] The assignment module 4 is used for replacing the cotton feeding speed of the previous moment with the cotton feeding speed of the next moment.

Claims

1. A method for automatically adjusting the feeding speed of a fine cotton cleaning machine, characterized in that: include: S1. Obtaining a target pressure value of the fine cotton cleaner and a real-time pressure value after feeding cotton, and obtaining an error between the target pressure value and the actual pressure value; S2. Based on the error between the target pressure value and the actual pressure value, the improved particle swarm algorithm is used to calculate the proportional coefficient and the integral coefficient. The calculation process is as follows: Taking the minimum error as the objective function, it is specifically expressed as: Particles update their speed and position according to the following rules: x ij (t+1)=x ij (t)+v ij (t+1) Among them, v ij (t+1) is the velocity of the i-th particle in the j-th dimension at time t+1, η is the inertia weight, v ij (t) is the velocity of the i-th particle in the j-th dimension at time t, c1 and c2 are learning factors, let c1 = c2 = 2, r1(t) and r2(t) are random numbers between [0, 1], p ij (t) is the individual extreme value of the i-th particle in the j-th dimension at time t, p gj (t) is the global extreme value of the i-th particle in the j-th dimension at time t, x ij (t) is the position of the i-th particle in the j-th dimension at time t, x ij (t+1) is the position of the i-th particle in the j-th dimension at time t+1; η is the inertia weight, and its value will be adjusted with the number of iterations. The specific expression is as follows: Where n is the current number of iterations and N is the maximum number of iterations; The proportionality coefficient K p and the integral coefficient K i Composition particle code string [K p K i ], the global extreme value obtained in the first dimension is K p The value of the second dimension is the global extreme value of K i The value of S3. Based on the target pressure value, real-time pressure value, proportional coefficient and integral coefficient, the PID algorithm is used to calculate the cotton feeding speed of the fine cotton cleaning machine at the next moment. The calculation formula is as follows: Among them, FV n is the cotton feeding speed at the next moment, TP0 is the target pressure value, AP n-1 is the current actual pressure value, t1 is the time to obtain the current actual pressure value, and t2 is the time to reach the target pressure; S4. Replace the cotton feeding speed at the previous moment with the cotton feeding speed at the next moment, repeat steps S1 to S3, calculate the cotton feeding speed of the fine cotton cleaner at the next moment, and repeat the cycle in sequence.

2. An automatic cotton feeding speed adjustment device for a fine cotton cleaning machine, characterized in that: include: An acquisition module is used to obtain the target pressure value of the fine cotton cleaning machine and the real-time pressure value after cotton feeding, and to obtain the error between the target pressure value and the actual pressure value; The proportional coefficient and integral coefficient calculation module is used to calculate the proportional coefficient and integral coefficient based on the error between the target pressure value and the actual pressure value using the improved particle swarm algorithm. The calculation process is as follows: Taking the minimum error as the objective function, it is specifically expressed as: Particles update their speed and position according to the following rules: x ij (t+1)=x ij (t)+v ij (t+1) Among them, v ij (t+1) is the velocity of the i-th particle in the j-th dimension at time t+1, η is the inertia weight, v ij (t) is the velocity of the i-th particle in the j-th dimension at time t, c1 and c2 are learning factors, let c1 = c2 = 2, r1(t) and r2(t) are random numbers between [0, 1], p ij (t) is the individual extreme value of the i-th particle in the j-th dimension at time t, p gj (t) is the global extreme value of the i-th particle in the j-th dimension at time t, x ij (t) is the position of the i-th particle in the j-th dimension at time t, x ij (t+1) is the position of the i-th particle in the j-th dimension at time t+1; η is the inertia weight, and its value will be adjusted with the number of iterations. The specific expression is as follows: Where n is the current number of iterations and N is the maximum number of iterations; The proportionality coefficient K p and the integral coefficient K i Composition particle code string [K p K i ], the global extreme value obtained in the first dimension is K p The value of the second dimension is the global extreme value of K i The value of The cotton feeding speed calculation module is used to calculate the cotton feeding speed of the fine cotton cleaning machine at the next moment based on the target pressure value, real-time pressure value, proportional coefficient and integral coefficient using the PID algorithm. The calculation formula is as follows: Among them, FV n is the cotton feeding speed at the next moment, TP0 is the target pressure value, AP n-1 is the current actual pressure value, t1 is the time to obtain the current actual pressure value, and t2 is the time to reach the target pressure; The assignment module is used to replace the cotton feeding speed at the previous moment with the cotton feeding speed at the next moment.

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