CN-121978953-A - Self-adaptive control method for needle tooth density of wool spinning carding machine based on fiber fineness monitoring

CN121978953ACN 121978953 ACN121978953 ACN 121978953ACN-121978953-A

Abstract

The invention discloses a wool spinning carding machine needle tooth density self-adaptive control method and system based on fiber fineness monitoring, and relates to the field of mechanical intelligent control, wherein the method comprises the steps of acquiring fiber fineness monitoring data of a target scene and carding zone operation characteristic data in real time; the method comprises the steps of obtaining target working condition pin density through fiber fineness monitoring data, constructing a working condition density distribution model of the target carding machine pin density, initializing the working condition density distribution model, calculating expected working condition pin density by combining the working condition density distribution model, carding zone operation characteristic data and a pre-constructed second relation model, adjusting the working condition density distribution model, outputting an optimal apparent pin density set value based on the working condition density distribution model, generating a control instruction and driving a pin density executing mechanism of the carding machine to act. The invention solves the problems that the prior art relies on manual sampling and off-line detection, the information is seriously lagged, the adaptability of needle tooth density is poor, and the dynamic operation condition of the carding machine is not considered.

Inventors

WU JING
ZHOU DAOXING
Yao Piao

Assignees

江苏中纺联针织有限公司

Dates

Publication Date: 20260505
Application Date: 20260209

Claims (10)

1. The self-adaptive control method for the needle tooth density of the wool spinning carding machine based on fiber fineness monitoring is characterized by comprising the following steps: Acquiring fiber fineness monitoring data and carding area operation characteristic data of a target scene in real time; inputting the fiber fineness monitoring data into a pre-constructed first relation model to obtain matched target working condition pin tooth density; constructing a working condition density distribution model of the needle tooth density of the target carding machine, and initializing the working condition density distribution model based on the target working condition needle tooth density; Combining the working condition density distribution model, the carding zone operation characteristic data and a pre-constructed second relation model, calculating to obtain the expected working condition pin tooth density, and iteratively solving and adjusting the working condition density distribution model by taking the expected working condition pin tooth density approaching the target working condition pin tooth density as an optimization target; and outputting an optimal apparent needle tooth density set value based on the working condition density distribution model meeting the optimization target, generating a control instruction and driving a needle tooth density executing mechanism of the carding machine to act.
2. The adaptive control method for the needle tooth density of the wool spinning carding machine based on fiber fineness monitoring according to claim 1, wherein the carding zone operation characteristic data at least comprises operation speed data of a carding roller and characteristic temperature data of a carding zone.
3. The adaptive control method for the needle tooth density of the wool spinning carding machine based on the fiber fineness monitoring according to claim 1, wherein the real-time acquisition of the fiber fineness monitoring data and the carding zone operation characteristic data of a target scene comprises the following steps: Collecting fiber fineness monitoring data in real time through a fiber fineness on-line monitoring component arranged at a feeding mechanism of a target carding machine, wherein the fiber fineness monitoring data at least comprises the average diameter of fed fibers; And respectively acquiring the running speed data of the carding roller and the characteristic temperature data of the carding area through an encoder assembly and a non-contact temperature measuring assembly which are arranged at the carding roller of the target carding machine, and outputting the running characteristic data of the carding area.
4. The adaptive control method for the needle tooth density of the wool spinning carding machine based on fiber fineness monitoring according to claim 1, wherein the construction of the first relation model comprises the following steps: Acquiring historical production data of a target carding machine, wherein the historical production data comprises historical fiber fineness data and corresponding pin tooth density records of high-quality output wool tops; screening data homologous to the target carding machine and the real-time raw material type from the historical production data to obtain sample data; And based on the sample data, performing analysis training, and establishing the first relation model taking the fineness of fibers as an input, wherein the first relation model is constructed based on any one of a mapping function and a rule base.
5. The adaptive control method for the pin density of the wool spinning carding machine based on the fiber fineness monitoring according to claim 1, wherein constructing a working condition density distribution model of the pin density of a target carding machine and initializing the working condition density distribution model based on the target working condition pin density comprises: Extracting a plurality of groups of sample apparent pin tooth density and sample working condition pin tooth density distribution according to historical production data of a target carding machine, and correspondingly matching and determining a distribution base model of the working condition density distribution model; combining the distribution base model, a plurality of groups of sample apparent needle tooth densities and sample working condition needle tooth density distribution, and analyzing and determining distribution parameters of the working condition density distribution model; And taking the target working condition pin tooth density as a distribution center of the working condition density distribution model, and executing initialization by combining the distribution base model and the distribution parameters.
6. The adaptive control method for the needle tooth density of the wool spinning carding machine based on fiber fineness monitoring according to claim 1, wherein the construction of the second relation model comprises the following steps: constructing a first mechanism model of the target carding machine based on a priori knowledge graph, wherein the first mechanism model takes the carding operation characteristic data as input and outputs a first equivalent density adjustment coefficient for representing the influence of centrifugal force; Constructing a second mechanism model of the target carding machine based on a priori knowledge graph, wherein the second mechanism model takes the carding operation characteristic data and the working condition density distribution model as inputs, and outputs a second equivalent density adjustment coefficient for representing the friction temperature rise influence; and combining the first mechanism model and the second mechanism model to construct the second relation model.
7. The wool spinning carding machine needle tooth density self-adaptive control method based on fiber fineness monitoring according to claim 1, wherein the working condition density distribution model, the carding operation characteristic data and a second pre-constructed relation model are combined, the expected working condition needle tooth density is calculated, the expected working condition needle tooth density approaches the target working condition needle tooth density to be an optimization target, and the working condition density distribution model is solved and adjusted in an iteration mode, and the method comprises the following steps: Inputting the working condition density distribution model and the carding operation characteristic data of the current iteration step into the second relation model; calculating and outputting a first equivalent density adjustment coefficient and a second equivalent density adjustment coefficient under the current iteration step through the second relation model, and correspondingly adjusting the distribution center of the working condition density distribution model; Calculating mathematical expectation as the expected working condition needle tooth density based on the adjusted working condition density distribution model, and calculating the difference between the expected working condition needle tooth density and the target working condition needle tooth density; And iteratively adjusting the distribution center of the working condition density distribution model by taking the difference value minimization as a target and combining an optimization algorithm until the difference value is smaller than a preset convergence threshold.
8. The adaptive control method for the needle tooth density of the wool spinning carding machine based on fiber fineness monitoring according to claim 1, wherein the method for outputting the optimal apparent needle tooth density set value, generating a control instruction and driving a needle tooth density executing mechanism of the carding machine to act based on the working condition density distribution model meeting an optimization target comprises the following steps: extracting a distribution center set value from the working condition density distribution model meeting an optimization target, and outputting the distribution center set value as the optimal apparent pin tooth density set value; Generating the control instruction based on machine language according to the optimal apparent needle tooth density set value, issuing the control instruction to the needle tooth density executing mechanism, and executing needle tooth density control; the needle gear density executing mechanism comprises any one of a needle gear mechanical mechanism with dynamically adjustable needle gear density and a needle gear unit group with different preset needle gear densities.
9. The adaptive control method for the needle tooth density of the wool spinning carding machine based on fiber fineness monitoring according to claim 1, wherein the method further comprises the steps of generating a control command and driving a needle tooth density executing mechanism of the carding machine to act, and then: recording an operation log of a target carding machine, combining the operation log with a preset posterior constraint to obtain quality feedback data of output wool tops, Analyzing, screening and obtaining posterior feedback data according to the quality feedback data and the corresponding optimal apparent needle tooth density set value; and based on the posterior feedback data, performing Bayesian updating on the distribution parameters in the working condition density distribution model.
10. The adaptive control method for the needle tooth density of the wool spinning carding machine based on fiber fineness monitoring according to claim 9, wherein the posterior constraint at least comprises any one of: the continuous operation time of the target carding machine reaches a preset time period from the last Bayesian updating; And the quality feedback data of the output wool tops monitored in real time exceeds a preset quality fluctuation threshold value.

Description

Self-adaptive control method for needle tooth density of wool spinning carding machine based on fiber fineness monitoring Technical Field The invention relates to the field of mechanical intelligent control, in particular to a wool spinning carding machine needle tooth density self-adaptive control method based on fiber fineness monitoring. Background The carding process is a core process for preparing wool tops, and has the task of opening, carding and impurity removal of wool fibers through needle teeth rotating at high speed by a carding machine, so that wool tops with uniform structures and good fiber orientation are provided for subsequent spinning. The needle tooth density is a key technological parameter for determining carding quality, fiber damage degree and doffing rate. In the traditional carding process, the needle tooth density is usually preset by an operator according to the raw material types, firstly, a static control mode in the production process depends on manual sampling and off-line detection, information is seriously lagged, the needle tooth density cannot be dynamically adjusted according to the fineness of fibers fed in real time, and the quality and the yield of wool tops are affected. Secondly, the operation working conditions of dynamic changes such as speed, temperature and the like in the high-speed operation process of the carding machine are not considered, so that the stability of the process quality is difficult to ensure. Meanwhile, the random fluctuation of the fiber needle tooth density in the actual running process and the slow time-varying characteristic of the carding machine are not considered, so that the process effect is gradually deteriorated. Disclosure of Invention The application provides a wool spinning carding machine needle tooth density self-adaptive control method based on fiber fineness monitoring, aiming at solving the problems that the prior art relies on manual sampling and off-line detection, information is seriously lagged, needle tooth density adaptability is poor, and the dynamic operation working condition of a carding machine is not considered. In view of the above problems, the present application provides a method for adaptively controlling the needle tooth density of a wool spinning carding machine based on fiber fineness monitoring. The application provides a wool spinning carding machine needle tooth density self-adaptive control method based on fiber fineness monitoring, which comprises the following steps: Acquiring fiber fineness monitoring data and carding area operation characteristic data of a target scene in real time; inputting the fiber fineness monitoring data into a pre-constructed first relation model to obtain matched target working condition pin tooth density; constructing a working condition density distribution model of the needle tooth density of the target carding machine, and initializing the working condition density distribution model based on the target working condition needle tooth density; Combining the working condition density distribution model, the carding zone operation characteristic data and a pre-constructed second relation model, calculating to obtain the expected working condition pin tooth density, and iteratively solving and adjusting the working condition density distribution model by taking the expected working condition pin tooth density approaching the target working condition pin tooth density as an optimization target; and outputting an optimal apparent needle tooth density set value based on the working condition density distribution model meeting the optimization target, generating a control instruction and driving a needle tooth density executing mechanism of the carding machine to act. Optionally, the operation characteristic data of the carding area at least comprises operation speed data of the carding roller and characteristic temperature data of the carding area. Optionally, acquiring fiber fineness monitoring data and carding area operation feature data of the target scene in real time includes: Collecting fiber fineness monitoring data in real time through a fiber fineness on-line monitoring component arranged at a feeding mechanism of a target carding machine, wherein the fiber fineness monitoring data at least comprises the average diameter of fed fibers; And respectively acquiring the running speed data of the carding roller and the characteristic temperature data of the carding area through an encoder assembly and a non-contact temperature measuring assembly which are arranged at the carding roller of the target carding machine, and outputting the running characteristic data of the carding area. Optionally, the constructing of the first relation model includes: Acquiring historical production data of a target carding machine, wherein the historical production data comprises historical fiber fineness data and corresponding pin tooth density records of high-quality output wool tops; scr