阅读说明：本技术 一种智能并条管理系统 (Intelligent drawing management system ) 是由 付孝军 李秋华 于 2020-04-22 设计创作，主要内容包括：一种智能并条管理系统,该系统包括监测模块、喂入控制模块、牵伸控制模块、输出控制模块和远程管理中心,所述监测模块、喂入控制控制模块、牵伸控制模块、输出控制模块分别与远程管理中心相连,所述远程管理中心根据监测数据计算喂棉、牵伸和输棉调控参数,并分别发送至喂棉控制模块、牵伸控制模块和输棉控制模块,对并条工序进行控制处理,通过实时监测棉条质量,对牵伸速度进行实时调控,实现牵伸速度与棉条匀整率的最佳适配调控,从而显著提高输出棉条的匀整率。(The utility model provides an intelligence drawing management system, this system includes monitoring module, feeding control module, draft control module, output control module and remote management center, monitoring module, feeding control module, draft control module, output control module link to each other with the remote management center respectively, the remote management center is according to monitoring data calculation feeding cotton, draft and defeated cotton regulation and control parameter to respectively send to feeding cotton control module, draft control module and defeated cotton control module, control the drawing process and handle, through real-time supervision silver quality, regulate and control the draft speed in real time, realize the best adaptation regulation and control of draft speed and silver regularity to show the regularity that improves the output silver.)

1. The utility model provides an intelligence drawing management system, its characterized in that, includes monitoring module, feeding control module, draft control module, output control module and remote management center, monitoring module, feeding control module, draft control module, output control module link to each other with the remote management center respectively, the remote management center is according to monitoring data calculation feeding, draft and defeated cotton regulation and control parameter to send respectively to feeding control module, draft control module and defeated cotton control module, control the processing to the drawing process.

2. The intelligent drawing management system of claim 1, wherein the remote management center comprises a data receiving unit, a simulation computing unit, a machine learning unit, a database unit and a data output unit; the data receiving unit is used for receiving monitoring data, the simulation calculation unit is used for simulating and calculating cotton feeding, drafting and cotton conveying regulation and control parameters according to the monitoring data, the machine learning unit is used for carrying out depth feedback and learning on the monitoring data and optimizing the regulation and control parameters step by step, the database unit is used for storing the monitoring data, the regulation and control parameters and standard values, and the data output unit is used for outputting the cotton feeding, drafting and cotton conveying regulation and control parameters.

3. The intelligent drawing management system of claim 2, wherein the feeding control module is used for controlling the cotton feeding speed of the cotton feeding roller, the drafting control module is used for controlling the drafting speed of the drafting roller, and the output control module is used for controlling the speed of the compacting roller.

4. The intelligent drawing management system of claim 2, wherein the monitoring module comprises a sliver monitoring unit and a speed monitoring unit, the sliver monitoring unit is used for monitoring feeding and outputting sliver data, and the speed monitoring unit is used for monitoring the speed of the feeding roller, the drawing roller and the pinch roller.

5. The intelligent drawing management system of claim 4, wherein the sliver monitoring unit monitors the thickness of the fed sliver and the output sliver in real time by using sensors, and the speed monitoring unit monitors the speeds of the feeding roller, the drawing roller and the compacting roller by using a rotating speed encoder.

6. The intelligent drawing management system of claim 5, wherein the sliver monitoring unit further comprises a weighing sensor, the weighing sensor is used for detecting the weight of the feeding sliver and outputting the weight of the sliver; and the remote management center calculates the linear densities of the feeding cotton sliver and the output cotton sliver according to the weights of the feeding cotton sliver and the output cotton sliver.

7. The intelligent drawing management system of claim 6, wherein the remote management center compares the thickness or linear density of the fed sliver and the output sliver with a standard value, calculates a mechanical draft multiple, calculates the speeds of the feeding roller, the drafting roller and the compacting roller according to the mechanical draft multiple, and outputs the speeds to the feeding control module, the drafting control module and the output control module through the data output unit to control the cotton feeding speed, the drafting speed and the compacting roller speed.

8. The intelligent drawing management system of claim 7, wherein the simulation computation unit of the remote management center simulates a thickness or linear density curve of the feeding sliver and the output sliver on a length scale respectively according to the real-time thickness or linear density of the feeding sliver and the output sliver and by taking the length of the sliver as an abscissa.

9. The intelligent drawing management system of claim 8, wherein the simulation calculation unit of the remote management center calculates the delay time of the sliver from feeding to output according to the speeds of the feeding roller, the drafting roller and the compacting roller and the distance between the feeding roller and the compacting roller, and integrates the simulation of the thickness of the fed sliver and the thickness of the output sliver in the same length scale coordinate system for the equivalent comparison according to the delay time.

10. The intelligent drawing management system of claim 9, wherein the machine learning unit of the remote management center performs deep learning and feedback on the comparison results of the thickness or linear density of the fed cotton sliver and the output cotton sliver and the control parameters, so as to gradually optimize the control parameters of cotton feeding, drafting and cotton conveying.

Technical Field

The invention belongs to the technical field of spinning, and particularly relates to an intelligent drawing management system.

Background

The drawing frame generally comprises a feeding mechanism, a drafting mechanism and a drawing mechanism, is mainly used in the processing technologies of cotton, chemical fiber textile and the like, and can be used for producing fiber strips with uniform evenness by the procedures of drafting, merging, mixing and slivering, and processing a plurality of fibers into fiber strips with certain quality requirements. In order to improve the drawing quality of the drawing frame, the speed of the drafting rollers of the drafting mechanism is required to be accurately controlled, and the drafting ratio is adjusted by changing the speed of the drafting rollers, so that the thickness of the sliver is evened. In the prior art, a autoleveling system is usually adopted to control the cotton sliver evenness rate, the detection mechanism is used for detecting the thickness or linear density of the cotton sliver, the detected signal is compared with a standard value, and then the drafting multiple of the cotton sliver is changed by controlling the rotating speed of a servo motor in a drafting mechanism, so that autoleveling is realized, and the purpose of improving the quality of the discharged cotton sliver is achieved.

The current auto-leveling control system can be divided into three control modes: open loop control systems, closed loop control systems, and hybrid loop control systems. The open-loop control system detects the linear density of the cotton sliver firstly and then evenly, namely, the linear density of the cotton sliver is detected firstly, a detection point is positioned at the position of feeding the cotton sliver, the deviation after the measured value is compared with the set value is sent to a controller, and then the rotating speed of a rear roller is adjusted, so that the linear density of the output cotton sliver is adjusted. The method can not compensate the unevenness in the drafting process, can not eliminate the influence of the drafting interference, and has poor adaptability. The closed-loop control system is characterized in that the cotton sliver is homogenized and then detected, in the dynamic process of normal work of the adjusting mechanism, the fine fluctuation amplitude of the cotton sliver output by the closed-loop system is larger than that of the open-loop system, but the closed-loop system can automatically correct the parameter change of each link and the influence of environmental interference due to the action of a feedback loop, and the 'drift' of the weight of the raw cotton sliver is solved, so that the average thickness of the output cotton sliver can be kept stable, and the long-segment and quantitative control is better. However, the closed-loop control system cannot even the uneven waves with the wavelength equal to or less than the distance from the leveling point to the detection point, the distance from the leveling point to the detection point is called leveling dead zone, and the required time is called leveling dead time. Due to the presence of the leveling dead zone, it can only level out the unevenness of the longer segments. The larger the leveling dead zone, the longer the leveling segment can be, and the bad cotton sliver uniformity of the middle and short segments can be caused by the malfunction of the system. The hybrid ring control system has the advantages of both open-loop and closed-loop systems, can overcome the respective defects, and has better comprehensive performance. However, the hybrid loop control system needs to solve the problems in both open-loop and closed-loop systems, and is much more complex in mechanism and technology, higher in cost, and further needs to be perfected and simplified urgently.

Based on the intelligent drawing management system, the simulation operation and the machine learning are applied to the drawing management system, the high-precision control of the drawing process is realized, and the sliver discharging quality is obviously improved.

Disclosure of Invention

Aiming at the defects in the prior art, the invention aims to provide an intelligent drawing management system, which calculates the delay time of a leveling dead zone through a drafting speed, further simulates and eliminates monitoring and control errors caused by the leveling dead zone, continuously optimizes cotton feeding, drafting and cotton conveying regulation and control parameters through machine learning, realizes high-precision control of a drawing process and obviously improves the sliver output quality.

In order to achieve the purpose, the invention adopts the following technical scheme:

the utility model provides an intelligence drawing management system, its characterized in that, includes monitoring module, feeding control module, draft control module, output control module and remote management center, monitoring module, feeding control module, draft control module, output control module link to each other with the remote management center respectively, the remote management center is according to monitoring data calculation feeding, draft and defeated cotton regulation and control parameter to send respectively to feeding control module, draft control module and defeated cotton control module, control the processing to the drawing process.

Further, the remote management center comprises a data receiving unit, a simulation calculation unit, a machine learning unit, a database unit and a data output unit; the data receiving unit is used for receiving monitoring data, the simulation calculation unit is used for simulating and calculating cotton feeding, drafting and cotton conveying regulation and control parameters according to the monitoring data, the machine learning unit is used for carrying out depth feedback and learning on the monitoring data and optimizing the regulation and control parameters step by step, the database unit is used for storing the monitoring data, the regulation and control parameters and standard values, and the data output unit is used for outputting the cotton feeding, drafting and cotton conveying regulation and control parameters.

Further, feeding control module is used for controlling the cotton feeding speed of feeding cotton roller, drafting control module is used for controlling the drafting speed of drafting roller, output control module is used for controlling the speed of roller.

Further, the monitoring module comprises a cotton sliver monitoring unit and a speed monitoring unit, the cotton sliver monitoring unit is used for monitoring feeding and outputting cotton sliver data, and the speed monitoring unit is used for monitoring the speeds of a feeding roller, a drafting roller and a compacting roller.

Further, the sliver monitoring unit adopts a sensor to monitor the thickness of the fed sliver and the output sliver in real time, and the speed monitoring unit adopts a rotating speed encoder to monitor the speed of the feeding roller, the drafting roller and the compacting roller.

Further, the cotton sliver monitoring unit also comprises a weighing sensor, and the weighing sensor is used for detecting the weight of the fed cotton sliver and the weight of the output cotton sliver; and the remote management center calculates the linear densities of the feeding cotton sliver and the output cotton sliver according to the weights of the feeding cotton sliver and the output cotton sliver.

Furthermore, the remote management center compares the thickness or linear density of the fed sliver and the output sliver with a standard value, calculates a mechanical draft multiple, calculates the speeds of the feeding roller, the draft roller and the compacting roller according to the mechanical draft multiple, and then respectively outputs the speeds to the feeding control module, the draft control module and the output control module through the data output unit to control the cotton feeding speed, the draft speed and the compacting roller speed.

Furthermore, the simulation calculation unit of the remote management center respectively simulates the thickness or linear density curve graphs of the feeding cotton sliver and the output cotton sliver on the length scale by taking the length of the cotton sliver as the abscissa according to the real-time thickness or linear density of the feeding cotton sliver and the output cotton sliver.

Furthermore, the simulation calculation unit of the remote management center calculates the delay time of the cotton sliver from feeding to output according to the speeds of the feeding roller, the drafting roller and the compacting roller and the distance between the feeding roller and the compacting roller, and integrates the thickness of the fed cotton sliver and the thickness of the output cotton sliver in a same length scale coordinate system according to the delay time for performing an equivalent comparison.

Furthermore, the machine learning unit of the remote management center carries out deep learning and feedback on the comparison result of the thickness or linear density of the fed cotton sliver and the output cotton sliver and the regulation and control parameters, and realizes the gradual optimization of the regulation and control parameters of cotton feeding, drafting and cotton conveying.

Advantageous effects

Compared with the prior art, the intelligent drawing management system provided by the invention has the following beneficial effects:

(1) the invention realizes the optimal adaptive regulation and control of the drafting speed and the cotton sliver evenness rate by monitoring the cotton sliver quality in real time and regulating and controlling the drafting speed in real time, thereby obviously improving the output cotton sliver evenness rate.

(2) According to the drawing method, the delay time of the leveling dead zone is calculated through the drawing speed and the leveling dead zone, the quality simulation of the fed cotton sliver and the quality simulation of the output cotton sliver are integrated in a coordinate system with the same length scale according to the delay time to perform equal point comparison, the monitoring and control errors caused by the leveling dead zone are eliminated, and the high-precision management and control of the drawing process are realized.

(3) The invention realizes the gradual optimization of the cotton feeding, drafting and cotton conveying regulation and control parameters by deeply learning and feeding the comparison result of the thickness or linear density of the fed cotton sliver and the output cotton sliver and the regulation and control parameters through the machine learning unit.

Drawings

FIG. 1 is a schematic diagram of a drawing management system according to the present invention.

Detailed Description

The technical solutions of the embodiments of the present invention will be described clearly and completely with reference to the accompanying drawings, and it is to be understood that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments; all other embodiments, which can be derived by a person skilled in the art from the embodiments of the present invention without any inventive step, are within the scope of the present invention.

The utility model provides an intelligence drawing management system, includes monitoring module, feeding control module, draft control module, output control module and remote management center, monitoring module, feeding control module, draft control module, output control module link to each other with the remote management center respectively, the remote management center is according to monitoring data calculation feeding cotton, draft and defeated cotton regulation and control parameter to send respectively to feeding cotton control module, draft control module and defeated cotton control module, control the processing to the drawing process.

The remote management center comprises a data receiving unit, a simulation calculation unit, a machine learning unit, a database unit and a data output unit; the data receiving unit is used for receiving monitoring data, the simulation calculation unit is used for simulating and calculating cotton feeding, drafting and cotton conveying regulation and control parameters according to the monitoring data, the machine learning unit is used for carrying out depth feedback and learning on the monitoring data and optimizing the regulation and control parameters step by step, the database unit is used for storing the monitoring data, the regulation and control parameters and standard values, and the data output unit is used for outputting the cotton feeding, drafting and cotton conveying regulation and control parameters.

Further, feeding control module is used for controlling the cotton feeding speed of feeding cotton roller, drafting control module is used for controlling the drafting speed of drafting roller, output control module is used for controlling the speed of roller.

Further, the monitoring module comprises a cotton sliver monitoring unit and a speed monitoring unit, the cotton sliver monitoring unit is used for monitoring feeding and outputting cotton sliver data, and the speed monitoring unit is used for monitoring the speeds of a feeding roller, a drafting roller and a compacting roller.

Further, the sliver monitoring unit adopts a sensor to monitor the thickness of the fed sliver and the output sliver in real time, and the speed monitoring unit adopts a rotating speed encoder to monitor the speed of the feeding roller, the drafting roller and the compacting roller.

Further, the cotton sliver monitoring unit also comprises a weighing sensor, and the weighing sensor is used for detecting the weight of the fed cotton sliver and the weight of the output cotton sliver; and the remote management center calculates the linear densities of the feeding cotton sliver and the output cotton sliver according to the weights of the feeding cotton sliver and the output cotton sliver.

Furthermore, the remote management center compares the thickness or linear density of the fed sliver and the output sliver with a standard value, calculates a mechanical draft multiple, calculates the speeds of the feeding roller, the draft roller and the compacting roller according to the mechanical draft multiple, and then respectively outputs the speeds to the feeding control module, the draft control module and the output control module through the data output unit to control the cotton feeding speed, the draft speed and the compacting roller speed.

Furthermore, the simulation calculation unit of the remote management center respectively simulates the thickness or linear density curve graphs of the feeding cotton sliver and the output cotton sliver on the length scale by taking the length of the cotton sliver as the abscissa according to the real-time thickness or linear density of the feeding cotton sliver and the output cotton sliver.

Furthermore, the simulation calculation unit of the remote management center calculates the delay time of the cotton sliver from feeding to output according to the speeds of the feeding roller, the drafting roller and the compacting roller and the distance between the feeding roller and the compacting roller, and integrates the thickness of the fed cotton sliver and the thickness of the output cotton sliver in a same length scale coordinate system according to the delay time for performing an equivalent comparison.

Furthermore, the machine learning unit of the remote management center carries out deep learning and feedback on the comparison result of the thickness or linear density of the fed cotton sliver and the output cotton sliver and the regulation and control parameters, and realizes the gradual optimization of the regulation and control parameters of cotton feeding, drafting and cotton conveying.

The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art should be considered to be within the technical scope of the present invention, and the technical solutions and the inventive concepts thereof according to the present invention should be equivalent or changed within the scope of the present invention.