Method for controlling and adjusting shredding quality of shredding machine

Abstract

The invention relates to the technical field of tobacco primary processing, in particular to a tobacco cutting quality control and adjustment method of a tobacco cutter. Equipment data of a tobacco cutter is collected through a sensor, correlation analysis and weight calculation are carried out, equipment data with high correlation and large weight with the tobacco cutting quality are obtained, the equipment data serve as parameters mainly influencing the tobacco cutting quality, and a data model and an optimal tobacco cutting quality production curve are obtained and established by carrying out a single variable method experiment. A real-time change curve is built through collected real-time change parameters, shredding quality prediction is carried out according to a data model and an optimal quality curve, and a shredding machine automatically adjusts equipment parameters mainly influencing the shredding quality in real time by comparing the real-time change curve, the prediction curve and the optimal shredding quality index curve of shredding quality indexes. And a subsequent real-time curve and a prediction curve tend to an optimal shredding quality index curve, so that stable and qualified products are obtained while misoperation and lead-lag operation of employees are solved.

Description

Technical Field

[0001] The invention relates to the technical field of tobacco shredding, and in particular to a method for controlling and adjusting the shredding quality of a shredding machine. Background Art

[0002] The shredding process is a key process in tobacco silk thread production. The function of the shredder is to cut the processed tobacco leaves into shreds of a width that meets the requirements of the silk thread production process specifications. The shredding width and discharge uniformity of the shredder have an important impact on the continuous production, product efficiency and product quality of subsequent processes.

[0003] At present, the slicing machine has few adjustable parameters and no standard adjustment range. The adjustable parameters still need to be adjusted by the operator based on experience. This will lead to the possibility of advance and lag operation when different personnel operate the equipment, the stability of the discharge cannot be guaranteed, and there are differences in product quality.

[0004] In view of the above problems, the inventors of the present invention finally obtained the present invention after a long period of research and practice. Summary of the invention

[0005] In order to solve at least one aspect of the above technical problems, the present invention provides a method for controlling and adjusting the cutting quality of a slicing machine, which avoids the possibility of operators operating ahead of time or behind time, ensures the stability of the discharge, and ensures that the product quality is qualified and stable.

[0006] The technical solution adopted by the present invention is:

[0007] A method for controlling and adjusting the cutting quality of a cutting machine is provided, comprising the following steps:

[0008] S1: Collect equipment data of the shredder through sensors;

[0009] S2: performing correlation analysis on the equipment data and the slicing quality, screening out equipment data with high correlation and heavy weight with the slicing quality, and taking them as the parameters that mainly affect the slicing quality;

[0010] S3: conducting a single variable method experiment based on the parameters that mainly affect the shredded quality, and establishing a data model of the correlation between the parameters and the shredded quality index and an optimal shredded quality index curve;

[0011] S4: establishing a real-time change curve of the parameters that mainly affect the slicing quality, and establishing a real-time change curve of the slicing quality index;

[0012] S5: obtaining a prediction curve of the shredded wire quality index according to the real-time variation curve of the parameter and the data model;

[0013] S6: By comparing the real-time change curve of the shredded quality index, the predicted curve of the shredded quality index and the optimal shredded quality index curve, the parameters are automatically adjusted in real time so that the subsequent real-time shredded quality index curve and the predicted curve of the shredded quality index tend to the optimal shredded quality index curve.

[0014] In some embodiments, in step S1, the equipment data includes one or more of the following: material flow rate, chain speed, compressed air pressure, knife door height, knife roller speed, slip coefficient, grinding wheel feed rate, and blade feed rate.

[0015] In some embodiments, in step S3, the single variable method experiment is performed on tobacco of different brands and specifications, so as to obtain data models and optimal shred quality index curves of tobacco of different brands and specifications.

[0016] In some embodiments, step S3 further includes: finding the parameter combination with the best shred quality through a single variable method experiment, and establishing an evaluation system.

[0017] In some embodiments, in step S3, the shred quality index includes one or more of the following: shred width, shred qualified rate, whole shred rate, raw smoke volume, and runaway film volume.

[0018] In some embodiments, step S3 further includes: setting an adjustment range of a parameter that mainly affects the shredded quality based on a single variable method experiment.

[0019] In some implementations, in step S6, the real-time automatic adjustment of the parameters is performed within a set parameter adjustment range.

[0020] In some implementations, the control adjustment method further includes step S7: the operator fine-tunes the parameters based on the automatic adjustment.

[0021] Compared with the prior art, the beneficial effects of the present invention are as follows: by installing sensors, the equipment data can be fully quantified, reducing the errors caused by the operator's experience judgment and manual detection. The real-time change curve of the wire cutting quality index and the optimal wire cutting quality index curve are obtained, and the uniformity and stability of the wire cutting quality are ensured by comparing and adjusting the parameters toward the optimal wire cutting quality. The wire cutting machine equipment parameters are automatically adjusted to reduce the operating intensity of employees. The production quality deviation caused by the advanced and lagging operation of employees is avoided, and the qualified rate of products is improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0023] Figure 1 A flow chart showing a method for controlling and adjusting the cutting quality of a cutting machine according to an embodiment of the present invention;

[0024] Figure 2 A comparison diagram showing a real-time variation curve, a prediction curve and an optimal curve of the shred width according to an embodiment of the present invention is shown;

[0025] Figure 3 A sampling analysis table showing device data according to an embodiment of the present invention;

[0026] Figure 4 A sampling and analysis table of the measured chain speed in one embodiment of the present invention is shown. DETAILED DESCRIPTION

[0027] The above and other technical features and advantages of the present invention are described in more detail below in conjunction with the accompanying drawings.

[0028] As used herein, the term "including" and its variations mean open inclusion, i.e., "including but not limited to". Unless otherwise stated, the term "or" means "and / or". The term "based on" means "based at least in part on". The terms "an example embodiment" and "an embodiment" mean "at least one example embodiment". The term "another embodiment" means "at least one additional embodiment". Other explicit and implicit definitions may also be included below.

[0029] At present, there are few adjustable technical parameters for wire cutters and no standard for the adjustment range. The wire cutting quality is entirely regulated by the operator's experience, resulting in differences in wire cutting quality when different people operate the same equipment, and stability cannot be guaranteed. The wire cutting width is uneven, the standard is too large, and the wire cutting quality is lower than the enterprise standard pass rate and the process specification pass rate. In this embodiment, a method for controlling and adjusting the wire cutting quality of a wire cutter is provided to solve the above problems.

[0030] Reference Figure 1Specifically, the equipment data of the shredder is collected through sensors, and the shredding process capability data such as shredding width is calculated through the equipment data. Combined with the established shredding process index data, the equipment parameters that affect the shredding quality index are quantified and pointed to the optimal shredding process index. Correlation analysis and weight calculation are performed to obtain equipment data with high correlation and large weight with shredding quality, which are used as the parameters that mainly affect the shredding quality. By conducting single variable experiments on the parameters that mainly affect the shredding quality, the same single experiment is conducted on different brands and specifications, and the data model and the optimal shredding quality production curve for different brands and specifications of tobacco are obtained and established.

[0031] By collecting real-time changing parameters, a real-time changing curve is built and the wire cutting quality is predicted based on the data model and the optimal quality curve. The wire cutting machine automatically adjusts the equipment parameters that mainly affect the wire cutting quality by comparing the real-time changing curve, the predicted curve and the optimal wire cutting quality index curve of the wire cutting quality index, so that the subsequent real-time curve and predicted curve tend to the optimal wire cutting quality index curve, thereby solving the problems of employee misoperation and advanced and lagging operation while obtaining stable and qualified products.

[0032] In some embodiments, the shred quality index includes shred width, shred qualified rate, whole shred rate, raw smoke volume, and runaway film volume. Figure 2 , select the wire cutting width in the wire cutting quality index to establish a curve, compare the real-time change curve of the actual wire cutting width of the wire cutting machine, the predicted curve of the wire cutting width and the optimal wire cutting width curve, and adjust the parameters so that the subsequent real-time change curve of the actual wire cutting width of the wire cutting machine and the predicted curve of the wire cutting width tend to the optimal wire cutting width curve. It can be understood that the wire cutting width is only one of the wire cutting quality indicators, and the adjustment of the parameters requires the comprehensive comparison of the curves of various quality indicators.

[0033] In some embodiments, the equipment data includes material flow rate, chain speed, compressed air pressure, knife door height, knife roller speed, slip coefficient, grinding wheel feed, blade feed, etc. Through the collection of equipment data by sensors, a real-time change curve of equipment data or parameters that mainly affect the quality of wire cutting is established, and the data of each trend chart is quantified to realize online monitoring of the operation of the wire cutting machine, thereby ensuring the wire cutting quality of the wire cutting machine and the stability of equipment operation.

[0034] At the same time, reference Figure 3 , digitizing each trend chart can more intuitively find problems, analyze the stability of the cutting quality through sampling data, and determine the equipment operation status through the coefficient of variation index. Figure 4According to the test data, the measured coefficient of variation of the copper chain speed is greater than 1, which indicates that the chain data index is unstable and the chain operation is abnormal. After investigation, it is found that there is dust accumulation inside the copper chain, which requires maintenance. The monitoring effect is stable and reliable, and can accurately feedback the equipment operation status to ensure stable equipment operation and product quality.

[0035] In some embodiments, a single variable method experiment is used to find the parameter combination with the best shred quality, and an evaluation system is established. Based on the single variable method experiment, the adjustment range of the parameter that mainly affects the shred quality is set, and the adjustment range of the parameter is divided into a general adjustment range for the entire equipment and an adjustment range for different brands and specifications of shredded tobacco. The operator can fine-tune the parameter on the basis of automatic adjustment, and the automatic adjustment of the parameter and the manual fine-tuning of the operator are performed within the corresponding adjustment range.

[0036] The above are only preferred embodiments of the present invention, which are only illustrative and not restrictive. The structures and connection modes of the components in the present invention can be changed, and any equivalent transformations and improvements based on the technical solution of the present invention should not be excluded from the protection scope of the present invention.

Claims

1. A method for controlling and adjusting the cutting quality of a cutting machine, characterized in that: The steps include: S1: Collect equipment data of the shredder through sensors; S2: performing correlation analysis on the equipment data and the slicing quality, screening out equipment data with high correlation and heavy weight with the slicing quality, and taking them as the parameters that mainly affect the slicing quality; S3: conducting a single variable method experiment based on the parameters that mainly affect the shredded quality, and establishing a data model of the correlation between the parameters and the shredded quality index and an optimal shredded quality index curve; S4: establishing a real-time change curve of the parameters that mainly affect the slicing quality, and establishing a real-time change curve of the slicing quality index; S5: obtaining a prediction curve of the shredded wire quality index according to the real-time variation curve of the parameter and the data model; S6: By comparing the real-time change curve of the shredded quality index, the predicted curve of the shredded quality index and the optimal shredded quality index curve, the parameters are automatically adjusted in real time so that the subsequent real-time shredded quality index curve and the predicted curve of the shredded quality index tend to the optimal shredded quality index curve.

2. A method for controlling and adjusting the cutting quality of a slicing machine as claimed in claim 1, characterized in that: In step S1, the equipment data includes one or more of the following: material flow rate, chain speed, compressed air pressure, knife door height, knife roller speed, slip coefficient, grinding wheel feed, and blade feed.

3. The method for controlling and adjusting the cutting quality of a slicing machine according to claim 1, characterized in that: In step S3, the single variable method experiment is carried out on tobacco of different brands and specifications, so as to obtain data models and optimal shred quality index curves of tobacco of different brands and specifications.

4. The method for controlling and adjusting the cutting quality of a slicing machine according to claim 1, characterized in that: Step S3 also includes: finding the parameter combination with the best shred quality through a single variable method experiment and establishing an evaluation system.

5. The method for controlling and adjusting the cutting quality of a slicing machine according to claim 1, characterized in that: In step S3, the shred quality index includes one or more of the following: shred width, shred qualified rate, whole shred rate, raw smoke volume, and runaway film volume.

6. The method for controlling and adjusting the cutting quality of a slicing machine according to claim 1, characterized in that: Step S3 also includes: setting the adjustment range of the parameters that mainly affect the shredded quality based on the single variable method experiment.

7. A method for controlling and adjusting the cutting quality of a slicing machine as claimed in claim 6, characterized in that: In step S6, the parameters are automatically adjusted in real time within a set parameter adjustment range.

8. The method for controlling and adjusting the cutting quality of a slicing machine according to claim 1, characterized in that: The step S7 is also included: the operator fine-tunes the parameters based on the automatic adjustment.

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