Textile yarn production monitoring, regulating and controlling method and system

Abstract

The invention discloses a spinning yarn production monitoring and regulating method and system, and relates to the technical field of spinning yarn production.The method comprises the steps that firstly, according to yarn production records, the production grade when all production equipment control data combinations in a production line process all raw material humidity combinations is analyzed, and a production raw material humidity production table is generated; then, when yarn production is carried out, according to the humidity of each raw material, equipment control data in each production stage are confirmed and set, each production stage is monitored in the yarn production, and when abnormity occurs, corresponding response and adjustment of the equipment control data in the subsequent production stage are carried out according to the type of the abnormity; intelligent and automatic monitoring and control of the textile yarn production line are achieved, the loss cost of raw materials is reduced, the qualification of the production quality of textile yarn is ensured, the loss and maintenance cost of equipment are reduced, and the production efficiency of textile yarn is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of textile yarn production, and particularly relates to a method and system for monitoring and regulating textile yarn production. Background Art

[0002] With the continuous development of technology, more and more production lines in textile yarn production factories adopt intelligent equipment for production, and intelligent monitoring is carried out on the intelligent equipment and production quality, which can timely detect abnormal situations of the equipment and fluctuations in production quality, so as to timely maintain the equipment and adjust process parameters to ensure the efficient operation of the production line.

[0003] The prior art, such as the invention patent with the publication number CN119359135A, discloses a method for monitoring and regulating textile yarn production, including the following steps: Step 1, the raw materials are inspected by a comprehensive inspection device to conduct preliminary inspection and screening of the raw materials. By setting up an intelligent management system, the whole process of yarn production is monitored, and data of each link are collected in real time and transmitted to the system center. When the system detects unqualified product values, its built-in intelligent algorithm will immediately start the analysis program, judge the problem and trigger corresponding countermeasures. If the problem stems from the raw materials, the system will immediately mark this batch of raw materials as unavailable, and if the problem appears in the subsequent production process, such as improper fiber treatment or substandard quality of the fine yarn, the system will quickly send a stop work instruction to the production line, achieving the effect of reducing the consumption of the production line.

[0004] The prior art, such as the invention patent with the publication number CN118505068A, discloses a method for monitoring and regulating textile yarn production, including: determining the basic operation data of each facility by obtaining the fiber properties of various raw materials, and correcting the corresponding implementation steps of the textile yarn by detecting the defect status of each production process of the textile yarn in real time; by setting two correction processing methods, and taking the first correction method as the preferred correction method, while timely correcting the deviation and preventing the problem from further deteriorating, for minor deviations that do not need to be processed immediately, they can be selectively processed or not processed; by comparing the production quality effect of the textile yarn corresponding to the current correction method with the expected effect of another correction method, to judge the rationality of the processing method of the current correction method, and accordingly select the correction method with the best cost-benefit.

[0005] The above solution specifically discloses the monitoring and regulation of multiple links in textile yarn production. However, the humidity of raw materials in textile yarn production directly has an adverse impact on multiple subsequent production links and the quality of the final product. For example: the flexibility of cotton fibers with high humidity increases, and the friction between them increases, making it difficult to be fully loosened during the opening and cleaning process, and it is easy to form cotton bundles or lumps, affecting the carding and drafting of fibers in subsequent processes; high humidity increases the stickiness of cotton, making it easy to adhere to components such as beaters and rollers of the opening and cleaning equipment, resulting in beater winding, affecting the normal operation of the equipment, and may also cause equipment failures, reducing production efficiency; but the above solution lacks the detection of the humidity of raw materials before production, nor does it perform corresponding pretreatment on the raw materials according to the humidity of the raw materials, unable to ensure that the humidity of the raw materials is within the range of safe production, unable to ensure the qualification of subsequent production and the quality of the final product, increasing the probability of equipment failures during the production process, increasing equipment maintenance costs, and at the same time reducing the production efficiency of textile yarns.

[0006] In each production stage of textile yarn production, when the equipment processes raw materials with different humidities, the required process parameters are also different. For example: for raw materials with high humidity, the beater speed should be appropriately increased to enhance the loosening effect, and for raw materials with high humidity, the fibers are prone to adhesion, so the interval between the cylinder and the flat should be appropriately reduced to enhance the carding effect. However, in the above solution, the parameters of the equipment in each production stage are not adjusted accordingly according to the humidity of the raw materials, unable to achieve intelligent and automated regulation of textile yarns, reducing the production quality and production effect of textile yarns, and at the same time unable to ensure the quality of the finished product. Summary of the Invention

[0007] Aiming at the above existing technical deficiencies, the purpose of the present invention is to provide a method and system for monitoring and regulating textile yarn production.

[0008] To solve the above technical problems, the present invention adopts the following technical solutions: In the first aspect, the present invention provides a method for monitoring and regulating textile yarn production, including the following steps: S1. Obtain the raw material data, equipment process data of each production stage, and production quality data corresponding to each historical production from the yarn production records, and generate a raw material humidity production table.

[0009] S2. Obtain the raw material data in the current production. Based on the raw material humidity production table, analyze whether the raw materials need pretreatment. If pretreatment is required, first perform pretreatment on the raw materials, and then set the equipment control data for each production stage. If pretreatment is not required, directly set the equipment control data for each production stage.

[0010] S3. When the equipment in each production stage is working, obtain the operation data and production quality data of the equipment in each production stage, analyze the production status of each production stage, and based on the production status of each production stage, make a production response for the next production stage, and at the same time feedback the equipment operation data and production quality data of each production stage to S1.

[0011] In a second aspect, the present invention provides a textile yarn production monitoring and control system, including: a production analysis module, which is used to obtain the raw material data corresponding to each historical production, the equipment process data of each production stage, and the production quality data from the yarn production records, and generate a raw material humidity production table.

[0012] A production setting module, which is used to obtain the raw material data in the current production, and based on the raw material humidity production table, analyze whether the raw material needs pretreatment. If pretreatment is required, first pretreat the raw material, and then set the equipment control data for each production stage. If pretreatment is not required, directly set the equipment control data for each production stage.

[0013] A production control module, which is used to obtain the operation data and production quality data of the equipment in each production stage when the equipment in each production stage is working, analyze the production status of each production stage, and based on the production status of each production stage, make a production response for the next production stage, and at the same time feedback the equipment operation data and production quality data of each production stage to the production analysis module.

[0014] The beneficial effects of the present invention are as follows: The present application provides a textile yarn production monitoring and control method and system. First, according to the yarn production records, a raw material humidity production table is generated. Then, when yarn production is carried out, according to the humidity of each raw material, the equipment control data in each production stage is confirmed and set, and each production stage is monitored during yarn production. When an abnormality occurs, corresponding responses are made according to the type of abnormality and the equipment control data in the subsequent production stage is adjusted, realizing intelligent and automated monitoring and control of the textile yarn production line, reducing the loss cost of raw materials, ensuring the qualification of the production quality of textile yarns, reducing the loss and maintenance cost of equipment, and improving the production efficiency of textile yarns. Description of the Drawings

[0015] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0016] Figure 1 It is a schematic flowchart of the implementation steps of the method of the present invention.

[0017] Figure 2 This is a schematic diagram of the system structure connection of the present invention. Specific implementation mode

[0018] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without making creative efforts belong to the scope of protection of the present invention.

[0019] Embodiment 1:

[0020] Refer to Figure 1 As shown, a method for monitoring and regulating the production of textile yarns includes the following steps: S1. Obtain the raw material data corresponding to each historical production, the equipment process data of each production stage, and the production quality data from the yarn production records, and generate a raw material humidity production table.

[0021] In the above, obtain the yarn production records from the yarn production control center.

[0022] Among them, the raw material data includes the humidity of each raw material, and the humidity of each raw material is used as the raw material humidity combination. A humidity sensor can be used to collect the humidity of each raw material.

[0023] The equipment process data includes equipment control data and operation data. For example: each production stage includes a raw material opening stage, a carding stage, a combing stage, a drawing stage, a roving stage, and a spinning stage, etc. The equipment in the carding stage is a carding machine, the equipment in the combing stage is a comber, the equipment in the drawing stage is a draw frame, the equipment in the roving stage is a roving frame, and the equipment in the spinning stage is a spinning frame, etc.

[0024] The equipment control data is the parameters for controlling the equipment to work. For example: the equipment control data of the carding machine includes the beater speed, the feed roller speed, the bar grate spacing, and the hopper pressure, etc.; the equipment control data of the comber includes the cylinder speed, the licker-in speed, and the doffer speed, etc.; the equipment control data can be obtained from the equipment control terminal. The equipment control terminal sends the equipment control data to the equipment through the Internet of Things, and the equipment works according to its control data.

[0025] The operating data are the parameters that reflect the device status when the device is working. For example, the operating data of a ring spinning frame are mechanical vibration values, noise values, etc. When the ring spinning frame is running at high speed, if there are excessive mechanical vibrations and noises, it may be caused by reasons such as unbalanced spindles and bent rollers. These abnormalities affect the service life of the device and the spinning quality. Therefore, it is necessary to detect the operating data. The operating data of the device can be obtained from the device monitoring terminal. There are several sensors installed in the device, including vibration sensors, noise sensors, etc. The sensors transmit the collected data to the device monitoring terminal through the Internet of Things.

[0026] The production quality data of each production stage are the quality data of the products after each production stage is completed. Among them, for example, the production quality data of the carding stage include the sliver evenness and fiber straightness, etc., and the production quality data of the drawing stage include the roving evenness and the straightness and parallelism of the roving, etc.; The sliver evenness and roving evenness can be detected by a yarn evenness tester, the fiber straightness can be obtained by using a fiber image analyzer, and the straightness and parallelism of the roving can be collected by using a fiber straightness meter.

[0027] In a specific embodiment, the generation process of the raw material humidity production table is as follows: Obtain the raw material humidity combinations corresponding to each historical production from the raw material data corresponding to each historical production, obtain the equipment control data and operating data from the equipment process data of each production stage in each historical production, take the equipment control data of each production stage corresponding to the same historical production as a target production, and take the equipment control data of each production stage in the target production as the production equipment control data combination, so as to obtain each production equipment control data combination, and the production quality data of each production stage in each historical production, and count the production quality data and each operating data of each production stage when each production equipment control data combination processes each raw material humidity combination.

[0028] Use the production quality data and each operating data of each production stage when each production equipment control data combination processes each raw material humidity combination to analyze the production grade when each production equipment control data combination processes each raw material humidity combination, and thus construct the raw material humidity production table.

[0029] In the above, the analysis process of the production grade when each production equipment control data combination processes each raw material humidity combination is as follows: Obtain the production quality data threshold and the operating data threshold of each production stage from the production control center, use the production quality data of each production stage and the production quality data threshold of each production stage when each production equipment control data combination processes each raw material humidity combination to calculate the production quality grade when each production equipment control data combination processes each raw material humidity combination, denoted as a1 xy, where \(x\) represents the number of combinations of production equipment control data, \(y\) represents the number of combinations of raw material humidity, and both \(x\) and \(y\) are positive integers. Among them, the production quality grades include Grade 1, Grade 2, and Grade 3.

[0030] It should be noted that the higher the grade, the better the production quality. The production quality data thresholds and operation data thresholds for each production stage are the reference values for evaluating whether the production quality and operation are normal, and are set by production managers according to the specific production requirements of the factory.

[0031] Preferably, the calculation process of the production quality grade when each combination of production equipment control data processes each combination of raw material humidity is as follows: Denote the production quality data of each production stage when each combination of production equipment control data processes each combination of raw material humidity as \(M1\) xyrg , where \(r\) represents the number of each production stage, \(g\) represents the number of each production quality data, and both \(r\) and \(g\) are positive integers; Denote the production quality data threshold of each production stage as \(M1\) r ; The expression of the production quality grade analysis model is:

[0032] In the formula, \(R\) and \(G\) respectively represent the number of production stages and the number of production quality data, \(M1\) xyr ( g+1 ) represents the \((g + 1)\)-th production quality data of the \(y\)-th production stage when the \(x\)-th combination of production equipment control data processes the \(y\)-th combination of raw material humidity, \(\Delta M1\) r represents the preset production quality data difference threshold of the \(y\)-th production stage, \(\delta\) min , \(\delta\) max are respectively the preset lower limit value and upper limit value of production quality evaluation.

[0033] Among the above, 1, 2, and 3 in the expression of the production quality grade analysis model respectively represent Grade 1, Grade 2, and Grade 3.

[0034] It should be added that the production quality data difference threshold of each production stage represents the critical value of the difference in production quality data in each production stage, and is the basis for evaluating whether the production quality of each production stage is stable. Its specific value is set by production managers according to the specific production requirements of the factory and is not limited here.

[0035] The lower limit value and upper limit value of production quality assessment are the lower and upper benchmark values used to evaluate the production quality level. When it is less than the lower limit value of production quality assessment, it indicates that the production quality and stability are poor, and the production quality level is Grade 1; when it is greater than or equal to the lower limit value of production quality assessment and less than the upper limit value of production quality assessment, it indicates that the production quality and stability are good, and the production quality level is Grade 2; when it is greater than or equal to the upper limit value of production quality assessment, it indicates that the production quality and stability are very good, and the production quality level is Grade 3; the specific values of the lower limit value and upper limit value of production quality assessment are set by production management personnel according to the specific production requirements of the factory, and are not restricted here.

[0036] Using the operation data of each production stage and the operation data threshold of each production stage when processing each raw material humidity combination with each production equipment control data combination, calculate the equipment operation level when processing each raw material humidity combination with each production equipment control data combination, denoted as a2 xy , where the equipment operation level includes Grade 1, Grade 2, and Grade 3.

[0037] It should be noted that the calculation method of the equipment operation level when processing each raw material humidity combination with each production equipment control data combination is the same as the calculation method of the production quality level when processing each raw material humidity combination with each production equipment control data combination, and will not be elaborated here.

[0038] When a1 xy = Grade 3 ∧ a2 xy = Grade 3, then the production level when the xth production equipment control data combination processes the yth raw material humidity combination is Grade 3.

[0039] When a1 xy = Grade 2 ∧ a2 xy = Grade 2, then the production level when the xth production equipment control data combination processes the yth raw material humidity combination is Grade 2.

[0040] When a1 xy = Grade 1 ∨ a2 xy = Grade 1, then the production level when the xth production equipment control data combination processes the yth raw material humidity combination is Grade 1.

[0041] Preferably, the raw material humidity production table is in the form of a table of the production levels when each production equipment control data combination processes each raw material humidity combination.

[0042] For example: The control data combinations of each production device include A, B, and C, and the humidity combinations of each raw material include D, E, and F. Among them, the production grades of the D, E, and F raw material humidity combinations processed by the A production device control data combination are 1st grade, 2nd grade, and 3rd grade respectively, the production grades of the D, E, and F raw material humidity combinations processed by the B production device control data combination are 2nd grade, 3rd grade, and 1st grade respectively, and the production grades of the D, E, and F raw material humidity combinations processed by the C production device control data combination are 3rd grade, 1st grade, and 3rd grade respectively.

[0043] The raw material humidity production table is as follows:

[0044] Raw material humidity production table

[0045]

[0046]

[0047] S2. Obtain the raw material data in the current production. Based on the raw material humidity production table, analyze whether the raw material needs pretreatment. If pretreatment is required, first perform pretreatment on the raw material, and then set the equipment control data for each production stage. If pretreatment is not required, directly set the equipment control data for each production stage.

[0048] In a specific embodiment, the process of analyzing whether the raw material needs pretreatment is as follows: S21. Obtain the humidity of each raw material from the raw material humidity production table, and compare it with the humidity of each raw material in each raw material humidity combination in the raw material humidity production table. If the humidity of each raw material is different from the humidity of each raw material in each raw material humidity combination, it indicates that the raw material needs pretreatment.

[0049] S22. If the humidity of each raw material corresponds to the humidity of each raw material in a certain raw material humidity combination, then use this raw material humidity combination as the current raw material humidity combination. Obtain the production grades of each production device control data combination processing the current raw material humidity combination from the raw material humidity production table. If the production grades of each production device control data combination processing the current raw material humidity combination are all less than 2nd grade, it indicates that the raw material needs pretreatment. If there is at least one production device control data combination processing the current raw material humidity combination with a production grade greater than 2nd grade, it indicates that the raw material does not need pretreatment.

[0050] In another specific embodiment, the process of performing pretreatment on the raw material is as follows: Obtain each raw material humidity combination with a production grade of 1st grade processed by each production device control data combination from the raw material humidity production table as each marked raw material humidity combination. Obtain the humidity of each raw material in each marked raw material humidity combination, and select the maximum and minimum values of the humidity as the upper humidity limit value and lower humidity limit value of each raw material. Then, use the humidity of each raw material to calculate the pretreatment method of the raw material, where the pretreatment method includes drying or humidifying and proportional mixing.

[0051] Using the control data combinations of each production equipment in the raw material humidity production table to process the production grades of each raw material humidity combination, obtaining the control data combinations of each production equipment with the production grade greater than level 2 for processing each raw material humidity combination, thereby calculating the priority coefficient of each raw material humidity combination, and selecting the raw material humidity combination with the largest priority coefficient as the target raw material humidity combination.

[0052] Preferably, the calculation process of the priority coefficient of each raw material humidity combination is as follows: count the number of control data combinations of production equipment with the production grade greater than level 2 for processing each raw material humidity combination as the number of optional control data combinations of production equipment for each raw material humidity combination, and calculate the average value of the production grades of the control data combinations of each production equipment with the production grade greater than level 2 for processing each raw material humidity combination to obtain the average production grade for processing each raw material humidity combination. Normalize the number of optional control data combinations of production equipment and the average production grade of each raw material humidity combination, and record the processed values as U1 y and U2 y , the priority coefficient of each raw material humidity combination

[0053] When the pretreatment method of the raw material is drying or humidifying, use the pretreatment equipment to perform pretreatment on each equipment until the humidity of each raw material is the same as the humidity of each raw material in the target raw material humidity combination, stop the pretreatment, and then use the target raw material humidity combination as the current raw material humidity combination.

[0054] When the pretreatment method of the raw material is proportional mixing, obtain the raw material mixing records from the data storage cloud, obtain the historical humidity and mixing ratio data of each raw material when each historical proportional mixing target raw material humidity combination is performed from the raw material mixing records, select each historical proportional mixing with the same corresponding humidity of each raw material as each reference mixing, obtain the mixing ratio data of each reference mixing, perform data clustering on the mixing ratio data of each reference mixing, and use the clustering result as the mixing ratio data of each raw material, and perform corresponding proportional mixing during pretreatment. After the mixing is completed, use the target raw material humidity combination as the current raw material humidity combination.

[0055] In another specific embodiment, the process of setting the control data of the equipment in each production stage is as follows: extract the production grades of the control data combinations of each production equipment for processing the current raw material humidity combination from the raw material humidity production table, and select the control data combinations of each production equipment with the production grade of level 2 for processing the current raw material humidity combination as each primary selected control data combination.

[0056] Obtain the equipment control data in each production stage of the current production line from the equipment control center, compare it with the equipment control data in each production stage of each initial selected production equipment control data combination, analyze the regulation fluctuation value of each initial selected production equipment control data combination, select the initial selected production equipment control data combination with the smallest regulation fluctuation value as the final selected production equipment control data combination, use the equipment control data in each production stage of the final selected production equipment control data combination as the equipment control data for each production stage, and then set the equipment control data for each production stage.

[0057] Preferably, the analysis process of the regulation fluctuation value of each initial selected production equipment control data combination is as follows: Subtract the equipment control data in each production stage of the current production line from the equipment control data in each production stage of each initial selected production equipment control data combination, then divide by the equipment control data in each production stage of the current production line, and then perform an average value calculation to obtain the regulation fluctuation value of each initial selected production equipment control data combination.

[0058] S3. When the equipment in each production stage is working, obtain the operation data and production quality data of the equipment in each production stage, analyze the production status of each production stage, and based on the production status of each production stage, perform a production response for the next production stage, and at the same time feedback the equipment operation data and production quality data of each production stage to S1.

[0059] In the above, after the equipment operation data and production quality data of each production stage are feedback to S1, S1 updates the raw material humidity production table for the next production of the production line.

[0060] In a specific embodiment, the specific process of analyzing the production status of each production stage is as follows: Obtain the production quality data threshold and operation data threshold of each production stage from the production control center, and record them as q1′ r and q2′ r , and record the production quality data and operation data of the production stage as q1 r and q2 r .

[0061] When q1 r ≥q1′ r ∧q2 r ≤q2′ r , it indicates that the rth production stage is producing normally; when q1 r <q1′ r ∧q2 r ≤q2′ r , it indicates that the product production in the rth production stage is abnormal; when q1 r ≥q1′ r ∧q2 r >q2′ r, indicating equipment anomalies in the r-th production stage; when q1 < q1' r ∧q2 r > q2' r , indicating that all production in the r-th production stage is abnormal.

[0062] In another specific embodiment, the production response for the next production stage is carried out based on the production levels of each production stage. The specific process is as follows: S31. When the r-th production stage is producing normally, a first type of production signal is output, and the equipment control data for the (r + 1)-th production stage remains unchanged.

[0063] S32. When product production in the r-th production stage is abnormal, a second type of production signal is output, and equipment production in the r-th production stage is stopped. At the same time, the staff conducts product anomaly investigation and isolation based on the second type of production signal, and then restarts equipment production in the r-th production stage according to the equipment control data of the r-th production stage, and obtains the production quality data and operation data of the r-th production stage after restarting, and then adjusts the equipment control data for the (r + 1)-th production stage.

[0064] S33. When there are equipment anomalies in the r-th production stage, a third type of production signal is output, and equipment production in the r-th production stage is stopped, reminding the staff to perform equipment maintenance for this production stage. After the staff completes the equipment maintenance, the equipment production for this production stage is restarted according to the equipment control data of the r-th production stage.

[0065] S34. When all production in the r-th production stage is abnormal, a fourth type of production signal is output, and equipment production in the r-th production stage is stopped. At the same time, the staff conducts product anomaly investigation, isolation, and equipment maintenance. After completion, the equipment production for this production stage is restarted according to the equipment control data of the r-th production stage, and the adjustment is made according to the adjustment method of the equipment control data for the (r + 1)-th production stage in S32.

[0066] Preferably, the adjustment of the equipment control data for the (r + 1)-th production stage is carried out as follows: Obtain the equipment control data, production quality data, and operation data of the r-th production stage and the (r + 1)-th production stage in each historical production with normal production from the yarn production records.

[0067] For each historical production, the equipment control data, production quality data, and operation data of the r-th production stage are recorded as each marked historical production corresponding to the equipment control data, production quality data, and operation data of the r-th production stage that are the same. Obtain the equipment control data, production quality data, and operation data of the (r + 1)-th production stage in each marked historical production. At the same time, based on the raw material humidity production table and the yarn production record, obtain the production grade of the combined production of the current raw material humidity combination corresponding to the production equipment control data of each marked historical production, which is recorded as the production grade of each marked historical production. Calculate the value degree of each marked historical production, select the marked historical production grade with the largest value degree as the marked historical production, use the equipment control data of the (r + 1)-th production stage in the marked historical production as the equipment control data of the (r + 1)-th production stage, and at the same time obtain the equipment control data of each production stage after the (r + 1)-th production stage in the marked historical production from the yarn production record, and adjust each production stage after the (r + 1)-th production stage.

[0068] Embodiment 2:

[0069] Refer to Figure 2 As shown in the figure, a textile yarn production monitoring and control system includes: a production analysis module, a production setting module, and a production control module.

[0070] The production analysis module is used to obtain the raw material data corresponding to each historical production, the equipment process data of each production stage, and the production quality data from the yarn production record, and generate a raw material humidity production table.

[0071] The production setting module is used to obtain the raw material data in the current production. Based on the raw material humidity production table, analyze whether the raw material needs pre-treatment. If pre-treatment is required, first pre-treat the raw material, and then set the equipment control data for each production stage. If pre-treatment is not required, directly set the equipment control data for each production stage.

[0072] The production control module is used to obtain the operation data and production quality data of the equipment in each production stage when the equipment in each production stage is working, analyze the production status of each production stage, and based on the production status of each production stage, make a production response for the next production stage. At the same time, feedback the equipment operation data and production quality data of each production stage to the production analysis module.

[0073] The above content is only an example and explanation of the concept of the present invention. Those skilled in the art of this technology can make various modifications or supplements to the described specific embodiments or use similar methods to replace them, as long as they do not deviate from the concept of the invention or exceed the scope defined by this specification, they should all fall within the protection scope of the present invention.

Claims

1. A method for monitoring and regulating the production of textile yarns, characterized in that, It includes the following steps: S1. Obtain the raw material data corresponding to each historical production, the equipment process data of each production stage, and the production quality data from the yarn production records, and generate a raw material humidity production table; S2. Obtain the raw material data in the current production. Based on the raw material humidity production table, analyze whether the raw materials need pretreatment. If pretreatment is required, first perform pretreatment on the raw materials, and then set the equipment control data for each production stage. If pretreatment is not required, directly set the equipment control data for each production stage; S3. When the equipment in each production stage is working, obtain the operation data and production quality data of the equipment in each production stage, analyze the production status of each production stage, and based on the production status of each production stage, make a production response for the next production stage. At the same time, feedback the equipment operation data and production quality data of each production stage to S1.

2. A method for monitoring and regulating the production of textile yarns according to claim 1, characterized in that, The generation process of the raw material humidity production table is as follows: Obtain the raw material humidity combinations corresponding to each historical production from the raw material data corresponding to each historical production, obtain the equipment control data and operation data from the equipment process data of each production stage in each historical production. Take the equipment control data of each production stage corresponding to the same historical production as a target production, and take the equipment control data of each production stage in the target production as a production equipment control data combination, so as to obtain each production equipment control data combination, and the production quality data of each production stage in each historical production, and count the production quality data and operation data of each production stage when each production equipment control data combination processes each raw material humidity combination; Use the production quality data and operation data of each production stage when each production equipment control data combination processes each raw material humidity combination to analyze the production grade when each production equipment control data combination processes each raw material humidity combination, and thus construct a raw material humidity production table.

3. The textile yarn production monitoring and control method according to claim 2, characterized in that The analysis process of the production grade when each production equipment control data combination processes each raw material humidity combination is as follows: Obtain the production quality data thresholds and operation data thresholds at each production stage from the production control center, and use the production equipment control data combinations to process the production quality data at each production stage and the production quality data thresholds at each production stage when processing each raw material humidity combination, and calculate the production quality grade when the production equipment control data combinations process each raw material humidity combination, denoted as a1 xy , where x represents the number of the production equipment control data combination, y represents the number of the raw material humidity combination, and both x and y are positive integers. Among them, the production quality grades include Grade 1, Grade 2, and Grade 3; Using the control data of each production device to process the operating data at each production stage and the operating data threshold at each production stage when combining the humidity of each raw material, calculate the equipment operation level when the control data of each production device processes the humidity combination of each raw material, denoted as a2 xy , where the equipment operation level includes level 1, level 2, and level 3; When a1 is satisfied xy = level 3 ∧ a2 xy = level 3, the production level when the xth production equipment control data combines to process the yth raw material humidity combination is level 3; When a1 is satisfied xy = Level 2 ∧ a2 xy = Level 2, the production level is Level 2 when the xth production equipment control data combination processes the yth raw material humidity combination; When a1 xy = Level 1 ∨ a2 xy = Level 1, the production level when the xth production equipment control data combination processes the yth raw material humidity combination is Level 1.

4. A method for monitoring and regulating the production of textile yarns according to claim 1, characterized in that, The specific process of analyzing whether the raw materials need pretreatment is as follows: S21. Obtain the humidity of each raw material from the raw material humidity production table, and compare it with the humidity of each raw material in each raw material humidity combination in the raw material humidity production table. If the humidity of each raw material is different from the humidity of each raw material in each raw material humidity combination, it indicates that the raw materials need pretreatment; S22. If the humidity of each raw material is the same as the humidity of each raw material in a certain raw material humidity combination, take this raw material humidity combination as the current raw material humidity combination, and obtain the production grade of each production equipment control data combination processing the current raw material humidity combination from the raw material humidity production table. If the production grades of all production equipment control data combinations processing the current raw material humidity combination are less than level 2, it indicates that the raw materials need pretreatment. If there is at least one production equipment control data combination whose production grade for processing the current raw material humidity combination is greater than level 2, it indicates that the raw materials do not need pretreatment.

5. A method for monitoring and regulating the production of textile yarns according to claim 4, characterized in that, The specific process of performing pretreatment on the raw materials is as follows: Obtain each raw material humidity combination with a production level of 1 for the combined processing of production equipment control data from the raw material humidity production table as each marked raw material humidity combination. Obtain the humidity of each raw material in each marked raw material humidity combination, and select the maximum and minimum humidity values as the upper and lower humidity limit values of each raw material. Thus, using the humidity of each raw material, calculate the pretreatment method of the raw material, where the pretreatment method includes drying or humidifying and proportional mixing; Using the production levels of the combined processing of each raw material humidity combination by each production equipment control data in the raw material humidity production table, obtain each production equipment control data combination with a production level greater than 2 for processing each raw material humidity combination. Thus, calculate the priority coefficient of each raw material humidity combination, and select the raw material humidity combination with the largest priority coefficient as the target raw material humidity combination; When the pretreatment method of the raw material is drying or humidifying, use the pretreatment equipment to perform pretreatment on each equipment until the humidity of each raw material is the same as the humidity of each raw material in the target raw material humidity combination, then stop the pretreatment, and then use the target raw material humidity combination as the current raw material humidity combination; When the pretreatment method of the raw material is proportional mixing, obtain the raw material mixing records from the data storage cloud, obtain the historical humidity and mixing ratio data of each raw material when each historical proportional mixing target raw material humidity combination is obtained from the raw material mixing records, select each historical proportional mixing with the same corresponding historical humidity of each raw material as each reference mixing, obtain the mixing ratio data of each reference mixing, perform data clustering on the mixing ratio data of each reference mixing, and use the clustering result as the mixing ratio data of each raw material, and perform corresponding proportional mixing during pretreatment. After mixing is completed, use the target raw material humidity combination as the current raw material humidity combination.

6. A method for monitoring and regulating the production of textile yarns according to claim 5, characterized in that, The specific process of setting the equipment control data for each production stage is as follows: Extract the production levels of the combined processing of each production equipment control data for the current raw material humidity combination from the raw material humidity production table, and select each production equipment control data combination with a production level of 2 for processing the current raw material humidity combination as each preliminary selected production equipment control data combination; Obtain the equipment control data for each production stage in the current production line from the equipment control center, and compare it with the equipment control data for each production stage in each preliminary selected production equipment control data combination, analyze the regulation fluctuation value of each preliminary selected production equipment control data combination, and select the preliminary selected production equipment control data combination with the smallest regulation fluctuation value as the final selected production equipment control data combination. Use the equipment control data for each production stage in the final selected production equipment control data combination as the equipment control data for each production stage, and then perform the setting of the equipment control data for each production stage.

7. A method for monitoring and regulating the production of textile yarns according to claim 3, characterized in that, The specific process of analyzing the production status of each production stage is as follows: Obtain the production quality data threshold and the operation data threshold at each production stage from the production control center, and denote them as q1′ r and q2′ r , where r represents the number of each production stage, r is a positive integer, and denote the production quality data and the operation data at the production stage as q1 r and q2 r ; When q1 r ≥q1′ r ∧q2 r ≤q2′ r , it indicates that the production in the r-th production stage is normal; when q1 r <q1′ r ∧q2 r ≤q2′ r , it indicates that the production of the product in the r-th production stage is abnormal; when q1 r ≥q1′ r ∧q2 r >q2′ r , it indicates that the equipment in the r-th production stage is abnormal; when q1 < q1′ r ∧q2 r >q2′ r , it indicates that the entire production in the r-th production stage is abnormal.

8. A method for monitoring and regulating the production of textile yarns according to claim 7, characterized in that, Based on the production levels of each production stage, the production response for the next production stage is as follows: S31. When the r-th production stage is producing normally, output a type I production signal and keep the equipment control data of the (r + 1)-th production stage unchanged; S32. When the product production in the r-th production stage is abnormal, a second-class production signal is output, and the equipment production in the r-th production stage is stopped. At the same time, the staff conducts product abnormality investigation and isolation based on the second-class production signal, and then, according to the equipment control data of the r-th production stage, restarts the equipment production in the r-th production stage, and obtains the production quality data and operation data of the r-th production stage after restarting. Then, the equipment control data of the (r + 1)-th production stage is adjusted; S33. When the equipment in the r-th production stage is abnormal, a third-class production signal is output, and the equipment production in the r-th production stage is stopped, reminding the staff to perform equipment maintenance in this production stage. After the staff completes the equipment maintenance, the equipment production in this production stage is restarted according to the equipment control data of the r-th production stage; S34. When all the production in the r-th production stage is abnormal, a fourth-class production signal is output, and the equipment production in the r-th production stage is stopped. At the same time, the staff conducts product abnormality investigation, isolation, and equipment maintenance. After completion, the equipment production in the r-th production stage is restarted according to the equipment control data of the r-th production stage, and the adjustment is carried out according to the adjustment method of the equipment control data of the (r + 1)-th production stage in S32.

9. The monitoring and control method for textile yarn production according to claim 8, wherein, The specific process of adjusting the equipment control data of the (r + 1)-th production stage is as follows: Obtain the equipment control data, production quality data, and operation data of the r-th production stage and the (r + 1)-th production stage in each historical production with normal production from the yarn production record; Record the historical productions in which the equipment control data, production quality data, and operation data of the r-th production stage in each historical production are the same as those of the r-th production stage as each marked historical production. Obtain the equipment control data, production quality data, and operation data of the (r + 1)-th production stage in each marked historical production. At the same time, based on the raw material humidity production table and the yarn production record, obtain the production grade of the combined production of the production equipment control data corresponding to each marked historical production for the current raw material humidity combination, which is recorded as the production grade of each marked historical production. Calculate the value degree of each marked historical production, select the marked historical production grade with the largest value degree as the marked historical production, use the equipment control data of the (r + 1)-th production stage in the marked historical production as the equipment control data of the (r + 1)-th production stage, and at the same time obtain the equipment control data of each production stage after the (r + 1)-th production stage in the marked historical production from the yarn production record, and adjust each production stage after the (r + 1)-th production stage.

10. A textile yarn production monitoring and control system for implementing the textile yarn production monitoring and control method according to any one of claims 1-9, characterized in that, It includes: A production analysis module, which is used to obtain the raw material data, equipment process data of each production stage, and production quality data corresponding to each historical production from the yarn production record, and generate a raw material humidity production table; A production setting module, which is used to obtain raw material data during current production, analyze whether the raw materials need pretreatment based on the raw material humidity production table. If pretreatment is required, the raw materials are pretreated first, and then the equipment control data for each production stage is set. If pretreatment is not required, the equipment control data for each production stage is directly set; A production control module, which is used to obtain the operation data and production quality data of the equipment in each production stage when the equipment in each production stage is working, analyze the production status of each production stage, and make a production response for the next production stage based on the production status of each production stage. At the same time, the equipment operation data and production quality data of each production stage are fed back to the production analysis module.

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