Production line intelligent control method for spinning production of degradable environment-friendly yarn

Abstract

The invention relates to the technical field of yarn fabric production, in particular to a production line intelligent control method for degradable environment-friendly yarn spinning production, which comprises the steps of deploying environment sensing equipment in a workshop where a spinning production line is located, sensing environment information of the workshop where the spinning production line is located based on the environment sensing equipment, and creating a cloud database, a cloud database is applied to store the historically perceived environmental information of a workshop where the spinning production line is located; according to the invention, global and distributed monitoring and control are carried out on each spinning production line in the spinning workshop through a large amount of suitable deployment of the environment sensing equipment, the environment of the spinning workshop is effectively maintained to be stable for a long time, and the service life of the spinning workshop is prolonged. And safe production of spinning workshops is guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of textile production, and specifically relates to an intelligent control method for the production line of degradable environmental protection yarn spinning. Background Art

[0002] A spinning production line is a production system that processes fiber raw materials into yarns. It loosens and mixes fibers in the opening and cleaning process, combs them into single fibers through carding, further drafts and twists them into a preliminary yarn through drawing and roving, and finally further drafts and twists them into qualified yarns in the spinning process, achieving an efficient conversion from fibers to yarns.

[0003] The invention patent application with the application number 202311671074.3 discloses an intelligent control system for spinning production based on machine vision, including: a cotton web image acquisition module for acquiring cotton web detection images; a cotton web image feature extraction module for extracting texture features from the cotton web detection images to obtain a cotton web texture enhancement feature map; and a knife-cylinder gap determination module for determining the gap between the dust removal knife and the cylinder based on the cotton web texture enhancement feature map.

[0004] This application aims to solve the problem that: "In the carding process, the gap between the dust removal knife and the cylinder is mainly adjusted relying on the experience of operators to remove impurities. Usually, finer spinning requirements can set a smaller knife-cylinder gap to obtain a better carding effect. While coarser fibers and coarser spinning may require a larger knife-cylinder gap to avoid excessive cutting and over carding. However, due to the different impurity contents of cotton webs made of different batches, different varieties, and different processing technologies, relying on the experience of operators to adjust the gap between the dust removal knife and the cylinder often results in an unsatisfactory impurity removal effect or excessive impurity removal, leading to fiber damage."

[0005] However, the spinning process has relatively strict requirements on the production environment. Poor temperature, humidity, and air cleanliness can cause certain harm to the health of workers and easily lead to problems such as fiber brittle fracture, entanglement, and fiber static electricity accumulation.

[0006] Therefore, an intelligent control method for the production line of degradable environmental protection yarn spinning is proposed. Summary of the Invention

[0007] In view of the above-mentioned drawbacks of the prior art, the present invention provides an intelligent control method for the production line of degradable environmental protection yarn spinning, which solves the technical problems raised in the above background art.

[0008] To achieve the above objectives, the present invention is realized through the following technical solutions:

[0009] An intelligent control method for the production line of degradable environmental protection yarn spinning includes:

[0010] Deploy environmental perception devices inside the workshop where the spinning production line is located. Based on the environmental perception devices, perceive the environmental information of the workshop where the spinning production line is located, create a cloud database, and use the cloud database to store the historical environmental information of the workshop where the spinning production line is located; set the trigger threshold for maintenance equipment, obtain the latest stored environmental information in the cloud database, and based on the comparison between the environmental information and the trigger threshold for maintenance equipment, trigger the operation of the maintenance equipment; generate a visualization graph representing the change of environmental information based on the environmental information of the workshop where the spinning production line is located stored in the cloud database. After each operation of the spinning production line ends, traverse the visualization graph and analyze the fault risk of the spinning production line based on the visualization graph; set the determination threshold for the fault risk of the spinning production line, obtain the analysis result of the fault risk of the spinning production line, and based on the comparison between the analysis result and the spinning production line, determine whether there is a fault in the spinning production line; generate a management message for the spinning production line and output it.

[0011] Furthermore, the environmental perception devices deployed inside the workshop where the spinning production line is located include: temperature sensors, humidity sensors, air parameter sensors, and vibration sensors. Each group of environmental perception devices is integrated by a temperature sensor, a humidity sensor, an air parameter sensor, and a vibration sensor. When the environmental perception devices are deployed inside the workshop where the spinning production line is located, they are deployed around the ground of the spinning production line in the workshop and are distributed in a matrix on the inner walls and ceilings of the workshop.

[0012] Among them, when the cloud database stores the historical environmental information perceived by the environmental perception devices, the environmental information synchronization mark for performing the storage operation is marked with the deployment position coordinates of its source environmental perception device.

[0013] Furthermore, inside the workshop where the spinning production line is located, the adjacent spacing of the environmental perception devices deployed around the spinning production line is one-half of the adjacent spacing of the environmental perception devices deployed on the walls and ceilings of the workshop where the spinning production line is located. The adjacent spacing of the environmental perception devices deployed around the spinning production line is equal, and the adjacent spacing of the environmental perception devices deployed on the walls and ceilings of the workshop where the spinning production line is located is equal.

[0014] The adjacent spacing of the environmental perception devices deployed around the ground of the spinning production line in the workshop where the spinning production line is located follows:

[0015]

[0016] In the formula: D is the adjacent spacing of the deployment of environmental perception devices; L MAX 、W MAX are the maximum values of the length and width of the spinning production line in the spinning workshop; n is the total number of spinning production lines in the spinning workshop; L i 、W i 、H i are the length, width, and height of the i-th spinning production line in the spinning workshop; L0, W0, and H0 are the length, width, and height of the spinning workshop.

[0017] When calculating D based on Equation (1), take "≈" and round down the value of D. When calculating D based on Equation (2), take "=". When the D obtained based on Equation (1) holds in Equation (2), calculate D through Equation (2).

[0018] Furthermore, the maintenance equipment is installed in the workshop where the spinning production line is located. The maintenance equipment includes: air conditioners, humidifiers, honeycomb dust filtering units, and independent power control switches. There are several groups of independent power control switches, and each group of independent power control switches corresponds to each spinning production line in the spinning workshop one by one.

[0019] The triggering thresholds of the maintenance equipment correspond one by one to temperature, humidity, air dust content, and vibration signals. The temperature, humidity, air dust content, and vibration signals are sensed based on a temperature sensor, a humidity sensor, an air parameter sensor, and a vibration sensor respectively. The air conditioners, humidifiers, honeycomb dust filtering units, and independent power control switches in the maintenance equipment are applied to the triggering thresholds corresponding to temperature, humidity, air dust content, and vibration signals.

[0020] Furthermore, after the vibration signal is sensed based on the vibration sensor, a quantization operation is synchronously performed. Based on the comparison between the quantized vibration signal and the corresponding triggering threshold of the maintenance equipment, the independent power control switch is triggered to operate based on the comparison result.

[0021] The quantization operation of the vibration signal is as follows:

[0022]

[0023] In the formula: K is the kurtosis of the vibration signal; K norr is the preset safety kurtosis threshold of the vibration signal; m is the number of sampling points in the vibration signal; x j is the jth sampling value; is the sample mean; s is the sample standard deviation; g is the quantization value;

[0024] Among them, K norr is user-defined, and the time intervals between adjacent sampling points in the vibration signal are equal.

[0025] Furthermore, when the temperature in the environmental information meets the triggering threshold of the maintenance equipment, the humidity meets the triggering threshold of the maintenance equipment, and the air dust content meets the triggering threshold of the maintenance equipment, control the corresponding maintenance equipment to operate and coordinate the values of temperature, humidity, and air dust content to deviate from the triggering threshold of the maintenance equipment.

[0026] Among them, when the quantified vibration signal in the environmental information meets the maintenance equipment trigger threshold, the spinning production line closest to the sensing equipment to which the vibration signal belongs is controlled to be shut down by the independent power control switch, and the spinning workshop staff repairs the spinning production line. After the repair is completed, the independent power control switch controls the spinning production line to restart.

[0027] Furthermore, when performing the analysis operation on the fault risk of the spinning production line, the corresponding visualization images of the environmental perception devices deployed around the location of the spinning production line and the environmental perception devices deployed on the walls and ceilings of the spinning workshop are used as the analysis targets;

[0028] The visualization graph representing the change in environmental information is a line graph.

[0029] Furthermore, the fault risk analysis logic of the spinning production line is expressed as:

[0030]

[0031] In the formula: f C , f RH , f c , f g are a set of fault risk parameters represented by the visualization graph of the corresponding environmental perception devices; (C MAX - C MIN ) now is the difference between the maximum value and the minimum value in the latest visualization graph representing temperature; (C MAX - C MIN ) before is the difference between the maximum value and the minimum value in the previous updated visualization graph compared to the latest visualization graph representing temperature; (RH MAX - RH MIN ) now is the difference between the maximum value and the minimum value in the latest visualization graph representing humidity; (RH MAX - RH MIN ) before is the difference between the maximum value and the minimum value in the previous updated visualization graph compared to the latest visualization graph representing humidity; (c MAX - c MIN ) now is the difference between the maximum value and the minimum value in the latest visualization graph representing the dust content; (c MAX - c MIN ) before is the difference between the maximum value and the minimum value in the previous updated visualization graph compared to the latest visualization graph representing the dust content; (g MAX - g MIN ) now is the difference between the maximum value and the minimum value in the latest visualization graph representing the quantization value; (g MAX - gMIN ) before is the difference between the maximum value and the minimum value in the previous updated visualization graph compared to the visualization graph representing the quantization value in the latest update;

[0032] Then the fault risk parameter determined by the spinning production line based on a set of environmental perception devices is:

[0033] f = f C ·ω C + f RH ·ω RH + f c ·ω c + f g ·ω g ;

[0034] In the formula: ω C , ω RH , ω c , ω g are weights, ω C , ω RH , ω c , ω g are all greater than zero, and the sum of them is 1, and the values of each item are user-defined;

[0035] Then the fault risk value determined by the spinning production line based on its related environmental perception devices is:

[0036]

[0037] In the formula: u is the total number of environmental perception devices related to the spinning production line; f v is the fault risk parameter determined by the vth group of environmental perception devices.

[0038] Furthermore, the fault risk determination threshold of the spinning production line is user-defined. If F is user-defined and F is greater than or equal to the fault risk determination threshold of the spinning production line, it is determined that the spinning production line has a fault. Otherwise, it is determined that the spinning production line has no fault problem.

[0039] Furthermore, the spinning production line management message corresponds to each spinning production line in the spinning workshop. The spinning production line transmits through the wireless network from the spinning production line control panel output to the mobile computer device held by the user terminal, and the user terminal reads the spinning production line management message in the mobile computer;

[0040] Among them, the content of the spinning production line management message includes: the visualization graph representing the change of environmental information of the latest corresponding spinning production line, the results of each fault risk analysis and the determination results, and the operation records of the spinning production line configuration maintenance equipment.

[0041] Adopting the technical solution provided by the present invention, compared with the known public technology, it has the following beneficial effects:

[0042] The present invention provides an intelligent control method for the production line of degradable environmental protection yarn spinning. During the implementation of this method, through a large number of appropriate deployments of environmental perception devices, global and distributed monitoring and control are carried out on each spinning production line in the spinning workshop, effectively maintaining the long-term stability of the environment in the spinning workshop, ensuring the safe production of the spinning workshop. At the same time, visual graphs are generated based on the environmental information of the spinning workshop, bringing convenient data reading services to the management users of the spinning workshop. At the same time, fault prediction is carried out on each spinning production line in the spinning workshop in combination with the visual graphs, so as to facilitate the management users of the spinning workshop to perform maintenance on each spinning production line in the spinning workshop predictably. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] 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 drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0044] Figure 1 It is a schematic flow chart of an intelligent control method for the production line of degradable environmental protection yarn spinning. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0045] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts fall within the scope of protection of the present invention.

[0046] The following further describes the present invention with reference to the embodiments.

[0047] Embodiment:

[0048] An intelligent control method for the production line of degradable environmental protection yarn spinning in this embodiment, as Figure 1 shown, includes:

[0049] Deploy environmental perception devices inside the workshop where the spinning production line is located, create a cloud database based on the environmental information of the workshop where the spinning production line is located sensed by the environmental perception devices, and store the historical environmental information of the workshop where the spinning production line is located sensed by applying the cloud database;

[0050] The environmental perception devices deployed inside the workshop where the spinning production line is located include: temperature sensors, humidity sensors, air parameter sensors, and vibration sensors. Each group of environmental perception devices is integrated by a temperature sensor, a humidity sensor, an air parameter sensor, and a vibration sensor. When the environmental perception devices are deployed inside the workshop where the spinning production line is located, they are deployed around the ground of the spinning production line in the workshop and are distributed in a matrix on the inner walls and ceiling of the workshop;

[0051] Among them, when the cloud database stores the historical environmental information of the environmental perception devices, the environmental information synchronization mark for performing the storage operation is marked with the deployment position coordinates of its source environmental perception device;

[0052] Inside the workshop where the spinning production line is located, the adjacent spacing of the environmental perception devices deployed around the spinning production line is half of the adjacent spacing of the environmental perception devices deployed on the walls and ceiling of the workshop where the spinning production line is located. The adjacent spacing of the environmental perception devices deployed around the spinning production line is equal, and the adjacent spacing of the environmental perception devices deployed on the walls and ceiling of the workshop where the spinning production line is located is equal; The adjacent spacing of the environmental perception devices deployed around the ground of the spinning production line deployed in the workshop where the spinning production line is located follows:

[0053]

[0054] In the formula: D is the adjacent deployment spacing of the environmental perception devices; L MAX 、W MAX are the maximum values of the length and width of the spinning production line in the spinning workshop; n is the total number of spinning production lines in the spinning workshop; L i 、W i 、H i are the length, width, and height of the i-th spinning production line in the spinning workshop; L0, W0, and H0 are the length, width, and height of the spinning workshop;

[0055] Among them, when calculating D based on formula (1), take "≈" and round D down. When calculating D based on formula (2), take "=". When D obtained based on formula (1) holds in formula (2), calculate D through formula (2);

[0056] By designing the spacing of the environmental perception devices deployed in the spinning workshop through the above logical formula, it is ensured that the deployment of the environmental perception devices is balanced and reasonable, and the environmental information of the spinning workshop can be effectively and comprehensively perceived.

[0057] Set the maintenance device trigger threshold, obtain the latest stored environmental information in the cloud database, and trigger the operation of the maintenance device based on the comparison between the environmental information and the maintenance device trigger threshold;

[0058] The maintenance equipment is installed in the workshop where the spinning production line is located. The maintenance equipment includes: air conditioners, humidifiers, honeycomb dust filtering units, and independent power control switches. There are several groups of independent power control switches, and each group of independent power control switches corresponds one-to-one with each spinning production line in the spinning workshop;

[0059] The triggering thresholds of the maintenance equipment correspond one-to-one with temperature, humidity, air dust content, and vibration signals. The temperature, humidity, air dust content, and vibration signals are respectively sensed based on temperature sensors, humidity sensors, air parameter sensors, and vibration sensors. The air conditioners, humidifiers, honeycomb dust filtering units, and independent power control switches in the maintenance equipment are applied to the triggering thresholds corresponding to temperature, humidity, air dust content, and vibration signals;

[0060] After the vibration signal is sensed based on the vibration sensor, a quantization operation is synchronously performed. Based on the comparison between the quantized vibration signal and the corresponding triggering threshold of the maintenance equipment, the independent power control switch is triggered to operate based on the comparison result;

[0061] The quantization operation of the vibration signal is as follows:

[0062]

[0063] In the formula: K is the kurtosis of the vibration signal; K norr is the preset safety kurtosis threshold of the vibration signal; m is the number of sampling points in the vibration signal; x j is the jth sampling value; is the sample mean; s is the sample standard deviation; g is the quantization value;

[0064] Among them, K norr is customized by the user side, and the time intervals between adjacent sampling points in the vibration signal are equal;

[0065] Through the above logical formula, the logic of the vibration signal quantization is defined.

[0066] When the temperature in the environmental information meets the triggering threshold of the maintenance equipment, when the humidity meets the triggering threshold of the maintenance equipment, and when the air dust content meets the triggering threshold of the maintenance equipment, the corresponding maintenance equipment is controlled to operate to coordinate the temperature, humidity, and air dust content values to deviate from the triggering threshold of the maintenance equipment;

[0067] Among them, when the quantized vibration signal in the environmental information meets the triggering threshold of the maintenance equipment, the spinning production line closest to the sensing equipment to which the vibration signal belongs is controlled to be shut down by the independent power control switch, and the spinning workshop staff repairs the spinning production line. After the repair is completed, the independent power control switch controls the spinning production line to restart;

[0068] Generate a visualization graph representing the change in environmental information based on the environmental information of the workshop where the spinning production line is stored in the cloud database. After each spinning production line finishes running, traverse the visualization graph and analyze the fault risk of the spinning production line based on the visualization graph;

[0069] When performing the analysis operation on the fault risk of the spinning production line, use the visualization images corresponding to the environmental perception devices deployed around the location of the spinning production line and the environmental perception devices deployed on the walls and ceilings of the spinning workshop as the analysis targets;

[0070] The visualization graph representing the change in environmental information is a line graph;

[0071] Set the fault risk determination threshold for the spinning production line, obtain the analysis result of the fault risk of the spinning production line, and compare it with the spinning production line based on the analysis result to determine whether there is a fault in the spinning production line;

[0072] The fault risk analysis logic of the spinning production line is expressed as:

[0073]

[0074] In the formula: f C , f RH , f c , f g are the fault risk parameters represented by the visualization graph corresponding to a group of environmental perception devices; (C MAX -C MIN ) now is the difference between the maximum value and the minimum value in the latest visualization graph representing temperature; (C MAX -C MIN ) before is the difference between the maximum value and the minimum value in the previous updated visualization graph compared to the latest visualization graph representing temperature; (RH MAX -RH MIN ) now is the difference between the maximum value and the minimum value in the latest visualization graph representing humidity; (RH MAX -RH MIN ) before is the difference between the maximum value and the minimum value in the previous updated visualization graph compared to the latest visualization graph representing humidity; (c MAX -c MIN ) now is the difference between the maximum value and the minimum value in the latest visualization graph representing dust content; (c MAX -c MIN ) before is the difference between the maximum value and the minimum value in the previous updated visualization graph compared to the latest visualization graph representing dust content; (g MAX -g MIN ) nowis the difference between the maximum and minimum values in the visualization graph representing the latest quantization value; (g MAX -g MIN ) before is the difference between the maximum and minimum values in the previous updated visualization graph compared to the visualization graph representing the latest quantization value;

[0075] Then the fault risk parameter determined by the spinning production line based on a group of environmental perception devices is:

[0076] f = f C ·ω C + f RH ·ω RH + f c ·ω c + f g ·ω g ;

[0077] Where: ω C , ω RH , ω c , ω g are weights, ω C , ω RH , ω c , ω g are all greater than zero, and the sum of them is 1, and the values of each item are user-defined;

[0078] Then the fault risk value determined by the spinning production line based on its related environmental perception devices is:

[0079]

[0080] Where: u is the total number of environmental perception devices related to the spinning production line; f v is the fault risk parameter determined by the vth group of environmental perception devices;

[0081] The fault risk determination threshold of the spinning production line is user-defined, F is user-defined, and if F is greater than or equal to the fault risk determination threshold of the spinning production line, it is determined that the spinning production line has a fault, otherwise, it is determined that the spinning production line has no fault problem; through the above logical formula calculation, the fault risk of the environmental perception devices is represented in a digital form, providing support for the final prediction result of the spinning production line fault.

[0082] Generate a management message for the spinning production line and output it.

[0083] In this embodiment, through the execution of the method in the above embodiment, an environmental control system that can comprehensively and specifically serve each spinning production line is provided for the spinning workshop, effectively ensuring the stable operation of each spinning production line in the spinning workshop and enabling the long-term and healthy execution of spinning production work, and reducing the manual management cost of the spinning workshop to a certain extent.

[0084] As Figure 1 shown, the spinning line management message corresponds to each spinning line in the spinning workshop one by one. The spinning line is transmitted from the spinning line control panel output to the mobile computer device held by the user terminal through the wireless network, and the user terminal reads the spinning line management message in the mobile computer;

[0085] Among them, the content of the spinning line management message includes: a visual graph representing the change of environmental information of the latest corresponding spinning line, the analysis results and determination results of each fault risk, and the operation record of the spinning line configuration maintenance equipment.

[0086] Through the above settings, it provides further output logic setting and message content limitation for the method in this embodiment when executing the message output result.

[0087] In summary, during the execution of the method in the above embodiment, through the large-scale and appropriate deployment of environmental perception devices, the global and distributed monitoring and control of each spinning line in the spinning workshop are carried out, effectively maintaining the long-term stability of the environment in the spinning workshop, ensuring the safe production of the spinning workshop. At the same time, a visual graph is generated based on the environmental information of the spinning workshop, bringing convenient data reading services to the management users of the spinning workshop. At the same time, the fault of each spinning line in the spinning workshop is predicted in combination with the visual graph, so as to facilitate the management users of the spinning workshop to maintain each spinning line in the spinning workshop predictably.

[0088] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements will not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. An intelligent control method for the production line of degradable environmental protection yarn spinning, characterized in that, Including: Deploy environmental perception devices inside the workshop where the spinning production line is located, sense the environmental information of the workshop where the spinning production line is located based on the environmental perception devices, create a cloud database, and store the historical environmental information of the workshop where the spinning production line is located perceived by using the cloud database; Set the maintenance equipment trigger threshold, obtain the latest stored environmental information in the cloud database, and trigger the operation of the maintenance equipment based on the comparison between the environmental information and the maintenance equipment trigger threshold; Generate a visualization graph representing the change of environmental information based on the environmental information of the workshop where the spinning production line is located stored in the cloud database. After each operation of the spinning production line ends, traverse the visualization graph and analyze the fault risk of the spinning production line based on the visualization graph; Set the spinning production line fault risk determination threshold, obtain the spinning production line fault risk analysis result, and determine whether there is a fault in the spinning production line based on the comparison between the analysis result and the spinning production line; Generate a spinning production line management message and output it.

2. The intelligent control method for the production line of degrading environmentally friendly yarn spinning according to claim 1, wherein, The environmental perception devices deployed inside the workshop where the spinning production line is located include: temperature sensors, humidity sensors, air parameter sensors, vibration sensors. Each group of environmental perception devices is integrated by a temperature sensor, a humidity sensor, an air parameter sensor, and a vibration sensor. When the environmental perception devices are deployed inside the workshop where the spinning production line is located, they are deployed around the ground of the spinning production line in the workshop and are distributed in a matrix on the inner walls and the top surface of the workshop; Among them, when the cloud database stores the historical environmental information perceived by the environmental perception devices, the environmental information for which the storage operation is executed is synchronously marked with the deployment position coordinates of its source environmental perception device.

3. The intelligent control method for the production line of degrading environmental protection yarn spinning according to claim 1, characterized in that, Inside the workshop where the spinning production line is located, the adjacent spacing of the environmental perception devices deployed around the spinning production line is one-half of the adjacent spacing of the environmental perception devices deployed on the walls and the top surface of the workshop where the spinning production line is located. The adjacent spacing of the environmental perception devices deployed around the spinning production line is equal, and the adjacent spacing of the environmental perception devices deployed on the walls and the top surface of the workshop where the spinning production line is located is equal; The adjacent spacing of the environmental perception devices deployed around the ground where the spinning production line is deployed in the workshop where the spinning production line is located follows: Where: D is the adjacent spacing of the deployment of environmental perception devices; L MAX , W MAX are the maximum values of the length and width of the spinning production line in the spinning workshop; n is the total number of spinning production lines in the spinning workshop; L i , W i , H i are the length, width and height of the i-th spinning production line in the spinning workshop; L0, W0, H0 are the length, width and height of the spinning workshop; Among them, when calculating D based on formula (1), take "≈", and round down the value of D. When calculating D based on formula (2), take "=". When D obtained based on formula (1) holds in formula (2), calculate D through formula (2).

4. The intelligent control method for a production line of producing degradable environmental protection yarn by spinning, as claimed in claim 1, wherein, The maintenance equipment is installed inside the workshop where the spinning production line is located. The maintenance equipment includes: air conditioners, humidifiers, honeycomb dust filtration units, and independent power control switches. There are several groups of the independent power control switches, and several groups of the independent power control switches correspond to each spinning production line in the spinning workshop one by one; The maintenance equipment trigger threshold corresponds to temperature, humidity, dust content in the air, and vibration signals respectively. The temperature, humidity, dust content in the air, and vibration signals are respectively sensed based on the temperature sensors, humidity sensors, air parameter sensors, and vibration sensors. The air conditioners, humidifiers, honeycomb dust filtration units, and independent power control switches in the maintenance equipment are applied to the trigger thresholds corresponding to the temperature, humidity, dust content in the air, and vibration signals.

5. The intelligent control method for a production line of degrading environmental protection yarn spinning according to claim 1, characterized in that, After the vibration signal is sensed by the vibration sensor, a quantization operation is synchronously performed. Based on the comparison between the quantized vibration signal and the corresponding maintenance equipment trigger threshold, the independent power control switch is triggered to operate based on the comparison result. The quantization operation of the vibration signal is as follows: Where: K is the kurtosis of the vibration signal; K norr is the preset safety kurtosis threshold of the vibration signal; m is the number of sampling points in the vibration signal; x j is the j-th sampling value; is the sample mean; s is the sample standard deviation; g is the quantization value; Among them, K norr is defined by the client, and the time intervals between adjacent sampling points in the vibration signal are equal.

6. The intelligent control method for the production line of a degradable environmental protection yarn spinning according to claim 1, wherein When the temperature in the environmental information meets the maintenance equipment trigger threshold, the humidity meets the maintenance equipment trigger threshold, and the air dust content meets the maintenance equipment trigger threshold, the corresponding maintenance equipment is controlled to operate, and the values of temperature, humidity, and air dust content are coordinated to deviate from the maintenance equipment trigger threshold. Among them, when the quantized vibration signal in the environmental information meets the maintenance equipment trigger threshold, the spinning production line closest to the sensing device to which the vibration signal belongs is controlled to shut down by the independent power control switch, and the spinning production line is repaired by the staff in the spinning workshop. After the repair is completed, the independent power control switch controls the spinning production line to restart.

7. An intelligent control method for a production line of degrading environmental protection yarn spinning according to claim 1, characterized in that When performing the analysis operation on the fault risk of the spinning production line, the corresponding visualization images of the environmental perception devices deployed around the location of the spinning production line and the environmental perception devices deployed on the walls and ceilings of the spinning workshop are used as the analysis target. The visualization graph representing the change in environmental information is a line graph.

8. The intelligent control method for the production line of degrading environmentally friendly yarn spinning according to claim 1, characterized in that The fault risk analysis logic of the spinning production line is expressed as: where: f C 、f RH 、f c 、f g are the fault risk parameters corresponding to the visual graphical representations of a group of environmental perception devices; (C MAX -C MIN ) now is the difference between the maximum and minimum values in the visual graph representing the latest temperature; (C MAX -C MIN ) before is the difference between the maximum and minimum values in the visual graph of the previous update compared to the visual graph representing the latest temperature; (RH MAX -RH MIN ( now is the difference between the maximum and minimum values in the visual graph representing the latest humidity; )RH MAX -RH MIN ) before is the difference between the maximum and minimum values in the visual graph of the previous update compared to the visual graph representing the latest humidity; (c MAX -c MIN ) now is the difference between the maximum and minimum values in the visual graph representing the latest dust content; (c MAX -c MIN ) before is the difference between the maximum and minimum values in the visual graph of the previous update compared to the visual graph representing the latest dust content; (g MAX -g MIN ) now is the difference between the maximum and minimum values in the visual graph representing the latest quantization value; (g MAX -g MIN ) before is the difference between the maximum and minimum values in the visual graph of the previous update compared to the visual graph representing the latest quantization value; Then the fault risk parameters determined by the spinning production line based on a group of environmental perception devices are: f = f C · ω C + f RH · ω RH + f c · ω c + f g · ω g ; where: ω C , ω RH , ω c , ω g are weights, ω C , ω RH , ω c , ω g are all greater than zero, and their sum is 1, and the values of each item are user-defined; Then the fault risk value determined by the spinning production line based on its related environmental perception devices is: Where: u is the total number of environment perception devices related to the spinning production line; f v is the failure risk parameter determined for the v-th group of environment perception devices.

9. The intelligent control method for a production line of producing degradable environmental protection yarn by spinning, as claimed in claim 8, wherein The fault risk determination threshold of the spinning production line is user-defined. F is user-defined. If F is greater than or equal to the fault risk determination threshold of the spinning production line, it is determined that the spinning production line has a fault. Otherwise, it is determined that the spinning production line has no fault problem.

10. The intelligent control method for a production line of degradable environmental protection yarn spinning according to claim 1, characterized in that, The spinning production line management message corresponds to each spinning production line in the spinning workshop. The spinning production line is transmitted from the spinning production line control panel through the wireless network to the mobile computer device held by the user terminal, and the user terminal reads the spinning production line management message in the mobile computer. Among them, the content of the spinning production line management message includes: the visualization graph representing the change in environmental information of the latest corresponding spinning production line, the analysis results and determination results of each fault risk, and the operation record of the configuration maintenance equipment of the spinning production line.

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