Spinning processing production line fault monitoring system and method

Abstract

The invention discloses a spinning processing production line fault monitoring system and method, and relates to the technical field of spinning production line monitoring, the spinning processing production line fault monitoring system comprises a raw material detection module, a production management module, a production fault monitoring module, an inspection module and an execution terminal.The raw material safety is ensured by analyzing and monitoring various types of spinning raw materials; the method comprises the following steps: analyzing each production device, matching the appropriate production device for each type of spinning, thereby ensuring the production quality and the production speed of the spinning, monitoring the working parameters of each production device and the production process of the finished spinning product in the production process, avoiding the quality problem caused by the deviation of the working parameters of the devices, and improving the production efficiency. And finally, quality detection is carried out on various types of finished spinning products which are produced, quality classification is carried out on the various types of finished spinning products, a data basis can be provided for subsequent monitoring, and long-term development of the industry is also facilitated.

Description

Technical Field

[0001] The present application relates to the technical field of spinning production line monitoring, and in particular to a spinning processing production line fault monitoring system and method. Background Art

[0002] With the continuous development of society and economy, users have more and more demands for spinning. Fault monitoring of spinning production lines is a key link to ensure production efficiency and product quality. Therefore, this application proposes a spinning processing production line fault monitoring system and method.

[0003] Existing technology, such as the invention application patent with announcement number: CN118821061A, discloses an intelligent detection and analysis system for spinning and plucking fault risks, which includes a data acquisition module, a server, a cotton nep state analysis module, a disease state analysis module, a bag discharge state analysis module, an impact factor analysis module, an equipment operation analysis module, a fault risk analysis module and a display terminal; by analyzing and processing the cotton nep state information, disease state information and bag discharge state information in the spinning and plucking process, the corresponding impact index is obtained, and the comprehensive impact index is analyzed to obtain the impact factor coefficient, and at the same time, the equipment operation status information is monitored and analyzed, and then combined with the impact factor coefficient, the equipment operation status is evaluated, the failure risk of the spinning and plucking equipment is accurately determined, and the failure risk level is given, thereby enabling the enterprise to take preventive measures in a timely manner to ensure the continuous and stable operation of the production line and thus improve production efficiency and product quality.

[0004] Existing technologies such as the invention application patent with announcement number: CN119721644A discloses a textile yarn production monitoring and control method, which involves the field of intelligent management and control of production lines, including: based on predetermined yarn characteristics and predetermined spinning parameters, performing difference feature analysis on multiple similar devices in multiple equipment domains, and determining multiple high-difference equipment domains; according to predetermined yarn characteristics, performing fault probability trend analysis on multiple high-difference equipment domains, obtaining multiple probability trend coefficient sets to compensate for multiple benchmark failure rates, and obtaining multiple adaptive failure rate sets; configuring multiple adaptive monitoring parameter sets according to multiple adaptive failure rate sets, and performing production monitoring and control on multiple high-difference equipment domains. This can solve the technical problem that traditional methods lack dynamic adjustment capabilities and cannot set up corresponding monitoring and control schemes according to the actual status of the equipment and the type of yarn products when monitoring resources are limited, resulting in poor monitoring and control effects. It can optimize the allocation of monitoring resources and significantly improve the monitoring and control effects of yarn production.

[0005] Regarding the above scheme, there are the following technical problems: the current technology mainly analyzes and processes the cotton nep information in the spinning and cotton picking process, and at the same time monitors and analyzes the equipment operation status information, and then combines the analysis results of the cotton nep information and the analysis results of the equipment operation status information to evaluate the equipment operation status, or monitor the real-time status and regulation of the equipment. It does not analyze the cotton nep raw material information and equipment information before production. The main purpose of fault monitoring is to improve production quality and production efficiency. When the quality of the production raw materials or production equipment used does not meet the standards, only monitoring the production process cannot improve production efficiency and production quality. Summary of the Invention

[0006] The purpose of this application is to provide a spinning processing production line fault monitoring system and method to solve the problems existing in the background technology.

[0007] In order to solve the above technical problems, the present application adopts the following technical solution: In the first aspect, the present application provides a spinning processing production line fault monitoring system, including: a raw material detection module: used to obtain the production plan corresponding to the current production workshop from the production plan table, and then obtain the types of spinning raw materials and the quantity of each type of spinning raw materials from the production plan, and then perform quality inspection on each type of spinning raw materials.

[0008] Production management module: used to obtain the production information of each production equipment in the production workshop, and then analyze and obtain the production behavior evaluation coefficient of each production equipment for each type of spinning, so as to obtain each production equipment for each type of spinning.

[0009] Production fault monitoring module: It is used to monitor the faults of various production equipment during the spinning production process, monitor the production status of various types of spinning, and determine whether to start the fault repair mechanism based on the fault conditions of each production equipment and the production status of each type of spinning.

[0010] Inspection module: used to perform quality inspection on various types of spun yarns produced and classify them according to the quality inspection results.

[0011] Execution terminal: used to display the analysis results of the raw material detection module, production management module, production fault monitoring module and inspection module.

[0012] In a second aspect, the present application provides a spinning processing production line fault monitoring method, including: step one, obtaining the production plan corresponding to the current production workshop from the production plan table, and then obtaining each type of spinning raw material and the quantity of each type of spinning raw material from the production plan, and then performing quality inspection on each type of spinning raw material.

[0013] Step 2: Obtain the production information of each production equipment in the production workshop, and then analyze and obtain the production behavior evaluation coefficient of each production equipment for each type of spinning, thereby obtaining each production equipment for each type of spinning.

[0014] Step 3: During the spinning production process, each production equipment is monitored for faults, and the production status of each type of spinning is monitored at the same time. It is determined whether to start the fault repair mechanism based on the fault conditions of each production equipment and the production status of each type of spinning.

[0015] Step 4: Perform quality inspection on the various types of spun yarn produced, and classify the various types of spun yarn according to the quality inspection results.

[0016] Step 5: Display the analysis results of the raw material detection module, production management module, production fault monitoring module and inspection.

[0017] The beneficial effect of the present application is that the present application analyzes the quality of each spinning raw material, analyzes the production information of each production equipment, and then matches each production equipment with each spinning type to obtain suitable production equipment, monitors each production equipment and spinning products during the production process, and performs quality inspection on each type of spinning products after spinning is completed, thereby classifying each type of spinning products, thereby completing the monitoring of the entire process of each type of spinning production, solving the problem that the current technology only monitors the production process, and at the same time matching the production equipment for spinning greatly improves the production efficiency and production quality of each type of spinning, monitors the equipment parameters and spinning products, and greatly reduces the raw material cost loss and equipment damage, which is beneficial to extending the service life of each production equipment and the long-term development of the enterprise. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0019] Figure 1 This is a schematic diagram of the system structure connection for this application.

[0020] Figure 2 This is a flowchart of the steps for implementing the application method. DETAILED DESCRIPTION

[0021] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0022] Reference Figure 1 As shown, the present application provides a spinning processing production line fault monitoring system in the first aspect, including the following modules: a raw material detection module: used to obtain the production plan corresponding to the current production workshop from the production plan table, and then obtain the types of spinning raw materials and the quantity of each type of spinning raw materials from the production plan, and then perform quality inspection on each type of spinning raw materials.

[0023] It should be noted that the production plan includes the types of spinning raw materials, the quantity of each type of spinning raw materials, the production cycle, etc.

[0024] It should be noted that the types of spinning raw materials include natural fiber raw materials and chemical fiber raw materials, wherein natural fiber raw materials include plant fibers and animal fibers, etc., and chemical fiber raw materials include cellulose fibers and synthetic fibers, etc.

[0025] In a specific example, the quality inspection of each type of spinning raw material is carried out as follows: the quantity of each type of spinning raw material is compared to obtain the ratio of each type of spinning raw material, each type of spinning raw material is sampled according to the ratio of each type of spinning raw material, and the spinning raw materials of the same type obtained by sampling are mixed and evenly divided into two parts to obtain each sample of each type of spinning raw material, and each sample of each type of spinning raw material is subjected to physical property inspection and chemical property inspection to obtain the physical property evaluation coefficient aχ of each type of spinning raw material. i and chemical performance evaluation coefficient bχ i , where i is the number of each spinning type and i is a positive integer.

[0026] Substitute the physical property evaluation coefficients and chemical property evaluation coefficients of various types of spinning raw materials into the spinning raw material quality evaluation model, and the spinning raw material quality evaluation model expression is:

[0027] Output the quality characteristic value χ of the spinning raw material type i i , where ζ′ and ζ″ represent the set physical property evaluation coefficient threshold and chemical property evaluation coefficient threshold of each type of spinning raw materials, respectively.

[0028] If the quality characteristic value of a certain type of spinning raw material is 1, the spinning raw material of this type stored in the warehouse will be directly used for spinning production. If the quality characteristic value of a certain type of spinning raw material is -1, it is necessary to re-purchase the spinning raw material of this type and use the newly purchased spinning of this type for spinning production.

[0029] It should be noted that sampling of various types of spinning raw materials is carried out according to the ratio of each type of spinning raw materials. For example, if the ratio of plant fiber: animal fiber: synthetic fiber is 3:1:2, then 6 parts of textile fiber, 2 parts of animal fiber and 4 parts of synthetic fiber can be taken, or 3 parts of textile fiber, 1 part of animal fiber and 2 parts of synthetic fiber can be taken. The specific decision is made by the relevant staff.

[0030] It should be noted that the physical property evaluation coefficient thresholds and chemical property evaluation coefficient thresholds of the various types of spinning raw materials are set by the relevant staff themselves. For example, the average physical quality evaluation coefficient and average chemical quality evaluation coefficient of each type of spinning raw materials used in the historical production of qualified spinning products can be used as the physical property evaluation coefficient thresholds and chemical property evaluation coefficient thresholds corresponding to each type of spinning. No specific restrictions are made here.

[0031] In a specific example, when analyzing the physical property evaluation coefficients and chemical property evaluation coefficients of various types of spinning raw materials, the specific analysis process is as follows: use HVI to measure the average length and linear density of various types of fiber raw material samples, and then use a fiber strength meter to measure the strength of various types of fiber raw material samples. The fiber length, linear density and strength of each type of sample are recorded as L i 、R i and G i , according to the calculation formula: Get the physical quality evaluation coefficient aχ of the spinning raw material numbered type i i , where L′, R′ and G′ represent the fiber length threshold, linear density threshold and strength threshold set for each type of spinning raw material, respectively.

[0032] The thermal stability of each type of fiber raw material sample was measured by thermogravimetric analysis, and the impurity content of each type of fiber raw material sample was measured using an impurity analyzer. The thermal stability and impurity content of each type of fiber raw material sample were recorded as F i and D i , according to the calculation formula: Calculate the chemical quality evaluation coefficient bχ of the spinning raw material numbered type i i , where F i ′ and D i ' represents the thermal stability threshold and impurity content threshold of each type of spinning raw material.

[0033] It should be noted that the fiber length threshold, linear density threshold, strength threshold, thermal stability threshold and impurity content threshold of each type of spinning raw material are all obtained by referring to the spinning raw material standard table.

[0034] Production management module: used to obtain the production information of each production equipment in the production workshop, and then analyze and obtain the production behavior evaluation coefficient of each production equipment for each type of spinning, so as to obtain each production equipment for each type of spinning.

[0035] It should be noted that spinning types include pure cotton spinning and chemical fiber spinning.

[0036] In a specific example, the production information includes the types of yarn produced, the production qualification rate of each type of yarn, and the production efficiency.

[0037] In a specific example, the production behavior evaluation coefficient of each production equipment for each type of spinning is obtained by analyzing the production information of each production equipment, and the production qualification rate and production efficiency of each type of spinning produced by each production equipment are obtained based on the production information of each production equipment, and the production demand of each type of spinning is obtained from the production plan, and the production demand of each type of spinning, the production qualification rate and production efficiency of each type of spinning produced by each production equipment are respectively recorded as θ j ,η h→j and Where j is the number of each spinning type, h is the number of each production equipment, and the production demand of each type of spinning, the production qualification rate and production efficiency of each type of spinning produced by each production equipment are substituted into the production equipment matching model. According to the production equipment matching model expression: Output the production behavior evaluation coefficient Q of the h-th production equipment corresponding to the j-th type of spinning h→j , where J represents the total number of spinning types, η′ j and They respectively represent the set standard values ​​of the qualified rate and production efficiency for each type of spinning.

[0038] The production behavior evaluation coefficients of each production equipment for each type of spinning are sorted from large to small, and the production equipment for each type of spinning is obtained in sequence according to the sorting results.

[0039] It should be noted that the standard values ​​of the qualified rate and production efficiency of each type of spinning are the average qualified rate and average production efficiency of each production equipment for each type of spinning.

[0040] Production fault monitoring module: It is used to monitor the faults of various production equipment during the spinning production process, monitor the production status of various types of spinning, and determine whether to start the fault repair mechanism based on the fault conditions of each production equipment and the production status of each type of spinning.

[0041] In a specific example, the fault monitoring of each production equipment is performed, and the specific monitoring process is as follows: each monitoring time point is set according to a preset time interval, and the working parameters of each production equipment are read through the parameter monitoring panel of each production equipment at each monitoring time point. At the same time, the standard value of each working parameter and each allowable offset value of each production equipment are read from the technical manual of each production equipment. By comparing the working parameters of each production equipment read at each monitoring time point with the corresponding standard value of each working parameter, the actual error of each working parameter of each production equipment at each monitoring time point is obtained, and the actual error of the working parameters of each production equipment at each monitoring time point is compared with the corresponding allowable offset values, thereby obtaining the fault monitoring result of each production equipment at each monitoring time point.

[0042] At the same time, high-definition cameras installed in the current workshop are used to collect images of yarns of various types at various collection time points, and the characteristic parameters of various types of spinning are obtained through image processing technology. The threshold values ​​of various characteristic parameters of various types of spinning are obtained from the spinning quality standard table, and the characteristic parameters of various types of spinning are compared with the corresponding characteristic parameter thresholds to obtain the production status of various types of spinning at each monitoring time point.

[0043] In a specific example, the fault repair mechanism is judged based on the fault conditions of each production equipment and the production status of each type of spinning. The specific process is as follows: the actual error of the working parameters of each production equipment at each monitoring time point is compared with the corresponding allowable offset values. When the working parameters of a production equipment at each monitoring time point are faulty, the fault repair mechanism needs to be started, and the pre-written algorithm of each production equipment is enabled to perform parameter correction on the faulty production equipment. When the actual error of the working parameters of the corrected production equipment still exceeds the corresponding allowable offset value, an alarm needs to be issued to remind the relevant staff.

[0044] The characteristic parameters of each type of spinning are compared with the corresponding characteristic parameter thresholds. When a characteristic parameter of a certain type of spinning fails, the assistance of the corresponding production equipment is immediately stopped and an alarm is issued to remind relevant staff.

[0045] It should be noted that the characteristic parameters include defect distribution rate, hairiness number and yarn tension, etc.

[0046] Inspection module: used to perform quality inspection on various types of spun yarns produced and classify them according to the quality inspection results.

[0047] In a specific example, the quality inspection of the completed yarn is carried out, and the specific process is as follows: random sampling of various types of completed yarn is carried out, and the sampled yarns of the same type are mixed, and the mixed yarns of various types are evenly divided into two parts, and performance inspection and appearance inspection are carried out respectively.

[0048] For performance testing, HVI was used to obtain the linear density of each type of spinning sample, and a fiber strength measuring instrument was used to measure the strength of each type of spinning sample.

[0049] For appearance inspection, under standard light distance, the number of defects and hairiness on the surface of each type of spinning sample is obtained through microscope observation, and then the defect distribution rate of each type of spinning sample is obtained by combining the area of ​​each type of spinning sample.

[0050] The linear density, strength and defect release rate of each type of spinning sample are normalized and then input into the spinning finished product quality evaluation model. According to the spinning finished product quality evaluation model expression: w =Y w *ρ1+Z w *ρ2+V w *ρ3 outputs the quality assessment coefficient κ of each type of spinning product w , where w represents the number of each type of spinning product, w is a positive integer, Y w 、Z w and V w They represent the linear density, strength and defect release rate of each type of spun yarn respectively, and ρ1, ρ2 and ρ3 represent the weight factors corresponding to the linear density, strength and defect release rate of the spun yarn respectively.

[0051] It should be noted that the weight factors corresponding to the linear density, strength and defect release rate of the finished spinning product are obtained by analytic hierarchy process analysis, wherein the analytic hierarchy process is an existing technology and will not be described in detail.

[0052] In a specific example, the classification of various types of spinning is carried out according to the quality inspection results, and the specific process is as follows: the quality evaluation coefficients of the finished products of various types of spinning are compared with the set first-class spinning quality threshold and the second-class spinning quality threshold. When the quality evaluation coefficient of a certain type of spinning product is greater than the set first-class spinning quality threshold, the finished product of this type of spinning is recorded as first-class spinning. If the quality evaluation coefficient of a certain type of spinning product is less than the set first-class spinning quality threshold but greater than or equal to the second-class spinning quality threshold, the finished product of this type of spinning is recorded as second-class spinning. When the quality evaluation coefficient of a certain type of spinning product is less than the set second-class spinning quality evaluation coefficient, the spinning of this type is recorded as unqualified spinning.

[0053] It should be noted that the set class-one spinning quality threshold and class-two spinning quality threshold are obtained by relevant staff by referring to relevant spinning production instruction documents, and will not be repeated here.

[0054] Execution terminal: used to display the analysis results of the raw material detection module, production management module, production fault monitoring module and inspection module.

[0055] Reference Figure 2 As shown, the present application provides a spinning processing production line fault monitoring method in the second aspect, including the following steps: Step 1, obtain the production plan corresponding to the current production workshop from the production plan table, and then obtain the types of spinning raw materials and the quantity of each type of spinning raw materials from the production plan, and then perform quality inspection on each type of spinning raw materials.

[0056] Step 2: Obtain the production information of each production equipment in the production workshop, and then analyze and obtain the production behavior evaluation coefficient of each production equipment for each type of spinning, thereby obtaining each production equipment for each type of spinning.

[0057] Step 3: During the spinning production process, each production equipment is monitored for faults, and the production status of each type of spinning is monitored at the same time. It is determined whether to start the fault repair mechanism based on the fault conditions of each production equipment and the production status of each type of spinning.

[0058] Step 4: Perform quality inspection on the various types of spun yarn produced, and classify the various types of spun yarn according to the quality inspection results.

[0059] Step 5: Display the analysis results of the raw material detection module, production management module, production fault monitoring module and inspection and packaging module.

[0060] The above content is merely an example and explanation of the concept of the present application. Technicians in this technical field may make various modifications or additions to the described specific embodiments or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined in this application, they should all fall within the scope of protection of this application.

Claims

1. A spinning production line fault monitoring system, characterized in that: include: Raw material detection module: used to obtain the production plan corresponding to the current production workshop from the production plan table, and then obtain the types and quantities of each type of spinning raw materials from the production plan, and then perform quality inspection on each type of spinning raw materials; Production management module: used to obtain the production information of each production equipment in the production workshop, and then analyze and obtain the production behavior evaluation coefficient of each production equipment for each type of spinning, so as to obtain the production equipment for each type of spinning; Production fault monitoring module: used to monitor the faults of various production equipment during the spinning production process, monitor the production status of various types of spinning, and determine whether to start the fault repair mechanism based on the fault conditions of each production equipment and the production status of each type of spinning; Inspection module: used to conduct quality inspection on various types of spun yarns produced and classify them according to the quality inspection results; Execution terminal: used to display the analysis results of the raw material detection module, production management module, production fault monitoring module and inspection and packaging module.

2. A spinning production line fault monitoring system according to claim 1, characterized in that: The specific process of quality inspection of various types of spinning raw materials is as follows: The quantities of various types of spinning raw materials are compared to obtain the ratios of various types of spinning raw materials. According to the ratios of various types of spinning raw materials, various types of spinning raw materials are sampled. The spinning raw materials of the same type obtained by sampling are mixed and evenly divided into two parts to obtain samples of various types of spinning raw materials. Physical and chemical property tests are performed on the samples of various types of spinning raw materials to obtain the physical property evaluation coefficients aχ of various types of spinning raw materials. i and chemical performance evaluation coefficient bχ i , where i is the number of each spinning type, and i is a positive integer; Substitute the physical property evaluation coefficients and chemical property evaluation coefficients of various types of spinning raw materials into the spinning raw material quality evaluation model, and the spinning raw material quality evaluation model expression is: Output the quality characteristic value χ of the spinning raw material type i i , where ζ′ and ζ″ represent the threshold values ​​of the physical property evaluation coefficient and the chemical property evaluation coefficient of each type of spinning raw materials, respectively; If the quality characteristic value of a certain type of spinning raw material is 1, the spinning raw material of this type stored in the warehouse will be directly used for spinning production. If the quality characteristic value of a certain type of spinning raw material is -1, it is necessary to re-purchase the spinning raw material of this type and use the newly purchased spinning of this type for spinning production.

3. A spinning production line fault monitoring system according to claim 2, characterized in that: When analyzing the physical property evaluation coefficients and chemical property evaluation coefficients of various types of spinning raw materials, the specific analysis process is as follows: The average length and linear density of each type of fiber raw material sample were measured using HVI, and the strength of each type of fiber raw material sample was measured using a fiber strength meter. The fiber length, linear density and strength of each type of sample were recorded as L i 、R i and G i , according to the calculation formula: Get the physical quality evaluation coefficient aχ of the spinning raw material numbered type i i , where L′, R′, and G′ represent the fiber length threshold, linear density threshold, and strength threshold of each type of spinning raw material, respectively; The thermal stability of each type of fiber raw material sample was measured by thermogravimetric analysis, and the impurity content of each type of fiber raw material sample was measured using an impurity analyzer. The thermal stability and impurity content of each type of fiber raw material sample were recorded as F i and D i , according to the calculation formula: Calculate the chemical quality evaluation coefficient bχ of the spinning raw material numbered type i i , where F i ′ and D i ' represents the thermal stability threshold and impurity content threshold of each type of spinning raw material.

4. A spinning production line fault monitoring system according to claim 3, characterized in that: The production information includes the types of yarn produced, the production qualification rate of each type of yarn, and the production efficiency.

5. A spinning production line fault monitoring system according to claim 4, characterized in that: The above analysis further obtains the production behavior evaluation coefficient of each production equipment for each type of spinning, and the specific process is as follows: Based on the production information of each production equipment, the production qualification rate and production efficiency of each type of spinning produced by each production equipment are obtained, and the production demand of each type of spinning is obtained from the production plan. The production demand of each type of spinning, the production qualification rate and production efficiency of each type of spinning produced by each production equipment are respectively recorded as θ j ,η h→j and Where j is the number of each spinning type, h is the number of each production equipment, and the production demand of each type of spinning, the production qualification rate and production efficiency of each type of spinning produced by each production equipment are substituted into the production equipment matching model. According to the production equipment matching model expression: Output the production behavior evaluation coefficient Q of the h-th production equipment corresponding to the j-th type of spinning h→j , where J represents the total number of spinning types, η′ j and Respectively represent the set standard values ​​of qualified rate and production efficiency for each type of spinning; The production behavior evaluation coefficients of each production equipment for each type of spinning are sorted from large to small, and the production equipment for each type of spinning is obtained in sequence according to the sorting results.

6. A spinning production line fault monitoring system according to claim 5, characterized in that: The specific monitoring process for fault monitoring of each production equipment is as follows: Each monitoring time point is set according to a preset time interval, and at each monitoring time point, the working parameters of each production equipment are read through the parameter monitoring panel of each production equipment. At the same time, the standard value of each working parameter and each allowable offset value of each production equipment are read from the technical manual of each production equipment. By comparing the working parameters of each production equipment read at each monitoring time point with the corresponding standard value of each working parameter, the actual error of each working parameter of each production equipment at each monitoring time point is obtained, and the actual error of the working parameter of each production equipment at each monitoring time point is compared with the corresponding allowable offset values, thereby obtaining the fault monitoring result of each production equipment at each monitoring time point; At the same time, high-definition cameras installed in the current workshop are used to collect images of yarns of various types at various collection time points, and the characteristic parameters of various types of spinning are obtained through image processing technology. The threshold values ​​of various characteristic parameters of various types of spinning are obtained from the spinning quality standard table, and the characteristic parameters of various types of spinning are compared with the corresponding characteristic parameter thresholds to obtain the production status of various types of spinning at each monitoring time point.

7. A spinning production line fault monitoring system according to claim 6, characterized in that: The specific process of determining whether to start the fault repair mechanism is as follows: Compare the actual error of the working parameters of each production equipment at each monitoring time point with the corresponding allowable offset values. When the working parameters of a production equipment at each monitoring time point are faulty, the fault repair mechanism needs to be activated, and the pre-written algorithm of each production equipment needs to be used to correct the parameters of the faulty production equipment. If the actual error of the working parameters of the production equipment after correction still exceeds the corresponding allowable offset value, an alarm needs to be issued to remind relevant staff; The characteristic parameters of each type of spinning are compared with the corresponding characteristic parameter thresholds. When a characteristic parameter of a certain type of spinning fails, the assistance of the corresponding production equipment is immediately stopped and an alarm is issued to remind relevant staff.

8. A spinning production line fault monitoring system according to claim 7, characterized in that: The specific process of quality inspection of the finished spinning is as follows: Randomly sample the various types of spun yarns produced, mix the sampled spun yarns of the same type, and evenly divide the mixed spun yarns into two parts for performance testing and appearance testing respectively; For performance testing, the linear density of each type of spinning sample was obtained using HVI testing, and the strength of each type of spinning sample was measured using a fiber strength measuring instrument; For appearance inspection, under standard light distance, the number of defects and hairiness on the surface of each type of spinning sample is observed through a microscope, and then the defect distribution rate of each type of spinning sample is obtained by combining the area of ​​each type of spinning sample; Substitute the linear density, strength and defect release rate of each type of spinning sample into the spinning finished product quality evaluation model, and output the quality evaluation coefficient of each type of spinning finished product according to the spinning finished product quality evaluation model expression.

9. A spinning production line fault monitoring system according to claim 8, characterized in that: The specific process of classifying various types of yarns according to the quality inspection results is as follows: The obtained quality assessment coefficients of each type of spinning product are compared with the set first-class spinning quality threshold and second-class spinning quality threshold. When the quality assessment coefficient of a certain type of spinning product is greater than the set first-class spinning quality threshold, the finished product of this type of spinning is recorded as first-class spinning. If the quality assessment coefficient of a certain type of spinning product is less than the set first-class spinning quality threshold but greater than or equal to the second-class spinning quality threshold, the finished product of this type of spinning is recorded as second-class spinning. When the quality assessment coefficient of a certain type of spinning product is less than the set second-class spinning quality assessment coefficient, the spinning of this type is recorded as unqualified spinning.

10. A spinning process production line fault monitoring method performed by the spinning process production line fault monitoring system according to any one of claims 1 to 9, characterized in that: include: Step 1: Obtain the production plan corresponding to the current production workshop from the production plan table, and then obtain the types and quantities of each type of spinning raw materials from the production plan, and then perform quality inspection on each type of spinning raw materials; Step 2: Obtain the production information of each production equipment in the production workshop, and then analyze and obtain the production behavior evaluation coefficient of each production equipment for each type of spinning, so as to obtain each production equipment for each type of spinning; Step 3: During the spinning production process, each production equipment is monitored for faults, and the production status of each type of spinning is monitored. It is determined whether to start a fault repair mechanism based on the fault conditions of each production equipment and the production status of each type of spinning; Step 4: Perform quality inspection on the various types of spun yarn produced, and classify the various types of spun yarn according to the quality inspection results; Step 5: Display the analysis results of the raw material detection module, production management module, production fault monitoring module and inspection.

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