Textile processing production line fault monitoring system and method based on data analysis

Abstract

The invention relates to the technical field of production line fault monitoring, in particular to a textile processing production line fault monitoring system and method based on data analysis, and the system comprises a production line fault monitoring platform, a production line data unit, a fault feedback unit, a fault supervision unit, a progressive positioning unit, a tracking marking unit and a visual feedback unit. According to the invention, operation state risk supervision and assessment analysis is carried out based on monitoring qualification, so that operation supervision and fault feedback are carried out on the textile processing production line, the operation safety of the textile processing production line is improved, fault positioning feedback management analysis is carried out on the working information of the target production line in a progressive manner, and the operation safety of the textile processing production line is improved. According to the method, the fault equipment of the target production line can be further tracked and positioned, and the in-depth part tracking and marking analysis can be carried out, so that the internal parts of the fault target equipment in the target production line can be managed and maintained in a targeted manner according to the information feedback condition, and the influence of operation and maintenance on the processing efficiency of the textile processing production line can be reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of production line fault monitoring, and in particular to a textile processing production line fault monitoring system and method based on data analysis. Background Art

[0002] With the rapid development of industrial automation technology, automated production lines are increasingly being used. These production lines can significantly reduce production costs and improve production efficiency. However, while achieving production efficiency and quality, automated production lines also encounter more failure risks. How to quickly identify and repair these failures to ensure the normal operation of the production line has become crucial.

[0003] The textile industry is a labor-intensive industry with a high degree of external dependence. The raw materials of textiles mainly include cotton, cashmere, wool, silk, chemical fiber, feathers and down, etc. The downstream industries of the textile industry mainly include the clothing industry, household textiles, industrial textiles, etc. However, in the existing textile processing production line fault monitoring technology, it is impossible to supervise and analyze the accuracy of textile processing production line fault monitoring, which leads to low accuracy of textile processing production line monitoring, and affects the operation and maintenance management efficiency of textile processing production lines. It is also impossible to accurately locate the faulty components in the faulty equipment in the faulty production line, which is not conducive to reasonable and targeted management, and increases the risk of operation and maintenance affecting the processing efficiency of textile processing production lines.

[0004] In view of the above technical defects, a solution is now proposed. Summary of the invention

[0005] The purpose of the present invention is to provide a textile processing production line fault monitoring system and method based on data analysis to solve the above-mentioned technical defects. The present invention conducts preliminary production line operation safety supervision feedback verification analysis on visual monitoring data to determine whether the textile processing production line fault feedback information is accurate, so as to rationally optimize and adjust the production line fault monitoring system according to the information feedback situation to ensure the accuracy and effectiveness of the fault feedback information, and conducts fault location feedback management analysis on the working information of the target production line in a progressive manner to further track and locate the faulty equipment of the target production line, which is helpful for reasonable and targeted management of the faulty equipment, as well as in-depth operation data of electrical components in the faulty target equipment, and in-depth component tracking and marking analysis of the operation data to determine the location of the faulty components inside the faulty target equipment, so as to conduct targeted management and maintenance of the internal components of the faulty target equipment in the target production line according to the information feedback situation, so as to improve the fault repair efficiency of the textile processing production line, and at the same time help to reduce the impact of operation and maintenance on the processing efficiency of the textile processing production line.

[0006] The object of the present invention can be achieved by the following technical solutions: A textile processing production line fault monitoring system based on data analysis, comprising a production line fault monitoring platform, a production line data unit, a fault feedback unit, a fault supervision unit, a progressive positioning unit, a tracking marking unit and a visual feedback unit;

[0007] The production line data unit is used to collect visual monitoring data and operation risk data of the textile processing production line, and send the visual monitoring data and operation risk data to the fault feedback unit and the fault supervision unit respectively;

[0008] After receiving the visual monitoring data, the fault feedback unit immediately performs production line operation safety supervision feedback verification analysis on the visual monitoring data, compares and analyzes the obtained early warning operation efficiency evaluation coefficient J, and sends the obtained qualified signal and unqualified signal to the visual feedback unit;

[0009] The fault monitoring unit responds to the qualified signal and performs operation status risk monitoring assessment analysis on the received operation risk data, performs comparative analysis on the obtained production line fault risk coefficient G, and obtains a fault signal;

[0010] The progressive positioning unit is used to respond to the fault signal and collect the working information of the textile processing production line, and perform fault positioning feedback management analysis on the working information to obtain the feedback signal and the fault target device;

[0011] The tracking marking unit is used to respond to feedback signals and collect operating data of electrical components in the faulty target equipment, and perform in-depth component tracking marking analysis on the operating data to obtain an alarm signal. When an alarm signal is generated, the tracking marking unit responds to the alarm signal to perform fault information feedback display analysis, and sends the obtained display fault string to the visual feedback unit.

[0012] Preferably, the production line operation safety supervision feedback verification and analysis process of the fault feedback unit is as follows:

[0013] The operation time period of the textile processing production line is collected and set as the time threshold, and the visual monitoring data of the textile processing production line within the time threshold is obtained. The visual monitoring data represents the early warning matching index and the fault early warning index. The early warning matching index and the fault early warning index are labeled JP and GJ respectively. The early warning matching index JP and the fault early warning index GJ are substituted into the formula J = [GJ × a1 ÷ (JP × a2)] 2 ×a3 obtains the early warning efficiency evaluation coefficient, where a1 and a2 are the preset proportional factor coefficients of the early warning matching index and the fault early warning index respectively, a3 is the preset fault tolerance factor coefficient, a1, a2 and a3 are all greater than zero, and J is the early warning efficiency evaluation coefficient. The early warning efficiency evaluation coefficient J is compared with the preset early warning efficiency evaluation coefficient threshold value entered and stored internally to obtain qualified signals and unqualified signals.

[0014] Preferably, the warning matching index represents the proportion of the total number of deviation warnings in the total number of historical fault warnings, and the total number of deviation warnings represents the sum of the number of times the warning shows that the production line number is inconsistent with the set production line number and the number of false warnings; the fault warning index represents the proportion of the number of times the fault location is qualified in the total number of historical fault warnings, and qualified fault location indicates that the equipment number in the faulty production line corresponds to the set number itself.

[0015] Preferably, the operation status risk supervision assessment and analysis process of the fault supervision unit is as follows:

[0016] The operation risk data of each textile processing production line within the time threshold is obtained. The operation risk data includes the operation performance index and the processing evaluation index. The operation performance index and the processing evaluation index are labeled YB and JP respectively. The production line failure risk coefficient G is obtained according to the formula. The production line failure risk coefficient G is compared and analyzed with the preset production line failure risk coefficient threshold value stored in the internal input:

[0017] If the ratio between the production line failure risk coefficient G and the preset production line failure risk coefficient threshold is less than 1, no signal is generated; if the ratio between the production line failure risk coefficient G and the preset production line failure risk coefficient threshold is greater than or equal to 1, a fault signal is generated.

[0018] Preferably, the operation performance index represents the value obtained by deducting the total amount of qualified textiles produced by the textile processing production line within a time threshold from the total amount of material input; the processing evaluation index represents the ratio between the textile processing qualification rate and the total energy consumption of the textile processing production line.

[0019] Preferably, the fault location feedback management and analysis process of the progressive location unit is as follows:

[0020] The textile processing production line corresponding to the fault signal is obtained and set as the target production line, and the working information of each processing equipment in the target production line within the time threshold is obtained, and the working information represents the continuous frame feature image;

[0021] The processed textile image of the processing device is obtained from the continuous frame feature image, and then the difference value between the processed textile image and the set processed textile image is obtained, and the difference value between the processed textile image and the set processed textile image is set as the processing deviation index, and the processing deviation index is compared and analyzed with the preset processing deviation index threshold value recorded and stored internally:

[0022] If the processing deviation index is less than or equal to the preset processing deviation index threshold, no signal is generated;

[0023] If the processing deviation index is greater than a preset processing deviation index threshold, the corresponding processing equipment is determined to be a faulty target equipment, and a feedback signal is generated at the same time.

[0024] Preferably, the in-depth component tracking mark analysis process of the tracking mark unit is as follows:

[0025] Obtaining the operating data of each electrical component of the fault target equipment within the time threshold, the operating data including the actual parameter value and the heat load assessment value, comparing and analyzing the actual parameter value and the heat load assessment value with the preset actual parameter value threshold and the preset heat load assessment value threshold recorded and stored internally, and obtaining the fault target component and the alarm signal;

[0026] The actual parameter value represents the deviation between the actual operating parameters of each electrical component and the rated operating parameters. The actual operating parameters include the actual operating voltage value and the actual operating power value. The thermal load assessment value represents the product value obtained by multiplying the heat generation and the heating rate of each electrical component after data normalization.

[0027] Preferably, the tracking marking unit responds to the alarm signal to perform fault information feedback display analysis:

[0028] The part number of the faulty target part is obtained, and characters are extracted from the part number of the faulty target part, and the character string composed of the character extraction of the part number of the faulty target part is set as the first identification string. At the same time, the device number of the faulty target equipment is obtained, and the character string composed of the character extraction of the device number of the faulty target equipment is set as the second identification string. The production line number of the target production line is obtained, and characters are extracted from the production line number of the target production line, and the character string composed of the character extraction of the production line number of the target production line is set as the third identification string. The character string composed of the first identification string, the second identification string and the third identification string is set as the display fault string.

[0029] The beneficial effects of the present invention are as follows:

[0030] (1) The present invention conducts preliminary production line operation safety supervision feedback verification analysis on visual monitoring data to determine whether the fault feedback information of the textile processing production line is accurate, so as to rationally optimize and adjust the production line fault monitoring system according to the information feedback to ensure the accuracy and effectiveness of the fault feedback information, thereby helping to improve the efficiency of production line maintenance management, and conducts operation status risk supervision assessment and analysis on the operation risk data of the textile processing production line through information feedback, so as to conduct operation supervision and fault feedback on the textile processing production line, so as to improve the operation safety of the textile processing production line;

[0031] (2) The present invention performs fault location feedback management analysis on the working information of the target production line in a progressive manner, so as to further track and locate the faulty equipment on the target production line, which helps to manage the faulty equipment in a reasonable and targeted manner, as well as in-depth operation data of electrical components in the faulty target equipment, and performs in-depth component tracking and marking analysis on the operation data to determine the location of the faulty component inside the faulty target equipment, so as to carry out targeted management and maintenance of the internal components of the faulty target equipment in the target production line according to the information feedback, so as to improve the fault repair efficiency of the textile processing production line, and at the same time help to reduce the impact of operation and maintenance on the processing efficiency of the textile processing production line. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] The present invention will be further described below in conjunction with the accompanying drawings;

[0033] Figure 1 It is a flowchart of the system of the present invention;

[0034] Figure 2 It is a reference analysis diagram of the method of the present invention. DETAILED DESCRIPTION

[0035] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0036] Embodiment 1:

[0037] See also Figure 1 to Figure 2 As shown, the present invention is a textile processing production line fault monitoring system based on data analysis, including a production line fault monitoring platform, a production line data unit, a fault feedback unit, a fault supervision unit, a progressive positioning unit, a tracking mark unit and a visual feedback unit, the production line fault monitoring platform is connected to the production line data unit in a one-way communication, the production line data unit is connected to the fault feedback unit and the fault supervision unit in a one-way communication, the fault feedback unit is connected to the fault supervision unit and the visual feedback unit in a one-way communication, the fault supervision unit is connected to the progressive positioning unit in a one-way communication, the progressive positioning unit is connected to the tracking mark unit in a one-way communication, and the tracking mark unit is connected to the visual feedback unit in a one-way communication;

[0038] When the operation management instruction is generated based on the production line fault monitoring platform, the operation management instruction is sent to the production line data unit. After receiving the operation management instruction, the production line data unit immediately collects the visual monitoring data and operation risk data of the textile processing production line, and sends the visual monitoring data and operation risk data to the fault feedback unit and the fault supervision unit respectively. After receiving the visual monitoring data, the fault feedback unit immediately verifies and analyzes the production line operation safety supervision feedback of the visual monitoring data to determine whether the textile processing production line fault feedback information is accurate, so as to make timely optimization and adjustment to ensure the accuracy and effectiveness of the fault feedback information. The specific production line operation safety supervision feedback verification and analysis process is as follows:

[0039] The operation time period of the textile processing production line is collected and set as the time threshold, and the visual monitoring data of the textile processing production line within the time threshold is obtained. The visual monitoring data represents the early warning matching index and the fault early warning index. The early warning matching index and the fault early warning index are labeled JP and GJ respectively. The early warning matching index JP and the fault early warning index GJ are substituted into the formula J = [GJ × a1 ÷ (JP × a2)] 2 ×a3 to obtain the early warning operation efficiency evaluation coefficient, where a1 and a2 are the preset proportional factor coefficients of the early warning matching index and the fault early warning index respectively. The proportional factor coefficient is used to correct the deviation of various parameters in the formula calculation process, so as to make the calculation result more accurate. a3 is the preset fault tolerance factor coefficient. a1, a2 and a3 are all greater than zero. J is the early warning operation efficiency evaluation coefficient. The early warning operation efficiency evaluation coefficient J is compared with the preset early warning operation efficiency evaluation coefficient threshold value stored in the internal input for analysis:

[0040] If the ratio between the early warning operation efficiency evaluation coefficient J and the preset early warning operation efficiency evaluation coefficient threshold is less than 1, a qualified signal is generated;

[0041] If the ratio between the early warning operation efficiency evaluation coefficient J and the preset early warning operation efficiency evaluation coefficient threshold is greater than or equal to 1, an unqualified signal is generated, and the qualified signal and the unqualified signal are sent to the visual feedback unit. After receiving the qualified signal and the unqualified signal, the visual feedback unit immediately displays the preset early warning text corresponding to the qualified signal and the unqualified signal, so as to rationally optimize and adjust the production line fault monitoring system according to the information feedback, so as to improve the accuracy and effectiveness of the production line early warning;

[0042] In the embodiment of the present invention, the warning matching index represents the proportion of the total number of deviation warnings in the total number of historical fault warnings, and the total number of deviation warnings represents the sum of the number of times the warning display production line number is inconsistent with the set production line number and the number of false warnings. It should be noted that the optimization demand degree of the production line fault monitoring system is analyzed from the perspective of fault monitoring accuracy, so as to improve the accuracy of supervision and warning of textile processing production lines;

[0043] In the embodiment of the present invention, the fault warning index represents the proportion of the number of fault location qualified in the total number of historical fault warnings, and the qualified fault location represents the one-to-one correspondence between the equipment number in the faulty production line and the set own number. It should be noted that the accuracy of the production line fault monitoring system is analyzed from the perspective of fault location, so as to reasonably optimize and adjust, so as to improve the accuracy of supervision and warning of textile processing production lines;

[0044] When a qualified signal is generated, the fault supervision unit responds to the qualified signal and performs operation status risk supervision assessment and analysis on the received operation risk data, so as to perform operation supervision and fault feedback on the textile processing production line to improve the operation safety of the textile processing production line. The specific operation status risk supervision assessment and analysis process is as follows:

[0045] Obtain the operation risk data of each textile processing production line within the time threshold. The operation risk data includes the operation performance index and the processing evaluation index. The operation performance index and the processing evaluation index are marked as YB and JP respectively. According to the formula The production line failure risk coefficient is obtained, where f1 and f2 are the preset weight factor coefficients of the operation performance index and the processing evaluation index respectively, f3 is the preset correction factor coefficient, f1, f2 and f3 are all greater than zero, G is the production line failure risk coefficient, and the production line failure risk coefficient G is compared and analyzed with the preset production line failure risk coefficient threshold value stored in the internal input:

[0046] If the ratio between the production line failure risk factor G and the preset production line failure risk factor threshold is less than 1, no signal is generated;

[0047] If the ratio between the production line failure risk factor G and the preset production line failure risk factor threshold is greater than or equal to 1, a failure signal is generated;

[0048] In the embodiment of the present invention, the operation performance index represents the value obtained by subtracting the total amount of qualified textiles produced from the total amount of material input of the textile processing production line within the time threshold. It should be noted that the larger the value of the operation performance index, the greater the abnormal risk of the textile processing production line;

[0049] In the embodiment of the present invention, the processing evaluation index represents the ratio between the textile processing qualification rate and the total energy consumption of the textile processing production line. It should be noted that, from the perspective of energy consumption and processing efficiency, in order to achieve low-consumption and high-efficiency processing, the smaller the value of the processing evaluation index, the greater the abnormal risk of the textile processing production line.

[0050] Embodiment 2:

[0051] When a fault signal is generated, the progressive positioning unit is used to respond to the fault signal and collect the working information of the textile processing production line, and perform fault positioning feedback management and analysis on the working information, so as to reasonably and targetedly manage the faulty equipment according to the information feedback, so as to improve the efficiency of fault repair of the textile processing production line, thereby helping to reduce the impact of operation and maintenance on the processing efficiency of the textile processing production line. The specific fault positioning feedback management and analysis process is as follows:

[0052] The textile processing production line corresponding to the fault signal is obtained and set as the target production line, and the working information of each processing equipment in the target production line within the time threshold is obtained, and the working information represents the continuous frame feature image;

[0053] A processed textile image of the processing equipment is obtained from the continuous frame feature images, and then a difference value between the processed textile image and a set processed textile image is obtained, and the difference value between the processed textile image and the set processed textile image is set as a processing deviation index. It should be noted that the larger the value of the processing deviation index is, the greater the processing failure risk of the processing equipment is;

[0054] Compare and analyze the processing deviation index with the preset processing deviation index threshold value stored in the internal storage:

[0055] If the processing deviation index is less than or equal to the preset processing deviation index threshold, no signal is generated;

[0056] If the processing deviation index is greater than the preset processing deviation index threshold, the corresponding processing equipment is determined to be a faulty target equipment, and a feedback signal is generated at the same time;

[0057] When a feedback signal is generated, the tracking tag unit is used to respond to the feedback signal and collect the operating data of the electrical components in the faulty target device, and perform in-depth component tracking tag analysis on the operating data to determine the location of the faulty component inside the faulty target device, so as to accurately perform operation and maintenance management on the faulty component to improve the fault repair efficiency of the textile processing production line. The specific in-depth component tracking tag analysis process is as follows:

[0058] The operation data of each electrical component of the fault target equipment within the time threshold is obtained. The operation data includes the actual parameter value and the heat load assessment value. The actual parameter value and the heat load assessment value are compared and analyzed with the preset actual parameter value threshold and the preset heat load assessment value threshold that are recorded and stored internally:

[0059] If the actual value of the parameter is less than the preset actual value threshold of the parameter, and the heat load evaluation value is less than the preset heat load evaluation value threshold, no signal is generated;

[0060] If the actual value of the parameter is greater than or equal to the preset actual value threshold of the parameter, or the heat load assessment value is greater than or equal to the preset heat load assessment value threshold, the corresponding electrical component is determined to be a fault target component, and an alarm signal is generated at the same time;

[0061] In the implementation of the present invention, the actual value of the parameter represents the deviation between the actual operating parameter of each electrical component and the rated operating parameter. The actual operating parameter includes the actual operating voltage value, the actual operating power value, etc. It should be noted that the analysis is performed from the perspective of the operating parameters to understand the failure risk of the electrical component;

[0062] In the implementation of the present invention, the heat load evaluation value represents the product value obtained by multiplying the heat generation and the heating rate of each electrical component after data normalization. It should be noted that the analysis is performed from the perspective of heat to determine whether the electrical component is operating normally;

[0063] When an alarm signal is generated, the tracking marking unit responds to the alarm signal and performs fault information feedback display analysis. The specific fault information feedback display analysis process is as follows:

[0064] The part number of the faulty target component is obtained, and characters are extracted from the part number of the faulty target component, and the character string composed of the character extraction of the part number of the faulty target component is set as a first identification string. At the same time, the device number of the faulty target equipment is obtained, and the character string composed of the character extraction of the device number of the faulty target equipment is set as a second identification string. The production line number of the target production line is obtained, and characters are extracted from the production line number of the target production line, and the character string composed of the character extraction of the production line number of the target production line is set as a third identification string. The character string composed of the first identification string, the second identification string and the third identification string is set as a display fault string, and the display fault string is sent to a visual feedback unit. After receiving the display fault string, the visual feedback unit immediately presents a preset warning text corresponding to the display fault string, so as to perform targeted management and maintenance of the internal components of the equipment in the faulty production line according to the information feedback, so as to improve the fault repair efficiency of the textile processing production line, thereby helping to reduce the impact of operation and maintenance on the processing efficiency of the textile processing production line.

[0065] Implementation three:

[0066] The textile processing production line fault monitoring method based on data analysis includes the following steps:

[0067] Step 1: Collect visual monitoring data and operation risk data of the textile processing production line, and substitute them into step 2 for production line operation safety supervision feedback verification analysis and step 3 for operation status risk supervision assessment analysis;

[0068] Step 2: Conduct verification and analysis of the visual monitoring data for production line operation safety supervision feedback, compare and analyze the obtained early warning operation efficiency evaluation coefficient J, and obtain qualified and unqualified signals;

[0069] Step 3: Respond to the qualified signal in step 2 and conduct an operation status risk supervision assessment and analysis on the operation risk data, and compare and analyze the obtained production line failure risk coefficient G. If a failure signal is obtained, proceed to step 4;

[0070] Step 4: Collect the working information of the textile processing production line through information feedback, and perform fault location feedback management analysis on the working information. If a feedback signal is obtained, proceed to step 5;

[0071] Step 5: Perform in-depth component tracking and marking analysis on the collected operation data in a progressive manner. If an alarm signal is obtained, perform fault information feedback display analysis and display the obtained fault string feedback display;

[0072] In summary, the present invention preliminarily performs production line operation safety supervision feedback verification analysis on visual monitoring data to determine whether the fault feedback information of the textile processing production line is accurate, so as to rationally optimize and adjust the production line fault monitoring system according to the information feedback situation to ensure the accuracy and effectiveness of the fault feedback information, thereby helping to improve the production line maintenance management efficiency, and the operation risk data of the textile processing production line is subjected to operation status risk supervision assessment analysis by means of information feedback, so as to perform operation supervision and fault feedback on the textile processing production line, so as to improve the operation safety of the textile processing production line, and at the same time, the working information of the target production line is subjected to fault location feedback management analysis in a progressive manner, so as to further track and locate the faulty equipment of the target production line, which is helpful for reasonable and targeted management of the faulty equipment, and in-depth operation data of the electrical components in the faulty target equipment, and in-depth component tracking and marking analysis of the operation data to determine the position of the faulty components inside the faulty target equipment, so as to carry out targeted management and maintenance of the internal components of the faulty target equipment in the target production line according to the information feedback situation, so as to improve the fault repair efficiency of the textile processing production line, and at the same time, it is helpful to reduce the impact of operation and maintenance on the processing efficiency of the textile processing production line.

[0073] The threshold is set to facilitate comparison. The size of the threshold depends on the amount of sample data and the number of bases set by technicians in this field for each group of sample data; as long as it does not affect the proportional relationship between the parameter and the quantized value.

[0074] The above formulas are obtained by collecting a large amount of data for software simulation and selecting a formula that is close to the actual value. The coefficients in the formula are set by technical personnel in this field according to actual conditions. The above is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited to this. Any technical personnel familiar with the technical field within the technical scope disclosed by the present invention, according to the technical solution and the inventive concept of the present invention, make equivalent replacement or change, which should be covered within the protection scope of the present invention.

Claims

1. A textile processing production line fault monitoring system based on data analysis, characterized in that: It includes production line fault monitoring platform, production line data unit, fault feedback unit, fault supervision unit, progressive positioning unit, tracking marking unit and visual feedback unit; The production line data unit is used to collect visual monitoring data and operation risk data of the textile processing production line, and send the visual monitoring data and operation risk data to the fault feedback unit and the fault supervision unit respectively; After receiving the visual monitoring data, the fault feedback unit immediately performs production line operation safety supervision feedback verification analysis on the visual monitoring data, compares and analyzes the obtained early warning operation efficiency evaluation coefficient J, and sends the obtained qualified signal and unqualified signal to the visual feedback unit; The fault monitoring unit responds to the qualified signal and performs operation status risk monitoring assessment analysis on the received operation risk data, performs comparative analysis on the obtained production line fault risk coefficient G, and obtains a fault signal; The progressive positioning unit is used to respond to the fault signal and collect the working information of the textile processing production line, and perform fault positioning feedback management analysis on the working information to obtain the feedback signal and the fault target device; The tracking marking unit is used to respond to feedback signals and collect operating data of electrical components in the faulty target equipment, and perform in-depth component tracking marking analysis on the operating data to obtain an alarm signal. When an alarm signal is generated, the tracking marking unit responds to the alarm signal to perform fault information feedback display analysis, and sends the obtained display fault string to the visual feedback unit.

2. The textile processing production line fault monitoring system based on data analysis according to claim 1 is characterized in that: The production line operation safety supervision feedback verification and analysis process of the fault feedback unit is as follows: The operation time period of the textile processing production line is collected and set as the time threshold, and the visual monitoring data of the textile processing production line within the time threshold is obtained. The visual monitoring data represents the early warning matching index and the fault early warning index. The early warning matching index and the fault early warning index are labeled JP and GJ respectively. The early warning matching index JP and the fault early warning index GJ are substituted into the formula J = [GJ × a1 ÷ (JP × a2)] 2 ×a3 obtains the early warning efficiency evaluation coefficient, where a1 and a2 are the preset proportional factor coefficients of the early warning matching index and the fault early warning index respectively, a3 is the preset fault tolerance factor coefficient, a1, a2 and a3 are all greater than zero, and J is the early warning efficiency evaluation coefficient. The early warning efficiency evaluation coefficient J is compared with the preset early warning efficiency evaluation coefficient threshold value entered and stored internally to obtain qualified signals and unqualified signals.

3. The textile processing production line fault monitoring system based on data analysis according to claim 2 is characterized in that: The warning matching index represents the proportion of the total number of deviation warnings in the total number of historical fault warnings, and the total number of deviation warnings represents the sum of the number of times the warning display production line number is inconsistent with the set production line number and the number of false warnings; The fault warning index represents the proportion of the number of times the fault location is qualified in the total number of historical fault warnings. The qualified fault location indicates that the equipment number in the faulty production line corresponds to the set own number one by one.

4. The textile processing production line fault monitoring system based on data analysis according to claim 3 is characterized in that: The operation status risk supervision assessment and analysis process of the fault supervision unit is as follows: The operation risk data of each textile processing production line within the time threshold is obtained. The operation risk data includes the operation performance index and the processing evaluation index. The operation performance index and the processing evaluation index are labeled YB and JP respectively. The production line failure risk coefficient G is obtained according to the formula. The production line failure risk coefficient G is compared and analyzed with the preset production line failure risk coefficient threshold value stored in the internal input: If the ratio between the production line failure risk factor G and the preset production line failure risk factor threshold is less than 1, no signal is generated; If the ratio between the production line failure risk coefficient G and the preset production line failure risk coefficient threshold is greater than or equal to 1, a failure signal is generated.

5. The textile processing production line fault monitoring system based on data analysis according to claim 4 is characterized in that: The operation performance index represents the value obtained by deducting the total amount of qualified textiles produced from the total material input of the textile processing production line within the time threshold; the processing evaluation index represents the ratio between the textile processing qualification rate and the total energy consumption of the textile processing production line.

6. The textile processing production line fault monitoring system based on data analysis according to claim 5 is characterized in that: The fault location feedback management and analysis process of the progressive location unit is as follows: The textile processing production line corresponding to the fault signal is obtained and set as the target production line, and the working information of each processing equipment in the target production line within the time threshold is obtained, and the working information represents the continuous frame feature image; The processed textile image of the processing device is obtained from the continuous frame feature image, and then the difference value between the processed textile image and the set processed textile image is obtained, and the difference value between the processed textile image and the set processed textile image is set as the processing deviation index, and the processing deviation index is compared and analyzed with the preset processing deviation index threshold value recorded and stored internally: If the processing deviation index is less than or equal to the preset processing deviation index threshold, no signal is generated; If the processing deviation index is greater than a preset processing deviation index threshold, the corresponding processing equipment is determined to be a faulty target equipment, and a feedback signal is generated at the same time.

7. The textile processing production line fault monitoring system based on data analysis according to claim 6 is characterized in that: The in-depth component tracking mark analysis process of the tracking mark unit is as follows: Obtaining the operating data of each electrical component of the fault target equipment within the time threshold, the operating data including the actual parameter value and the heat load assessment value, comparing and analyzing the actual parameter value and the heat load assessment value with the preset actual parameter value threshold and the preset heat load assessment value threshold recorded and stored internally, and obtaining the fault target component and the alarm signal; The actual parameter value represents the deviation between the actual operating parameters of each electrical component and the rated operating parameters. The actual operating parameters include the actual operating voltage value and the actual operating power value. The thermal load assessment value represents the product value obtained by multiplying the heat generation and the heating rate of each electrical component after data normalization.

8. The textile processing production line fault monitoring system based on data analysis according to claim 7 is characterized in that: The tracking marking unit responds to the alarm signal to perform fault information feedback display analysis: The part number of the faulty target part is obtained, and characters are extracted from the part number of the faulty target part, and the character string composed of the character extraction of the part number of the faulty target part is set as the first identification string. At the same time, the device number of the faulty target equipment is obtained, and the character string composed of the character extraction of the device number of the faulty target equipment is set as the second identification string. The production line number of the target production line is obtained, and characters are extracted from the production line number of the target production line, and the character string composed of the character extraction of the production line number of the target production line is set as the third identification string. The character string composed of the first identification string, the second identification string and the third identification string is set as the display fault string.

9. A textile processing production line fault monitoring method based on data analysis, the method being applied to the textile processing production line fault monitoring system based on data analysis as claimed in claim 8, characterized in that: The following steps are involved: Step 1: Collect visual monitoring data and operation risk data of the textile processing production line, and substitute them into step 2 for production line operation safety supervision feedback verification analysis and step 3 for operation status risk supervision assessment analysis; Step 2: Conduct verification and analysis of the visual monitoring data for production line operation safety supervision feedback, compare and analyze the obtained early warning operation efficiency evaluation coefficient J, and obtain qualified and unqualified signals; Step 3: Respond to the qualified signal in step 2 and conduct an operation status risk supervision assessment and analysis on the operation risk data, and compare and analyze the obtained production line failure risk coefficient G. If a failure signal is obtained, proceed to step 4; Step 4: Collect the working information of the textile processing production line through information feedback, and perform fault location feedback management analysis on the working information. If a feedback signal is obtained, proceed to step 5; Step 5: Perform in-depth component tracking and marking analysis on the collected operating data in a progressive manner. If an alarm signal is obtained, perform fault information feedback display analysis and display the obtained fault string feedback.

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