Intelligent maintenance and operation data management method for printing apparatus

Abstract

The present application belongs to the technical field of printing operation and maintenance management, and provides an intelligent maintenance and operation data management method for a printing device, comprising: confirming high-stability fault parameters of the printing device; performing fluctuation analysis on a time coverage ratio used when the high-stability fault parameters are confirmed by fault tracing multiple times, confirming a time limited coverage ratio of each high-stability fault parameter; determining a current parameter transition period of the printing device and identifying a to-be-limited fault parameter in the high-stability fault parameters in combination with current order specification conversion requirements; collecting the current parameter transition period of the printing device and the time limited coverage ratio of each high-stability fault parameter, calculating a data acquisition limited frequency of each to-be-limited fault parameter of the printing device in the current parameter transition period, identifying a to-be-limited fault parameter that needs to be corrected in data acquisition frequency, and correcting the data acquisition frequency through the data acquisition limited frequency, so as to realize efficient printing operation and maintenance management.

Description

Technical Field

[0001] This invention belongs to the field of printing operation and maintenance management technology, specifically a method for intelligent maintenance and operation data management of printing equipment. Background Technology

[0002] In the printing production process, frequent changes in order specifications (such as paper type and weight switching) are common. During these changes, operating parameters such as roller pressure and paper feed speed need to be adjusted. During this period, the equipment is in a parameter transition phase of unstable operation, making it highly susceptible to paper jams. Existing maintenance and data management methods for printing equipment have several limitations: Firstly, conventional data acquisition systems often focus on stable production phases, significantly reducing the data acquisition frequency during parameter transition periods (e.g., from 10ms / time to 100ms / time). If a paper jam subsequently occurs, the intelligent maintenance system, lacking complete data from the transition period, struggles to determine whether the root cause is improper parameter adjustment or mechanical failure, greatly increasing the difficulty of tracing the problem. Secondly, existing methods fail to accurately identify the differences in fault risk for different operating parameters, leading to a generalization of data monitoring targets. This wastes acquisition resources and may miss high-risk parameters. Furthermore, the acquisition frequency during parameter transition periods is often a fixed preset value, failing to consider the actual data requirements (such as time coverage ratio) for different parameters during fault tracing. This often results in incomplete data due to excessively low acquisition frequencies or redundant data due to excessively high frequencies.

[0003] Therefore, the present invention provides a method for intelligent maintenance and operation data management of printing equipment. Summary of the Invention

[0004] In order to overcome the shortcomings of the prior art, at least one technical problem raised in the background art is solved.

[0005] The technical solution adopted by this invention to solve its technical problem is: an intelligent maintenance and operation data management method for printing equipment, comprising the following steps:

[0006] Step S10: Perform fault source confirmation frequency and stability analysis on the historical paper jam fault traceability data of the printing equipment to confirm the high-stability fault parameters of the printing equipment.

[0007] Step S20: Perform a fluctuation analysis on the time coverage ratio used when the high-stability fault parameters are repeatedly confirmed by fault source tracing, and confirm the time-limited coverage ratio of each high-stability fault parameter.

[0008] The time coverage ratio represents the ratio between the total data acquisition time of the high-stability fault parameter and the parameter transition period when the high-stability fault parameter is identified as the root cause of the paper jam fault in each paper jam fault tracing and confirmation of the printing equipment.

[0009] Among them, the parameter transition period refers to the duration of time required to adjust the operating parameters when switching between different specification orders;

[0010] The process for confirming the time-limited coverage ratio of each high-stability fault parameter is as follows:

[0011] The time coverage ratios used when high-stability fault parameters are repeatedly confirmed by fault source tracing are integrated to obtain a time coverage ratio sequence. The coefficient of variation of the time coverage ratio sequence is calculated to obtain the time coverage fluctuation value. The volatility of the time coverage ratio used when high-stability fault parameters are repeatedly confirmed by fault source tracing is judged based on the time coverage fluctuation value.

[0012] If the volatility is weak, the time coverage ratio sequence is averaged to obtain the time-limited coverage ratio of the high-stability fault parameters. If the volatility is strong, the maximum value in the time coverage ratio sequence is selected as the time-limited coverage ratio of the high-stability fault parameters.

[0013] Step S30: Obtain the parameter transition period between different specification order conversions through historical order conversion data, and determine the current parameter transition period of the printing equipment and identify the fault parameters to be limited among the high stability fault parameters by combining the current order specification conversion requirements;

[0014] Step S40: Combine the current parameter transition period of the printing equipment with the time limit coverage ratio of each high-stability fault parameter, calculate the data acquisition limit frequency of each fault parameter to be limited in the current parameter transition period, compare it with the preset data acquisition frequency of the printing equipment in the current parameter transition period, identify the fault parameters to be limited that need data acquisition frequency correction, and correct the data acquisition frequency through the data acquisition limit frequency.

[0015] As a further technical solution of the present invention: the process of confirming the high stability fault parameters of the printing equipment is as follows:

[0016] If the operating parameters are identified as the root cause of the paper jam during paper jam troubleshooting in the printing equipment, then the operating parameters will be marked as paper jam fault parameters.

[0017] The frequency and stability of the operating parameters marked as paper jam fault parameters are analyzed to obtain the paper jam fault frequency value and paper jam fault stability value of the operating parameters, and the high stability fault value of the operating parameters is obtained after deviation processing.

[0018] If the high stability fault value meets the preset requirements, the operating parameter will be marked as a high stability fault parameter.

[0019] As a further technical solution of the present invention: the paper jam failure frequency value of the operating parameters is obtained by statistically analyzing the proportion of times the operating parameters are marked as paper jam failure parameters in multiple paper jam failure tracing operations of the printing equipment.

[0020] As a further technical solution of the present invention: the method for obtaining the stable value of paper jam faults is as follows:

[0021] The number of unmarked intervals between two consecutive times an operating parameter is marked as a paper jam fault parameter is counted. The number of unmarked intervals represents the number of times an operating parameter is marked as a non-paper jam fault parameter between two consecutive times it is marked as a paper jam fault parameter.

[0022] By integrating the number of unmarked intervals between each two adjacent parameters marked as paper jam faults, an unmarked interval sequence is obtained. The coefficient of variation of the unmarked interval sequence is calculated to obtain the stable value of the paper jam fault.

[0023] As a further technical solution of the present invention: the process of determining the current parameter transition period of the printing equipment is as follows:

[0024] By using historical order conversion data, extract historical orders with the same specification conversion as the current order. If the current order specification is converted from 80g coated paper printing to 120g cardstock printing, then the historical orders are also converted from 80g coated paper printing to 120g cardstock printing. Obtain the parameter transition period of the historical orders during the conversion and integrate them into a parameter transition period set.

[0025] Select the minimum parameter transition period from the parameter transition period set as the current parameter transition period for the printing equipment.

[0026] As a further technical solution of the present invention: the process of identifying the fault parameter to be limited in the high-stability fault parameters is as follows:

[0027] If a high stability fault parameter causes a paper jam in the printing equipment during a historical order conversion with the same specifications as the current order, then the high stability fault parameter will be marked as a fault parameter to be limited.

[0028] As a further technical solution of the present invention: the process of calculating the data acquisition frequency limit of each fault parameter to be limited in the printing equipment during the current parameter transition period is as follows:

[0029] Based on the time-limited coverage ratio of each high-stability fault parameter, determine the time-limited coverage ratio of the fault parameter to be limited;

[0030] The product of the current parameter transition period of the printing equipment and the time limit coverage ratio of the fault parameters to be limited is used to obtain the limited collection time of the fault parameters to be limited within the current parameter transition period of the printing equipment.

[0031] The ratio of the current parameter transition period of the printing equipment to the limited collection time of the fault parameters to be limited is calculated to obtain the data collection limit frequency of the fault parameters to be limited within the current parameter transition period.

[0032] As a further technical solution of the present invention: the process of identifying the fault parameters that need to be corrected for data acquisition frequency, and correcting the data acquisition frequency by limiting the data acquisition frequency, is as follows:

[0033] If the data acquisition frequency of the fault parameter to be limited during the current parameter transition period is lower than the preset data acquisition frequency, the fault parameter to be limited needs to have its data acquisition frequency corrected, and the data acquisition frequency of the fault parameter to be limited should be corrected according to the data acquisition frequency limit.

[0034] The beneficial effects of this invention are as follows: By analyzing historical paper jam failure data, high-stability fault parameters are identified, accurately pinpointing key operating parameters that are prone to failure and exhibit stable performance. This avoids ineffective investment in low-risk parameters in conventional monitoring. For high-stability fault parameters, the fluctuation of the time coverage ratio is analyzed, and a time-limited coverage ratio is determined. This ensures that the data collection volume during the parameter transition period can meet the fault tracing requirements, solving the problem that conventional systems cannot meet the data support for subsequent fault tracing due to a reduction in the collection frequency during the transition period (e.g., from 10ms / time to 100ms / time). The parameter transition period is determined in conjunction with the current order specification conversion requirements, and fault parameters to be limited are screened, making the monitoring strategy deeply adapted to the actual production scenario. This avoids resource waste in general modes and ensures that monitoring is strengthened only for high-risk parameters that have caused failures in the current conversion scenario. By calculating the data collection limit frequency and correcting the preset frequency, a balance is struck between collection efficiency and resources while ensuring the time coverage ratio. This ensures that the transition period data is both complete and not excessively redundant, ultimately enabling the intelligent operation and maintenance system to accurately trace the root cause of the fault based on complete transition period data when a paper jam occurs. Attached Figure Description

[0035] The invention will now be further described with reference to the accompanying drawings.

[0036] Figure 1 This is a flowchart illustrating the steps of an intelligent maintenance and operation data management method for printing equipment according to an embodiment of the present invention;

[0037] Figure 2 This is a logic diagram of an intelligent maintenance and operation data management method for printing equipment according to an embodiment of the present invention. Detailed Implementation

[0038] To make the technical means, creative features, objectives and effects of this invention easier to understand, the invention will be further described below in conjunction with specific embodiments.

[0039] Example: Please refer to Figures 1-2As shown in the figure, the intelligent maintenance and operation data management method for printing equipment according to an embodiment of the present invention specifically includes the following steps:

[0040] Step S10: Perform fault source confirmation frequency and stability analysis on the historical paper jam fault traceability data of the printing equipment to confirm the high-stability fault parameters of the printing equipment.

[0041] In step S10, the historical paper jam failure tracing data includes various operating parameters that caused the printing equipment to experience paper jam failures during historical operations each time;

[0042] The operating parameters include, but are not limited to, roller pressure and paper feeding speed.

[0043] In step S10, the process of confirming the high stability fault parameters of the printing equipment is as follows:

[0044] Based on any operating parameter;

[0045] If the operating parameters are identified as the root cause of the paper jam during paper jam troubleshooting in the printing equipment, then the operating parameters will be marked as paper jam fault parameters.

[0046] If the operating parameters are not identified as the root cause of the paper jam fault during paper jam troubleshooting in the printing equipment, then the operating parameters will be marked as non-paper jam fault parameters.

[0047] The proportion of times that the operating parameters were marked as paper jam fault parameters in multiple paper jam fault tracing operations of the printing equipment was statistically analyzed to obtain the paper jam fault frequency value of the operating parameters.

[0048] Based on any operating parameter;

[0049] The number of unmarked intervals between two consecutive times an operating parameter is marked as a paper jam fault parameter is counted. The number of unmarked intervals represents the number of times an operating parameter is marked as a non-paper jam fault parameter between two consecutive times it is marked as a paper jam fault parameter.

[0050] For example, the number of unmarked intervals can specifically represent: paper jam fault parameter, non-paper jam fault parameter, non-paper jam fault parameter, non-paper jam fault parameter, paper jam fault parameter. Then, the number of unmarked intervals between two consecutive running parameters marked as paper jam fault parameters is three.

[0051] The number of unmarked intervals between each two adjacent parameters marked as paper jam faults is integrated to obtain the unmarked interval sequence. The coefficient of variation of the unmarked interval sequence is calculated to obtain the stable value of the paper jam fault.

[0052] The deviation between the paper jam failure frequency value and the paper jam failure stability value is calculated to obtain the high-stability failure value of the operating parameters.

[0053] It should be noted that the physical meaning of the high stability fault value is as follows: the high stability fault value is calculated through the paper jam fault frequency value and the paper jam fault stability value. The paper jam fault frequency value reflects the frequency of paper jam faults caused by operating parameters in the printing equipment, while the paper jam fault stability value reflects the stable performance of the operating parameters in causing paper jam faults. The higher the high stability fault value, the higher the risk of paper jam faults caused by the operating parameters. Therefore, in order to prevent insufficient data monitoring during the parameter transition period caused by order conversion, which may lead to the problem of data not meeting the traceability integrity requirements, it is necessary to analyze and adjust the data monitoring frequency of the operating parameters.

[0054] In some embodiments, a high-stability fault value is compared with a high-stability fault threshold;

[0055] If the high stability fault value is greater than or equal to the high stability fault threshold, the operating parameter will be marked as a high stability fault parameter.

[0056] If the high stability fault value is less than the high stability fault threshold, the operating parameter will be marked as a non-high stability fault parameter.

[0057] Understandably, the significance of step S10 lies in: analyzing various operating parameters in the historical paper jam failure traceability data of the printing equipment, statistically analyzing the frequency of their identification as the root cause of failure (paper jam failure frequency value) and the stability of adjacent failure intervals (paper jam failure stability value), calculating high-stability failure values ​​and comparing them with thresholds, and marking high-stability failure parameters. This process accurately identifies high-risk operating parameters that are prone to causing paper jam failures and exhibit stable performance, providing a clear target for targeted data monitoring during the parameter transition period of order conversion, and avoiding resource waste or traceability loopholes caused by ambiguous monitoring targets.

[0058] Step S20: Perform a fluctuation analysis on the time coverage ratio used when the high-stability fault parameters are repeatedly confirmed by fault source tracing, and confirm the time-limited coverage ratio of each high-stability fault parameter.

[0059] In step S20, the time coverage ratio represents the ratio between the total data acquisition time corresponding to the high-stability fault parameter and the parameter transition period when the high-stability fault parameter is identified as the root cause of the paper jam fault in each paper jam fault tracing and confirmation of the printing equipment. For example, if the parameter transition period is 5 minutes (300,000 milliseconds) and the data acquisition frequency of the high-stability fault parameter is 10 milliseconds / time, then the total data acquisition time of the high-stability fault parameter is 30,000 milliseconds, and the time coverage ratio is 30,000 / 300,000 (1 / 10=0.1).

[0060] The calculation of the total data acquisition time for high-stability fault parameters is illustrated below:

[0061] The number of data acquisitions is calculated based on the parameter transition period and the data acquisition frequency of high-stability fault parameters.

[0062] 300,000 milliseconds ÷ 10 milliseconds / time = 30,000 times;

[0063] The total data acquisition time for high-stability fault parameters is calculated by the number of data acquisitions and the time per data acquisition (1 millisecond / acquisition):

[0064] 30,000 times * 1 millisecond / time = 30,000 milliseconds;

[0065] It is understandable that the reason for adopting the time coverage ratio in this invention is that when tracing paper jam faults in printing equipment, effective tracing requires a certain amount of data support. For example, during the parameter transition period, the data collection frequency will decrease, resulting in data collection at the reduced data collection frequency, which leads to insufficient data (too incomplete) data, ultimately making it impossible to effectively trace paper jam faults in printing equipment.

[0066] In step S20, the process of confirming the time-limited coverage ratio of each high-stability fault parameter is as follows:

[0067] Based on any highly stable fault parameter;

[0068] The time coverage ratios used when the high-stability fault parameters are repeatedly confirmed by fault tracing are integrated to obtain a time coverage ratio sequence. The coefficient of variation of the time coverage ratio sequence is calculated to obtain the time coverage fluctuation value.

[0069] In some embodiments, the time coverage fluctuation value is compared with the time coverage fluctuation threshold;

[0070] If the time coverage fluctuation value is greater than or equal to the time coverage fluctuation threshold, it indicates that the time coverage ratio used when the high-stability fault parameter is repeatedly confirmed by fault source tracing has strong fluctuations.

[0071] If the time coverage fluctuation value is less than the time coverage fluctuation threshold, it means that the time coverage ratio used when the high-stability fault parameters are repeatedly confirmed by fault source tracing has weak fluctuation.

[0072] The time-limited coverage ratio of each high-stability fault parameter is determined based on the fluctuation of the time coverage ratio used when the high-stability fault parameters are repeatedly confirmed by fault source tracing. Specifically:

[0073] If the time coverage ratio used when the high-stability fault parameters are repeatedly confirmed by fault source tracing has weak fluctuations, then the time coverage ratio sequence is averaged to obtain the time-limited coverage ratio of the high-stability fault parameters.

[0074] If the time coverage ratio used when the high-stability fault parameter is repeatedly confirmed by fault source tracing is highly volatile, then the maximum value in the time coverage ratio sequence is selected as the time-limited coverage ratio of the high-stability fault parameter.

[0075] It should be noted that when the volatility is high, the purpose of selecting the maximum value in the time coverage ratio sequence as the time limit coverage ratio for the high stability fault parameter is to ensure a high time coverage ratio, so that when limiting the data acquisition frequency in the subsequent process, the effective data acquisition can be met as much as possible, and the effective data traceability can be guaranteed when the printing equipment experiences paper jam faults.

[0076] Understandably, the significance of step S20 lies in: for highly stable fault parameters, analyzing the fluctuation of the total data acquisition time and the time coverage ratio of the parameter transition period when the parameter is repeatedly identified as the root cause of the fault, determining the strength of the fluctuation through the coefficient of variation, and thus determining the time-limited coverage ratio (taking the average value when the fluctuation is weak, and the maximum value when the fluctuation is strong). This ensures that, when the data acquisition frequency is limited in the future, there is sufficient data to support the effective tracing of paper jam faults during the parameter transition period based on reliable time coverage requirements, avoiding tracing failure due to insufficient data.

[0077] Step S30: Obtain the parameter transition period between different specification order conversions through historical order conversion data, and determine the current parameter transition period of the printing equipment and identify the fault parameters to be limited among the high stability fault parameters by combining the current order specification conversion requirements;

[0078] In step S30, the historical order conversion data includes the parameter transition period required for printing conversion between orders of different specifications;

[0079] The parameter transition period specifically refers to the duration of adjusting operating parameters when switching between printing orders of different specifications. For example, when switching from printing on 80g coated paper to printing on 120g cardstock, parameters such as roller pressure and paper feeding speed need to be adjusted. The entire parameter transition process lasts 3-5 minutes, during which the equipment is in an unstable operating state.

[0080] In step S30, the process of determining the current parameter transition period of the printing equipment is as follows:

[0081] By using historical order conversion data, extract historical orders that have the same specification conversion status as the current order, obtain the parameter transition period of the historical orders during the conversion, and integrate them into a parameter transition period set;

[0082] For example, if the current order specification is changed from 80g coated paper printing to 120g cardstock printing, then based on the historical order conversion data, the parameter transition period of the historical orders when switching from 80g coated paper printing to 120g cardstock printing is obtained and integrated into a parameter transition period set.

[0083] Select the minimum parameter transition period from the parameter transition period set as the current parameter transition period for the printing equipment;

[0084] It is understandable that, since the parameter transition periods within the parameter transition period set are inconsistent, selecting the minimum parameter transition period as the current parameter transition period for the printing equipment can ensure that the data collection during the subsequent parameter transition period can meet the requirements for effective traceability of paper jam faults.

[0085] In step S30, the process of identifying the fault parameters to be limited from the high-stability fault parameters is as follows:

[0086] Based on any highly stable fault parameter;

[0087] If a high stability fault parameter causes a paper jam in the printing equipment during a historical order conversion with the same specification as the current order conversion, then the high stability fault parameter will be marked as a fault parameter to be limited.

[0088] If a high stability fault parameter has never caused a paper jam in a historical order conversion with the same order specification as the current order conversion, then the high stability fault parameter will be marked as an unrestricted fault parameter.

[0089] It should be noted that the reason for identifying the fault parameters to be limited among the high-stability fault parameters is that the high-stability fault parameters represent the operating parameters that often cause paper jams in the printing equipment. However, in the current type of order conversion, there may be some high-stability fault parameters that do not cause paper jams in the printing equipment. Therefore, based on the current type of order conversion, the fault parameters to be limited are identified to achieve efficient management of data collection for the printing equipment during the parameter transition period.

[0090] Understandably, the significance of step S30 lies in: combining historical order conversion data to obtain the parameter transition period set corresponding to the current order specification conversion and selecting the minimum value as the current transition period; simultaneously, filtering out potential fault parameters from the high-stability fault parameters that have caused paper jams in the same historical conversions. This process clarifies the time range of the current parameter transition period and focuses on high-risk parameters related to the current order conversion, achieving targeted data collection and management, avoiding excessive monitoring of irrelevant parameters, and improving efficiency.

[0091] Step S40: Combine the current parameter transition period of the printing equipment and the time limit coverage ratio of each high-stability fault parameter, calculate the data acquisition limit frequency of each fault parameter to be limited in the current parameter transition period, compare it with the preset data acquisition frequency of the printing equipment in the current parameter transition period, identify the fault parameters to be limited that need data acquisition frequency correction, and correct the data acquisition frequency through the data acquisition limit frequency.

[0092] In step S40, the process of calculating the data acquisition frequency limit for each fault parameter to be limited in the printing equipment during the current parameter transition period is as follows:

[0093] Based on any fault parameter to be defined;

[0094] Based on the time-limited coverage ratio of each high-stability fault parameter, determine the time-limited coverage ratio of the fault parameter to be limited;

[0095] It should be noted that the fault parameters to be limited are obtained based on the identification of high-stability fault parameters. Therefore, the time-limited coverage ratio of the fault parameters to be limited can be determined from the time-limited coverage ratio of each high-stability fault parameter.

[0096] The product of the current parameter transition period of the printing equipment and the time limit coverage ratio of the fault parameters to be limited is used to obtain the limited collection time of the fault parameters to be limited within the current parameter transition period of the printing equipment.

[0097] The ratio of the current parameter transition period of the printing equipment to the limited collection time of the fault parameter to be limited is calculated to obtain the data collection limit frequency of the fault parameter to be limited within the current parameter transition period.

[0098] For example, if the parameter transition period is 5 minutes (300,000 milliseconds), and the time limit coverage ratio of the fault parameter to be limited is 1 / 20, then the limited collection duration of the fault parameter to be limited is 15,000 seconds (to ensure effective traceability of the fault parameter to be limited when a paper jam occurs), and the data collection frequency of the fault parameter to be limited is 300,000 / 15,000 = 20 milliseconds / time.

[0099] In step S40, the process of identifying the fault parameters that require data acquisition frequency correction and correcting the data acquisition frequency by limiting the data acquisition frequency is as follows:

[0100] If the data acquisition frequency of the fault parameter to be limited during the current parameter transition period is higher than or equal to the preset data acquisition frequency, no operation will be performed.

[0101] If the data acquisition frequency of the fault parameter to be limited during the current parameter transition period is lower than the preset data acquisition frequency, the fault parameter to be limited needs to have its data acquisition frequency corrected.

[0102] It should be noted that the preset data acquisition frequency is pre-set by the printing equipment acquisition system. For example, conventional data acquisition systems focus on the stable production stage, and the data acquisition frequency will be automatically reduced during the parameter transition period (e.g., from 10ms / time to 100ms / time).

[0103] For fault parameters that require data acquisition frequency correction, the data acquisition frequency of the fault parameters to be limited is corrected according to the data acquisition frequency limit.

[0104] Understandably, the significance of step S40 lies in calculating the data acquisition frequency limit based on the current parameter transition period and the time-limited coverage ratio of the fault parameters to be limited. After comparing this frequency with the preset data acquisition frequency, parameters with frequencies lower than the preset frequency are corrected. This quantitative calculation ensures that the acquisition frequency of the fault parameters to be limited during the transition period meets the time coverage requirements, avoiding incomplete data due to insufficient acquisition frequency during the parameter transition period. Ultimately, this ensures effective traceability when paper jams occur, achieving precise data management for printing equipment.

[0105] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for intelligent maintenance and operation data management of printing equipment, characterized in that: Includes the following steps: Step S10: Perform fault source confirmation frequency and stability analysis on the historical paper jam fault traceability data of the printing equipment to confirm the high-stability fault parameters of the printing equipment. Step S20: Perform a fluctuation analysis on the time coverage ratio used when the high-stability fault parameters are repeatedly confirmed by fault source tracing, and confirm the time-limited coverage ratio of each high-stability fault parameter. The time coverage ratio represents the ratio between the total data acquisition time of the high-stability fault parameter and the parameter transition period when the high-stability fault parameter is identified as the root cause of the paper jam fault in each paper jam fault tracing and confirmation of the printing equipment. Among them, the parameter transition period refers to the duration of time required to adjust the operating parameters when switching between different specification orders; The process for confirming the time-limited coverage ratio of each high-stability fault parameter is as follows: The time coverage ratios used when high-stability fault parameters are repeatedly confirmed by fault source tracing are integrated to obtain a time coverage ratio sequence. The coefficient of variation of the time coverage ratio sequence is calculated to obtain the time coverage fluctuation value. The volatility of the time coverage ratio used when high-stability fault parameters are repeatedly confirmed by fault source tracing is judged based on the time coverage fluctuation value. If the volatility is weak, the time coverage ratio sequence is averaged to obtain the time-limited coverage ratio of the high-stability fault parameters. If the volatility is strong, the maximum value in the time coverage ratio sequence is selected as the time-limited coverage ratio of the high-stability fault parameters. Step S30: Obtain the parameter transition period between different specification order conversions through historical order conversion data, and determine the current parameter transition period of the printing equipment and identify the fault parameters to be limited among the high stability fault parameters by combining the current order specification conversion requirements; Step S40: Combine the current parameter transition period of the printing equipment with the time limit coverage ratio of each high-stability fault parameter, calculate the data acquisition limit frequency of each fault parameter to be limited in the current parameter transition period, compare it with the preset data acquisition frequency of the printing equipment in the current parameter transition period, identify the fault parameters to be limited that need data acquisition frequency correction, and correct the data acquisition frequency through the data acquisition limit frequency.

2. The intelligent maintenance and operation data management method for printing equipment according to claim 1, characterized in that: The process of confirming the high stability fault parameters of the printing equipment is as follows: If the operating parameters are identified as the root cause of the paper jam during paper jam troubleshooting in the printing equipment, then the operating parameters will be marked as paper jam fault parameters. The frequency and stability of the operating parameters marked as paper jam fault parameters are analyzed to obtain the paper jam fault frequency value and paper jam fault stability value of the operating parameters, and the high stability fault value of the operating parameters is obtained after deviation processing. If the high stability fault value meets the preset requirements, the operating parameter will be marked as a high stability fault parameter.

3. The intelligent maintenance and operation data management method for printing equipment according to claim 2, characterized in that: The paper jam failure frequency value of the operating parameters is obtained by statistically analyzing the proportion of times the operating parameters are marked as paper jam failure parameters in multiple paper jam failure tracing operations of the printing equipment.

4. The intelligent maintenance and operation data management method for printing equipment according to claim 3, characterized in that: The method for obtaining the stable value of the paper jam fault is as follows: The number of unmarked intervals between two consecutive times an operating parameter is marked as a paper jam fault parameter is counted. The number of unmarked intervals represents the number of times an operating parameter is marked as a non-paper jam fault parameter between two consecutive times it is marked as a paper jam fault parameter. By integrating the number of unmarked intervals between each two adjacent parameters marked as paper jam faults, an unmarked interval sequence is obtained. The coefficient of variation of the unmarked interval sequence is calculated to obtain the stable value of the paper jam fault.

5. The intelligent maintenance and operation data management method for printing equipment according to claim 1, characterized in that: The process of determining the current parameter transition period of the printing equipment is as follows: By using historical order conversion data, extract historical orders with the same specification conversion as the current order. If the current order specification is converted from 80g coated paper printing to 120g cardstock printing, then the historical orders are also converted from 80g coated paper printing to 120g cardstock printing. Obtain the parameter transition period of the historical orders during the conversion and integrate them into a parameter transition period set. Select the minimum parameter transition period from the parameter transition period set as the current parameter transition period for the printing equipment.

6. The intelligent maintenance and operation data management method for printing equipment according to claim 5, characterized in that: The process of identifying the fault parameters to be limited from the high-stability fault parameters is as follows: If a high stability fault parameter causes a paper jam in the printing equipment during a historical order conversion with the same specifications as the current order, then the high stability fault parameter will be marked as a fault parameter to be limited.

7. The intelligent maintenance and operation data management method for printing equipment according to claim 6, characterized in that: The process of calculating the data acquisition frequency limit for each fault parameter to be limited in the printing equipment during the current parameter transition period is as follows: Based on the time-limited coverage ratio of each high-stability fault parameter, determine the time-limited coverage ratio of the fault parameter to be limited; The product of the current parameter transition period of the printing equipment and the time limit coverage ratio of the fault parameters to be limited is used to obtain the limited collection time of the fault parameters to be limited within the current parameter transition period of the printing equipment. The ratio of the current parameter transition period of the printing equipment to the limited collection time of the fault parameters to be limited is calculated to obtain the data collection limit frequency of the fault parameters to be limited within the current parameter transition period.

8. The intelligent maintenance and operation data management method for printing equipment according to claim 7, characterized in that: The process of identifying fault parameters that require data acquisition frequency correction and then correcting the data acquisition frequency by limiting the data acquisition frequency is as follows: If the data acquisition frequency of the fault parameter to be limited during the current parameter transition period is lower than the preset data acquisition frequency, the fault parameter to be limited needs to have its data acquisition frequency corrected, and the data acquisition frequency of the fault parameter to be limited should be corrected according to the data acquisition frequency limit.

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