A detection frequency adjustment method for an archive room device and a related device

Abstract

The application provides a detection frequency adjustment method for an archive warehouse device and related equipment, and relates to the technical field of intelligent operation and maintenance of archive warehouse devices. The method comprises the following steps: calculating an environmental deviation amplitude of a current environmental parameter in the archive warehouse relative to a preset environmental standard value; calculating a maintenance demand index and an archive vulnerability index according to the environmental deviation amplitude, a device fault risk level of a target component and an archive sensitivity level; obtaining a time correction step length based on an index difference value mapping; if the maintenance demand index is greater than or equal to the archive vulnerability index, the time correction step length is deducted from the remaining waiting time length of the current detection cycle, so that the next detection action is performed in advance; otherwise, the time correction step length is added to the remaining waiting time length of the current detection cycle, so that the next detection action is delayed. The method can ensure that the mechanical performance of the device is in a controlled state while reducing the physical damage risk caused by the action performed during the archive fragile period.

Description

Technical Field

[0001] This application relates to the field of intelligent operation and maintenance technology for archive storage equipment, and in particular to a method and related equipment for adjusting the detection frequency of archive storage equipment. Background Technology

[0002] Intelligent mobile shelving units, as core equipment in modern archives, undertake the task of high-density storage of paper archives, ancient books and documents, and precision objects. To ensure that the transmission components (such as motors, chains, and bearings) of the mobile shelving system are always in good mechanical condition, periodic functional testing and maintenance are required. This involves driving each row of shelves to perform physical actions such as opening and closing, braking, and positioning to verify the integrity of the components and prevent corrosion, jamming, or lubrication failure caused by prolonged inactivity.

[0003] The relevant technologies primarily employ adaptive detection strategies based on environmental perception or risk assessment. Specifically, when the monitoring system detects adverse changes in the warehouse environment (such as a significant increase in air humidity, drastic temperature fluctuations, or increased dust concentration), the system can determine, based on equipment maintenance logic, that the risk of corrosion or the probability of failure of mechanical components will increase significantly. Based on this determination, the system can automatically adjust the detection plan, strengthening the inspection of equipment by shortening the detection cycle and increasing the frequency of physical actions, striving to detect potential mechanical hazards as early as possible and ensure that the equipment operates without defects.

[0004] However, when the storage environment becomes abnormal (such as frequent power outages in summer leading to continuous high humidity and heat), not only are the metal parts of the equipment prone to corrosion, but the paper archives or ancient documents stored in the mobile shelving may also soften due to moisture absorption, resulting in a significant decrease in paper strength and entering a "vulnerable period" with extremely unstable physical properties. At this time, if the system only follows the equipment maintenance logic and forcibly executes high-frequency mechanical motion detection, the micro-vibrations, inertial impacts, and shelf resonances generated during the frequent start-stop and braking of the mobile shelving will be directly transmitted to the archives in their most vulnerable state, easily inducing irreversible physical damage events such as the adhesion and breakage of ancient books or the displacement and damage of cultural relics. Summary of the Invention

[0005] This application provides a method and related equipment for adjusting the detection frequency of archival storage equipment, which addresses the problem that related technologies increase the detection frequency based on the risk of equipment failure when the environment is abnormal, ignoring the weakening effect of the environment on the stored entities, resulting in high-frequency mechanical detection actions easily causing physical damage to archives in a fragile state.

[0006] Firstly, this application provides a method for adjusting the detection frequency of archival storage equipment, the method comprising: Collect current environmental parameters within the archive storage room and calculate the environmental deviation of the current environmental parameters relative to preset environmental standard values; A maintenance demand index characterizing the urgency of equipment maintenance is calculated based on the environmental deviation magnitude and the equipment failure risk level of the target component. The equipment failure risk level is determined based on the historical failure frequency and failure impact of the target component. The maintenance demand index increases monotonically with the increase of the environmental deviation magnitude. Based on the environmental deviation magnitude and the sensitivity level of the target component, an archive vulnerability index characterizing the archive's tolerance to detection actions is calculated. The archive vulnerability index increases non-linearly with the increase of the environmental deviation magnitude. Calculate the index difference between the maintenance demand index and the archive fragility index, and obtain the time correction step based on the index difference; Determine whether the maintenance demand index is greater than or equal to the file fragility index; If so, the time correction step size is deducted from the remaining waiting time of the current detection cycle, so that the next detection action is executed in advance; If not, the time correction step is added to the remaining waiting time of the current detection cycle, so that the next detection action is postponed.

[0007] By adopting the above technical solution, the system dynamically adjusts the timing of detection based on the degree of influence of environmental deviations on the urgency of equipment maintenance and the physical sensitization effect of the environment on the archives. This ensures that the mechanical performance of the equipment is under control while reducing the risk of physical damage caused by actions performed during the vulnerable period of the archives.

[0008] In some embodiments, the step of determining the equipment failure risk level based on the historical failure frequency and failure impact of the target component specifically includes: Obtain the number of failures of the target component within a preset historical period and the average downtime caused by a single failure; The number of failures is mapped to a frequency score within a first preset interval, and the average downtime is mapped to a severity score within a second preset interval. A comprehensive risk score for the target component is determined based on the frequency score and the severity score, and the equipment failure risk level of the target component is determined based on the score interval corresponding to the comprehensive risk score, wherein the score interval corresponds one-to-one with the equipment failure risk level.

[0009] By adopting the above technical solution, the system incorporates the historical operational data dimension of equipment components, mapping fault frequency and downtime into a concrete risk level. This transforms maintenance requirement assessment from a single environmental extrapolation into a multi-dimensional comprehensive diagnosis, ensuring that the calculated maintenance urgency more objectively reflects the true health status and historical stability of the target components, and improving the targeting and accuracy of decisions regarding the timing of inspections.

[0010] In some embodiments, the step of calculating the maintenance demand index characterizing the urgency of equipment maintenance based on the environmental deviation magnitude and the equipment failure risk level of the target component specifically includes: The duration of the abnormal environmental deviation is monitored to obtain the duration of the abnormality. The time-accumulation factor is obtained by mapping the duration of the anomaly, and the time-accumulation factor characterizes the cumulative corrosion effect of long-term environmental anomalies on equipment components; The environmental deviation magnitude is weighted and compensated using the aforementioned time-accumulation factor to obtain the comprehensive environmental load value. The maintenance demand index is calculated by positively correcting the equipment failure risk level based on the comprehensive environmental load value.

[0011] By adopting the above technical solution, the system generates a time-accumulation factor based on the duration of environmental anomalies to characterize the cumulative corrosion effect on equipment components caused by prolonged harsh operating conditions. By weighting and compensating for environmental load and correcting the risk level, the maintenance demand index can sensitively capture the gradual wear caused by continuous environmental anomalies, ensuring that the adjustment of the detection frequency better matches the actual cumulative fatigue level of the equipment.

[0012] In some embodiments, the step of calculating the archive vulnerability index, which characterizes the archive's tolerance to detection actions, based on the environmental deviation magnitude and the archive sensitivity level of the target component, specifically includes: Multiple sets of environmental parameters are collected within a preset sliding time window, and fluctuation characteristic values ​​are calculated based on the multiple sets of environmental parameters. The fluctuation characteristic values ​​characterize the steady-state damage degree of the environmental parameters and the repeated stretching fatigue effect on the archival fibers. A basic vulnerability value is obtained based on the environmental deviation amplitude mapping, and the fluctuation characteristic value is used as an amplification factor to amplify the basic vulnerability value to obtain a corrected vulnerability coefficient. The basic vulnerability value follows a preset nonlinear surge rule as the environmental deviation amplitude increases. The product of the modified fragility coefficient and the sensitivity level of the archive is calculated to obtain the archive fragility index.

[0013] By employing the above technical solution, the system extracts environmental fluctuation feature values ​​based on a sliding time window, identifying the repeated stretching and fatigue effects of environmental oscillations on archival fibers. This feature is then used to nonlinearly amplify the basic vulnerability value, ensuring that the archival vulnerability index more accurately depicts the decline in the archive's resilience under stress fluctuations.

[0014] In some embodiments, after the step of adding the time correction step to the remaining waiting time of the current detection cycle, thereby delaying the execution of the next detection action, the method further includes: The cumulative lag time is obtained by statistically analyzing the consecutive delay operations performed for the current detection action to be executed and summing the time correction step size corresponding to each delay operation. When the cumulative lag time exceeds the preset safety circuit breaker threshold, an immediate detection start command is generated, and the system enters a forced detection state.

[0015] By adopting the above technical solution, the system monitors the cumulative lag time caused by continuous delayed operations and sets a safety circuit breaker threshold for the waiting period. When the cumulative delay is too long, a forced detection is triggered. This mechanism prevents the equipment from being indefinitely suspended for testing due to the environment being in a sensitive state for a long time, and curbs the risk of the equipment functioning to completely stop due to excessive protection of files or rusting and jamming due to long-term inactivity.

[0016] In some embodiments, the step of generating the instant detection startup command specifically includes: Acquire multiple alternative detection methods for the target component and determine the vibration intrusion level corresponding to each alternative detection method; The candidate detection method with the lowest vibration intrusion level is selected as the target detection method; Generate an instant detection start command that includes the target detection method.

[0017] By adopting the above technical solution, the system evaluates the vibration intrusion level of multiple alternative detection methods under forced detection scenarios and uses this as the selection criterion. By selecting the detection mode with the least physical disturbance, "flexible" verification is performed to ensure that even under extreme working conditions where detection must be initiated, the physical impact transmitted to the archived entity can be minimized.

[0018] In some embodiments, after the step of determining whether the maintenance demand index is greater than or equal to the file fragility index, the method further includes: Obtain preset detection operation parameters, including the number of detection personnel, the power of the detection equipment, and the estimated operation time; Based on the aforementioned testing operation parameters, estimate the expected fluctuation values ​​of environmental parameters within the archive storage area during the execution of the testing action; Calculate the sum of the current environmental parameters and the expected fluctuation value, and determine whether the sum exceeds the preset threshold range for secure file storage; If so, an environmental pre-compensation command is generated, and the environmental adjustment equipment is driven to pre-adjust the environmental parameters in the archive storage room in the opposite direction to the expected fluctuation value before the detection action begins, until the superposition value of the adjusted environmental parameters and the expected fluctuation value falls within the preset threshold range.

[0019] By adopting the above technical solution, the system predicts and analyzes the environmental fluctuations caused by detection actions, and drives the equipment to pre-adjust environmental parameters in the opposite direction when the risk exceeds the limit. This proactive intervention strategy reserves a buffer safety margin before the action is executed, and artificially constructs a micro-environment window that meets safety standards, so that even when environmental parameters are critical, necessary detection actions can be implemented within a controlled safety range.

[0020] Secondly, this application provides a detection frequency adjustment system for archive storage equipment, the system comprising: one or more processors and a memory; The memory is coupled to the one or more processors. The memory is used to store computer program code, which includes computer instructions. The one or more processors call the computer instructions so that the system can implement the detection frequency adjustment method for archive storage equipment provided in the above embodiment, which will not be described in detail here.

[0021] Thirdly, this application provides a computer-readable storage medium including instructions that, when executed on a detection frequency adjustment system for archive storage equipment, enable the system to implement a detection frequency adjustment method for archive storage equipment provided in the above embodiments, which will not be elaborated here.

[0022] Fourthly, this application provides a computer program product, including a computer program / instruction. When the computer program / instruction is run on a detection frequency adjustment system for archive storage equipment, the system can implement a detection frequency adjustment method for archive storage equipment provided in the above embodiments, which will not be elaborated here.

[0023] One or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages: 1. The system quantifies the risk of corrosion / seizing of mechanical parts caused by environmental deviations (maintenance demand index) and the risk of softening / fragility of archival fibers (archival fragility index). By comparing the urgency of the two, it determines whether the detection action should be "advanced" or "delayed". This solves the deep contradiction that equipment urgently needs active rust prevention in extreme environments such as humidity and heat, while archives, due to their fragility, urgently need static protection. It achieves a precise balance between ensuring the mechanical performance of equipment and the physical protection of precious objects.

[0024] 2. The system incorporates a safety circuit breaker logic based on cumulative lag time. Once the delayed operation exceeds the safety threshold, the system will no longer compromise indefinitely, but will forcibly initiate detection to prevent complete equipment failure. This forced execution is not a crude intervention, but rather combines a "vibration intrusion" screening mechanism to automatically select the alternative detection method with the least physical disturbance, ensuring that even in extreme operating conditions where a deadlock must be broken, the core function verification can still be completed with the lowest possible mechanical impact.

[0025] 3. The system can predict environmental fluctuations that may be caused by the detection operation itself (personnel entry, equipment heating, etc.) and calculate its superposition effect with the current parameters. When the prediction results indicate a risk of exceeding limits, the system will drive the regulating equipment to perform reverse pre-adjustment (such as pre-cooling or pre-dehumidification) before the action begins, artificially creating a "safety buffer zone" for environmental parameters. This feedforward control mechanism ensures that necessary operation and maintenance activities can still be safely carried out within a controlled and compliant micrometeorological window under critical environmental conditions. Attached Figure Description

[0026] Figure 1 This is a flowchart illustrating a method for adjusting the detection frequency of archive storage equipment in an embodiment of this application; Figure 2 This is another flowchart illustrating a method for adjusting the detection frequency of archive storage equipment in this application embodiment; Figure 3 This is a schematic diagram of a physical device structure for a detection frequency adjustment system for archive storage equipment in this application embodiment. Detailed Implementation

[0027] The terminology used in the following embodiments of this application is for the purpose of describing particular embodiments only and is not intended to be limiting of this application. As used in the specification and appended claims of this application, the singular expressions “a,” “an,” “the,” “the,” “the,” and “this” are intended to include the plural expressions as well, unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used in this application refers to any or all possible combinations including one or more of the listed items.

[0028] Hereinafter, the terms "first" and "second" are used for descriptive purposes only and should not be construed as implying or suggesting relative importance or implicitly indicating the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature, and in the description of the embodiments of this application, unless otherwise stated, "multiple" means two or more.

[0029] There is a dynamic balance between the stable operation of archival storage equipment and the secure storage of archival materials. Abnormal environments can easily lead to equipment malfunctions requiring increased monitoring, while archival materials may become vulnerable to the physical disturbances caused by environmental factors and cannot withstand the physical disturbances of monitoring. Therefore, this application scientifically adjusts the monitoring frequency by combining environmental conditions, equipment risks, and the resilience of the archives, thus ensuring both equipment maintenance needs are met and preventing damage to the archives. Please refer to [link / reference] for details. Figure 1 This is a flowchart illustrating a method for adjusting the detection frequency of archive storage equipment in an embodiment of this application.

[0030] S101. Collect the current environmental parameters in the archive storage room and calculate the environmental deviation of the current environmental parameters relative to the preset environmental standard value.

[0031] Among them, the current environmental parameters refer to the environmental data related to equipment operation and archive storage that are monitored in real time in the archive storage room, including air humidity, temperature, dust concentration, etc.; the preset environmental standard values ​​refer to the environmental parameter standard range that is set in advance based on the requirements for safe storage of archives and the normal operation of equipment; the environmental deviation range refers to the degree of deviation between the current environmental parameters and the preset environmental standard values.

[0032] This step is performed at the initial stage of the system's detection frequency adjustment process. It is applicable to all scenarios where the detection frequency of the archive storage equipment needs to be dynamically adjusted. Whether it is a situation of slow environmental changes in daily operation and maintenance or a situation of sudden environmental anomalies (such as a power outage causing a sudden change in temperature and humidity), it is necessary to obtain basic environmental data through this step first.

[0033] Specifically, the system activates various environmental sensors deployed within the archive storage room. These sensors capture key environmental data such as humidity, temperature, and dust concentration in real time, forming a set of current environmental parameters. Subsequently, the system retrieves pre-stored preset environmental standard values. These standard values ​​are determined by considering the optimal environmental conditions for archive storage (e.g., a suitable humidity range of 45%-60% and a temperature range of 14℃-24℃ for paper archives) and the environmental requirements for normal equipment operation. Finally, by calculating the difference between each current environmental parameter and its corresponding preset standard value (or, if it's a range standard value, calculating the deviation from the range boundary), the overall environmental deviation is obtained.

[0034] Furthermore, the system can also employ a weighted modulus method when calculating environmental deviations. For humidity parameters, the focus is on positive deviations (high humidity), as these directly lead to rusting and paper softening; for temperature parameters, the focus is on drastic fluctuations. For example, if the standard humidity is set at 50%, and the current humidity is 70%, the relative deviation is +0.4 (i.e., 40%). This deviation value will serve as the basic physical quantity input for subsequent risk calculations.

[0035] In some embodiments, the system can simultaneously start data acquisition by controlling humidity sensors, temperature sensors, and dust sensors distributed in different areas of the warehouse (such as the top, middle, and bottom of the mobile shelving, and the corners and center of the warehouse), collecting data once every 5 seconds for 10 consecutive times; averaging the collected environmental data of the same type each time to obtain the current stable value of each type of environmental parameter; retrieving preset environmental standard values, for each type of environmental parameter, if the current stable value is higher than the upper limit of the standard value, the difference between the current stable value and the upper limit of the standard value is calculated as the deviation amplitude of the parameter; if it is lower than the lower limit of the standard value, the difference between the lower limit of the standard value and the current stable value is calculated as the deviation amplitude of the parameter; if it is within the standard range, the deviation amplitude is 0; according to the weight ratio of the impact of each environmental parameter on the equipment and archives (such as humidity weight 0.4, temperature weight 0.3, dust concentration weight 0.3), the weighted sum of the deviation amplitudes of each parameter is calculated to obtain the final environmental deviation amplitude.

[0036] S102. The maintenance demand index, which characterizes the urgency of equipment maintenance, is calculated based on the environmental deviation range and the equipment failure risk level of the target component.

[0037] Among them, the target component refers to the core components of the archive storage equipment that need to be inspected and maintained, such as the transmission components of intelligent mobile shelving, such as motors, chains, and bearings; the equipment failure risk level is determined based on the historical failure frequency and failure impact of the target component, and is used to characterize the possibility of the target component failing and the severity of the consequences of the failure; the maintenance demand index is a quantitative indicator obtained by combining the environmental deviation range and the equipment failure risk level, and is used to reflect the urgency of equipment maintenance, and this index increases monotonically with the increase of the environmental deviation range.

[0038] Specifically, the system obtains the equipment failure risk level of the identified target component, which is derived by analyzing the component's past failure data. Next, combining this with the previously calculated environmental deviation range, and considering that a larger environmental deviation indicates more severe corrosion and wear on the equipment component, leading to more urgent maintenance needs, and that the maintenance demand index monotonically increases with the environmental deviation range, a preset algorithm is used to integrate the environmental deviation range and the equipment failure risk level. For example, a higher equipment failure risk level corresponds to a higher basic maintenance demand, which is then proportionally increased based on the magnitude of the environmental deviation, ultimately yielding a maintenance demand index that accurately reflects the current urgency of equipment maintenance.

[0039] In some embodiments, the system can retrieve the base score corresponding to the equipment failure risk level of the target component (e.g., 8 points for high risk, 5 points for medium risk, and 3 points for low risk); determine the amplification coefficient based on the environmental deviation range, with a higher amplification coefficient for a larger environmental deviation range (e.g., coefficient 1.0 for a deviation range of 0-10%, coefficient 1.2 for 10%-20%, and coefficient 1.5 for above 20%); and multiply the base score by the amplification coefficient to obtain the maintenance demand index (e.g., for a medium-risk component with a 15% environmental deviation range, the maintenance demand index = 5 × 1.2 = 6).

[0040] Optionally, the system can also establish a correspondence table between environmental deviation range and basic maintenance demand increment (e.g., 5% deviation range corresponds to increment 1, 10% corresponds to increment 2, 15% corresponds to increment 3, etc.), and query the corresponding basic increment based on the current environmental deviation range; determine the risk weight based on the equipment failure risk level (high risk weight 0.6, medium risk weight 0.4, low risk weight 0.2); calculate the product of the basic increment and the risk weight, and add the initial score corresponding to the equipment failure risk level (high risk initial score 6, medium risk initial score 4, low risk initial score 2) to obtain the maintenance demand index (e.g., for low-risk components corresponding to a 10% environmental deviation range, the maintenance demand index = 2 + 2 × 0.2 = 2.4).

[0041] S103. The archive vulnerability index, which characterizes the archive's tolerance to detection actions, is calculated based on the environmental deviation range and the archive sensitivity level of the target component.

[0042] Among them, the archive sensitivity level refers to the classification of the sensitivity of archives to detection actions and environmental changes, which is determined based on the type, rarity, and preservation status of the archives; the archive vulnerability index is a quantitative indicator obtained by combining the environmental deviation range and the archive sensitivity level, used to characterize the archives' tolerance to detection actions, and this index increases non-linearly with the increase of the environmental deviation range.

[0043] Specifically, the system acquires the sensitivity level of the target component. Different types of archives (such as ancient books and documents, ordinary paper archives, and precision physical archives) have different sensitivity levels, with precious and fragile archives having higher sensitivity levels. Then, it combines the environmental deviation range. Since the greater the environmental deviation, the more unstable the physical properties of the archive (such as fiber softening and strength reduction), the lower its tolerance to detection actions. Moreover, this decrease in tolerance is not linear. After the environmental deviation exceeds a certain threshold, the vulnerability of the archive will increase sharply. Therefore, a preset nonlinear algorithm is used to fuse the environmental deviation range and the archive sensitivity level to calculate the final archive vulnerability index, which can accurately reflect the current tolerance of the archive to detection actions.

[0044] In some embodiments, the system can obtain the basic vulnerability score corresponding to the sensitivity level of the archive (7 points for high sensitivity, 4 points for medium sensitivity, and 2 points for low sensitivity); establish a mapping relationship between the environmental deviation range and the nonlinear growth coefficient (e.g., a deviation range of 0-10% corresponds to a coefficient of 1.0, 10%-20% corresponds to a coefficient of 1.5, 20%-30% corresponds to a coefficient of 2.5, and above 30% corresponds to a coefficient of 4.0), obtain the corresponding growth coefficient based on the current environmental deviation range; multiply the basic vulnerability score by the growth coefficient to obtain the archive vulnerability index (e.g., for high-sensitivity archives with a 25% environmental deviation range, the archive vulnerability index = 7 × 2.5 = 17.5).

[0045] In some specific embodiments, the archive vulnerability index increases non-linearly with the increase of environmental deviation. Specifically, the system can use an exponential growth model for fitting. The formula for calculating the archive vulnerability index is: Among them, the environmental deviation range is The sensitivity level of the archives is L (value 1-5), and the vulnerability index of the archives is [missing information]. k is a preset material susceptibility coefficient (e.g., k is 1.5 for paper archives and 0.8 for film archives).

[0046] It should be noted that, to ensure the numerical comparability of the "Maintenance Needs Index" and the "Archival Fragility Index," a normalization module is pre-implemented before subsequent comparisons. For example, the system sets the numerical output range for both to be a dimensionless interval of [0, 100]. Specifically, for equipment, a state of "immediate jamming failure" corresponds to 100 points; for archives, an extreme fragile state of "paper crumbling upon contact" corresponds to 100 points. Through this isomorphic mapping, the numerical comparison in S105 is essentially a trade-off between the "expected economic loss due to equipment failure risk" and the "expected value loss due to physical damage to archives."

[0047] S104. Calculate the index difference between the maintenance demand index and the file fragility index, and obtain the time correction step based on the index difference mapping.

[0048] Among them, the index difference refers to the value obtained by subtracting the file vulnerability index from the maintenance demand index, which is used to reflect the imbalance between equipment maintenance needs and file tolerance; the time correction step is the amount of time determined based on the index difference to adjust the remaining waiting time of the detection cycle, which is the core parameter for realizing the adjustment of the detection frequency.

[0049] Specifically, the system calculates the difference between the maintenance demand index and the archive vulnerability index. A positive difference indicates that the equipment maintenance demand exceeds the archive's risk tolerance; a negative difference indicates that the archive's risk tolerance exceeds the equipment maintenance demand; and a zero difference indicates that the two are in a relatively balanced state. The system then retrieves a preset mapping table between the index difference and the time correction step size. This table is based on extensive experimental data and practical maintenance experience. Different index differences correspond to different time correction steps; the larger the absolute value of the index difference, the longer the corresponding time correction step size. This allows for precise adjustment of the detection cycle based on the degree of imbalance between equipment and archive needs.

[0050] Optionally, the system can retrieve the specific values ​​of the maintenance demand index and the file fragility index. For example, if the maintenance demand index is 8.5 and the file fragility index is 5.2, the index difference can be calculated as 8.5 - 5.2 = 3.3. The system can then retrieve a preset mapping table, which specifies that an index difference of 0-1 corresponds to a time correction step of 1 hour, 1-2 corresponds to 2 hours, 2-3 corresponds to 3 hours, and 3 and above corresponds to 4 hours. Based on the calculated index difference of 3.3, the system can query the mapping table to obtain the corresponding time correction step of 4 hours. The system can then verify the mapped time correction step to ensure that it is within a preset reasonable range (e.g., 0.5 hours to 8 hours). If it exceeds this range, the boundary value of the range will be used.

[0051] Optionally, the system can also maintain an internal "Risk-Time Dynamic Adjustment Table." For example, when the index difference (maintenance-vulnerability) is in the range [0, 10], the step size is set to 2 hours; in the range [10, 30], the step size is set to 6 hours; and in the range [30, 50], the step size is set to 12 hours. This tiered mapping mechanism prevents the system from frequently adjusting the detection plan due to minor numerical fluctuations, ensuring the stability of operation and maintenance scheduling.

[0052] S105. Determine whether the maintenance demand index is greater than or equal to the file fragility index.

[0053] Specifically, the system compares the maintenance demand index and the file vulnerability index to determine whether the maintenance demand index reaches or exceeds the file vulnerability index. The purpose is to clarify the priority of equipment maintenance needs and file protection needs in the current scenario: if the maintenance demand index is greater than or equal to the file vulnerability index, it indicates that the risk of equipment failure and the urgency of maintenance are higher, and the system proceeds to step S106 to determine that equipment maintenance needs to be prioritized; if the maintenance demand index is less than the file vulnerability index, it indicates that the file has extremely low tolerance to detection actions, and the system proceeds to step S107 to determine that the detection actions may cause serious damage to the file, and the file needs to be protected first.

[0054] S106. Deduct the time correction step from the remaining waiting time of the current detection cycle so that the next detection action is executed in advance.

[0055] The remaining waiting time for the current testing cycle refers to the time from the current moment to the execution time of the next testing action according to the original testing plan; early execution means adjusting the execution time of the next testing action forward, and conducting the test earlier than the originally planned time.

[0056] Specifically, the system queries the original plan information for the current detection cycle to determine the original execution time of the next detection action, and then calculates the remaining waiting time between the current time and the original execution time. Subsequently, the previously obtained time correction step is subtracted from this remaining waiting time to obtain a new remaining waiting time. The execution time corresponding to the new remaining waiting time is the actual execution time of the next detection action, which is earlier than the originally planned execution time. This allows for the early execution of detection actions, timely equipment inspection and maintenance, and reduces the risk of equipment failure.

[0057] Optionally, the system can retrieve the original detection plan, obtain the original execution time of the next detection action as 10:00 AM the following day, the current time as 3:00 PM the current day, and calculate the remaining waiting time as 19 hours; retrieve the previously obtained time correction step size as 4 hours; subtract the time correction step size from the remaining waiting time, i.e., 19-4=15 hours, to obtain the new remaining waiting time; based on the current time and the new remaining waiting time, calculate the actual execution time of the next detection action as 6:00 AM the following day, and generate a detection reminder instruction to ensure that relevant personnel or equipment perform the detection on time.

[0058] S107. Add a time correction step to the remaining waiting time of the current detection cycle, so that the next detection action is postponed. Delayed execution refers to adjusting the execution time of the next detection action to be later than originally planned, so that the detection is carried out later.

[0059] Specifically, the system queries the original plan information for the current detection cycle to determine the original execution time of the next detection action and the remaining waiting time corresponding to the current moment. Then, it adds the time correction step to this remaining waiting time to obtain the extended remaining waiting time. The execution time corresponding to the extended remaining waiting time is the actual execution time of the next detection action, which is later than the originally planned execution time. This achieves the postponement of the detection action, providing a more stable preservation environment for the archives and reducing the risk of damage caused by the detection action.

[0060] In some embodiments, the system can also obtain the current remaining waiting time as 48 hours through the detection cycle management module; confirm that the time correction step is 5 hours, and that the increased remaining waiting time does not exceed the preset maximum detection cycle (e.g., if the original detection cycle is 7 days, it can be extended to a maximum of 10 days, i.e., 240 hours, 48+5=53 hours < 240 hours); update the remaining waiting time and adjust it to 53 hours; generate a detection postponement record, detailing the original execution time, the adjusted execution time, the time correction step, and the reason for the adjustment. It is understood that other methods can also be used to postpone the execution of detection actions, such as setting a maximum postponement time limit or dynamically adjusting the correction step based on the file status, etc., which are not limited here.

[0061] In practice, the system can generate a "Timer_Update" instruction and send it to the main control board (MCU) of the mobile shelving unit. After receiving the instruction, the main control board rewrites the interrupt trigger register value of the internal RTC (real-time clock) and postpones the original wake-up time by the calculated correction step, thereby suspending the self-test drive circuit of the motor at the physical level.

[0062] To further improve the accuracy, safety, and comprehensiveness of inspection frequency adjustments, this application addresses potential issues in the core framework, such as one-sided risk assessment, coarse index calculation, and loss of control in extreme scenarios, by refining the logic for determining equipment failure risk levels, optimizing the calculation dimensions of maintenance demand index and archive vulnerability index, adding a safety circuit breaker mechanism for delayed inspection, optimizing the low-disturbance method for mandatory inspection, and supplementing the environmental pre-compensation process before inspection. This ensures that in complex and ever-changing warehouse environments, it can accurately balance the needs of equipment maintenance and archive protection while avoiding secondary risks caused by excessive adjustments. Please refer to [link / reference] for details. Figure 2 This is another flowchart illustrating a method for adjusting the detection frequency of archive storage equipment in this application.

[0063] S201. Obtain the number of failures of the target component within a preset historical period and the average downtime caused by a single failure.

[0064] Among them, the preset historical period refers to the time range for statistical analysis of target component failure data, which can be determined based on component characteristics and operation and maintenance experience, such as 1 year, 6 months, etc.; the number of failures refers to the total number of times the target component fails within the preset historical period, which is used to reflect the frequency of component failures; the average downtime caused by a single failure refers to the average time taken from the occurrence of each failure to normal operation after repair, which is used to reflect the degree of impact of the failure on equipment operation.

[0065] This step is performed before calculating the equipment failure risk level. It is a crucial step in obtaining basic failure data and is suitable for scenarios where it is necessary to assess the risk level of components based on historical failure information.

[0066] Specifically, the system obtains the specific type of the target component (such as the motor or chain of a mobile shelving unit), and then retrieves the fault records of that target component from the equipment maintenance database according to a preset historical period (such as the last 12 months). It extracts the occurrence time and repair completion time of each fault from the fault records and counts the number of faults occurring within that period. Simultaneously, it calculates the downtime for each fault (repair completion time minus fault occurrence time), and then sums all the single downtimes and divides them by the number of faults to obtain the average downtime caused by a single fault, ensuring that the acquired data accurately reflects the historical fault status of the target component.

[0067] S202. Map the number of failures to a frequency score within a first preset interval, and map the average downtime to a severity score within a second preset interval.

[0068] The first preset interval refers to a pre-defined scoring range for dividing the number of fault occurrences. The interval boundaries and corresponding scores are determined based on a reasonable distribution of component fault frequencies. The frequency score is the score obtained by mapping the number of fault occurrences to the first preset interval, used to quantify the frequency of component faults. The second preset interval refers to a pre-defined scoring range for dividing the average downtime, and the interval division needs to be combined with the severity gradient of the fault impact. The severity score is the score obtained by mapping the average downtime to the second preset interval, used to quantify the severity of the fault's impact on equipment operation.

[0069] Specifically, the system retrieves a preset first interval and its corresponding frequency scoring rules (e.g., 0-2 fault occurrences correspond to the first interval with a frequency score of 3; 3-5 fault occurrences correspond to the second interval with a frequency score of 6; 6 or more fault occurrences correspond to the third interval with a frequency score of 10). Based on the number of fault occurrences obtained in S201, the system determines the first preset interval to which the fault belongs, and then maps it to obtain the corresponding frequency score. Subsequently, it retrieves a preset second interval and its corresponding severity scoring rules (e.g., average downtime of 0-1 hour corresponds to the first interval with a severity score of 2; 1-3 hours corresponds to the second interval with a severity score of 5; 3 hours or more corresponds to the third interval with a severity score of 8). Based on the average downtime obtained in S201, the system determines the second preset interval to which the average downtime belongs, and maps it to obtain the corresponding severity score, ensuring that the score accurately reflects the frequency and impact of the fault.

[0070] In some embodiments, the system can retrieve a first preset interval configuration table, which specifies the frequency scores (2, 5, 8, and 10 points) corresponding to the fault occurrence intervals (0-1 times, 2-4 times, 5-8 times, 9 times and above); compare the fault occurrence count obtained in S201 (e.g., 7 times) with the interval in the configuration table, determine that it belongs to the 5-8 times interval, and map it to obtain a frequency score of 8 points; retrieve a second preset interval configuration table, which specifies the severity scores (1, 4, 7, and 9 points) corresponding to the average downtime intervals (0-0.5 hours, 0.5-2 hours, 2-4 hours, 4 hours and above); compare the average downtime obtained in S201 (e.g., 3 hours) with the interval in the configuration table, determine that it belongs to the 2-4 hours interval, and map it to obtain a severity score of 7 points; record the mapped frequency score and severity score, and simultaneously mark the corresponding interval affiliation.

[0071] S203. Determine the comprehensive risk score of the target component based on the frequency score and severity score, and determine the equipment failure risk level of the target component based on the score range corresponding to the comprehensive risk score.

[0072] Among them, the comprehensive risk score refers to the score obtained by fusing the frequency score and the severity score through a preset algorithm, which is used to comprehensively reflect the failure risk level of the target component; the score interval corresponding to the comprehensive risk score refers to the pre-set comprehensive score range used to divide different risk levels, and each interval corresponds to a unique equipment failure risk level; the equipment failure risk level refers to the graded description of the failure risk of the target component, such as low risk, medium risk, high risk, etc., which is used to intuitively reflect the risk status of the component.

[0073] Specifically, the system retrieves a preset comprehensive risk score calculation rule, which specifies the fusion method for frequency and severity scores (such as weighted summation, product normalization, etc.). Based on this rule, the frequency and severity scores obtained in S202 are fused and calculated to obtain a comprehensive risk score. Subsequently, a preset correspondence table between score ranges and equipment failure risk levels is retrieved (e.g., a comprehensive risk score of 0-4 corresponds to low risk, 5-7 to medium risk, and 8-10 to high risk). Based on the calculated comprehensive risk score, its corresponding score range is determined, thereby obtaining the corresponding equipment failure risk level, ensuring that the risk level comprehensively reflects the component's failure risk.

[0074] Optionally, the system can retrieve preset fusion rules, specifying that the frequency score weight is 0.4 and the severity score weight is 0.6, and the comprehensive risk score = frequency score × 0.4 + severity score × 0.6; substituting the frequency score (e.g., 8 points) and severity score (e.g., 7 points) obtained from S202, the comprehensive risk score is calculated as 8 × 0.4 + 7 × 0.6 = 3.2 + 4.2 = 7.4 points; the system retrieves the table corresponding to the score range and risk level, where 0-4 points correspond to low risk, 4-7 points correspond to medium risk, and 7-10 points correspond to high risk; the system determines that the comprehensive risk score of 7.4 points falls within the 7-10 point range, and the corresponding equipment failure risk level is high risk; a risk level determination report is generated, recording the frequency score, severity score, comprehensive risk score, and final risk level, and archived for future reference.

[0075] S204. Monitor the duration of environmental deviations within the abnormal range to obtain the duration of the abnormality and the corresponding cumulative factor.

[0076] Among them, the abnormal range refers to the range in which the preset environmental deviation exceeds the normal allowable range, that is, the environmental deviation is not within the reasonable fluctuation range, indicating that the environment is in an abnormal state; the duration of abnormality refers to the length of time that the environmental deviation remains in the abnormal range, which is used to reflect the degree of persistence of environmental abnormality; the time accumulation factor is a coefficient mapped based on the duration of abnormality, which is used to characterize the cumulative corrosion effect of long-term environmental abnormality on equipment components. The longer the duration of abnormality, the larger the time accumulation factor.

[0077] Specifically, the system retrieves a preset normal range for environmental deviation (e.g., ±10% is considered normal) and monitors in real time whether the current environmental deviation is within this range. When the environmental deviation exceeds the normal range, a timing function is activated. Timing continues until the deviation returns to normal, at which point the timing stops; this duration is the duration of the anomaly. Subsequently, a preset mapping table between the duration of the anomaly and the cumulative effect factor is retrieved (e.g., factor 1.0 for 0-2 hours, factor 1.3 for 2-6 hours, factor 1.6 for 6-12 hours, and factor 2.0 for over 12 hours). Based on the obtained duration of the anomaly, the corresponding cumulative effect factor is determined to ensure that this factor accurately reflects the cumulative impact of the environmental anomaly.

[0078] S205. The environmental deviation amplitude is weighted and compensated using the time-accumulation factor to obtain the comprehensive environmental load value. Based on the comprehensive environmental load value, the equipment failure risk level is positively corrected, and the maintenance demand index is calculated.

[0079] Among them, the comprehensive environmental load value refers to the value obtained after weighting the environmental deviation amplitude through the time-accumulation factor, which is used to comprehensively reflect the combined impact of the magnitude of environmental deviation and the duration of abnormality on the equipment; positive correction refers to the adjustment of the basic score corresponding to the equipment failure risk level based on the comprehensive environmental load value. The larger the comprehensive environmental load value, the larger the correction amplitude; the maintenance demand index is a quantitative indicator that characterizes the urgency of equipment maintenance after correction. It increases monotonically with the increase of the environmental deviation amplitude.

[0080] Specifically, the system obtains the environmental deviation magnitude from S101 and the time-accumulation factor from S204, multiplies the two, and obtains the comprehensive environmental load value. This value reflects both the degree of deviation between the current environment and the standard value, and incorporates the cumulative impact of the duration of environmental anomalies. Subsequently, it retrieves the basic maintenance score corresponding to the equipment failure risk level (e.g., 3 points for low risk, 6 points for medium risk, and 9 points for high risk), and determines the correction coefficient based on the comprehensive environmental load value (the higher the comprehensive environmental load value, the higher the correction coefficient). Multiplying the basic maintenance score by the correction coefficient yields the maintenance demand index, ensuring that this index comprehensively and accurately reflects the current urgency of equipment maintenance.

[0081] Optionally, the system can retrieve the environmental deviation range of S101 (e.g., 25%) and the time-accumulation factor of S204 (e.g., 1.6); calculate the comprehensive environmental load value = environmental deviation range × time-accumulation factor = 25% × 1.6 = 40%; retrieve the basic maintenance score of 6 points corresponding to the equipment failure risk level (e.g., medium risk); 4. establish the correspondence between the comprehensive environmental load value and the correction coefficient (e.g., load value 0-20% corresponds to coefficient 1.0, 20%-40% corresponds to coefficient 1.5, and above 40% corresponds to coefficient 2.0), determine the correction coefficient of 1.5 corresponding to the 40% load value; calculate the maintenance demand index = basic maintenance score × correction coefficient = 6 × 1.5 = 9 points; if the comprehensive environmental load value is 0 (no environmental abnormalities), then the correction coefficient is 1.0, and the maintenance demand index = basic maintenance score × 1.0, that is, it is determined only based on the risk level of the equipment itself.

[0082] S206. Collect multiple sets of environmental parameters within a preset sliding time window, and calculate the fluctuation characteristic value based on the multiple sets of environmental parameters.

[0083] Among them, the preset sliding time window refers to a time interval that is pre-set, has a fixed length, and can be continuously updated over time, such as 5 minutes or 10 minutes, and is used to collect environmental parameters within a continuous time period; the fluctuation characteristic value refers to the value calculated based on multiple sets of environmental parameters within the preset sliding time window, and is used to characterize the degree of steady-state damage to environmental parameters and the repeated stretching fatigue effect on the archive fibers. The greater the fluctuation of environmental parameters, the higher the fluctuation characteristic value.

[0084] Specifically, the system determines the length of a preset sliding time window (e.g., 10 minutes), and then collects multiple sets of environmental parameters (e.g., humidity, temperature, etc.) within this time window according to a preset collection frequency (e.g., once per minute). After collection, the system processes the multiple sets of environmental parameters, calculates the fluctuation of the parameters, such as calculating the standard deviation and range (the difference between the maximum and minimum values), and then merges these fluctuation indicators through a preset algorithm to obtain a fluctuation characteristic value. This value can accurately reflect the instability of the environmental parameters over a period of time.

[0085] In some embodiments, the system can preset the sliding time window length to 8 minutes and the collection frequency to collect environmental parameters (humidity) once every 1 minute; tracing back 8 minutes from the current moment, 8 sets of humidity data (e.g., 50%, 52%, 48%, 55%, 53%, 49%, 51%, 54%) are collected within this time period; the range of this set of data is calculated as: maximum value 55% - minimum value 48% = 7%; the standard deviation of the data (reflecting the degree of data dispersion) is calculated, resulting in a standard deviation ≈ 2.8%; the fluctuation characteristic value is calculated using a weighted summation method: range × 0.6 + standard deviation × 0.4 = 7% × 0.6 + 2.8% × 0.4 = 4.2% + 1.12% = 5.32%; if a set of data contains outliers (e.g., extreme values ​​exceeding the normal humidity range), the data is removed and the range and standard deviation are recalculated.

[0086] For archival storage scenarios, the coupling fluctuation rate of "humidity-temperature" should be a key focus. The system calculates the rate of change of "dew point temperature" per unit time. Drastic fluctuations in dew point temperature mean that bound water within the paper fibers repeatedly undergoes a physical process of "adsorption-desorption" (i.e., the "breathing effect"), a core factor contributing to the brittleness of ancient books. Including the dew point change rate in the calculation weight of the fluctuation characteristic value (with a proportion greater than 50%) can more accurately characterize the destructive force of the environment on the physical object.

[0087] S207. Based on the environmental deviation amplitude mapping, the basic vulnerability value is obtained, and the fluctuation characteristic value is used as the amplification factor to amplify the basic vulnerability value to obtain the modified vulnerability factor.

[0088] Among them, the basic vulnerability value refers to the numerical value representing the basic vulnerability of the archives obtained by mapping the environmental deviation amplitude. It follows a preset non-linear surge rule as the environmental deviation amplitude increases. The larger the environmental deviation amplitude, the faster the basic vulnerability value increases. The amplification factor refers to the coefficient that uses the fluctuation characteristic value as an adjustment factor for the basic vulnerability value, which is used to reflect the aggravating effect of environmental fluctuation on the vulnerability of the archives. The corrected vulnerability factor is the numerical value obtained after the basic vulnerability value is amplified by the fluctuation characteristic value, which is used to more accurately reflect the vulnerability of the archives under the combined effect of environmental deviation and fluctuation.

[0089] Specifically, the system retrieves a preset nonlinear mapping rule between environmental deviation range and basic vulnerability value (for example, when the environmental deviation range is 0-10%, the basic vulnerability value increases slowly; when it is 10%-20%, the growth rate accelerates; and when it is above 20%, it increases sharply). Based on the environmental deviation range obtained in S101, the corresponding basic vulnerability value is mapped. Subsequently, the fluctuation characteristic value obtained in S206 is used as an amplification factor and multiplied by the basic vulnerability value to obtain a corrected vulnerability coefficient. This coefficient reflects both the basic vulnerability impact of environmental deviation and the aggravating effect of environmental fluctuation on the degree of vulnerability, ensuring a comprehensive reflection of the vulnerability status of the archives.

[0090] S208. Calculate the product of the modified fragility coefficient and the sensitivity level of the archive to obtain the archive fragility index.

[0091] Among them, the archive vulnerability index is the final quantitative indicator used to characterize the archive's tolerance to detection actions after comprehensively adjusting the vulnerability coefficient and the archive sensitivity level. The higher the value, the more difficult it is for the archive to withstand the physical disturbance brought about by the detection action.

[0092] Specifically, the system retrieves the corrected fragility coefficient obtained from S207, which incorporates the impact of environmental deviations and fluctuations on the archives. Then, it retrieves the archive sensitivity level corresponding to the target component, reflecting the archive's inherent value, material characteristics, and other factors that affect its sensitivity to testing. Finally, the corrected fragility coefficient is multiplied by the archive sensitivity level to obtain the archive fragility index. This index reflects both the changes in archive fragility caused by environmental factors and the archive's inherent sensitivity characteristics, providing a comprehensive and accurate measure of the archive's tolerance to testing.

[0093] S209. Based on the comparison results of the maintenance demand index and the file vulnerability index, select whether to delay or advance the execution of the currently pending detection action.

[0094] Specifically, the system directly compares the maintenance demand index obtained in S205 with the file fragility index obtained in S208. If the maintenance demand index is greater than or equal to the file fragility index, it indicates that the risk of equipment failure is higher and the maintenance demand is more urgent, requiring priority to ensure equipment operation and maintenance. Therefore, the system chooses to execute the currently pending test action ahead of schedule. If the maintenance demand index is less than the file fragility index, it indicates that the file has extremely low tolerance to the test action, and the test action may cause irreversible damage to the file. Therefore, the system chooses to delay the execution of the currently pending test action.

[0095] S210. Count the consecutive delay operations performed for the current detection action to be executed, and add up the time correction step corresponding to each delay operation to obtain the cumulative lag time.

[0096] Among them, continuous postponement operation refers to the operation of postponing the execution of the same current detection action multiple times because the file fragility index is higher than the maintenance demand index, and no other detection action is inserted between each postponement; cumulative lag time refers to the total time obtained by summing the time correction steps corresponding to each continuous postponement operation, which is used to quantify the total extent of the postponement of the detection action.

[0097] Specifically, the system establishes a dedicated tracking file for the currently pending detection action, recording information such as the original planned execution time of the action, the trigger time for each postponement, and the corresponding time correction step. Each time a postponement operation is performed on the detection action, the system extracts the time correction step corresponding to the current and previous consecutive postponements from the tracking file, and accumulates these step values ​​to obtain the cumulative lag time.

[0098] S211. When the cumulative hysteresis time exceeds the preset safety fuse threshold, acquire multiple alternative detection methods for the target component and determine the vibration intrusion level corresponding to each alternative detection method.

[0099] Among them, the preset safety circuit breaker threshold refers to the maximum cumulative lag time that allows the detection action to be continuously postponed. This threshold is determined based on the maximum non-detection runtime that the equipment can withstand and the cumulative fault risk threshold. Alternative detection methods refer to different operating methods that can achieve the detection purpose for the functional detection of the target component, in addition to the conventional detection methods, such as conventional manual detection, remote data reading detection, low-power start-stop detection, etc. The vibration intrusion level refers to the classification used to measure the impact of vibration generated during the execution of each alternative detection method on the archive. The higher the level, the stronger the intrusion of the vibration on the archive and the greater the potential risk of damage.

[0100] Specifically, the system retrieves a preset safety trip threshold (e.g., 12 hours) and compares the cumulative hysteresis time obtained in S210 (e.g., 15 hours) with this threshold to confirm that the threshold has been exceeded. Subsequently, the system retrieves all alternative detection methods for the target component from the detection method database. These methods can all verify the functional status of the target component. Next, based on a preset vibration intrusion assessment standard, the system analyzes each alternative detection method, evaluating its impact on the data file regarding vibration intensity, propagation range, and duration during execution, thereby determining the corresponding vibration intrusion level (e.g., high, medium, and low).

[0101] S212. Select the candidate detection method with the lowest vibration intrusion level as the target detection method, and generate an instant detection start command containing the target detection method.

[0102] Among them, the target detection method refers to the detection method with the lowest vibration intrusion level and the least risk of physical damage to the archives selected from a variety of alternative detection methods; the immediate detection start command refers to an instruction that includes information such as the target detection method, detection execution time, and detection operation specifications, and is used to instruct relevant modules or personnel to immediately perform the detection action.

[0103] Specifically, the system selects the lowest-level detection method from the list of alternative detection methods and corresponding vibration intrusion levels obtained from S211. This method has the least impact on the files' vibration among all alternative methods. Subsequently, the system generates an immediate detection start command, which clearly includes the specific operation procedure of the target detection method, the executing entity (such as automatic detection equipment, maintenance personnel), the detection start time (such as immediate start or start within 30 minutes), and precautions during the detection process (such as controlling the power of the detection equipment, avoiding touching the file storage area, etc.), ensuring that the detection action can be executed safely and efficiently.

[0104] In some embodiments, the system can retrieve a list of alternative detection methods, where remote current data detection is a low-level method, low-speed no-load detection is a medium-level method, and manual start-stop detection is a high-level method; select remote current data detection with the lowest vibration intrusion level as the target detection method; generate an instant detection start command, which includes information such as the detection method being remote current data reading, the execution entity being an automatic detection terminal, the start time being within 10 minutes after the current moment, and the detection data transmission path; send the command to the automatic detection terminal and synchronize it to the operation and maintenance management platform to facilitate real-time monitoring of the detection progress.

[0105] It should be noted that steps S211-S212 above constitute the system's "safety circuit breaker mechanism": Although the harsh environment makes the archives susceptible to damage, if the inspection is postponed indefinitely, the mechanical parts may rust and become stuck. Future repairs would require disassembling the equipment, causing far greater disruption to the warehouse environment and the archives than a routine inspection. Therefore, when the circuit breaker threshold is reached (e.g., a continuous postponement exceeding 15 days), the system selects the "lowest vibration intrusion" silent current detection mode (i.e., only a weak current is applied to the motor to test the continuity of the circuit and the coil impedance, without driving the frame to produce macroscopic displacement), completing the minimum electrical health confirmation under the premise of "zero physical disturbance."

[0106] S213. Obtain the preset detection operation parameters, and estimate the expected fluctuation value of the environmental parameters in the archive storage room during the execution of the detection action based on the detection operation parameters.

[0107] Among them, the detection operation parameters refer to the preset parameters related to the execution of the detection action, including the number of detection personnel, the power of the detection equipment, and the estimated operation time. These parameters will directly affect the environmental conditions in the archive storage room. The expected fluctuation value refers to the range and trend of changes in environmental parameters (such as temperature and humidity) estimated by analyzing the possible impact on the environment during the execution of the detection action based on the detection operation parameters.

[0108] Specifically, the system retrieves preset testing operation parameters from the testing plan database. These parameters are pre-set based on past testing experience and equipment characteristics, such as the number of testing personnel being 2, the testing equipment power being 500W, and the estimated operation duration being 1 hour. Subsequently, the system analyzes the environmental impact of each testing operation parameter: testing personnel entering the warehouse bring in heat and moisture, causing an increase in temperature and humidity; the operation of the testing equipment generates heat, raising the temperature; the longer the operation duration, the more significant the changes in environmental parameters. Combining these influencing factors, the system uses a preset estimation model to comprehensively calculate the estimated fluctuation values ​​of environmental parameters such as temperature and humidity in the warehouse during the execution of the testing action; for example, the temperature is expected to rise by 2°C, and the humidity is expected to rise by 5%.

[0109] In some embodiments, the system can retrieve preset detection operation parameters: 3 inspection personnel, 800W inspection equipment power, and estimated operation time of 90 minutes; retrieve historical inspection data and statistically analyze the fluctuation of environmental parameters under the same or similar operation parameters, such as 3 people working for 90 minutes, the average temperature rises by 1.8℃ and the average humidity rises by 4%; 800W equipment running for 90 minutes, the average temperature rises by 2.2℃; considering the influence of personnel and equipment, estimate the expected fluctuation value: temperature rises by 1.8 + 2.2 = 4℃, humidity rises by 4%; correct the estimation result, considering the current ventilation conditions of the warehouse, if the ventilation is good, the temperature fluctuation value is reduced by 0.5℃, finally obtaining an estimated temperature rise of 3.5℃ and an estimated humidity rise of 4%.

[0110] S214. If the sum of the current environmental parameters and the expected fluctuation value exceeds the preset threshold range for safe storage of archives, an environmental pre-compensation command is generated, and the environmental adjustment equipment is driven to pre-adjust the environmental parameters in the archive storage room in the opposite direction to the expected fluctuation value change trend before the detection action begins, until the sum of the adjusted environmental parameters and the expected fluctuation value falls within the preset threshold range.

[0111] Among them, the superposition value refers to the value obtained by adding the current environmental parameter to the expected fluctuation value (if the expected fluctuation value is on an upward trend) or subtracting it (if the expected fluctuation value is on a downward trend), which is used to predict the actual environmental parameters during the execution of the detection action; the preset threshold range for safe storage of archives refers to the allowable range of environmental parameters set in advance based on the requirements for safe storage of archives, and exceeding this range will cause damage to the archives; the environmental pre-compensation instruction refers to the instruction used to instruct environmental conditioning equipment (such as air conditioners, dehumidifiers, humidifiers, etc.) to adjust the environmental parameters of the storage room in advance; the pre-adjustment refers to the proactive adjustment of environmental parameters before the detection action begins in order to offset the environmental fluctuations that may be caused by the detection action.

[0112] Specifically, the system calculates the sum of the current environmental parameters and the expected fluctuation value. For example, if the current temperature is 23℃ and the expected fluctuation value increases by 3℃, the sum of the values ​​would be 26℃. Then, it retrieves the preset temperature threshold range (e.g., 14℃-24℃) stored in the archive and determines that 26℃ exceeds this range. At this point, the system generates an environmental pre-compensation command, specifying the adjustment direction (opposite to the expected fluctuation value trend, i.e., cooling) and the adjustment target (so that the adjusted temperature, when summed with the expected fluctuation value of 3℃, falls within the 14℃-24℃ range). Next, the system sends the command to the environmental control equipment (e.g., an air conditioner), driving the equipment to initiate cooling operations. It continuously monitors changes in environmental parameters, calculating the sum of the adjusted parameters and the expected fluctuation value after each adjustment, until the sum falls within the preset threshold range, at which point the pre-adjustment stops.

[0113] Optionally, the system can calculate the superposition of the current environmental parameters (temperature 22℃, humidity 58%) and the expected fluctuation value (temperature rises by 3℃, humidity rises by 4%): temperature 25℃, humidity 62%; retrieve the preset threshold range (temperature 14℃-24℃, humidity 45%-60%), and determine that both temperature 25℃ and humidity 62% are outside the range; generate an environmental pre-compensation instruction, specifying the adjustment direction as cooling and dehumidification, with the adjustment target being to adjust the temperature to 21℃ (21+3=24℃) and humidity to 56% (56+4=60%); drive the air conditioner to start the cooling mode and the dehumidifier to start the dehumidification mode, monitor the environmental parameters every 10 minutes, and when the temperature drops to 21℃ and the humidity drops to 56%, calculate the superposition value as temperature 24℃ and humidity 60%, both falling within the threshold range, and stop the pre-adjustment.

[0114] The detection frequency adjustment system for archive storage equipment in this application is applied to electronic devices. Figure 3 A schematic diagram of the architecture of an electronic device suitable for implementing embodiments of the present invention is shown.

[0115] It should be noted that, Figure 3 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of use of the embodiments of the present invention.

[0116] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be implemented by instructions (computer programs), or by instructions (computer programs) controlling related hardware. These instructions can be stored in a computer-readable storage medium and loaded and executed by a processor. The electronic device of this embodiment includes a storage medium and a processor, wherein the storage medium stores multiple instructions that can be loaded by the processor to execute any step of the method provided in the embodiments of the present invention.

[0117] Specifically, the storage medium and the processor are electrically connected directly or indirectly to enable data transmission or interaction. For example, these components can be electrically connected to each other via one or more signal lines. The storage medium stores computer-executable instructions that implement data access control methods, including at least one software functional module that can be stored in the storage medium in the form of software or firmware. The processor executes various functional applications and data processing by running the software program and module stored in the storage medium. The storage medium can be, but is not limited to, Random Access Memory (RAM), Read-Only Memory (ROM), Programmable Read-Only Memory (PROM), Erasable Programmable Read-Only Memory (EPROM), Electrically Erasable Programmable Read-Only Memory (EEPROM), etc. The storage medium stores the program, and the processor executes the program after receiving the execution instructions.

[0118] Furthermore, the software programs and modules within the aforementioned storage medium may also include an operating system, which may include various software components and / or drivers for managing system tasks (e.g., memory management, storage device control, power management, etc.) and can communicate with various hardware or software components to provide an operating environment for other software components. The processor may be an integrated circuit chip with signal processing capabilities. The aforementioned processor may be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), etc., which can implement or execute the methods, steps, and logic flowcharts disclosed in this embodiment. The general-purpose processor may be a microprocessor or any conventional processor.

[0119] Since the instructions stored in the storage medium can execute the steps in any of the methods provided in the embodiments of the present invention, the beneficial effects of any of the methods provided in the embodiments of the present invention can be achieved, as detailed in the preceding embodiments, and will not be repeated here.

[0120] The above description is merely a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for adjusting the detection frequency of equipment in an archive storage room, characterized in that, The method includes: Collect current environmental parameters within the archive storage room and calculate the environmental deviation of the current environmental parameters relative to preset environmental standard values; A maintenance demand index characterizing the urgency of equipment maintenance is calculated based on the environmental deviation magnitude and the equipment failure risk level of the target component. The equipment failure risk level is determined based on the historical failure frequency and failure impact of the target component. The maintenance demand index increases monotonically with the increase of the environmental deviation magnitude. Based on the environmental deviation magnitude and the sensitivity level of the target component, an archive vulnerability index characterizing the archive's tolerance to detection actions is calculated. The archive vulnerability index increases non-linearly with the increase of the environmental deviation magnitude. Calculate the index difference between the maintenance demand index and the archive fragility index, and obtain the time correction step based on the index difference; Determine whether the maintenance demand index is greater than or equal to the file fragility index; If so, the time correction step size is deducted from the remaining waiting time of the current detection cycle, so that the next detection action is executed in advance; If not, the time correction step is added to the remaining waiting time of the current detection cycle, so that the next detection action is postponed.

2. The method according to claim 1, characterized in that, The steps for determining the equipment failure risk level based on the historical failure frequency and impact of the target component specifically include: Obtain the number of failures of the target component within a preset historical period and the average downtime caused by a single failure; The number of failures is mapped to a frequency score within a first preset interval, and the average downtime is mapped to a severity score within a second preset interval. A comprehensive risk score for the target component is determined based on the frequency score and the severity score, and the equipment failure risk level of the target component is determined based on the score interval corresponding to the comprehensive risk score, wherein the score interval corresponds one-to-one with the equipment failure risk level.

3. The method according to claim 1, characterized in that, The step of calculating the maintenance demand index, which characterizes the urgency of equipment maintenance, based on the environmental deviation magnitude and the equipment failure risk level of the target component, specifically includes: The duration of the abnormal environmental deviation is monitored to obtain the duration of the abnormality. The time-accumulation factor is obtained by mapping the duration of the anomaly, and the time-accumulation factor characterizes the cumulative corrosion effect of long-term environmental anomalies on equipment components; The environmental deviation magnitude is weighted and compensated using the aforementioned time-accumulation factor to obtain the comprehensive environmental load value. The maintenance demand index is calculated by positively correcting the equipment failure risk level based on the comprehensive environmental load value.

4. The method according to claim 1, characterized in that, The step of calculating the archive vulnerability index, which characterizes the archive's tolerance to detection actions, based on the environmental deviation amplitude and the archive sensitivity level of the target component, specifically includes: Multiple sets of environmental parameters are collected within a preset sliding time window, and fluctuation characteristic values ​​are calculated based on the multiple sets of environmental parameters. The fluctuation characteristic values ​​characterize the steady-state damage degree of the environmental parameters and the repeated stretching fatigue effect on the archival fibers. A basic vulnerability value is obtained based on the environmental deviation amplitude mapping, and the fluctuation characteristic value is used as an amplification factor to amplify the basic vulnerability value to obtain a corrected vulnerability coefficient. The basic vulnerability value follows a preset nonlinear surge rule as the environmental deviation amplitude increases. The product of the modified fragility coefficient and the sensitivity level of the archive is calculated to obtain the archive fragility index.

5. The method according to claim 1, characterized in that, Following the step of adding the time correction step to the remaining waiting time of the current detection cycle, thereby delaying the execution of the next detection action, the method further includes: The cumulative lag time is obtained by statistically analyzing the consecutive delay operations performed for the current detection action to be executed and summing the time correction step size corresponding to each delay operation. When the cumulative lag time exceeds the preset safety circuit breaker threshold, an immediate detection start command is generated, and the system enters a forced detection state.

6. The method according to claim 5, characterized in that, The step of generating the instant detection startup command specifically includes: Acquire multiple alternative detection methods for the target component and determine the vibration intrusion level corresponding to each alternative detection method; The candidate detection method with the lowest vibration intrusion level is selected as the target detection method; Generate an instant detection start command that includes the target detection method.

7. The method according to claim 1, characterized in that, After the step of determining whether the maintenance demand index is greater than or equal to the file fragility index, the method further includes: Obtain preset detection operation parameters, including the number of detection personnel, the power of the detection equipment, and the estimated operation time; Based on the aforementioned testing operation parameters, estimate the expected fluctuation values ​​of environmental parameters within the archive storage area during the execution of the testing action; Calculate the sum of the current environmental parameters and the expected fluctuation value, and determine whether the sum exceeds the preset threshold range for secure file storage; If so, an environmental pre-compensation command is generated, and the environmental adjustment equipment is driven to pre-adjust the environmental parameters in the archive storage room in the opposite direction to the expected fluctuation value before the detection action begins, until the superposition value of the adjusted environmental parameters and the expected fluctuation value falls within the preset threshold range.

8. A detection frequency adjustment system for archive storage equipment, characterized in that, The system includes: one or more processors and memory; The memory is coupled to the one or more processors, the memory being used to store computer program code, the computer program code including computer instructions, the one or more processors invoking the computer instructions to cause the system to perform the method as described in any one of claims 1-7.

9. A computer-readable storage medium comprising instructions, characterized in that, When the instruction is executed on the detection frequency adjustment system for the archive storage equipment, the system performs the method as described in any one of claims 1-7.

10. A computer program product comprising a computer program / instructions, characterized in that, When the computer program / instructions are run on the detection frequency adjustment system for archive storage equipment, the system performs the method as described in any one of claims 1-7.

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