Method and system for optimizing management decisions of equipment operation based on operation state data

Abstract

This invention relates to the field of equipment operation management technology, and discloses a method and system for optimizing equipment operation management decisions based on operational status data. The method includes: Step 1, acquiring current equipment operation status data, historical operation management data, historical maintenance management data, and historical energy consumption management data; Step 2, quantifying the current equipment status to obtain a comprehensive equipment status evaluation value; Step 3, generating an operational constraint set and a maintenance constraint set based on the comprehensive equipment status evaluation value; Step 4, screening and comparing candidate management schemes to obtain a comprehensive decision value; Step 5, determining the optimal management scheme based on the comprehensive decision value and resource utilization; Step 6, obtaining an operation plan and a maintenance plan based on the optimal management scheme; and Step 7, performing execution verification based on the operation plan and maintenance plan, and updating the basic equipment operation management data. This invention achieves collaborative optimization decision-making for equipment operation plans, maintenance plans, and resource allocation.

Description

Technical Field

[0001] This invention belongs to the field of equipment operation management technology, specifically relating to a method and system for optimizing equipment operation management decisions based on operational status data. Background Technology

[0002] As industrial equipment operation and management become increasingly information-based, data such as equipment status monitoring, maintenance records, energy consumption statistics, and task scheduling can now be collected and stored separately. However, in current technologies, this data is mostly still scattered across different business processes. For example, operational status data is typically used for status display or anomaly alarms, maintenance data is mainly used for work order processing, energy consumption data is mostly used for post-event statistical analysis, and operational scheduling data primarily serves task scheduling. The lack of a unified integration and collaborative processing mechanism among these various data types makes it difficult to directly translate the current equipment status into management decision-making data for operational arrangements, maintenance insertions, and resource allocation.

[0003] On the other hand, existing equipment management solutions often focus on single-step judgments when dealing with changes in equipment status. For example, they may decide whether to perform maintenance based solely on abnormal conditions or schedule maintenance periods based solely on pre-determined plans, failing to incorporate factors such as equipment operating capacity, maintenance pressure, energy consumption, and resource occupancy within the equipment group into a unified comparison process. When the same equipment status change simultaneously affects task execution, maintenance scheduling, and resource allocation, problems such as conflicts between operation and maintenance plans, a lack of unified evaluation criteria for multiple candidate solutions, and difficulty in coordinating resource competition within the equipment group can easily arise, thus affecting the executability of decision-making results and overall management effectiveness. Furthermore, some existing solutions rely on manual experience for plan adjustments or limit status analysis results to prompts and suggestions, lacking a mechanism for continuous verification and data write-back based on execution results, making it difficult to form a closed-loop update for subsequent plan optimization. Summary of the Invention

[0004] This invention provides a method and system for optimizing equipment operation management decisions based on operational status data. It solves the technical problems in related technologies where equipment operation status data, maintenance data, energy consumption data, and scheduling data are scattered and difficult to form a unified decision-making basis, which leads to conflicts between operation plans and maintenance plans, lack of a unified comparison standard for candidate solutions, difficulty in coordinating and allocating equipment group resources, and difficulty in optimizing decision results in a closed loop.

[0005] This invention provides a method for optimizing equipment operation management decisions based on operational status data, comprising the following steps: Step 1: Obtain the current operating status data, historical operation management data, historical maintenance management data, and historical energy consumption management data of the equipment, and integrate them to obtain the basic data for equipment operation management; Step 2: Based on the current operating status data, historical maintenance management data, and historical operation management data, the current status of the equipment is quantified to obtain a comprehensive evaluation value of the equipment status. Step 3: Generate an operational constraint set and a maintenance constraint set based on the comprehensive equipment status assessment value, historical operation management data, and historical maintenance management data; Step 4: Based on the running constraint set and the maintenance constraint set, select candidate management schemes from the preset candidate management schemes, compare and process each candidate management scheme, and obtain the comprehensive decision value corresponding to each candidate management scheme; Step 5: Based on the comprehensive decision value corresponding to each candidate management scheme, the resource occupancy corresponding to each candidate management scheme, the comprehensive evaluation value of equipment status, historical operation management data, and the total available resources of the equipment group, determine the optimal management scheme for each piece of equipment. Step 6: Adjust equipment tasks, equipment load, and operating times according to the optimal management plan to obtain the operation plan, and obtain the maintenance plan based on the comprehensive evaluation value of equipment status, historical maintenance management data, and historical operation management data; Step 7: Obtain the execution results based on the operation plan and maintenance plan, verify the execution results based on the comprehensive equipment status assessment values ​​before and after execution, obtain the status improvement amount, and update the basic data of equipment operation management based on the status improvement amount.

[0006] This invention also provides a device operation management decision optimization system based on operating status data, including: The basic data integration module is used to acquire the current operating status data, historical operation management data, historical maintenance management data, and historical energy consumption management data of the equipment, and integrate them to obtain the basic data for equipment operation management. The status assessment and processing module is used to quantify the current status of the equipment based on the current operating status data, historical maintenance management data, and historical operation management data, and obtain a comprehensive equipment status assessment value. The constraint set generation module is used to generate operation constraint sets and maintenance constraint sets based on the comprehensive evaluation value of equipment status, historical operation management data, and historical maintenance management data. The scheme selection and comparison module is used to select candidate management schemes from the preset candidate management schemes based on the operation constraint set and the maintenance constraint set, and to compare and process each candidate management scheme to obtain the comprehensive decision value corresponding to each candidate management scheme. The optimal solution determination module is used to determine the optimal management solution for each device based on the comprehensive decision value corresponding to each candidate management solution, the resource occupancy corresponding to each candidate management solution, the comprehensive evaluation value of equipment status, historical operation and management data, and the total available resources of the equipment group. The plan generation and adjustment module is used to adjust equipment tasks, equipment load and runtime according to the optimal management plan to obtain the operation plan, and to obtain the maintenance plan based on the comprehensive evaluation value of equipment status, historical maintenance management data and historical operation management data; The execution verification and update module is used to obtain the execution results based on the operation plan and maintenance plan, and to verify the execution results based on the comprehensive evaluation value of the equipment status before execution and the comprehensive evaluation value of the equipment status after execution, so as to obtain the status improvement amount, and update the basic data of equipment operation management based on the status improvement amount.

[0007] The beneficial effects of this invention are as follows: Based on the current operating status data of the equipment and historical operation, maintenance, and energy consumption data, this invention constructs basic data for equipment operation management and uniformly quantifies the current status of the equipment. This transforms multi-source data, originally scattered for monitoring, maintenance, and statistics, into evaluation criteria that can be directly used in management decisions. Furthermore, this invention simultaneously generates operating constraints and maintenance constraints, completing candidate scheme screening, comprehensive comparison, resource coordination, and optimal scheme determination within the same decision-making process. This ensures that adjustments to the operation plan and maintenance plans are no longer isolated, reducing plan conflicts and redundant adjustments. Simultaneously, this invention incorporates the resource occupancy of the equipment group into the scheme optimization process, improving the overall coordination and executability of the scheme determination results under conditions of limited shared resources. By verifying the execution results and writing back the basic data, a continuously updated closed-loop processing mechanism can be formed, ensuring that subsequent equipment operation management decisions are based on the latest status and execution results, thereby improving the synergy, accuracy, and overall optimization effect of equipment operation management. Attached Figure Description

[0008] Figure 1 This is a flowchart of the equipment operation management decision optimization method based on operating status data according to the present invention. Detailed Implementation

[0009] The subject matter described herein will now be discussed with reference to exemplary embodiments. It should be understood that these embodiments are discussed only to enable those skilled in the art to better understand and implement the subject matter described herein, and changes may be made to the function and arrangement of the elements discussed without departing from the scope of this specification. Various processes or components may be omitted, substituted, or added as needed in the examples. Furthermore, features described in some examples may be combined in other examples.

[0010] like Figure 1 As shown, the equipment operation management decision optimization method based on operating status data includes the following steps: Step 1: Obtain the current operating status data, historical operation management data, historical maintenance management data, and historical energy consumption management data of the equipment, and integrate them to obtain the basic data for equipment operation management; Step 2: Based on the current operating status data, historical maintenance management data, and historical operation management data, the current status of the equipment is quantified to obtain a comprehensive evaluation value of the equipment status. Step 3: Generate an operational constraint set and a maintenance constraint set based on the comprehensive equipment status assessment value, historical operation management data, and historical maintenance management data; Step 4: Based on the running constraint set and the maintenance constraint set, select candidate management schemes from the preset candidate management schemes, compare and process each candidate management scheme, and obtain the comprehensive decision value corresponding to each candidate management scheme; Step 5: Based on the comprehensive decision value corresponding to each candidate management scheme, the resource occupancy corresponding to each candidate management scheme, the comprehensive evaluation value of equipment status, historical operation management data, and the total available resources of the equipment group, determine the optimal management scheme for each piece of equipment. Step 6: Adjust equipment tasks, equipment load, and operating times according to the optimal management plan to obtain the operation plan, and obtain the maintenance plan based on the comprehensive evaluation value of equipment status, historical maintenance management data, and historical operation management data; Step 7: Obtain the execution results based on the operation plan and maintenance plan, verify the execution results based on the comprehensive equipment status assessment values ​​before and after execution, obtain the status improvement amount, and update the basic data of equipment operation management based on the status improvement amount.

[0011] In one embodiment of the present invention, the current operating status data, historical operation management data, historical maintenance management data, and historical energy consumption management data of the equipment are acquired and integrated to obtain basic equipment operation management data. The current operating status data refers to a set of real-time data reflecting the operating status of the equipment at the current acquisition moment, which may include equipment temperature, pressure, current, voltage, speed, start / stop status, etc. The historical operation management data is used to characterize the equipment's past task execution, load changes, start / stop status, and scheduling arrangements, and may include historical task number, historical load level, cumulative runtime, number of cycle start / stops, task priority, etc. The historical maintenance management data is used to characterize the equipment's past maintenance records, incomplete maintenance items, and available maintenance time arrangements, and may include maintenance work order records, number of incomplete maintenance items, maintenance action type, maintenance execution time, etc. The historical energy consumption management data is used to characterize the equipment's past energy consumption and its correspondence with the operating process, and may include cumulative energy consumption, time-period energy consumption, unit cycle energy consumption records, peak-valley time period energy consumption records, etc.

[0012] Specifically, in step 11, the target device is determined based on the device identifier. The current operating status data of the target device is obtained according to the current acquisition time, and historical operation management data, historical maintenance management data, and historical energy consumption management data of the target device are obtained according to the historical statistical time window. The device identifier is used to uniquely identify the device to be processed, avoiding data confusion between different devices. The historical statistical time window refers to a pre-set data retrieval time range to ensure the comparability and management reference significance of historical data; for example, it can be set according to the past week, the past month, or the past maintenance cycle. When the target device is an air compressor, the current operating status data such as temperature, current, and vibration of the air compressor can be obtained, along with its task execution records, start / stop records, maintenance work order records, and cumulative energy consumption records within the historical statistical time window.

[0013] Step 12 involves filtering, extracting fields, and performing consistency checks on the current operating status data, historical operation management data, historical maintenance management data, and historical energy consumption management data of the equipment. Specifically, duplicate records are retained only at the latest time, and records exceeding the historical statistical time window are discarded. The consistency of equipment identification, time range, and field units is verified. This consistency check refers to the unified verification of data from different data sources in terms of identification, time, and metering caliber to ensure that subsequent calculations are based on the same equipment, the same statistical range, and the same data unit. For example, the correspondence between kilowatt-hours in energy consumption data and hours in operating time must be consistent to accurately calculate the energy consumption per unit time; furthermore, if multiple records are collected from the same device at the same time, the record with the latest time and complete fields is retained.

[0014] Step 13: Extract the current task number, current load level, cumulative runtime, periodic start / stop count, current task priority, and set of alternative devices from historical operation management data; extract the number of incomplete maintenance items and set of allowed maintenance time windows from historical maintenance management data; extract the number of periodic alarm items from current device operating status data; and calculate the ratio between the cumulative energy consumption and cumulative runtime in historical energy consumption management data to obtain the unit time energy consumption value. This value is then integrated with the current device operating status data to obtain the basic data for device operation management. The set of alternative devices refers to the set of devices that can take over the tasks of the target device under the current management rules; the set of allowed maintenance time windows refers to the set of time intervals that meet the requirements of operation arrangements and maintenance rules and allow for the insertion of maintenance actions; the unit time energy consumption value refers to the energy consumption level of the device per unit runtime within the statistical period, used to characterize the energy efficiency characteristics of the device operation. For example, if a device has a cumulative energy consumption of 120 kWh and a cumulative runtime of 10 hours within a historical statistical time window, its unit time energy consumption value can be determined as 12 kWh / hour.

[0015] Through the above implementation process, this embodiment can structurally integrate real-time equipment status information with historical operation, maintenance, and energy consumption information to form unified basic data serving operation plan scheduling, maintenance plan arrangement, resource allocation, and decision comparison. Compared to processing methods that only display status or provide anomaly alarms, this embodiment emphasizes data organization and retrieval methods oriented towards management decision-making, providing stable data support for subsequent operation constraint generation, maintenance insertion judgment, candidate scheme selection, and equipment group resource coordination. This processing method helps improve the data synergy between equipment operation management and maintenance management, and enhances the accuracy and consistency of operation plan adjustments and maintenance arrangement generation.

[0016] In one embodiment of the present invention, the current state of the equipment is quantified based on current operating status data, historical maintenance management data, and historical operating management data to obtain a comprehensive equipment status evaluation value. This comprehensive equipment status evaluation value reflects the overall status level of the equipment under the current management scenario. Unlike judging whether the equipment is abnormal based solely on a single status parameter, this embodiment integrates multiple sources of status information and management information into a unified evaluation process. This ensures that the evaluation result not only reflects the current operational deviation of the equipment but also reflects the operational and maintenance pressures the equipment is under.

[0017] Specifically, in step 21, the basic data of equipment operation management of the target equipment is read, and the following data are extracted: current operating status data, historical operation management data, historical maintenance management data, current task number, current load level, cumulative runtime, number of periodic start-stop cycles, number of periodic alarm entries, and number of incomplete maintenance entries. The current task number and current load level are used to characterize the operating tasks currently undertaken by the equipment and their load status; the cumulative runtime, number of periodic start-stop cycles, and number of periodic alarm entries are used to reflect the operating burden of the equipment within the current statistical period; and the number of incomplete maintenance entries is used to characterize the backlog of current maintenance items.

[0018] Step 22: Based on the current task number and current load level, filter the corresponding historical operation records from the historical operation management data. For each status field in the current equipment operating status data, determine the average value of the corresponding historical operation records as the status baseline value, and determine the difference between the maximum and minimum values ​​of the corresponding historical operation records as the status allowable deviation. The status fields refer to various parameters reflecting the equipment's operating status, such as temperature, pressure, current, voltage, vibration, or speed. The status baseline value characterizes the equipment's normal operating level under the same task type and similar load conditions, and the status allowable deviation characterizes the acceptable fluctuation range of the status field under historical normal operating conditions. Using historical operation records matching the current task number and current load level as a reference avoids evaluation distortion caused by direct comparison between different operating conditions. For example, when a device is currently operating under high load, it is advisable to select historical operation records under high load conditions to determine the status baseline value and status allowable deviation, rather than directly comparing historical data under low load conditions.

[0019] Step 23: Based on the difference between the current value of each status field and the corresponding status baseline value, and the ratio of the difference to the allowable deviation of the corresponding status, determine the deviation ratio of each status field. Deviation ratios exceeding a preset upper limit are truncated, and weighted summations are performed according to the weights of the corresponding status fields to obtain the status deviation value. The deviation ratio reflects the degree of deviation of each status field relative to the normal operating baseline; the preset upper limit limits the impact of abnormal fluctuations in a single status field on the overall evaluation result, avoiding distortion of the comprehensive evaluation due to individual extreme values; the status field weights distinguish the differences in the degree of influence of different status fields on the equipment's operating status. Simultaneously, the cumulative runtime, the number of periodic start-stop cycles, and the number of periodic alarm entries are normalized and weighted to obtain the operating burden value. The operating burden value reflects the comprehensive operating pressure formed by the equipment within the current statistical period due to continuous operation, frequent start-stop cycles, or multiple alarms. For example, under the same status deviation conditions, equipment with a longer cumulative runtime and more start-stop cycles typically has a higher operating burden value, thus reflecting greater management attention in subsequent comprehensive evaluations.

[0020] Step 24: Normalize the number of incomplete maintenance items to obtain a maintenance burden value. This maintenance burden value reflects the degree of constraint imposed by currently incomplete maintenance items on subsequent operational arrangements. A higher number of incomplete maintenance items indicates a more significant maintenance backlog, and the constraints on subsequent operational management are typically stronger. Based on this, the status deviation value, operational burden value, and maintenance burden value are weighted according to their respective comprehensive evaluation weights, and the weighted results are summarized to obtain a comprehensive equipment status evaluation value. These comprehensive evaluation weights reflect the relative influence of status deviation, operational burden, and maintenance pressure on the overall evaluation. This method unifies the multidimensional influencing factors of the current equipment status into a single quantitative result, facilitating comparison, ranking, and decision-making in subsequent processing stages.

[0021] Through the above implementation process, this embodiment can uniformly quantify the current operating status of the equipment based on its current status, combined with historical operating conditions and maintenance backlog, avoiding the one-sidedness caused by relying solely on a single status parameter or a single alarm result. The resulting comprehensive equipment status evaluation value can reflect both the degree of deviation of the equipment's operating parameters from historical benchmarks and the operating burden and maintenance constraints of the equipment in the current cycle. This provides more comprehensive quantitative support for subsequent operating constraint generation, maintenance insertion judgment, candidate management scheme selection, and coordinated adjustment of operation and maintenance plans, helping to improve the accuracy, consistency, and overall optimization effect of equipment operation management decisions.

[0022] In one embodiment of the present invention, an operational constraint set and a maintenance constraint set are generated based on a comprehensive equipment status assessment value, historical operation management data, and historical maintenance management data. The operational constraint set refers to a set of constraints regarding whether the equipment should continue to perform tasks in its current state, what load it is allowed to bear, and how long it can operate continuously. The maintenance constraint set refers to a set of constraints regarding whether maintenance is required, when maintenance can be performed, and what maintenance method is appropriate. By introducing the comprehensive equipment status assessment value into both the operation and maintenance sides, the same equipment status can be simultaneously constrained in both task execution and maintenance execution arrangements, thereby providing a unified basis for subsequent candidate management scheme selection and plan coordination adjustments.

[0023] Specifically, in step 31, the comprehensive equipment status assessment value is compared with a preset segmented threshold to determine the operational constraint level. Combined with historical load records and continuous operation records corresponding to the current task number and load level from historical operation management data, the maximum allowable load level and the maximum allowable continuous operation time are determined. Simultaneously, a task transfer flag is determined based on the current task priority. The preset segmented threshold is used to divide the comprehensive equipment status assessment value into different level intervals, each corresponding to different levels of operational constraints. The operational constraint level characterizes the degree to which the equipment can currently handle tasks; a higher assessment value indicates a greater current operational risk or burden, and the corresponding operational constraints are typically more stringent. The maximum allowable load level refers to the highest operational load the equipment is allowed to handle in its current state; the maximum allowable continuous operation time refers to the longest continuous operation time the equipment can sustainably execute tasks in its current state; the task transfer flag indicates whether the current task needs to be transferred to another device for continued execution. This processing ensures that operational constraints are not solely determined by the current status score, but rather by combining the current task type, load conditions, and past operational patterns to form constraint results that better reflect the actual execution scenario. For example, if a device is still operational at present, but its comprehensive evaluation value is already in a high range, and historical records indicate that it is prone to malfunctions after running continuously for a certain period of time under the same load, its allowable load level or its allowable continuous running time can be reduced accordingly.

[0024] Step 32: A maintenance insertion value is obtained by weighting the number of incomplete maintenance items and the overall equipment status assessment value according to a preset weight. This value is then mapped to a maintenance constraint level and a maintenance insertion flag according to a preset interval mapping rule. The maintenance insertion value reflects the intensity of maintenance demand under the combined effect of the current equipment status and maintenance backlog, considering both the current overall equipment status level and the impact of incomplete maintenance items on subsequent operations. The maintenance constraint level characterizes the degree of restriction on the equipment during maintenance, and the maintenance insertion flag indicates whether maintenance processing needs to be inserted into the subsequent plan. By incorporating both the overall status assessment value and the number of incomplete maintenance items into the calculation, maintenance arrangements can be avoided by solely relying on abnormal status or maintenance backlog, ensuring that the formation of maintenance constraints simultaneously considers changes in equipment status and maintenance management pressure. For example, if the overall equipment status assessment value does not reach the highest level, but there are many incomplete maintenance items, its maintenance insertion value may still be high, thus triggering the maintenance insertion flag.

[0025] Step 33: Select the target maintenance window based on the maintenance insertion mark and the set of allowed maintenance windows, and determine the maintenance action category by combining the maintenance records of the corresponding task in the historical maintenance management data, generating a maintenance constraint set. The set of allowed maintenance windows refers to the set of time intervals during which maintenance actions are permitted without significantly affecting the established operational schedule; the target maintenance window is the specific time interval selected from the set of allowed maintenance windows for executing the current maintenance action; the maintenance action category refers to the maintenance processing method applicable to the current equipment state and task scenario, which may include review, maintenance, repair, component replacement, or shutdown. The corresponding task maintenance records in the historical maintenance management data can be used to reflect the maintenance methods typically used under similar task conditions and their execution timing, thus providing a reference for determining the current maintenance action category.

[0026] Through the above implementation process, this embodiment can simultaneously transform the comprehensive equipment status assessment results into operational and maintenance constraints. This means that the current equipment status is no longer simply stored as a single evaluation result, but is directly transformed into task capacity limits, continuous operation limits, maintenance insertion requirements, and maintenance implementation conditions. This not only improves the consistency between operational and maintenance schedules but also reduces conflicts and repeated adjustments in subsequent plan development, making equipment operation management more aligned with the actual needs of task allocation, resource scheduling, and plan coordination.

[0027] In one embodiment of the present invention, candidate management schemes are selected from a preset candidate management scheme based on an operational constraint set and a maintenance constraint set. These candidate management schemes are then compared and processed to obtain a comprehensive decision value corresponding to each candidate management scheme. The preset candidate management schemes refer to multiple optional processing schemes pre-defined for the current operation and maintenance management scenario of the equipment, representing the task maintenance, load adjustment, task transfer, maintenance insertion, or shutdown processing methods that the equipment can adopt under different constraint conditions. The comprehensive decision value is used to support the determination of the subsequent optimal management scheme.

[0028] Specifically, in step 41, each preset candidate management scheme is checked against its constraints. Candidate schemes that simultaneously meet the maximum allowable load level, maximum allowable continuous running time, and task transfer flag in the operational constraint set, as well as the maintenance insertion flag, target maintenance window, and maintenance action category in the maintenance constraint set, are retained, resulting in a candidate management scheme set. This candidate management scheme set refers to the set of executable schemes remaining after dual constraint screening from both the operational and maintenance sides. In other words, only schemes that do not exceed the current allowable load and continuous running limits in their operational arrangements, and that meet the insertion conditions, time conditions, and action type requirements in their maintenance arrangements, are retained for subsequent comparison. For example, if a device is not allowed to continue operating at high load in its current state, and a review action needs to be inserted within a specified maintenance window, then the scheme that continues to maintain high load without scheduling maintenance will be eliminated, while the scheme that reduces load and inserts a review action can be retained. Through this screening process, all schemes entering the comparison stage can meet the requirements of the current device state and management rules.

[0029] Step 42: For the candidate management scheme set, the ratio of the task load to the allowable load limit for each candidate scheme is processed to obtain the operation maintenance value; the ratio of maintenance arrangement resource usage to the historical total resource amount is processed to obtain the maintenance resource usage value; the ratio of the scheme's energy consumption to the historical energy consumption benchmark is processed to obtain the energy consumption cost value; the difference between the comprehensive equipment status assessment value before execution and the comprehensive equipment status assessment value after execution is normalized to obtain the status improvement value; and the operation maintenance value, maintenance resource usage value, energy consumption cost value, and status improvement value are weighted and summarized according to preset weights to obtain the comprehensive decision value. The operation maintenance value reflects the degree to which the candidate scheme maintains the current task carrying capacity. The closer the task load is to the allowable load limit and the less it exceeds the limit, the better the task maintenance capacity of the scheme under the constraints. The maintenance resource usage value characterizes the degree of maintenance resource usage during the implementation of the scheme. The maintenance resources may include maintenance personnel, maintenance workstations, maintenance tools, or maintenance time windows, etc. The energy consumption cost value reflects the energy consumption level after the implementation of the solution. The historical energy consumption benchmark can be determined based on historical energy consumption records under similar task types and load conditions. The state improvement value reflects the expected degree of equipment state improvement after the implementation of the candidate solution. The comprehensive equipment state evaluation value after execution can be estimated based on the load adjustment, task transfer, or maintenance results corresponding to the candidate solution, according to preset rules, rather than having to wait until the actual execution is completed. This approach can uniformly convert the management impact of different dimensions into comparable quantitative results, thereby facilitating the ranking and selection of multiple candidate solutions. For example, for two executable candidate solutions, if one solution has slightly higher maintenance requirements but can significantly reduce subsequent state burden and energy consumption, its comprehensive decision value may be higher than that of the other solution, which only maintains short-term operation but has limited improvement effects.

[0030] Step 43 involves associating and recording each candidate management scheme with its corresponding operation and maintenance value, maintenance resource occupancy value, energy consumption cost, status improvement value, and comprehensive decision value. This establishes a correspondence between candidate management schemes and comprehensive decision values, forming a candidate management scheme comparison result table. This table is a data table or data structure used to record the comparison results of each candidate scheme. It not only stores the scheme identifier but also records various evaluation indicators and their corresponding comprehensive decision values, facilitating subsequent scheme ranking, resource conflict resolution, and optimal management scheme selection. By establishing a unified comparison result table, different candidate schemes can be compared under the same evaluation criteria, reducing the arbitrariness and inconsistency caused by manual judgment.

[0031] Through the above implementation process, this embodiment can select executable solutions from multiple preset candidate management schemes based on the joint constraints of operation and maintenance. It then comprehensively compares each scheme from multiple aspects, including operation maintenance, resource consumption, energy consumption impact, and condition improvement. This not only improves the comprehensiveness of the candidate scheme comparison but also incorporates equipment operation arrangements, maintenance arrangements, and resource usage into a unified decision-making process. It avoids the bias caused by selecting based on a single indicator, thus providing a more reliable basis for determining the optimal management scheme and enhancing the rationality and synergy of equipment operation management decisions.

[0032] In one embodiment of the present invention, the optimal management scheme for each device is determined based on the comprehensive decision value corresponding to each candidate management scheme, the resource occupancy corresponding to each candidate management scheme, the comprehensive evaluation value of the equipment status, historical operation management data, and the total available resources of the equipment group. The optimal management scheme refers to the target scheme determined after satisfying the overall resource constraints of the equipment group, taking into account the scheme execution effect, resource occupancy level, and the current status of the equipment. This embodiment places multiple devices within the equipment group under unified resource conditions for scheme selection, ensuring that the determination of the optimal management scheme considers both the merits and demerits of individual device schemes and the resource coordination relationships at the equipment group level. The total available resources of the equipment group refer to the total amount of resources that the equipment group can use together within the current decision-making cycle, which may include the number of deployable alternative equipment, the number of available maintenance personnel, available maintenance workstations, available maintenance window length, or other limited resources.

[0033] Specifically, in step 51, the following data is retrieved: the candidate management scheme set, the comprehensive decision value corresponding to each candidate management scheme, the resource occupancy corresponding to each candidate management scheme, the comprehensive equipment status assessment value, historical operation management data, and the total available resources of the equipment group. The candidate management scheme set reflects the set of schemes that can enter the optimization process after screening by each device in the previous processing stage; the resource occupancy is used to characterize the usage requirements of the candidate management scheme on the common resources of the equipment group during execution; the comprehensive equipment status assessment value is used to reflect the current overall status level of the target equipment. After retrieving the above data, the scheme effectiveness, equipment status, and resource conditions can be incorporated into the same processing step, providing basic data support for subsequent sorting and verification. Historical operation management data can be used here to supplement the identification of the load arrangement, task connection relationship, and resource calling habits of the equipment in previous task executions, thereby making the scheme optimization results more consistent with the current operation organization mode of the equipment group.

[0034] Step 52: For each candidate management scheme, the resource occupancy of each scheme is compared with the total available resources of the equipment group to obtain the resource occupancy ratio. The comprehensive decision value, resource occupancy ratio, and comprehensive equipment status assessment value are then weighted and summed according to preset weights to obtain the scheme ranking value for each candidate management scheme. The resource occupancy ratio reflects the degree of resource occupancy of a candidate management scheme on the overall resources of the equipment group; a higher occupancy rate indicates a more significant consumption of shared resources. The scheme ranking value is used to uniformly rank the candidate management schemes to select the target scheme based on subsequent constraint verification. In this process, the comprehensive decision value reflects the overall performance of the scheme in terms of operation maintenance, maintenance occupancy, energy consumption impact, and status improvement; the resource occupancy ratio reflects the degree of consumption of the common resources of the equipment group by the scheme; and the comprehensive equipment status assessment value reflects the impact of the current status of the target equipment on the scheme selection. By incorporating the above factors into the ranking process, judgments cannot be made based solely on the score of a single scheme. For example, if two candidate schemes have similar overall decision values, the one that requires significantly less maintenance time window and alternative equipment resources can be ranked better and thus be more suitable for priority selection when the overall resources of the equipment group are limited.

[0035] Step 53: Perform constraint verification on the resource occupancy and total available resources of the equipment group for each candidate management scheme. Among the candidate management schemes that meet the constraint verification, select the one with the highest ranking value as the optimal management scheme for the corresponding equipment and record the association. The constraint verification refers to determining whether the candidate management scheme will exceed the resource supply limit of the equipment group in the current cycle or cause resource conflicts with other selected schemes during execution. Only candidate management schemes that simultaneously meet the resource constraints of the equipment group can enter the final selection stage. For candidate management schemes that pass the constraint verification, the system selects the one with the highest ranking value as the optimal management scheme for the corresponding equipment and records the optimal management scheme with the equipment identifier, resource occupancy, and ranking result for use in subsequent operation and maintenance plan generation. For example, when the candidate schemes for two equipment both require the same maintenance workstation during the same time period, but only one equipment is allowed to enter for maintenance during that time period, the scheme with the higher ranking value can be retained first, and the other equipment can be adjusted to the second highest ranking candidate scheme that still meets the resource constraints.

[0036] Through the above implementation process, this embodiment can uniformly sort and verify the candidate management schemes for each device under the overall resource constraints of the equipment group, avoiding resource contention, plan conflicts, or unfeasible execution caused by different devices selecting locally optimal schemes. This approach helps improve the overall coordination of the candidate scheme determination results, ensuring consistency between equipment operation arrangements, maintenance arrangements, and the use of shared resources, thereby enhancing the executability of equipment operation management decisions and the overall optimization effect.

[0037] In one embodiment of the present invention, an operation plan is obtained by adjusting equipment tasks, equipment load, and runtime according to the optimal management scheme, and a maintenance plan is obtained based on the comprehensive equipment status assessment value, historical maintenance management data, and historical operation management data. The operation plan refers to the execution scheme formed for the task arrangement, load configuration, and runtime of the target equipment within the current decision-making cycle; the maintenance plan refers to the arrangement result formed for the maintenance sequence, maintenance time, and maintenance actions of the target equipment within the current decision-making cycle.

[0038] Specifically, in step 61, the equipment tasks, initial equipment load, and initial running time are determined according to the optimal management scheme. The initial equipment load is compared with the historical load range corresponding to historical operation management data, and the initial equipment load exceeding the historical load range is adjusted to the historical load range. The initial running time is compared with the historical running time range corresponding to historical operation management data, and conflicting periods are postponed to obtain the operation plan. Here, the initial equipment load and initial running time refer to the planned load and planned execution time arrangement of the equipment directly determined according to the optimal management scheme; the historical load range refers to the historical acceptable load interval formed by the equipment under the same or similar task conditions, used to verify whether the current planned load is within a reasonable range. If the initial equipment load exceeds the historical load range, it is corrected to the corresponding range to avoid the planned load exceeding the equipment's usual carrying capacity. The conflicting period refers to the time interval where the initial running time overlaps with existing task arrangements, occupied time periods, or other operation arrangements of the equipment. For such periods, the running time can be rearranged by postponement to ensure that the operation plan can be implemented in time. For example, if a device is scheduled to perform a task during a certain time period according to the optimal management plan, but that time period is already occupied by a preceding task, the task can be postponed to the next available time period. Through this process, the operation plan can maintain the task direction determined by the optimal management plan while also conforming to the actual load capacity of the equipment and time constraints.

[0039] Step 62: Based on the comprehensive equipment status assessment value and the number of incomplete maintenance items in historical maintenance management data, a weighted average is performed according to preset weights to obtain a maintenance priority value. The maintenance order is determined from high to low maintenance priority values. Combined with the equipment idle time periods in historical operation management data and the target maintenance window and maintenance action category in the optimal management plan, the maintenance execution time is determined to obtain the maintenance plan. The maintenance priority value characterizes the urgency of the target equipment entering the maintenance schedule in the current cycle, reflecting both the current comprehensive status level of the equipment and the backlog of existing maintenance items. The higher the maintenance priority value, the more likely the equipment should be prioritized in the maintenance sequence. The equipment idle time period refers to the time interval during which the equipment is not undertaking operational tasks, identified based on historical operation management data and the current operation schedule. The target maintenance window refers to the time range within which maintenance can be performed, determined during the preceding constraint generation and scheme optimization stages. The maintenance action category refers to the maintenance processing method that the current equipment should perform, such as review, maintenance, repair, or component replacement. By combining maintenance priority ranking with equipment idle time periods, target maintenance windows, and maintenance action categories, a more suitable maintenance execution time can be determined. For example, if a piece of equipment has a high maintenance priority and has an idle time period the following morning that falls within the target maintenance window, the corresponding maintenance action can be scheduled for that idle time period. This allows maintenance insertion to be completed without significantly impacting existing operational tasks.

[0040] Step 63 involves associating the operation plan with the maintenance plan, recording equipment tasks, equipment load, runtime periods, maintenance sequence, maintenance execution time, target maintenance window, and maintenance action category to form an execution plan. The execution plan refers to the unified organization of operation-side and maintenance-side arrangements, describing the tasks, operating methods, and maintenance requirements that the equipment should perform within the current decision-making cycle. By associating the operation plan and maintenance plan, the previously separate operation and maintenance arrangements can be integrated into the same execution framework, facilitating unified distribution, scheduling, and tracking, and reducing discrepancies between plans.

[0041] Through the above implementation process, this embodiment can generate an operation plan that matches the actual operating capacity and time schedule of the equipment based on the optimal management scheme. Simultaneously, it generates a corresponding maintenance plan by combining the current status of the equipment and the maintenance backlog, and further integrates the two into an execution plan. This not only helps ensure the continuity and rationality of the operation task arrangement, but also improves the targeting and timing coordination of maintenance insertions, avoiding conflicts and repeated adjustments caused by the independent formulation of the operation plan and maintenance plan, thereby enhancing the executability of equipment operation management decisions and the synergistic effect of the plans.

[0042] In one embodiment of the present invention, execution results are obtained based on the operation plan and maintenance plan. These results are then verified using the comprehensive equipment status assessment values ​​before and after execution to obtain a status improvement amount. The equipment operation management basic data is then updated based on this status improvement amount. The execution results reflect the equipment task execution, load execution, operation time scheduling, and maintenance implementation. The status improvement amount refers to the change in the comprehensive equipment status assessment value before and after execution, characterizing the degree of improvement in equipment status resulting from the current round of operation management and maintenance arrangements. The equipment operation management basic data supports the next round of equipment status quantification, constraint generation, scheme comparison, and plan adjustment.

[0043] Specifically, in step 71, the executed equipment tasks, equipment load, running time, maintenance sequence, maintenance execution time, target maintenance window, and maintenance action category are collected according to the operation plan and maintenance plan to obtain the execution results. The current operating status data of the equipment after execution is then obtained based on the execution results. Here, the operation plan and maintenance plan correspond to the equipment's operation and maintenance arrangements within the current cycle, respectively. The collection processing refers to summarizing and organizing the actual completion information after the plan's execution to form a unified execution result record. The current operating status data of the equipment after execution refers to the real-time status data of the equipment after completing this round of task execution and maintenance processing, which can be collected by the monitoring system, control system, or maintenance record system. By merging and collecting the execution status on the operation side and the execution status on the maintenance side, the actual execution status of the equipment after this round of management actions can be comprehensively reflected. For example, if a piece of equipment completes load reduction operation and inserts short-term maintenance in this round of execution, its execution result records both the adjusted load and running time, as well as the corresponding maintenance sequence and maintenance action category.

[0044] Step 72: Based on the current operating status data of the equipment after execution, and following the quantitative processing rules for determining the comprehensive evaluation value of the equipment status before execution, obtain the comprehensive evaluation value of the equipment status after execution. Perform difference processing between the comprehensive evaluation value of the equipment status before execution and the comprehensive evaluation value of the equipment status after execution to obtain the status improvement amount, and determine the execution result verification mark based on the status improvement amount. The comprehensive evaluation value of the equipment status after execution refers to the comprehensive evaluation result obtained after recalculating the equipment status after execution using the same quantitative rules as before execution. Using the same quantitative caliber for comparison before and after execution ensures consistency and comparability in the judgment of status changes. The status improvement amount reflects the degree of change in the equipment status after this round of execution relative to before execution. When the comprehensive evaluation value of the equipment status after execution is lower than the comprehensive evaluation value of the equipment status before execution, it indicates that the equipment status has improved; conversely, if the difference between the two is small or no significant improvement is shown, it indicates that the execution arrangement of this round has limited effect on improving the equipment status. The execution result verification mark is a result identifier determined based on the status improvement amount, used to characterize whether this round of execution has met the preset improvement requirements. This mark may include types such as effective improvement, insufficient improvement, or need for continued monitoring.

[0045] Step 73: Update the basic data for equipment operation management based on the execution results, the current operating status data of the equipment after execution, the improvement in status, and the execution result verification mark. Specifically, the execution results are written into historical operation management data and historical maintenance management data; the current operating status data of the equipment after execution replaces the current operating status data of the equipment; and the improvement in status and the execution result verification mark are written into the data. Updating the basic data for equipment operation management means supplementing the basic data set with the operation information, maintenance information, status information, and evaluation results after the execution of this round of plans, ensuring that the basic data is consistent with the actual operating conditions of the equipment. Writing the execution results into historical operation management data and historical maintenance management data allows subsequent decision-making steps to directly reference the latest execution results when reading historical task arrangements, maintenance execution records, operational burdens, and maintenance backlogs. Replacing the current operating status data of the equipment after execution with the current operating status data ensures that the next round of status quantification targets the latest equipment status. Writing the improvement in status and the execution result verification mark helps identify which management arrangements have achieved good results and which arrangements still need further adjustment in subsequent scheme selection and execution effect analysis. For example, if the improvement in status is consistently low after multiple executions of a certain type of maintenance action, the priority of such arrangements can be reduced or the maintenance method adjusted accordingly.

[0046] Through the above implementation process, this embodiment can uniformly collect the actual execution status of operation and maintenance plans, and quantitatively verify the execution effect based on the changes in the comprehensive evaluation value of equipment status before and after execution. The execution results and verification results are then written back to the basic data of equipment operation management. This not only improves the completeness of the feedback on the execution of equipment operation and maintenance plans, but also ensures that the next round of status assessment, constraint generation, scheme comparison, and resource coordination are based on the latest execution results. It reduces the disconnect between static plans and actual execution, and enhances the continuity, verifiability, and closed-loop management effect of the equipment operation management decision-making optimization process.

[0047] This invention also provides a device operation management decision optimization system based on operating status data, including: The basic data integration module is used to acquire the current operating status data, historical operation management data, historical maintenance management data, and historical energy consumption management data of the equipment, and integrate them to obtain the basic data for equipment operation management. The status assessment and processing module is used to quantify the current status of the equipment based on the current operating status data, historical maintenance management data, and historical operation management data, and obtain a comprehensive equipment status assessment value. The constraint set generation module is used to generate operation constraint sets and maintenance constraint sets based on the comprehensive evaluation value of equipment status, historical operation management data, and historical maintenance management data. The scheme selection and comparison module is used to select candidate management schemes from the preset candidate management schemes based on the operation constraint set and the maintenance constraint set, and to compare and process each candidate management scheme to obtain the comprehensive decision value corresponding to each candidate management scheme. The optimal solution determination module is used to determine the optimal management solution for each device based on the comprehensive decision value corresponding to each candidate management solution, the resource occupancy corresponding to each candidate management solution, the comprehensive evaluation value of equipment status, historical operation and management data, and the total available resources of the equipment group. The plan generation and adjustment module is used to adjust equipment tasks, equipment load and runtime according to the optimal management plan to obtain the operation plan, and to obtain the maintenance plan based on the comprehensive evaluation value of equipment status, historical maintenance management data and historical operation management data; The execution verification and update module is used to obtain the execution results based on the operation plan and maintenance plan, and to verify the execution results based on the comprehensive evaluation value of the equipment status before execution and the comprehensive evaluation value of the equipment status after execution, so as to obtain the status improvement amount, and update the basic data of equipment operation management based on the status improvement amount.

[0048] It should be noted that the range and threshold size are set for ease of comparison. The size of the threshold depends on the amount of sample data and the number of bases set by those skilled in the art for each set of sample data, as long as it does not affect the ratio between the parameter and the quantized value.

[0049] The embodiments of the present invention have been described above, but the present invention is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms based on the guidance of the present embodiments, all of which are within the protection scope of the present embodiments.

Claims

1. A method for optimizing equipment operation management decisions based on operational status data, characterized in that, Includes the following steps: Step 1: Obtain the current operating status data, historical operation management data, historical maintenance management data, and historical energy consumption management data of the equipment, and integrate them to obtain the basic data for equipment operation management; Step 2: Based on the current operating status data, historical maintenance management data, and historical operation management data, the current status of the equipment is quantified to obtain a comprehensive evaluation value of the equipment status. Step 3: Generate an operational constraint set and a maintenance constraint set based on the comprehensive equipment status assessment value, historical operation management data, and historical maintenance management data; Step 4: Based on the running constraint set and the maintenance constraint set, select candidate management schemes from the preset candidate management schemes, compare and process each candidate management scheme, and obtain the comprehensive decision value corresponding to each candidate management scheme; Step 5: Based on the comprehensive decision value corresponding to each candidate management scheme, the resource occupancy corresponding to each candidate management scheme, the comprehensive evaluation value of equipment status, historical operation management data, and the total available resources of the equipment group, determine the optimal management scheme for each piece of equipment. Step 6: Adjust equipment tasks, equipment load, and operating times according to the optimal management plan to obtain the operation plan, and obtain the maintenance plan based on the comprehensive evaluation value of equipment status, historical maintenance management data, and historical operation management data; Step 7: Obtain the execution results based on the operation plan and maintenance plan, verify the execution results based on the comprehensive equipment status assessment values ​​before and after execution, obtain the status improvement amount, and update the basic data of equipment operation management based on the status improvement amount.

2. The equipment operation management decision optimization method based on operating status data according to claim 1, characterized in that, Acquire and integrate the equipment's current operating status data, historical operation management data, historical maintenance management data, and historical energy consumption management data to obtain basic equipment operation management data, including: Step 11: Determine the target device based on the device identifier, obtain the current operating status data of the target device according to the current collection time, and obtain the historical operation management data, historical maintenance management data and historical energy consumption management data of the target device according to the historical statistical time window; Step 12: Filter, extract, and verify the records, fields, and consistency of the current operating status data, historical operation management data, historical maintenance management data, and historical energy consumption management data of the equipment. Among these steps, duplicate records are retained based on the latest record, records that are outside the historical statistical time window are removed, and the consistency of equipment identification, time range, and field units is verified. Step 13: Extract the current task number, current load level, cumulative runtime, number of periodic start-stop cycles, current task priority, and set of alternative devices from historical operation management data; extract the number of incomplete maintenance items and set of allowed maintenance time windows from historical maintenance management data; extract the number of periodic alarm items from current equipment operating status data; and calculate the ratio between the cumulative energy consumption and cumulative runtime in historical energy consumption management data to obtain the energy consumption value per unit time. This value is then integrated with the current equipment operating status data to obtain the basic data for equipment operation management.

3. The equipment operation management decision optimization method based on operating status data according to claim 1, characterized in that, Based on the current operating status data, historical maintenance management data, and historical operation management data of the equipment, the current status of the equipment is quantified to obtain a comprehensive equipment status assessment value, including: Step 21: Read the basic data of equipment operation management of the target equipment, and extract the current operating status data, historical operation management data, historical maintenance management data, current task number, current load level, cumulative running time, number of cycle start-stop cycles, number of cycle alarm entries, and number of incomplete maintenance entries. Step 22: Based on the current task number and current load level, filter the corresponding historical operation records from the historical operation management data. For each status field in the current operation status data of the device, determine the average value of the corresponding historical operation records as the status baseline value, and determine the difference between the maximum and minimum values ​​of the corresponding historical operation records as the status allowable deviation. Step 23: Based on the difference between the current value of each status field and the corresponding status baseline value, and the ratio of the difference to the allowable deviation of the corresponding status, determine the deviation ratio of each status field. The deviation ratio exceeding the preset upper limit is truncated, and a weighted sum is performed according to the weight of the corresponding status field to obtain the status deviation value. The cumulative running time, the number of cycle start-stop times, and the number of cycle alarm entries are normalized and weighted to obtain the running burden value. Step 24: Normalize the number of incomplete maintenance items to obtain the maintenance burden value; weight the status deviation value, operation burden value and maintenance burden value according to the corresponding comprehensive evaluation weights, and summarize the weighted results to obtain the comprehensive equipment status evaluation value.

4. The equipment operation management decision optimization method based on operating status data according to claim 1, characterized in that, Based on the comprehensive equipment status assessment value, historical operation management data, and historical maintenance management data, an operation constraint set and a maintenance constraint set are generated, including: Step 31: Compare the comprehensive evaluation value of the equipment status with the preset segmented threshold to determine the operating constraint level. Combine the historical load records and continuous operation records corresponding to the current task number and current load level in the historical operation management data to determine the maximum allowable load level and the upper limit of the allowable continuous operation time. At the same time, determine the task transfer flag according to the current task priority. Step 32: The maintenance insertion value is obtained by weighting the number of incomplete maintenance items and the comprehensive evaluation value of equipment status according to the preset weights, and the maintenance insertion value is mapped to the maintenance constraint level and maintenance insertion mark according to the preset interval mapping rules. Step 33: Select the target maintenance window based on the maintenance insertion mark and the set of allowed maintenance windows, and determine the maintenance action category by combining the maintenance records of the corresponding task in the historical maintenance management data, and generate a set of maintenance constraints.

5. The equipment operation management decision optimization method based on operating status data according to claim 1, characterized in that, Based on the operational constraint set and the maintenance constraint set, candidate management schemes are selected from the preset candidate management schemes. These schemes are then compared and processed to obtain the comprehensive decision value for each candidate scheme, including: Step 41: Check each constraint of the preset candidate management scheme one by one, and retain the candidate schemes that simultaneously meet the maximum allowable load level, the maximum allowable continuous running time and the task transfer flag in the operation constraint set, as well as the maintenance insertion flag, the target maintenance time window and the maintenance action category in the maintenance constraint set, to obtain the candidate management scheme set. Step 42: For the candidate management scheme set, the task load of each candidate scheme is compared with the allowable load limit to obtain the operation maintenance value; the maintenance arrangement resource usage is compared with the historical total resource amount to obtain the maintenance resource usage value; the scheme energy consumption is compared with the historical energy consumption benchmark to obtain the energy consumption cost value; the difference between the comprehensive equipment status assessment value before execution and the comprehensive equipment status assessment value after execution is normalized to obtain the status improvement value; and the operation maintenance value, maintenance resource usage value, energy consumption cost value, and status improvement value are weighted and summarized according to preset weights to obtain the comprehensive decision value. Step 43: Link and record each candidate management scheme with its corresponding operation and maintenance value, maintenance resource consumption value, energy consumption cost, status improvement value and comprehensive decision value, establish the correspondence between candidate management schemes and comprehensive decision values, and form a candidate management scheme comparison result table.

6. The equipment operation management decision optimization method based on operating status data according to claim 1, characterized in that, Based on the comprehensive decision value corresponding to each candidate management scheme, the resource occupancy corresponding to each candidate management scheme, the comprehensive equipment status assessment value, historical operation management data, and the total available resources of the equipment group, the optimal management scheme for each piece of equipment is determined, including: Step 51: Read the candidate management scheme set, the comprehensive decision value corresponding to each candidate management scheme, the resource occupancy corresponding to each candidate management scheme, the comprehensive evaluation value of equipment status, historical operation management data, and the total available resources of the equipment group; Step 52: For each candidate management scheme, the resource occupancy of each candidate management scheme is compared with the total available resources of the equipment group to obtain the resource occupancy ratio. The comprehensive decision value, resource occupancy ratio and comprehensive equipment status evaluation value are weighted and summarized according to preset weights to obtain the scheme ranking value corresponding to each candidate management scheme. Step 53: Perform constraint verification on the resource occupancy and total available resources of the equipment group corresponding to each candidate management scheme. Among the candidate management schemes that meet the constraint verification, select the candidate management scheme with the highest scheme ranking value as the optimal management scheme for the corresponding equipment and record the association.

7. The equipment operation management decision optimization method based on operating status data according to claim 1, characterized in that, Based on the optimal management plan, equipment tasks, equipment load, and operating times are adjusted to obtain an operation plan. Furthermore, based on comprehensive equipment status assessments, historical maintenance management data, and historical operation management data, a maintenance plan is obtained, including: Step 61: Determine the equipment tasks, initial equipment load, and initial running time based on the optimal management plan; compare the initial equipment load with the historical load range corresponding to the historical operation management data; adjust the initial equipment load that exceeds the historical load range to the historical load range; compare the initial running time with the historical running time range corresponding to the historical operation management data; and postpone conflicting periods to obtain the operation plan. Step 62: Based on the comprehensive equipment status assessment value and the number of incomplete maintenance items in the historical maintenance management data, perform weighted processing according to preset weights to obtain maintenance priority values; determine the maintenance order from high to low maintenance priority values, and combine the equipment idle time periods in the historical operation management data with the target maintenance time window and maintenance action category in the optimal management plan to determine the maintenance execution time and obtain the maintenance plan; Step 63: Associate the operation plan with the maintenance plan, record the equipment task, equipment load, running time, maintenance sequence, maintenance execution time, target maintenance window and maintenance action category to form an execution plan.

8. The equipment operation management decision optimization method based on operating status data according to claim 1, characterized in that, The execution results are obtained based on the operation and maintenance plans. These results are then verified using the comprehensive equipment status assessment values ​​before and after execution to determine the improvement in equipment status. The basic equipment operation management data is then updated based on this improvement, including: Step 71: Based on the operation plan and maintenance plan, collect the executed equipment tasks, equipment load, running time, maintenance sequence, maintenance execution time, target maintenance window and maintenance action category to obtain the execution results, and obtain the current operating status data of the equipment after execution based on the execution results; Step 72: Based on the current operating status data of the equipment after execution, and according to the quantitative processing rules for determining the comprehensive evaluation value of the equipment status before execution, obtain the comprehensive evaluation value of the equipment status after execution; perform difference processing on the comprehensive evaluation value of the equipment status before execution and the comprehensive evaluation value of the equipment status after execution to obtain the status improvement amount, and determine the execution result verification mark based on the status improvement amount; Step 73: Update the basic data of equipment operation management based on the execution result, the current operating status data of the equipment after execution, the status improvement amount, and the execution result verification mark; wherein, the execution result is written into the historical operation management data and the historical maintenance management data, the current operating status data of the equipment after execution is replaced with the current operating status data of the equipment, and the status improvement amount and the execution result verification mark are written.

9. A device operation management decision optimization system based on operational status data, characterized in that, The equipment operation management decision optimization method based on operating status data as described in any one of claims 1-8 includes: The basic data integration module is used to acquire the current operating status data, historical operation management data, historical maintenance management data, and historical energy consumption management data of the equipment, and integrate them to obtain the basic data for equipment operation management. The status assessment and processing module is used to quantify the current status of the equipment based on the current operating status data, historical maintenance management data, and historical operation management data, and obtain a comprehensive equipment status assessment value. The constraint set generation module is used to generate operation constraint sets and maintenance constraint sets based on the comprehensive evaluation value of equipment status, historical operation management data, and historical maintenance management data. The scheme selection and comparison module is used to select candidate management schemes from the preset candidate management schemes based on the operation constraint set and the maintenance constraint set, and to compare and process each candidate management scheme to obtain the comprehensive decision value corresponding to each candidate management scheme. The optimal solution determination module is used to determine the optimal management solution for each device based on the comprehensive decision value corresponding to each candidate management solution, the resource occupancy corresponding to each candidate management solution, the comprehensive evaluation value of equipment status, historical operation and management data, and the total available resources of the equipment group. The plan generation and adjustment module is used to adjust equipment tasks, equipment load and runtime according to the optimal management plan to obtain the operation plan, and to obtain the maintenance plan based on the comprehensive evaluation value of equipment status, historical maintenance management data and historical operation management data; The execution verification and update module is used to obtain the execution results based on the operation plan and maintenance plan, and to verify the execution results based on the comprehensive evaluation value of the equipment status before execution and the comprehensive evaluation value of the equipment status after execution, so as to obtain the status improvement amount, and update the basic data of equipment operation management based on the status improvement amount.

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