Mine equipment operation and maintenance management system based on multi-dimensional data analysis

Abstract

The application discloses a mine equipment operation and maintenance management system based on multi-dimensional data analysis, relates to the technical field of mine operation and maintenance data management, and is used for solving the problem that operation and maintenance data is difficult to align; the application constructs a closed-loop operation and maintenance process of object alignment, time sequence verification, event merging, work order arrangement and scheduling write-back, unifies account books, point tables, work orders, sensor data and control logs into asset object keys, generates state frames and event frames, realizes multi-source data correlation, generates credible markers by means of missing measurement, marking, jump and drift marking, and cuts available time sequence fragments, suppresses false disposal, generates event clusters and cluster abstracts based on a rolling window, supports the generation of work order packages by matching a disposal template library, forms a resource constraint table and an alternative path set, and allocates a planned time window and a responsible team according to an urgency level field and a window demand field, and the resource is changed to rearrange incrementally and write back execution and acceptance record update templates, thereby improving disposal timeliness and executability.

Description

Technical Field

[0001] This invention relates to the field of mine operation and maintenance data management technology, and more specifically, to a mine equipment operation and maintenance management system based on multidimensional data analysis. Background Technology

[0002] In mining equipment operation and maintenance management scenarios, critical equipment such as crushing, conveying, drainage, and ventilation are constantly under high load and multiple operating conditions. Operation and maintenance management typically relies on ledgers, location lists, work orders, sensor data, and control logs to determine equipment health and schedule maintenance. Existing solutions mostly rely on scattered records from various business systems. There is a lack of unified object identification and a unified time base between sensor data collection, control logs, and work order flow. This results in inconsistent field definitions for the same equipment component in different systems, making it difficult to attribute operating status, operating conditions, and event records to the same maintainable object.

[0003] Meanwhile, network jitter, offline transmission, and sampling frequency differences exist in the mine, naturally leading to missing data, out-of-order data, jumps, and drift. Without reliable segmentation and extraction of usable segments, abnormal alarms are easily fragmented and repeatedly triggered, making it difficult for maintenance personnel to identify the event chain that truly needs to be addressed amidst information noise. Furthermore, existing work order generation and scheduling rely heavily on manual experience or static rules, often failing to link personnel availability windows, spare parts status, and work permit time windows as unified constraints. This results in work orders being generated but unexecutable, or frequent plan changes leading to increased on-site coordination costs. When resource status or event status changes, there is a lack of traceable incremental rescheduling and execution write-back mechanisms, making it difficult to reflect acceptance results back into the handling template and resource requirement parameters. This causes the same problems to recur, hinders the iteration of handling knowledge, and affects the timeliness and reliability of mine operation and maintenance management. Summary of the Invention

[0004] To overcome the aforementioned shortcomings of existing technologies, the following solutions are proposed to address the problem of difficulty in aligning operation and maintenance data in the background technologies described above.

[0005] To achieve the above objectives, the present invention provides the following technical solution:

[0006] The mine equipment operation and maintenance management system based on multidimensional data analysis includes an object alignment module, a timing verification module, an event merging module, a work order arrangement module, and a schedule write-back module, with data communication connections between modules;

[0007] The object alignment module is used to access ledgers, location tables, work orders, sensor data and control logs, generate asset object keys and generate status frames and event frames based on asset object keys;

[0008] The timing verification module is used to align the time base of the state frame and the event frame and generate a reliable marker, and output a usable timing segment;

[0009] The event merging module is used to generate event clusters and cluster summaries within a scrolling window based on available time-series fragments and asset object keys;

[0010] The work order orchestration module is used to generate work order packages based on the event cluster matching and handling template library, and to generate resource constraint tables based on personnel, spare parts and work permit data, and generate alternative path sets for the work order packages;

[0011] The scheduling write-back module is used to generate scheduling plans for work order packages based on resource constraint tables, perform incremental rescheduling when event clusters or resource status change, and write back work order execution records and acceptance records.

[0012] Furthermore, the object alignment module integrates ledgers, location tables, work orders, sensor data, and control logs to generate asset object keys and, based on these keys, generate status frames and event frames, including:

[0013] Analyze the equipment and component identifiers in the ledger, analyze the location identifiers and data acquisition channel identifiers in the location table, and establish a hierarchical mapping between equipment identifiers, component identifiers, and location identifiers;

[0014] Perform field unification on the equipment and component fields in the work order to obtain the work order object identifier;

[0015] Perform point mapping on the channel fields in the sensor data and control log to obtain the data acquisition object identifier;

[0016] Asset object keys are generated based on work order object identifiers and data collection object identifiers, and written into the location mapping table;

[0017] Data is aggregated based on asset object keys, generating status frames and event frames.

[0018] Furthermore, the status frame and event frame contain a fixed set of fields, which includes a timestamp, a data source identifier, an asset object key, and a field completeness flag.

[0019] The status frame also contains a set of status fields, which includes operating status, working condition fields, and a set of collected values.

[0020] The event frame also contains a set of event fields, which includes the event category, the set of event parameters, and the event flag.

[0021] Furthermore, the timing verification module aligns the state frame and event frame with a time base and generates a reliable marker, outputting usable timing segments, including:

[0022] The state frames and event frames are corrected according to time stamps to generate an alignment sequence.

[0023] When there are abnormal time intervals in the alignment sequence, a missing test flag is generated; when there is time reversal in the alignment sequence, a disordered flag is generated.

[0024] Jump markers are generated based on changes in the acquired values ​​of adjacent frames, and drift markers are generated based on the offset trends of consecutive frames;

[0025] Trusted markers are generated based on missing test markers, out-of-order markers, jump markers, and drift markers, and usable time segments are obtained by segmenting and aligning sequences according to trusted markers.

[0026] Furthermore, the event merging module generates event clusters within a scrolling window based on available time-series fragments and asset object keys, including:

[0027] Grouping available time-series fragments by asset object key yields the event sequence within the object;

[0028] Candidate aggregation intervals are determined based on temporal proximity constraints within an object's event sequence;

[0029] Within the candidate aggregation interval, merging is performed based on event category consistency constraints and state change pattern consistency constraints.

[0030] The merged result generates event cluster identifiers and determines the event cluster boundaries. The event cluster boundaries are determined by the timestamps of the first and last event frames within the event cluster.

[0031] Furthermore, in the event merging module, a cluster summary is generated based on the event cluster. The cluster summary includes the component scope field, urgency level field, evidence index field, disposal category field, and window requirement field.

[0032] The component scope field is determined based on the asset object key and the location mapping table; the urgency level field is determined based on the degree of deviation between the event category and the status field set; the evidence index field is generated based on the location markers of the event frame and status frame in the available time segment based on the event cluster boundary; the disposal category field is generated based on the mapping between the event category and the urgency level field; and the window requirement field is generated based on the disposal category field and the work permit data.

[0033] Furthermore, the work order orchestration module generates work order packages based on the event clusters and cluster digests matching processing template library, including:

[0034] Store the disposal template in the disposal template library, and associate the disposal template with the equipment model field, disposal category field, and component range field;

[0035] Select the target disposal template based on the disposal category field, component range field, and equipment model field in the cluster summary;

[0036] Generate work order package identifiers based on the target handling template and associate them with event cluster identifiers;

[0037] The work order package includes a sequence of work steps, a spare parts list, a tool list, skill requirements, a work permit list, and acceptance items. It also generates a step dependency description based on the sequence of work steps, which is used to constrain the order of the work steps.

[0038] Furthermore, the work order orchestration module generates a resource constraint table based on personnel, spare parts, and work permit data, including:

[0039] Extract team identifiers, skill identifiers, and available time windows from personnel data to form available personnel items;

[0040] Extract spare parts identifier, inventory status, in-transit status and occupied status from spare parts data to form spare parts available items;

[0041] Extract license type, license status, and license time window from the work permit data to form available license items;

[0042] Based on the skill requirements, spare parts list, and work permit list of the work order package, the available personnel items, spare parts items, and permit items are matched to generate a set of constraint items, and the set of constraint items and the corresponding available time window are written into the resource constraint table.

[0043] Furthermore, the work order orchestration module generates a set of alternative paths for the work order package, including:

[0044] Generate a set of constraint gap items for work order packages based on the resource constraint table;

[0045] When the set of constraint gaps exists, generate delayed window paths, split paths, alternative spare parts paths, outsourcing paths, and risk mitigation paths for work order packages;

[0046] The delayed window path is used to adjust the planned time window of the work order package to the corresponding available time window in the resource constraint table; the split path is used to split the work order package into inspection work order packages and maintenance work order packages and generate dependency descriptions; the alternative spare parts path is used to update the spare parts list of the work order package based on the spare parts data; the outsourcing path is used to map skill requirements to outsourcing resource requirements and write the outsourcing resource requirements into the resource constraint table; the risk suppression path is used to generate a risk suppression operation step sequence based on the handling template library and update the operation permit list of the work order package; each path is associated with trigger conditions and rollback conditions.

[0047] Furthermore, the scheduling write-back module generates a scheduling plan for the work order package based on the resource constraint table, performs incremental rescheduling when event clusters or resource status change, and writes back the work order execution record and acceptance record, including:

[0048] The order package sorting is determined based on the urgency level field and the window requirement field in the cluster summary corresponding to the event cluster.

[0049] Based on the resource constraint table, a scheduling plan is generated to allocate planning time windows and responsible work teams to work order packages;

[0050] When the event cluster changes or the personnel status, spare parts status, or work permit status corresponding to the resource constraint table changes, the affected work order package set is determined and the planned time window or responsible team is updated to generate incremental rearrangement results for the affected work order package set.

[0051] Collect work order execution records and acceptance records associated with the work order package identifier and write them into the work order data. Update the matching parameters and resource requirement parameters of the disposal template library based on the acceptance records.

[0052] The technical effects and advantages of the mine equipment operation and maintenance management system based on multidimensional data analysis of this invention are as follows:

[0053] This invention achieves traceable association and consistent utilization of multi-source data of mining equipment under a unified object and time benchmark by constructing a closed-loop operation and maintenance management process that includes object alignment, time sequence verification, event merging, work order arrangement and schedule writeback. It unifies ledgers, location tables, work orders, sensor data and control logs into asset object keys and encapsulates them into status frames and event frames, so that the operating status, working condition fields and collection value sets can form a contextual correspondence with event categories and event parameter sets, thereby reducing the handling deviation caused by unclear equipment ownership and broken evidence from the source.

[0054] Based on this, the timing verification module generates reliable markers and segments usable timing segments by using missing test markers, out-of-order markers, jump markers, and drift markers, thus preventing unreliable segments from entering subsequent analysis and improving the stability of event identification and correlation. The event merging module generates event clusters and outputs cluster summaries within a scrolling window based on time proximity constraints, event category consistency constraints, and state change pattern consistency constraints. It aggregates fragmented alarms and logs into manageable granularity and uses component scope fields, urgency level fields, evidence index fields, handling category fields, and window requirement fields as core information carriers to support accurate matching of the handling template library and generation of work order packages.

[0055] The work order orchestration module further structures and orchestrates the sequence of work steps, description of step dependencies, spare parts list, skill requirements and work permit list, and generates a resource constraint table and a set of alternative paths, so that the scheduling can simultaneously consider personnel, spare parts and permit time window constraints and provide an executable adjustment plan when resources change;

[0056] The scheduling write-back module determines the sorting and allocates planned time windows and responsible teams based on the urgency level field and window requirement field. When event clusters or resource status changes, it performs incremental rescheduling and writes back the work order execution record and acceptance record. At the same time, it updates the parameters of the disposal template library, realizing the accumulation and iteration of operation and maintenance knowledge, reducing the coordination costs caused by invalid work orders and duplicate scheduling, and improving the timeliness, executability and continuous adaptability of mine operation and maintenance disposal. Attached Figure Description

[0057] Figure 1 This is a schematic diagram of the structure of the mine equipment operation and maintenance management system based on multidimensional data analysis according to the present invention. Detailed Implementation

[0058] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0059] In order to achieve the above objectives, Figure 1 A schematic diagram of the structure of the mine equipment operation and maintenance management system based on multidimensional data analysis of the present invention is given, which specifically includes an object alignment module, a timing verification module, an event merging module, a work order arrangement module, and a schedule write-back module, with data communication connections between modules;

[0060] The object alignment module is used to access ledgers, location tables, work orders, sensor data and control logs, generate asset object keys and generate status frames and event frames based on asset object keys;

[0061] The timing verification module is used to align the time base of the state frame and the event frame and generate a reliable marker, and output a usable timing segment;

[0062] The event merging module is used to generate event clusters and cluster summaries within a scrolling window based on available time-series fragments and asset object keys;

[0063] The work order orchestration module is used to generate work order packages based on the event cluster matching and handling template library, and to generate resource constraint tables based on personnel, spare parts and work permit data, and generate alternative path sets for the work order packages;

[0064] The scheduling write-back module is used to generate scheduling plans for work order packages based on resource constraint tables, perform incremental rescheduling when event clusters or resource status change, and write back work order execution records and acceptance records.

[0065] The object alignment module is used to access ledgers, location tables, work orders, sensor data, and control logs, generate asset object keys, and generate status frames and event frames based on these asset object keys. The specific implementation is as follows:

[0066] The mine equipment operation and maintenance management system based on multidimensional data analysis is deployed at the data processing node on the mine operation and maintenance management side. It establishes data interface connections with the ledger management terminal, location table management terminal, work order management terminal, data acquisition terminal, and control system log terminal. It is used to unify scattered data into a unified data carrier required for subsequent analysis. Among them, the object alignment module serves as the data entry processing unit of the system. It accesses the ledger, location table, work order, sensor data, and control log and performs object consistency processing to ensure that sensor data and control log records can be accurately attributed to the same maintainable object, thereby meeting the requirements of multi-source data aggregation and context association in mine equipment operation and maintenance management.

[0067] The ledger should at least include equipment identifier, component identifier and equipment model fields; the location table should at least include location identifier and acquisition channel identifier; the work order should at least include equipment field and component field; the sensor data should at least include channel field, time stamp and acquisition value set; and the control log should at least include channel field, time stamp and operation status related records and event records.

[0068] The object alignment module defines the above field definitions upon initial access and maintains consistency throughout the entire process: Device identifier is used to uniquely identify a device instance, component identifier is used to uniquely identify a maintainable component unit under the device, point identifier is used to uniquely identify a measurement point or control point, acquisition channel identifier is used to express the channel number and address information of the acquisition end or control end, channel field is the field used to carry channel information in sensor data and control log, time stamp is the time information of record generation or acquisition, and acquisition value set is a set of acquisition value records related to the point within one acquisition cycle.

[0069] The object alignment module generates asset object keys in the order of processing and forms the input collection basis for state frames and event frames. The specific steps include:

[0070] First, parse the equipment identifier and component identifier in the ledger, then parse the location identifier and acquisition channel identifier in the location table, and establish a hierarchical mapping between equipment identifier, component identifier and location identifier. Each record in the hierarchical mapping must contain at least equipment identifier, component identifier, location identifier and acquisition channel identifier, and write it into the location mapping table. The location mapping table is used to map the channel field to the location identifier and trace its corresponding equipment identifier and component identifier.

[0071] The equipment and component fields in the work order are normalized to obtain the work order object identifier. Field normalization includes character whitespace pruning, delimiter unification, alias mapping and historical code mapping. Alias ​​mapping and historical code mapping are provided by a pre-set dictionary and the dictionary entries are output with the standard values ​​of equipment identifier and component identifier, thereby ensuring that the work order object identifier is consistent with the ledger.

[0072] Point mapping is performed on the channel fields in the sensor data and control log to obtain the acquisition object identifier. Point mapping includes normalizing the channel field to a standard format consistent with the acquisition channel identifier and searching for matching items in the point mapping table. When a match is successful, the point identifier is output along with the associated device identifier and component identifier, thus forming an acquisition object identifier that includes the device identifier, component identifier and point identifier.

[0073] Finally, an asset object key is generated based on the work order object identifier and the collection object identifier. The generation rule for the asset object key is to combine the equipment identifier, component identifier and location identifier in a preset order to form a unified code and perform character encoding standardization. The generated asset object key is written back to the location mapping table and stored in association with the location identifier, so that the asset object key can be directly located when the same collection channel identifier is accessed in the future and the object ownership remains stable.

[0074] After obtaining the asset object key, the object alignment module aggregates the accessed data based on the asset object key and generates status frames and event frames. The steps include:

[0075] Both the status frame and the event frame contain a fixed set of fields, which includes a time stamp, a data source identifier, an asset object key, and a field completeness flag. The data source identifier is used to distinguish the source of ledgers, location tables, work orders, sensor data, and control logs. The field completeness flag is used to identify whether the fixed set of fields and key business fields are complete and to record the categories of missing fields.

[0076] The field completeness flag defines a list of required fields based on the data source identifier. The list of required fields includes at least the timestamp, the asset object key, and the key business fields of the corresponding frame. The object alignment module performs field existence checks and null value checks on each input record. If the checks fail, the missing field category is written into the field completeness flag, and the record is still encapsulated as a status frame or event frame to retain evidence. However, when outputting to the timing verification module, a filterable flag is written synchronously to remove frames that do not meet the input requirements during the alignment sequence construction.

[0077] The status frame also contains a set of status fields, which includes operating status, working condition fields, and a set of collected values. The operating status is obtained by parsing the start / stop status records in the control log. The working condition fields are obtained by parsing the working condition records in the control log. The set of collected values ​​is formed by aggregating sensor data according to the asset object key, and each record in the set of collected values ​​contains at least a location identifier, a collection channel identifier, and a collected value.

[0078] The event frame also contains a set of event fields, which includes an event category, a set of event parameters, and event flags. The event category is mapped from the event class record in the control log or the work order status change record. The event parameter set is used to carry parameter fields related to the event category and includes at least one or more of the following: trigger condition field, current value field, and threshold field. The event flags are used to record the event source flag and the processing stage flag.

[0079] The status frames and event frames output by the object alignment module serve as input to the timing verification module. The timing verification module performs sequence correction under a unified time base and generates a reliable marker, thereby forming a usable timing segment and entering the event merging processing link.

[0080] The timing verification module is used to align the time base of the state frame and the event frame and generate a reliable marker, outputting a usable timing segment. Specifically, it is implemented as follows:

[0081] The time sequence verification module is deployed in the data processing link of the mine equipment operation and maintenance management process. It receives the status frame and event frame output by the object alignment module as input. Both the status frame and event frame contain time stamps, data source identifiers, asset object keys and field completeness markers. The time sequence verification module is used to unify the time stamps generated by different data sources to the same time base and form a comparable alignment sequence.

[0082] The time reference can be provided by the unified time service provided by the mine data processing node. The time service can use the network time protocol or the precision time protocol to synchronize and calibrate the clocks of the acquisition end and the log end, so that the time stamps generated by each data source have a consistent reference reference.

[0083] In scenarios where strict synchronization on the end side cannot be guaranteed, the timing verification module can maintain a time offset calibration record for each data source identifier, and convert the original time stamp into a unified time stamp according to the time offset calibration record during access, thereby completing the pre-processing for aligning the time reference.

[0084] After aligning the time base, the timing verification module performs sequence correction on the state frames and event frames based on the time stamps to generate an alignment sequence, specifically:

[0085] The input frames are grouped by asset object key. The status frames and event frames in each group are sorted by a unified time stamp. The two types of frames are then merged into a single time-ordered stream by the unified time stamp to form an aligned sequence.

[0086] When a reversed time stamp is found between two adjacent frames, the time sequence verification module generates an out-of-order marker on the corresponding frame and records the out-of-order marker, along with the asset object key and the data source identifier, as a traceable entry.

[0087] When the time stamp interval between two adjacent frames is found to exceed the allowable interval range corresponding to the data source identifier, the timing verification module generates a missing test mark. The allowable interval range is given by the point table or the sampling configuration of the data source identifier, which is used to describe the expected interval boundary of adjacent time stamps of the data source under normal acquisition or normal recording conditions.

[0088] During the sequence correction process, if multiple frame records correspond to the same unified timestamp, the time sequence verification module can determine the merging order according to the preset priority of the data source identifier, and retain the event marker on the event frame to distinguish the order of events under the same scale, so as to avoid the undeterminable repeated sorting of the alignment sequence.

[0089] The aforementioned out-of-order and missing test flags are used to characterize common out-of-order reporting and intermittent offline transmission scenarios in the industrial IoT data link, so as to enable segmented control of data availability in the future.

[0090] The timing verification module further generates jump markers based on the changes in the acquired values ​​of adjacent frames, and generates drift markers based on the offset trend of consecutive frames. The jump markers are generated in the following way:

[0091] Within the alignment sequence, adjacent state frames are selected, and a consistency comparison is performed on the set of collected values ​​with the same location identifier. If a sudden change occurs between adjacent time markers and the change does not meet the allowed change mode corresponding to the running status or working condition field, it is determined to be a jump and a jump marker is generated.

[0092] The threshold for determining abrupt change in the jump marker is given by the sampling configuration in the point table or by the allowable range maintained by event category. The timing verification module retrieves the corresponding threshold according to the point identifier and compares the difference between the collected values ​​of two adjacent frames with the threshold to complete the determination.

[0093] The drift marker is generated as follows: Select consecutive state frames within the alignment sequence, construct an offset trend determination window for the set of collected values ​​with the same location identifier, and if, under the condition of stable operation and no switching of operating conditions, the collected value shows a continuous same-direction offset relative to its historical reference level and exhibits a trend accumulation, it is determined to be a drift and a drift marker is generated.

[0094] The length and trend threshold of the drift marker offset trend determination window are given by the sampling configuration in the point table. The time sequence verification module retrieves by point identifier and accumulates the offset or number of offsets within the window to complete the trend determination.

[0095] Subsequently, the timing verification module generates trusted tags based on missing test tags, out-of-order tags, jump tags, and drift tags. Trusted tags can be obtained by rule mapping. Rule mapping includes at least tag priority constraints and conflict resolution constraints. Tag priority constraints are used to directly mark the corresponding time period as unavailable when missing test tags or out-of-order tags appear. Conflict resolution constraints are used to determine the attribution type of trusted tags when jump tags and drift tags appear simultaneously.

[0096] For example, when generating trusted markers, the system first determines whether missing test markers or out-of-order markers are triggered according to the marker priority sequence. If triggered, the trusted markers for the corresponding time period are set to unavailable. During the time period when missing test markers and out-of-order markers are not triggered, if only jump markers or only drift markers are triggered, the trusted markers are set to downgraded availability and the attribution type is recorded. If jump markers and drift markers are triggered simultaneously, the attribution decision table is called, and the attribution type is determined by combining the stability and trend consistency conditions of the running status and operating condition fields. If it is impossible to determine, the system outputs downgraded availability and records the composite attribution.

[0097] Finally, the timing verification module divides and aligns the sequence according to the trusted marker to obtain usable timing segments. The usable timing segment is a frame sequence that is continuous on a unified time marker and whose trusted marker meets the usability condition. It carries the start and end time markers of the segment and the set of asset object keys in the segment. This serves as the input boundary for the event merging module to generate event clusters and cluster summaries in the scrolling window, thereby avoiding the introduction of unusable segments into the event merging process.

[0098] It should be noted that the trusted flag includes at least three values: available, downgraded available, and unavailable. When the missing test flag or the out-of-order flag appears, the output is unavailable. When only the jump flag or the drift flag appears, the output is downgraded available. When none of the above flags appear and the field completeness flag meets the input requirements, the output is available.

[0099] The event merging module is used to generate event clusters and cluster summaries within a scrolling window based on available time-series segments and asset object keys. Specifically, it is implemented as follows:

[0100] The event merging module runs on the data processing node of the mine operation and maintenance management side. It receives the available time sequence segments output by the time sequence verification module and the asset object key output by the object alignment module, and performs event merging processing on the status frame and event frame in the scrolling window.

[0101] The scrolling window adopts an event-driven sliding window mechanism. The start and end time markers of the window are determined by the time markers of available time segments. The window advances continuously on the time axis according to a preset step. Within each window, event frames and status frames that fall within the window range and whose fields are complete and meet the input requirements are extracted.

[0102] The event merging module groups available time segments by asset object key to obtain an event sequence within the object. The event sequence within the object is a sequence of event frames arranged in order of time stamp under the same asset object key, and shares the same time axis with the status frame sequence under the same asset object key.

[0103] Within an object's event sequence, the event merging module determines candidate aggregation intervals based on time proximity constraints. These constraints limit the time stamp difference between adjacent event frames to within an allowable range and to be within the same scrolling window coverage area. This allows multiple event frames that may belong to the same maintenance event chain to be grouped into the same candidate aggregation interval, preventing long-distance events across windows from being mistakenly merged into the same event cluster.

[0104] The mechanism of segmenting continuously arriving data based on sliding windows and organizing the analysis objects in the order of event time is a common engineering implementation path for streaming windowing and event-time ordered processing, which can be used to support online merging and real-time updates.

[0105] Within the candidate aggregation interval, the event merging module performs merging based on event category consistency constraints and state change pattern consistency constraints to generate event clusters. The event category consistency constraints are used to determine whether the event categories of each event frame within the candidate aggregation interval belong to the same event cluster. The event cluster is defined by a pre-set event category merging table. The event category merging table maps the event categories from the control log source and the event categories from the work order source into a set of mergeable event categories. The event category merging table is maintained by the configuration management unit on the mine operation and maintenance management side and stored in the rule data area of ​​the data processing node.

[0106] The consistency constraint of state change pattern is used to determine whether the sequence of state frames in the candidate aggregation interval matches the state change pattern corresponding to the event cluster. The state change pattern takes the set of state fields as input and is organized in time stamp order. The set of state fields includes at least the running state, working condition field and the set of collected values. The event merging module extracts the running state transition sequence, working condition field switching sequence and the directional change sequence of the collected value set from the continuous state frames in the candidate aggregation interval, and matches them with the reference pattern in the state change pattern library. The state change pattern library is maintained by the configuration management unit of the mine operation and maintenance management side and stored in the rule data area of ​​the data processing node. The corresponding entries are retrieved by event category and asset object key and called in the scrolling window.

[0107] The matching process can be implemented by a time-marked alignment method, that is, for each type of sequence, the consistency item count and inconsistency item location are performed separately. When the inconsistency item does not trigger the preset tolerance condition, it is determined that the state change mode consistency constraint is met, thus allowing the event frames in the candidate aggregation interval to be merged into the same event cluster.

[0108] When the event category consistency constraint or the state change pattern consistency constraint is not met, the event merging module performs segmentation on the candidate aggregation interval and forms multiple event cluster candidates respectively.

[0109] After the merge is completed, the event merging module generates event cluster identifiers and determines event cluster boundaries for the merged results. The event cluster identifier is generated by combining the asset object key, the start time marker of the candidate aggregation interval, and the internal sequence number according to the preset coding rules. The event cluster boundary is determined by the time markers of the first and last event frames within the event cluster. The event cluster boundary is bound to the event cluster identifier and written into the event cluster record so that the work order arrangement module can trace the original evidence and time range according to the event cluster identifier.

[0110] This approach of using time constraints and consistency constraints to achieve event association and merging is a typical implementation idea of ​​event association and correlation merging, which can be used to reduce alarm fragmentation and improve the granularity of the objects to be handled.

[0111] After generating event clusters, the event merging module generates cluster summaries based on the event clusters. The cluster summaries include fields for component scope, urgency level, evidence index, disposal category, and window requirement, specifically:

[0112] The component scope field is determined based on the asset object key and the location mapping table. Specifically, the asset object key is extracted from each event frame in the event cluster and the equipment identifier and component identifier are parsed to obtain them. Then, the set of location identifiers associated with the asset object key is retrieved from the location mapping table, and the component scope field consisting of the component identifier and the set of location identifiers is output.

[0113] The urgency level field is determined based on the degree of deviation between the event category and the set of status fields. Specifically, the event category within the event cluster is used as the main index. For the monitoring items in the set of status fields associated with the event category, allowable intervals and allowable change patterns are defined. The status frames within the coverage area of ​​the event cluster boundary are checked frame by frame. The degree of deviation is obtained by a combination of the allowable interval overshoot and the number of allowable change pattern violations. That is, for each monitoring item, the overshoot of the collected value relative to the allowable interval boundary is calculated, and the largest overshoot is taken as the overshoot index. At the same time, the number of violations of the operating status and working condition fields relative to the allowable change pattern is counted as the pattern violation index. Then, the overshoot index and the pattern violation index are input into the urgency level mapping table to output the urgency level field.

[0114] The evidence index field is generated based on the location markers of event frames and status frames in available time segments by locating the event cluster boundary. Specifically, each available time segment is assigned a segment identifier, and each frame within the segment is assigned a location marker in the order of time markers. The location marker consists of the segment identifier and the frame sequence number. The event merging module filters the set of event frame location markers and the set of status frame location markers that fall within the boundary range according to the event cluster boundary and summarizes them into the evidence index field.

[0115] The disposal category field is generated based on the mapping between the event category and the urgency level field. The mapping relationship is given by the disposal category mapping table, which is categorized and maintained by the disposal strategy on the mine operation and maintenance management side.

[0116] The window requirement field is generated based on the disposal category field and the work permit data. Specifically, it extracts the permit type, permit status, and permit time window from the work permit data, and retrieves the permit type requirements and workable time window requirements corresponding to the disposal category based on the disposal category field to form the window requirement field and output it in association with the event cluster identifier.

[0117] The event merging module sends the event cluster, event cluster identifier, event cluster boundary, and cluster summary as a unified output object to the work order orchestration module to support the matching of the processing template library, the generation of work order packages, and the scheduling process.

[0118] For example, if the sensor data of a crusher experiences abnormal fluctuations in the collected values ​​within a short period, and the control log simultaneously displays an event frame indicating a change in operating status, and the corresponding component of the equipment has an unclosed maintenance record in the work order, the following modules are used: The object alignment module unifies the ledger, location table, work order, sensor data, and control log under the same asset object key to form status frames and event frames. The timing verification module aligns the time base, generates reliable markers, and outputs usable timing segments. The event merging module merges event frames that are adjacent in time, have the same event category, and consistent status change patterns into event clusters within a scrolling window and generates a cluster summary. The work order scheduling module selects target disposal templates from the disposal template library based on the cluster summaries, generates work order packages, and generates a resource constraint table. The scheduling write-back module determines the order of work order packages and allocates planned time windows and responsible work teams based on the urgency level field and window requirement field. Finally, it writes back the work order execution record and acceptance record to update the parameters of the disposal template library.

[0119] The work order orchestration module is used to generate work order packages based on the event cluster matching and handling template library, and to generate resource constraint tables based on personnel, spare parts, and work permit data. It also generates a set of alternative paths for the work order packages. Specifically, the implementation is as follows:

[0120] The work order orchestration module is deployed on the data processing node of the mine operation and maintenance management side. It receives the event cluster, event cluster identifier, and cluster summary associated with the event cluster identifier from the event merging module. The cluster summary includes at least the disposal category field, component scope field, urgency level field, evidence index field, and window requirement field. The work order orchestration module extracts the equipment model field from the ledger based on the asset object key associated with the event cluster identifier, and uses the equipment model field and the cluster summary together as the retrieval conditions for the disposal template library.

[0121] The work order arrangement module stores the disposal templates in the disposal template library in advance. Each disposal template is associated with the equipment model field, disposal category field, and component range field, and maintains the corresponding work step sequence, spare parts list, tool list, skill requirements, work permit list, and acceptance items.

[0122] The work order arrangement module selects the target disposal template from the disposal template library based on the disposal category field, component range field, and equipment model field in the cluster summary. During selection, the candidate disposal template set is first located by the equipment model field and disposal category field, and then the range consistency check is performed on the candidate disposal template set by the component range field to determine the target disposal template. The range consistency check takes the component identifier and location identifier set in the component range field as input and judges whether the component range field covered by the target disposal template matches the component range field of the cluster summary.

[0123] Subsequently, the work order orchestration module generates a work order package identifier based on the target disposal template and associates it with an event cluster identifier. The work order package identifier is generated by combining the event cluster identifier, the target disposal template identifier, and the internal sequence number according to a preset coding rule. The work order package contains the work step sequence, spare parts list, tool list, skill requirements, work permit list, and acceptance items. It also generates a step dependency description based on the work step sequence. The step dependency description uses the step identifier of the work step sequence as nodes and the preceding constraints as edges to form a set of preceding step identifiers and a set of succeeding step identifiers corresponding to each step identifier. This is used to limit the sequential and parallel constraints of the work step sequence.

[0124] The above method of mapping event merging results into executable work orders and explicitly organizing work steps and resource elements conforms to the work order management and maintenance operation organization model commonly used in asset-intensive industries.

[0125] In one embodiment, the work order orchestration module further generates a resource constraint table based on personnel, spare parts, and work permit data to express the executability of the work order package using resource constraints.

[0126] Personnel data includes at least team identifier, skill identifier, and available time window. The work order arrangement module extracts team identifier, skill identifier, and available time window from the personnel data to form personnel availability items. Personnel availability items record the correspondence between team identifier and skill identifier, and record the set of available time windows for team identifier on the future time axis.

[0127] Spare parts data includes at least spare parts identification, inventory status, transit status, and occupied status. The work order arrangement module extracts spare parts identification, inventory status, transit status, and occupied status from the spare parts data to form spare parts availability items. Spare parts availability items record the availability conclusion of the spare parts identification on the current and future time axis, and record the expected inbound time marker corresponding to the transit status for time window inference.

[0128] The work permit data includes at least the permit type, permit status, and permit time window. The work order orchestration module extracts the permit type, permit status, and permit time window from the work permit data to form permit availability items. Permit availability items record the set of permit time windows for the permit type on the future time axis and the permit status.

[0129] Subsequently, the work order orchestration module, based on the skill requirements, spare parts list, and work permit list of the work order package, matches the available personnel items, available spare parts items, and available permit items to generate a set of constraints. The matching rules are as follows:

[0130] Using the skill identifier in the skill requirements, search for the team identifier that meets the conditions in the personnel availability item and intersect their availability time windows. Using the spare parts identifier in the spare parts list, search for the time windows in the spare parts availability item that are available in inventory or in transit. Using the permit type in the work permit list, search for the time windows in the permit availability item that are available in permit status and covered by the permit time window. Then, merge the above time windows in a consistent manner to form the candidate availability time windows for the work order package.

[0131] Finally, the set of constraints and their corresponding available time windows are written into the resource constraint table. The resource constraint table is indexed by work order package identifier, and each work order package identifier records the team identifier constraint item corresponding to the skill requirements, the spare parts identifier constraint item corresponding to the spare parts list, the permit type constraint item corresponding to the work permit list, and their available time windows, thereby providing directly readable resource constraint input for subsequent scheduling generation and incremental reordering.

[0132] The above practice of incorporating personnel, spare parts, and permits into a unified constraint expression is consistent with the engineering management requirement that maintenance planning and scheduling must simultaneously consider labor, spare parts, and permit control.

[0133] In one embodiment, after the resource constraint table is generated, the work order orchestration module generates a set of alternative paths for the work order package, which is used to provide an executable alternative organization method for the same disposal target when resources are insufficient or permissions are limited.

[0134] The work order orchestration module generates a set of constraint gap items for each work order package based on the resource constraint table. This set consists of unmet skill requirements, unmet spare parts list items, and unmet work permit list items. The criterion for unmet requirements is that the constraint item set search result is empty or the corresponding available time window is empty. When a constraint gap item set exists, the work order orchestration module generates delayed window paths, split paths, alternative spare parts paths, outsourcing paths, and risk mitigation paths for each work order package. It also generates a path identifier for each path and associates it with the work order package identifier, trigger conditions, and rollback conditions.

[0135] The trigger condition for the delayed window path is that there is an available time window in the resource constraint table but it does not cover the current planned time window. The delayed window path will adjust the planned time window of the work order package to the corresponding available time window in the resource constraint table and keep the work order package identifier unchanged. The rollback condition is that after the adjustment, there is still a conflict of permitted time windows or the time limit constraint corresponding to the urgency level field is broken.

[0136] The trigger condition for splitting the path is that the skill requirements or the work permit list cannot be met simultaneously within the same time window. The splitting path splits the work order package into an inspection work order package and a maintenance work order package and generates new work order package identifiers for each. At the same time, a dependency description is generated to limit the inspection work order package to be executed before the maintenance work order package. The rollback condition is that the acceptance items of the inspection work order package are not met or the status change mode of the status frame corresponding to the evidence index field has not converged.

[0137] The trigger condition for the alternative spare parts path is that there is a spare parts identifier in the spare parts list that is not available in the available spare parts items. The alternative spare parts path replaces the spare parts identifier in the spare parts list with the available spare parts identifier according to the substitution relationship maintained in the spare parts data and updates the set of constraint items in the resource constraint table synchronously. The rollback condition is that the acceptance item corresponding to the alternative spare parts fails.

[0138] The trigger condition for the outsourcing path is that the skill identifier in the skill requirements has no matching team identifier in the personnel availability items. The outsourcing path maps the skill requirements to outsourcing resource requirements and writes the outsourcing resource requirements into the resource constraint table to form a new set of constraint items. The rollback condition is that the outsourcing resource requirements cannot be met within the time window specified by the window requirement field. The trigger condition for the risk suppression path is that the urgency level field reaches the preset risk threshold and there are gaps in the work permit list. The risk suppression path generates a risk suppression work step sequence based on the handling template library and inserts the work step sequence. At the same time, it updates the work permit list of the work order package to supplement the permit types corresponding to the risk suppression work step sequence. The rollback condition is that the newly added permit type is not available in the permit availability items or the newly added step dependency description causes the planned time window to not fall into the corresponding available time window in the resource constraint table.

[0139] In this way, the alternative path set provides optional operation space for the subsequent scheduling write-back module to perform incremental reordering when event clusters or resource states change, and is consistent with the management requirements that permission control operations need to be organized through formal authorization processes in high-risk environments.

[0140] The scheduling write-back module is used to generate scheduling plans for work order packages based on resource constraint tables, perform incremental rescheduling when event clusters or resource status change, and write back work order execution records and acceptance records. Specifically, it is implemented as follows:

[0141] The scheduling write-back module operates as a scheduling processing unit in the operation and maintenance management platform. Its inputs include the work order package, work order package identifier, step dependency description, and resource constraint table output by the work order orchestration module. The resource constraint table records the available time windows corresponding to personnel available items, spare parts available items, and licensed available items for each work order package identifier.

[0142] The scheduling write-back module first determines the order of work orders based on the urgency level field and window requirement field in the cluster summary corresponding to the event cluster. The urgency level field is used to express the priority of disposal under the same disposal category, and the window requirement field is used to express the work permit time window or work permit status requirement that the work order must fall into. Work permits are a management mechanism for written authorization and time range control of high-risk operations. When scheduling, the permit time window must be included as a scheduling boundary to ensure that the plan can be implemented.

[0143] In one embodiment, the scheduling write-back module generates a scheduling plan by allocating a planned time window and a responsible work team to the work order package based on the resource constraint table. The scheduling plan, indexed by the work order package identifier, includes at least the planned time window, the responsible work team, and the execution order of the steps consistent with the step dependency description.

[0144] When allocating planned time windows, the scheduling write-back module reads the set of constraints and available time windows corresponding to the work order package identifier. First, it uses the permitted available time windows limited by the window requirement field as candidate boundaries. Then, it checks the intersection of the available time windows of personnel available items and spare parts available items within the candidate boundaries to obtain the set of allocable time windows. Finally, it determines the planned time window within the set of allocable time windows according to the preset time priority rules.

[0145] When assigning responsibility teams, the scheduling write-back module searches for a set of team identifiers that meet the skill requirements of the work order package in the available personnel list, and performs availability filtering on the set of team identifiers in combination with the planned time window to obtain a candidate set of responsibility teams. Then, the responsibility teams are determined according to the preset team selection rules.

[0146] The above-mentioned approach of prioritizing work units and incorporating labor, materials, and permit conditions into the scheduling process is consistent with common engineering practices for maintenance work order scheduling.

[0147] For example, if the urgency level field of the cluster summary corresponding to a certain work order package is high and the window requirement field requires it to fall within the valid work permit time window, the scheduling write-back module first increases the sorting priority of the work order package according to the urgency level field, then selects the available time window that simultaneously satisfies the availability of personnel, spare parts, and permits in the resource constraint table as the planned time window, and identifies the responsible work team in the work team identifier that meets the skill requirements and writes it into the scheduling plan. When changes in personnel status, spare parts status, or work permit status cause changes in the available time window, only the planned time window or the responsible work team of the affected work order package set is updated to form an incremental reordering result.

[0148] The scheduling write-back module performs incremental rescheduling when event clusters or resource states change, and writes back work order execution records and acceptance records:

[0149] When a change in an event cluster is detected, the scheduling write-back module locates the set of affected work order packages by using the association between the event cluster identifier and the work order package identifier.

[0150] When changes in personnel status, spare parts status, or work permit status are detected in the resource constraint table, the scheduling write-back module locates the set of work order package identifiers referencing the resource using the team identifier, spare parts identifier, and permit type as indexes, and performs closure expansion with the step dependency description to obtain the set of affected work order packages. The closure expansion searches the work order package identifiers corresponding to the preceding and subsequent steps layer by layer based on the step dependency description, and includes work order packages that have dependencies on the affected work order packages into the affected work order package set. For the affected work order package set, the scheduling write-back module only updates the planned time window or responsible team and generates incremental rescheduling results. Work order packages not identified as affected retain their original scheduling plans, thus completing the incremental rescheduling.

[0151] Subsequently, the scheduling write-back module collects the work order execution records and acceptance records associated with the work order package identifier and writes them into the work order data. The work order execution record includes at least the actual start time marker, the actual completion time marker, the responsible team, the personnel on-duty status, and the spare parts requisition status. The acceptance record includes at least the acceptance item results and the acceptance time marker.

[0152] The scheduling write-back module updates the matching parameters and resource requirement parameters of the disposal template library based on the acceptance records. The matching parameters are used to correct the matching conditions between the disposal template and the equipment model field, disposal category field, and component range field. The resource requirement parameters are used to correct the entries in the skill requirements, spare parts list, tool list, and work permit list within the disposal template, so that the subsequent work order package generation and resource constraint table generation still operate in a closed loop along the same field caliber. The plan adjustment and rescheduling in industrial maintenance scenarios are part of the existing scheduling capabilities, and mainstream asset management and maintenance systems usually provide support for the rescheduling and cause recording of maintenance operations.

[0153] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, in the form of a computer program product.

[0154] Those skilled in the art will recognize that the modules and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0155] In addition, the functional modules in the various embodiments of this application can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module.

[0156] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0157] In conclusion, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A mine equipment operation and maintenance management system based on multidimensional data analysis, characterized in that: It includes an object alignment module, a timing verification module, an event merging module, a work order arrangement module, and a schedule write-back module, as well as data communication connections between modules; The object alignment module is used to access ledgers, location tables, work orders, sensor data and control logs, generate asset object keys and generate status frames and event frames based on asset object keys; The timing verification module is used to align the time base of the state frame and the event frame and generate a reliable marker, and output a usable timing segment; The timing verification module aligns the state frames and event frames with a time reference and generates a reliable marker, outputting usable timing segments. This includes: performing order correction on the state frames and event frames based on the time marker to generate an alignment sequence; generating a missing test marker when there is an abnormal time interval in the alignment sequence, and generating an out-of-order marker when there is a time reversal in the alignment sequence; generating a jump marker based on the changes in the acquired values ​​of adjacent frames, and generating a drift marker based on the offset trend of consecutive frames; generating a reliable marker based on the missing test marker, out-of-order marker, jump marker, and drift marker, and segmenting the alignment sequence according to the reliable marker to obtain usable timing segments. The event merging module generates event clusters and cluster summaries within a scrolling window based on available time-series segments and asset object keys. This generation process includes: grouping available time-series segments by asset object keys to obtain event sequences within each object; determining candidate aggregation intervals within the event sequences based on temporal proximity constraints; performing merging within the candidate aggregation intervals based on event category consistency constraints and state change pattern consistency constraints; generating event cluster identifiers and determining event cluster boundaries for the merged results, with the event cluster boundaries determined by the timestamps of the first and last event frames within the event cluster; and generating cluster summaries based on event clusters. These summaries include a component scope field, an urgency level field, an evidence index field, a disposal category field, and a window requirement field. The component scope field is determined based on the asset object key and a location mapping table; the urgency level field is determined based on the deviation between the event category and the state field set; the evidence index field is generated by locating the position markers of event frames and state frames within the available time-series segments based on the event cluster boundaries; the disposal category field is generated by mapping the event category and urgency level fields; and the window requirement field is generated based on the disposal category field and work permit data. The work order orchestration module generates work order packages based on the event cluster matching and handling template library, and generates a resource constraint table based on personnel, spare parts, and work permit data. It also generates a set of alternative paths for each work order package. The alternative path set generated by the work order orchestration module includes: generating a set of constraint gap items based on the resource constraint table; when constraint gap items exist, generating delayed window paths, split paths, alternative spare parts paths, outsourcing paths, and risk mitigation paths for the work order package; delayed window paths adjust the planned time window of the work order package to the corresponding available time window in the resource constraint table; split paths split the work order package into inspection work order packages and maintenance work order packages and generate dependency descriptions; alternative spare parts paths update the spare parts list of the work order package based on spare parts data; outsourcing paths map skill requirements to outsourcing resource requirements and write these requirements into the resource constraint table; and risk mitigation paths generate a risk mitigation operation step sequence based on the handling template library and update the work permit list of the work order package. Each path is associated with trigger conditions and rollback conditions. The scheduling write-back module is used to generate scheduling plans for work order packages based on resource constraint tables, perform incremental rescheduling when event clusters or resource status change, and write back work order execution records and acceptance records.

2. The mine equipment operation and maintenance management system based on multidimensional data analysis according to claim 1, characterized in that: The object alignment module integrates ledgers, location tables, work orders, sensor data, and control logs, generates asset object keys, and generates status frames and event frames based on these asset object keys, including: Analyze the equipment and component identifiers in the ledger, analyze the location identifiers and data acquisition channel identifiers in the location table, and establish a hierarchical mapping between equipment identifiers, component identifiers, and location identifiers; Perform field unification on the equipment and component fields in the work order to obtain the work order object identifier; Perform point mapping on the channel fields in the sensor data and control log to obtain the data acquisition object identifier; Asset object keys are generated based on work order object identifiers and data collection object identifiers, and written into the location mapping table; Data is aggregated based on asset object keys, generating status frames and event frames.

3. The mine equipment operation and maintenance management system based on multidimensional data analysis according to claim 2, characterized in that: Status frames and event frames contain a fixed set of fields, which includes a timestamp, a data source identifier, an asset object key, and a field completeness flag. The status frame also contains a set of status fields, which includes operating status, working condition fields, and a set of collected values. The event frame also contains a set of event fields, which includes the event category, the set of event parameters, and the event flag.

4. The mine equipment operation and maintenance management system based on multidimensional data analysis according to claim 1, characterized in that: The work order orchestration module generates work order packages based on the event clusters and cluster digests matching template library, including: Store the disposal template in the disposal template library, and associate the disposal template with the equipment model field, disposal category field, and component range field; Select the target disposal template based on the disposal category field, component range field, and equipment model field in the cluster summary; Generate work order package identifiers based on the target handling template and associate them with event cluster identifiers; The work order package includes a sequence of work steps, a spare parts list, a tool list, skill requirements, a work permit list, and acceptance items. It also generates a step dependency description based on the sequence of work steps, which is used to constrain the order of the work steps.

5. The mine equipment operation and maintenance management system based on multidimensional data analysis according to claim 4, characterized in that: The work order scheduling module generates a resource constraint table based on personnel, spare parts, and work permit data, including: Extract team identifiers, skill identifiers, and available time windows from personnel data to form available personnel items; Extract spare parts identifier, inventory status, in-transit status and occupied status from spare parts data to form spare parts available items; Extract license type, license status, and license time window from the work permit data to form available license items; Based on the skill requirements, spare parts list, and work permit list of the work order package, the available personnel items, spare parts items, and permit items are matched to generate a set of constraint items, and the set of constraint items and the corresponding available time window are written into the resource constraint table.

6. The mine equipment operation and maintenance management system based on multidimensional data analysis according to claim 1, characterized in that: The scheduling write-back module generates a scheduling plan for work order packages based on the resource constraint table, performs incremental rescheduling when event clusters or resource status change, and writes back the work order execution record and acceptance record, including: The order package sorting is determined based on the urgency level field and the window requirement field in the cluster summary corresponding to the event cluster. Based on the resource constraint table, a scheduling plan is generated to allocate planning time windows and responsible work teams to work order packages; When the event cluster changes or the personnel status, spare parts status, or work permit status corresponding to the resource constraint table changes, the affected work order package set is determined and the planned time window or responsible team is updated to generate incremental rearrangement results for the affected work order package set. Collect work order execution records and acceptance records associated with the work order package identifier and write them into the work order data. Update the matching parameters and resource requirement parameters of the disposal template library based on the acceptance records.

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