A report template full life cycle management method, device, equipment and medium

Abstract

The application provides a report template full life cycle management method, device, equipment and medium, wherein the method comprises: constructing an index dependency relationship directed acyclic graph based on indexes in a report template, wherein each index node is associated with at least one measurement point or sub-index, and an edge represents a calculation dependency relationship; when data of a bottom layer measurement point or a sub-index monitored is abnormal, traversing the directed acyclic graph to identify all upper layer index nodes affected by the abnormality; freezing the identified upper layer index nodes, and prohibiting data corresponding to the frozen index nodes from participating in report output; taking a node corresponding to the abnormality as a starting point, tracing nodes of a preset level upwards along a dependency edge to form a minimum reoperator graph, and performing data recalculation only on nodes in the minimum reoperator graph, so as to solve the problems of difficult data integration, inefficient abnormality propagation, rigid scheduling, inconvenient cooperation and lack of safe sharing of a general report tool in a power generation scene.

Description

Technical Field

[0001] This invention relates to the field of information technology and production data management for power generation enterprises, and in particular to a method, device, equipment, and medium for full lifecycle management of report templates. Background Technology

[0002] Power generation companies generate massive amounts of production data during daily operations, including data from various measurement points such as unit load, temperature, pressure, and emission concentrations, as well as calculated indicators such as coal consumption for power generation, plant power consumption rate, number of temperature and limit exceedances, and equipment start-up and shutdown records. This data is characterized by long cycles, high frequency, and large volume, and is scattered across real-time databases, relational databases, and manually entered records. Currently, operators and managers typically rely on general-purpose spreadsheet software (such as Microsoft Excel) or simple business intelligence reporting tools to process data, calculate indicators, and generate reports. These tools, as common solutions in existing technology, can complete basic reporting tasks through manual formula editing, timed updates, or manual data entry.

[0003] However, the aforementioned existing solutions have significant technical shortcomings when applied in the power generation industry. First, general-purpose reporting tools cannot directly interface with high-frequency measurement point streams in power plant real-time databases (such as PI and eDNA). Indicator calculations often require manual copying and pasting or writing external scripts, which is inefficient and prone to errors. Second, when a data anomaly occurs at a lower-level measurement point (such as transmission interruption or exceeding thresholds) or when an abnormal time period needs to be removed due to manual appeal, existing tools cannot automatically track all upper-level indicators affected by the anomaly. They can only trigger a full recalculation of the entire report or even the entire indicator tree, resulting in high computational overhead and slow response. Third, the automatic report generation scheduling only supports fixed-time triggering and cannot adapt to the operating conditions of frequent changes in unit load. This leads to generated report data often falling within the variable load and non-steady-state range, reducing its analytical value. Furthermore, when multiple people collaboratively design the same report template, the lack of effective version management and conflict resolution mechanisms makes it easy to overwrite others' modifications; when sharing reports across departments, it is also impossible to provide verifiable compliance proof while protecting the original data.

[0004] Therefore, there is an urgent need for a method for full lifecycle management of report templates to solve the technical problems of existing general-purpose reporting tools in power generation scenarios, such as difficulty in data integration, inefficient anomaly propagation, rigid scheduling, inconvenient collaboration, and lack of secure sharing. Summary of the Invention

[0005] To overcome the problems existing in related technologies, this disclosure provides a method, device, equipment, and medium for full lifecycle management of report templates, in order to solve the technical problems of existing general-purpose reporting tools in power generation scenarios, such as difficulty in data integration, inefficient anomaly propagation, rigid scheduling, inconvenient collaboration, and lack of secure sharing.

[0006] This specification provides one or more embodiments of a method for managing the entire lifecycle of report templates, including the following steps: Construct a directed acyclic graph of indicator dependencies based on the indicators in the report template, where each indicator node is associated with at least one measurement point or sub-indicator, and edges represent computational dependencies. When an anomaly is detected in the data of the underlying measurement points or sub-indicators, the directed acyclic graph is traversed to identify all upper-level indicator nodes affected by the anomaly. The identified upper-level indicator nodes are frozen, and the data corresponding to the frozen indicator nodes is prohibited from participating in the report output. Starting from the node corresponding to the anomaly, trace upwards along the dependent edges to nodes at a preset level to form a minimum recalculation subgraph, and only recalculate the data for the nodes within the minimum recalculation subgraph.

[0007] Preferably, the method further includes the following steps: The optimal scheduling window for automatic report generation is dynamically determined based on the load forecasting model. The load forecasting model predicts the trend of unit load changes in the future period based on historical load curves, meteorological data and power grid dispatching plans, and marks the steady-state window where the load fluctuation rate is lower than a preset threshold. The scheduling time of the report template is adjusted from a fixed time to be triggered within the steady-state window.

[0008] Preferably, the method further includes the following steps: For each modification to the report template, a differential change record is generated, which includes the modification location, old value, new value, operator, and timestamp. When multiple people are editing the same template at the same time, check whether the modification areas overlap; If the cells do not overlap, they will be automatically merged. If they overlap, the dependency tree depth of the formulas in the overlapping areas will be compared, and modifications with higher dependency depths will be retained first.

[0009] Preferably, the anomaly includes data exceeding limits, missing data, or invalid manual marking; The preset hierarchy is 3 layers.

[0010] Preferably, the method further includes the following steps: High-frequency event chains are extracted from historical over-temperature and over-limit events and equipment start-up and shutdown events using a sequence pattern mining algorithm; Inject the preceding feature patterns of the high-frequency event chain into early warning rules; Real-time monitoring of data flow; when a preceding feature pattern is matched, an early warning message is displayed in the corresponding report cell, and adjustment suggestions are pushed.

[0011] Preferably, the method further includes the following steps: In response to a request for secure sharing of report data, a verification credential based on zero-knowledge scope proof is generated, enabling the verifier to confirm that the indicator value meets a preset threshold without disclosing the actual value. The key operations of the report template are generated into hash values ​​and stored in the blockchain.

[0012] Preferably, the method further includes the following steps: When there is an approved abnormal appeal record, the removal logic of the abnormal appeal record is automatically propagated upwards along the directed acyclic graph to the affected upper-level indicators, without the need for reapplication.

[0013] This specification provides one or more embodiments of a report template lifecycle management device, including: The graph construction module is used to construct a directed acyclic graph of indicator dependencies based on the indicators in the report template. Each indicator node is associated with at least one measurement point or sub-indicator, and the edges represent computational dependencies. The anomaly detection module is used to traverse the directed acyclic graph and identify all upper-level indicator nodes affected by the anomaly when an anomaly is detected in the data of the lower-level measurement points or sub-indicators. The freeze control module is used to freeze the identified upper-level indicator nodes and prevent the data corresponding to the frozen indicator nodes from participating in report output. The minimum recalculation module is used to trace nodes at a preset level upwards along the dependent edges, starting from the node corresponding to the anomaly, to form a minimum recalculation subgraph, and only recalculates the data of the nodes in the minimum recalculation subgraph.

[0014] This specification provides one or more embodiments of a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the report template lifecycle management method described above.

[0015] This specification provides one or more embodiments of a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the report template lifecycle management method described above.

[0016] This disclosure provides a method, apparatus, device, and medium for full lifecycle management of report templates. Its advantages lie in: constructing a directed acyclic graph (DAG) to clarify the computational dependencies and data lineage between indicators, forming a traceable topology that provides a structured foundation for subsequent anomaly impact analysis, accurate recalculation, and full lifecycle management; identifying upper-level indicator nodes affected by anomalies, quickly locating the anomaly propagation path and impact range, avoiding full scans, improving anomaly response efficiency, and ensuring that only truly affected indicators are processed; freezing affected upper-level indicator nodes prevents abnormal data from contaminating report output, ensuring the accuracy and reliability of report results and preventing erroneous data from participating in the decision-making process; and constructing a minimal recalculation subgraph and recalculating only on it limits the recalculation scope to a local subgraph at a preset level above the anomaly node, significantly reducing computational overhead and improving data repair and recalculation efficiency. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in one or more embodiments of this specification or in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this specification. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 A flowchart illustrating a method for managing the entire lifecycle of a report template, provided for one or more embodiments of this specification; Figure 2 A schematic diagram of a report template lifecycle management device provided in one or more embodiments of this specification; Figure 3 This is a schematic diagram of the structure of a computer device provided for one or more embodiments of this specification. Detailed Implementation

[0019] To enable those skilled in the art to better understand the technical solutions in one or more embodiments of this specification, the technical solutions in one or more embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this specification, and not all of the embodiments. Based on one or more embodiments of this specification, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of this invention.

[0020] The present invention will now be described in detail with reference to specific embodiments and accompanying drawings.

[0021] Method Implementation Examples According to embodiments of the present invention, a method for full lifecycle management of report templates is provided. The overall architecture of the system includes the following core subsystems: a report template lifecycle management subsystem, covering template creation, design, version control, release, authorization, recalculation, archiving, and deletion; an indicator and measurement point governance subsystem, including indicator tree configuration, dependency graph, pre-calculation / post-calculation decomposition, and anomaly propagation blocking; an adaptive scheduling and resource management subsystem, including dynamic scheduling windows based on load forecasting and parallel recalculation task splitting; an intelligent early warning and analysis subsystem, including sequence pattern mining, counterfactual analysis, and early warning push for over-temperature / over-limit / start-stop events; and a secure sharing and auditing subsystem, including zero-knowledge scope proof, blockchain operation evidence storage, and self-destructing links. Figure 1 The diagram shown is a flowchart illustrating the report template lifecycle management method provided in this embodiment. The report template lifecycle management method according to this embodiment includes the following steps: S110. Users configure the report name, cycle type (daily / monthly), reporting method (automatic / manual / hybrid), and scheduling strategy (fixed or adaptive flexible window) through a wizard-driven interface. They can choose to create a new blank report, copy an existing report, or upload an Excel file as the report template. Based on the indicators in the report template, a Directed Acyclic Graph (DAG) of indicator dependencies is constructed. Specifically, indicators are created in the indicator tree, associated with measurement points, and pre-calculation / post-calculation formulas, dependent measurement points, and upper and lower limits are set. The system automatically constructs the DAG. Each indicator node is associated with at least one measurement point or sub-indicator. Edges represent computational dependencies. Each indicator node stores the following attributes: Radius of influence: the number of all upper-level indicators reachable from this indicator along the dependency edge; Sensitivity coefficient: the top-level Key Performance Indicator (KPI) affected when the indicator value changes by 1%, such as the percentage change in coal consumption for power generation.

[0022] The report template is attached to the system menu, and roles and permissions are assigned for internal publishing. A secure link is generated for external publishing, allowing for self-destructing views and zero-knowledge proof verification. The scheduling engine dynamically calculates the window daily based on load forecasts, triggering report generation. If historical data is missing, the administrator initiates supplementary calculations within a specified time period, with system resource awareness executing in parallel.

[0023] S120. When anomalies such as data exceeding limits, missing data, or invalid manual marking are detected in the data of the underlying measurement points or sub-indicators, the DAG is traversed to identify all upper-level indicator nodes affected by the anomalies. The abnormal node status is marked as abnormal, and the anomaly type and time window are recorded. The DAG is traversed to count all upper-level indicators that depend on the node. If there is an approved indicator anomaly appeal record within the abnormal time window of the node, the removal logic is automatically propagated upwards along the DAG to avoid duplicate applications.

[0024] S130. Freeze the identified affected upper-level indicator nodes and prohibit the data corresponding to the frozen indicator nodes from participating in the report output.

[0025] S140. Starting from the node corresponding to the anomaly, trace upwards along the dependent edge to nodes at a preset level. The preset level shall not exceed 3 levels to form a minimum recalculation subgraph. Only the nodes within the minimum recalculation subgraph are recalculated, rather than the entire index is refreshed.

[0026] Users can select the indicator name, the abnormal time period, fill in the reason for the appeal, and submit it. Once the appeal is approved, the abnormal data can be removed. When there is an approved abnormal appeal record, the removal logic of the abnormal appeal record is automatically propagated upwards along the DAG to the affected upper-level indicators, unfreezing the relevant indicators, and verifying data consistency based on the DAG, without the need for re-application.

[0027] The method provided in this embodiment clarifies the computational dependencies and data lineages between indicators by constructing a directed acyclic graph of indicator dependencies, forming a traceable topology that provides a structured foundation for subsequent anomaly impact analysis, accurate recalculation, and full lifecycle management. It identifies upper-level indicator nodes affected by anomalies, quickly locating the anomaly propagation path and impact range, avoiding full scans, improving anomaly response efficiency, and ensuring that only truly affected indicators are processed. Freezing affected upper-level indicator nodes prevents abnormal data from contaminating report output, ensuring the accuracy and reliability of report results and preventing erroneous data from participating in the decision-making process. Constructing a minimum recalculation subgraph and recalculating only on it limits the recalculation scope to a local subgraph at a preset level above the anomaly node, significantly reducing computational overhead and improving data repair and recalculation efficiency.

[0028] In one embodiment, the following steps are also included: The optimal scheduling window for automatic report generation is dynamically determined based on a load forecasting model employing a lightweight LSTM model.

[0029] The load forecasting model predicts the load change trend of the units in the next 24 to 48 hours based on historical load curves, meteorological data such as ambient temperature and wind speed, and power grid dispatch plans such as the next day's power generation curves. It marks the steady-state window where the load fluctuation rate is lower than a preset threshold, for example, the period when the load fluctuation rate is <5% / 15min.

[0030] Adjust the scheduling time of the report template from a fixed time to trigger within a steady-state window. For example, for daily reports, it can be set to be executed automatically between 8:00 and 10:00 every day, selecting a predictive steady-state window. The steady-state score of each candidate window is calculated at midnight of the same day, and the optimal window is selected to trigger generation.

[0031] When a supplementary calculation task is initiated, real-time data collection is performed on the database connection pool, CPU utilization, and memory usage. The time frame for supplementary calculations is divided into sub-tasks by day or week, and the parallelism is dynamically controlled based on the current resource availability. For example, the parallelism is 5 when the connection pool idle time is >10, and drops to 1 when it is <3. During idle periods, such as 1:00 AM to 5:00 AM, the priority of supplementary calculations is automatically increased.

[0032] The method provided in this embodiment dynamically identifies the steady-state window through the load forecasting model and adjusts the report scheduling time from a fixed time to trigger within the steady-state window, which can effectively avoid the impact of load fluctuations on report generation and improve the stability and data reliability of report output.

[0033] In one embodiment, the following steps are also included: It adopts a Git-like incremental storage engine to generate a differential change record (Change-Set) for each modification to the report template. The template modification includes changes to cell styles, formulas, data sources, aliases, permission configurations, etc. The differential change record includes the modification location, old value, new value, operator, and timestamp. Only the initial complete template and each Change-Set are saved, not a complete copy.

[0034] When multiple people are editing the same template at the same time, the conflict boundaries are first identified, and it is detected whether the modification areas overlap.

[0035] If the cells do not overlap, they will be automatically merged. For example, cells from different worksheets or different rows and columns will be automatically merged without any noticeable overlap. If the areas overlap, the dependency tree depth of the formulas within the overlapping areas will be compared. Modifications with higher dependency depths (i.e., modifications to cells referenced by multiple other formulas) will have higher priority and will be retained first, with a conflict resolution window displayed. For modifications to time-series data source configurations, attributes such as measurement point name, time range, and aggregation method will be automatically compared. If the attribute values ​​are completely identical, they will be considered equivalent modifications and automatically merged.

[0036] Users can mark any version as the production baseline, such as the version before the start of the heating season. During subsequent recalculations, users can choose to base the calculations on the latest template or a specific baseline template, providing a function to compare indicators between baselines.

[0037] The method provided in this embodiment supports full auditing through differential records, automatically merges non-overlapping edits, and retains complex modifications based on formula dependency depth for overlapping edits, thereby ensuring the consistency and correctness of templates under multi-person collaboration.

[0038] In one embodiment, the following steps are also included: In response to requests for secure sharing of report data, a verification credential based on zero-knowledge scope proof is generated. This allows the verifier to confirm that the indicator value meets a preset threshold without revealing the actual value. Specifically, when the operations department needs to prove to the safety supervision department that the hourly average NOx emission is below 50 mg / m³, but does not want to disclose the original emission value, a concise proof (<1KB) is generated using the Bulletproofs algorithm. The safety supervision department can verify the authenticity by inputting publicly available parameters such as time, unit, and threshold 50 into the system's built-in verifier; the actual value cannot be deduced from this information.

[0039] The key operations of the report template are hashed and stored on the blockchain using an enterprise-grade Hyperledger Fabric consortium blockchain. The key operations include the publication, deletion, and transfer of ownership of the report template; the submission, approval / rejection of appeals for abnormal indicators; the generation and cancellation of externally published links; and the batch import of data into the data writing module. The evidence stored includes the operator, timestamp, operation type, and hashes of the previous and subsequent states to ensure immutability and meet the audit compliance requirements of the power industry.

[0040] When publishing links externally, a one-time access option can be set. After the recipient clicks the link, the server generates a one-time session token. The token expires immediately after the page is rendered once, and the link cannot be opened again. The system automatically records the visitor's IP address, browser fingerprint, and access time, generating an access log.

[0041] The method provided in this embodiment verifies the indicator threshold without disclosing the specific value through zero-knowledge scope proof, thus ensuring data privacy and security. At the same time, it hashes key operations on the blockchain to ensure the immutability and auditability of report template operations, thereby improving the credibility of data sharing and evidence storage.

[0042] Device Examples According to embodiments of the present invention, a report template lifecycle management device is provided, such as... Figure 2 The diagram shown is a structural schematic of the report template lifecycle management device provided in this embodiment. The report template lifecycle management device according to this embodiment includes: The graph construction module 21 is used to construct a directed acyclic graph of indicator dependencies based on the indicators in the report template. Each indicator node is associated with at least one measurement point or sub-indicator, and the edges represent computational dependencies.

[0043] The anomaly identification module 22 is used to traverse the directed acyclic graph and identify all upper-level indicator nodes affected by the anomaly when an anomaly is detected in the data of the underlying measurement points or sub-indicators.

[0044] The anomaly identification module 22 is used to freeze the identified upper-level indicator nodes and prevent the data corresponding to the frozen indicator nodes from participating in the report output.

[0045] The minimum recalculation module 24 is used to trace the nodes of a preset level upward along the dependent edges, starting from the node corresponding to the exception, to form a minimum recalculation subgraph, and only recalculates the data of the nodes in the minimum recalculation subgraph.

[0046] The device provided in this embodiment constructs a directed acyclic graph of index dependencies through the graph construction module 21, clarifying the computational dependencies and data lineages between indicators and forming a traceable topology, providing a structured foundation for subsequent anomaly impact analysis, accurate recalculation, and full lifecycle management. The anomaly identification module 22 identifies upper-level indicator nodes affected by anomalies, quickly locating the anomaly propagation path and scope of impact, avoiding full scanning, improving anomaly response efficiency, and ensuring that only truly affected indicators are processed. The anomaly identification module 22 freezes affected upper-level indicator nodes, preventing abnormal data from contaminating the report output, ensuring the accuracy and reliability of the report results, and preventing erroneous data from participating in the decision-making process. The minimum recalculation module 24 constructs a minimum recalculation subgraph and recalculates only on it, limiting the recalculation scope to a local subgraph at a preset level above the anomaly node, significantly reducing computational overhead and improving data repair and recalculation efficiency.

[0047] The embodiments of the present invention are device embodiments corresponding to the above method embodiments. The specific operations of each module processing step can be understood with reference to the description of the method embodiments, and will not be repeated here.

[0048] like Figure 3 As shown, the present invention also provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, it implements the report template lifecycle management method in the above embodiments, or when the computer program is executed by a processor, it implements the report template lifecycle management method in the above embodiments.

[0049] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0050] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, for apparatus or system embodiments, since they are basically similar to method embodiments, the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments. The apparatus and system embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without creative effort.

[0051] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features. These modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention, and the contents not described in detail in the specification of the present invention are known to those skilled in the art.

Claims

1. A report template full life cycle management method, characterized in that, Includes the following steps: Construct a directed acyclic graph of indicator dependencies based on the indicators in the report template, where each indicator node is associated with at least one measurement point or sub-indicator, and edges represent computational dependencies. When an anomaly is detected in the data of the underlying measurement points or sub-indicators, the directed acyclic graph is traversed to identify all upper-level indicator nodes affected by the anomaly. The identified upper-level indicator nodes are frozen, and the data corresponding to the frozen indicator nodes is prohibited from participating in the report output. Starting from the node corresponding to the anomaly, trace upwards along the dependent edges to nodes at a preset level to form a minimum recalculation subgraph, and only recalculate the data for the nodes within the minimum recalculation subgraph.

2. The report template full life cycle management method of claim 1, wherein, It also includes the following steps: The optimal scheduling window for automatic report generation is dynamically determined based on the load forecasting model. The load forecasting model predicts the trend of unit load changes in the future period based on historical load curves, meteorological data and power grid dispatching plans, and marks the steady-state window where the load fluctuation rate is lower than a preset threshold. The scheduling time of the report template is adjusted from a fixed time to be triggered within the steady-state window.

3. The report template full life cycle management method of claim 1, wherein, It also includes the following steps: For each modification to the report template, a differential change record is generated, which includes the modification location, old value, new value, operator, and timestamp. When multiple people are editing the same template at the same time, check whether the modification areas overlap; If the cells do not overlap, they will be automatically merged. If they overlap, the dependency tree depth of the formulas in the overlapping areas will be compared, and modifications with higher dependency depths will be retained first.

4. The report template full life cycle management method of claim 1, wherein, The anomalies include data exceeding limits, missing data, or invalid manual labels; The preset hierarchy is 3 layers.

5. The report template full life cycle management method of claim 1, wherein, It also includes the following steps: High-frequency event chains are extracted from historical over-temperature and over-limit events and equipment start-up and shutdown events using a sequence pattern mining algorithm; Inject the preceding feature patterns of the high-frequency event chain into early warning rules; Real-time monitoring of data flow; when a preceding feature pattern is matched, an early warning message is displayed in the corresponding report cell, and adjustment suggestions are pushed.

6. The report template full life cycle management method of claim 1, wherein, It also includes the following steps: In response to a request for secure sharing of report data, a verification credential based on zero-knowledge scope proof is generated, enabling the verifier to confirm that the indicator value meets a preset threshold without disclosing the actual value. The key operations of the report template are generated into hash values ​​and stored in the blockchain.

7. The report template full life cycle management method of claim 1, wherein, It also includes the following steps: When there is an approved abnormal appeal record, the removal logic of the abnormal appeal record is automatically propagated upwards along the directed acyclic graph to the affected upper-level indicators, without the need for reapplication.

8. A report template full life cycle management apparatus, characterized by comprising: include: The graph construction module is used to construct a directed acyclic graph of indicator dependencies based on the indicators in the report template. Each indicator node is associated with at least one measurement point or sub-indicator, and the edges represent computational dependencies. The anomaly detection module is used to traverse the directed acyclic graph and identify all upper-level indicator nodes affected by the anomaly when an anomaly is detected in the data of the lower-level measurement points or sub-indicators. The freeze control module is used to freeze the identified upper-level indicator nodes and prevent the data corresponding to the frozen indicator nodes from participating in report output. The minimum recalculation module is used to trace nodes at a preset level upwards along the dependent edges, starting from the node corresponding to the anomaly, to form a minimum recalculation subgraph, and only recalculates the data of the nodes in the minimum recalculation subgraph.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the report template full lifecycle management method as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, the computer-readable storage medium comprising: When the computer program is executed by the processor, it implements the steps of the report template lifecycle management method as described in any one of claims 1 to 7.

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