Intelligent integrated grouting operation data management method

Abstract

The application discloses a smart integrated grouting operation data management method, relates to the field of grouting operation, and automatically collects grouting process data, writes dynamic time sequence data and static business data into a time sequence database and a relational database based on a multi-channel strategy, constructs a structured data lake with grouting holes as indexes, automatically generates a preliminary quality report containing process curves and determination conclusions, further integrates multi-hole data into a comprehensive evaluation report, drives online collaborative workflows of three parties of construction, supervision and owners based on the report, realizes electronic approval of abnormal treatment, all key reports and operation records are stored in a permission alliance chain managed by multiple parties, and the application realizes a paradigm shift from artificial experience judgment to data intelligent decision, from offline scattered management to online collaborative closed loop, and from information recording to credible notarization, and significantly improves the accuracy, efficiency and credibility of engineering quality management.

Description

Technical Field

[0001] This invention relates to the field of grouting operations, specifically to an intelligent integrated grouting operation data management method. Background Technology

[0002] Grouting is a crucial, concealed process in tunnel, water conservancy, and slope protection engineering to ensure structural safety and stability. Its quality highly depends on the precise control and recording of process parameters. Currently, the industry generally faces the following pain points in grouting operation data management:

[0003] Traditional management models primarily rely on manual paper-based recording and offline archiving, resulting in inefficiency, error-proneness, isolated data, and difficulty in traceability. Construction parameters (such as pressure and flow rate) are mostly read from mechanical instruments and manually recorded, leading to poor data real-time performance and the inability to generate continuous process curves, making it difficult to accurately reflect the dynamic process. Massive amounts of drilling records, material information, and grouting data are scattered across different stages and personnel's notebooks or simple spreadsheets, lacking a systematic connection centered on the "hole," forming "data silos." Once quality problems occur, tracing the cause becomes extremely difficult.

[0004] In recent years, some projects have attempted to introduce automated data acquisition equipment or industrial control systems (such as PLCs) to achieve automatic reading of sensor data. However, these systems are often limited to stand-alone data recording or simple local storage, with inconsistent data formats. They fail to effectively correlate and structurally integrate with borehole geological data, material traceability information, environmental parameters, etc., and cannot construct a complete construction digital twin. At the quality assessment level, there is still a heavy reliance on the subjective experience of technicians to review data curves for post-event judgment, lacking automatic, standardized intelligent judgment based on rule bases, and even more so, the inability to conduct trend analysis and anomaly early warning from the perspective of multi-source data fusion across the entire region.

[0005] In terms of multi-party collaborative management, information transmission and approval processes among construction, supervision, and owners still largely rely on offline paper forms, telephone communication, and meetings. This results in slow workflows, long signing cycles, and difficulty in solidifying operational records, leading to unclear accountability. Handling abnormal situations often results in repeated communication and inefficiency, hindering the formation of an efficient management loop. Furthermore, all electronic data is stored on centralized servers, posing a technical risk of unilateral alteration or subsequent denial. The ultimate credibility and legal validity of the data are insufficient, failing to meet the audit requirements for process evidence chains in high-standard projects. Summary of the Invention

[0006] The purpose of this invention is to provide an intelligent integrated grouting operation data management method to solve the problems mentioned in the background art.

[0007] To achieve the above objectives, the present invention provides the following technical solution: an intelligent integrated grouting operation data management method, comprising the following steps:

[0008] S1: Data structuring processing: Based on a multi-channel data writing strategy, the acquired grouting operation data is written into different databases according to different properties, and a structured data set lake with grouting holes as the index is constructed.

[0009] S2: Report generation. In response to the completion of single-hole grouting operation, a preliminary quality report containing process parameter curves and quality judgment is generated based on the structured data set lake by calling the preset quality judgment rule base. Based on the preliminary quality reports of multiple grouting holes in the specified area, multi-source data fusion analysis is performed to generate a comprehensive evaluation report including anomaly point identification.

[0010] S3: Driven by multi-party collaborative work, based on the preliminary quality report and the comprehensive evaluation report, the first party initiates an anomaly handling application with handling suggestions, the second party reviews the anomaly handling application and generates pre-processing opinions marked with anomaly level, and the third party conducts online final review of the pre-processing opinions that exceed the anomaly level threshold based on the comprehensive evaluation report, forming a closed loop and recording key operation records;

[0011] S4: Based on blockchain, the data is stored and traced with trusted evidence. The preliminary quality report, the comprehensive evaluation report and the key operation records are generated into digital fingerprints and stored in a permissioned consortium blockchain jointly maintained by multiple parties. A blockchain-based verification interface is provided to verify the authenticity and integrity of the report and operation records by comparing the on-chain and off-chain digital fingerprints, and to provide full lifecycle operation traceability query.

[0012] Preferably, the multi-channel data writing strategy includes a dynamic data channel and a static data channel. The dynamic data channel writes real-time dynamic data of the grouting process with timestamps into a time-series database optimized for time series storage. The static data channel writes the business-related data of the grouting holes and the grouting result summary information into a relational database, and associates and binds the grouting hole position number with the real-time dynamic data of the grouting process in the time-series database.

[0013] Preferably, the method for generating the preliminary quality report specifically includes the following steps:

[0014] Based on the hole location number of the grouting hole, the corresponding time series process data, business-related data and design parameters are indexed and aggregated from the structured data set lake;

[0015] Based on a pre-set quality judgment rule library, the aggregated data is calculated and compared with the rules, and the quality judgment conclusion is automatically output.

[0016] Based on the comparison results, a standardized report document containing process parameter curves including pressure-time and flow-time, as well as quality level determination, is automatically generated.

[0017] Preferably, the quality judgment rule base includes:

[0018] Based on the quantitative threshold rules of design parameters and engineering specifications, the thresholds for the final pressure, unit injection volume and grout density of grouting are determined.

[0019] An adaptive matching rule based on the geological description associated with the grouting hole is used to evaluate the consistency between actual grouting parameters and geological conditions;

[0020] The morphological conformity rules based on process parameter curves are used to evaluate the degree of agreement between the actual construction curve and the design process curve.

[0021] Based on the comparison results of the rules of one or more of the above dimensions, the corresponding quality level is automatically determined and output.

[0022] Preferably, the multi-source data fusion analysis includes:

[0023] Geological adaptability analysis: The actual grouting parameters in the preliminary quality reports of each grouting hole are compared and correlated with the corresponding borehole geological records to analyze the rationality of the matching between the construction results and the geological conditions;

[0024] Process compliance analysis: The process parameter curves of multiple grouting holes in the area are set together and compared with the design process requirement curve to evaluate the degree of standardization of construction operations.

[0025] Statistical trend analysis: Statistical analysis is performed on the key performance indicators of all grouting holes in the region to generate parameter distribution patterns and overall quality trends.

[0026] Preferably, the generation of the comprehensive evaluation report including anomaly identification specifically includes:

[0027] Based on the results of the statistical trend analysis, the preset statistical dispersion determination method is used to automatically identify grouting holes that deviate from the overall data distribution pattern as outliers.

[0028] The generated comprehensive assessment report uses visual charts to mark the anomalies, and provides preliminary cause classification or risk warnings based on the corresponding geological adaptability analysis and process compliance analysis results.

[0029] As a preferred method, the procedure for a first party to initiate an exception handling request with handling recommendations includes the following steps:

[0030] In the preliminary quality report or the comprehensive evaluation report, the first party initiates a structured application for the identified abnormal grouting holes;

[0031] The structured application must cite the anomaly report, describe the on-site situation, select or fill in the preliminary cause analysis, and select one or more disposal suggestions from the pre-set measures library;

[0032] The structured application supports uploading on-site photos or videos as supporting attachments, and must be submitted to the second party after being electronically authenticated by the first party.

[0033] Preferably, the second party reviews the anomaly handling application and generates preprocessing opinions marked with anomaly levels, specifically including:

[0034] The second party reviews the process parameter curves and business data of the grouting hole associated with the anomaly handling application for verification.

[0035] The second party determines an anomaly level for the anomaly handling application based on the complexity of the problem, the scope of its impact, and the handling measures.

[0036] If the anomaly level does not exceed the preset threshold, the second party has the right to directly approve the handling opinion, and the process returns to the first party for execution; if it exceeds the preset threshold, a pre-processing opinion with detailed analysis and suggestions is generated and then submitted to the third party for final review.

[0037] As a preferred method, generating a digital fingerprint and storing it in a permissioned consortium blockchain maintained by multiple parties includes the following steps:

[0038] For each of the preliminary quality report, the comprehensive evaluation report, and the key operation record to be stored, a unique digital fingerprint is calculated using a cryptographic hash function;

[0039] The digital fingerprint, along with the corresponding report identifier, operation type, and timestamp information, is packaged into a single evidence-based transaction and broadcast to the permissioned consortium blockchain network.

[0040] After the consortium blockchain network nodes reach a consensus, the evidence-preserving transaction is recorded on the blockchain and a transaction receipt containing its on-chain location is obtained. This receipt is then stored in association with the original off-chain file.

[0041] As a preferred method, the full lifecycle operation traceability query includes the following steps:

[0042] In response to a verification request, the digital fingerprint of the off-chain target file is recalculated immediately, and the original stored digital fingerprint is retrieved from the consortium blockchain based on the associated transaction receipt.

[0043] Compare the consistency of the two fingerprints. If they match, the verification is successful. If they do not match, a tampering alarm is triggered.

[0044] Based on the chronologically recorded and immutable evidence-based transactions on the consortium blockchain, a visualized traceability map of the entire lifecycle, from report generation to approval operations at all levels, is provided.

[0045] In summary, the beneficial effects of this invention are:

[0046] This invention establishes a digital foundation by enabling automated, accurate, and structured data collection throughout the entire construction process using IoT and database technologies. Through a rule engine and multi-source fusion analysis, it automatically generates intelligent diagnostic reports ranging from microscopic single-hole data to macroscopic regional data, transforming massive amounts of data into decision-making knowledge that directly guides action. Relying on electronic workflows, it clearly defines and connects the rights, responsibilities, and tasks of construction, supervision, and the owner, making anomaly handling efficient, transparent, and traceable. Finally, it introduces consortium blockchain technology to provide cryptographic-level tamper-proof evidence storage and verification capabilities for all key digital results, building a solid foundation of "technological trust." Overall, this solution significantly improves the precision of project quality control, management efficiency, and transparency, achieving a fundamental shift from passive post-event inspection to proactive process prevention, and from fuzzy experience-based decision-making to data-driven precise decision-making. Attached Figure Description

[0047] To more clearly illustrate the technical solutions in the embodiments of the invention or 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 of the invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0048] Figure 1 This is a schematic diagram of the overall process framework of the intelligent integrated grouting operation data management method of the present invention;

[0049] Figure 2 This is a schematic diagram of the process framework structure for report generation in the intelligent integrated grouting operation data management method of the present invention;

[0050] Figure 3 This is a schematic diagram of the process framework structure driven by multi-party collaborative work in the intelligent integrated grouting operation data management method of the present invention; Figure 4 This is a schematic diagram of the process framework structure of the blockchain-based trusted data storage and traceability in the intelligent integrated grouting operation data management method of the present invention. Detailed Implementation

[0051] The present invention will now be described in further detail with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention. These drawings are simplified schematic diagrams, which are only used to illustrate the basic structure of the present invention in a schematic manner, and therefore only show the components related to the present invention.

[0052] To facilitate understanding of the present invention, a more complete description of the invention will be given below with reference to the accompanying drawings, which illustrate several embodiments of the invention. However, the invention can be implemented in many different forms and is not limited to the embodiments described herein. Rather, these embodiments are provided so that the disclosure of the invention will be more thorough and complete.

[0053] All features disclosed in this specification, or all steps in all disclosed methods or processes, may be combined in any way, except for mutually exclusive features and / or steps.

[0054] Any feature disclosed in this specification (including any appended claims, abstract, and drawings) may be replaced by other equivalent or similar features for a similar purpose, unless specifically stated otherwise. That is, unless specifically stated otherwise, each feature is merely one example of a series of equivalent or similar features.

[0055] In this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," "linking," and "fixing," etc., should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection, a direct connection, or an indirect connection through an intermediate medium; they can refer to the internal communication of at least two elements or the interaction relationship of at least two elements, unless otherwise explicitly limited. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0056] Please see Figures 1-4 The present invention provides an embodiment of an intelligent integrated grouting operation data management method, which realizes the digital recording of grouting construction and constructs a new paradigm of modern engineering quality management characterized by multi-party co-governance, reliable data, and intelligent decision-making. Specifically, it includes the following steps:

[0057] Step 1: Data structuring

[0058] Based on a multi-channel data writing strategy, the acquired grouting operation data is written to different databases according to different properties, constructing a structured data collection lake indexed by grouting holes. Specifically:

[0059] Grouting operation data includes:

[0060] Dynamic process data: grouting pressure (MPa), real-time flow rate (L / min), cumulative grouting volume (m³), grout density (g / cm³), timestamp (accurate to the second), equipment ID, and GPS location.

[0061] Static associated data: borehole records (hole number, designed / actual hole depth, geological description), material information (cement batch, mix proportion), and environmental data (temperature, humidity).

[0062] The multi-channel data writing strategy includes dynamic data channels and static data channels, which are written to different databases based on their different properties;

[0063] Write to the time-series database: Write process data (dynamic change values ​​such as pressure, flow, and density) with high-precision timestamps to the time-series database. This database is highly optimized for time-series data, supports high-speed writing of massive amounts of data and fast aggregation queries by time range, and is very suitable for storing raw sensor data streams.

[0064] Writing to a relational database: Linking and storing related data and key summary information:

[0065] Establish / associate borehole records: Based on the location information in the data packet or the manually scanned borehole location QR code, associate and bind the grouting data with the borehole record table in the database (using the key field of "borehole number").

[0066] Record material and environmental information: The batches of materials used during the same work period, the mix proportions, and the average ambient temperature and humidity are recorded as metadata and stored in association with the grouting process records.

[0067] Store key outcome data: Calculate and store summary outcome data such as total grouting time, average pressure, and cumulative grouting volume for each hole.

[0068] This allows for the creation of a high-quality data lake containing millisecond-level process curves, precisely correlated business information, and complete, traceable job contexts.

[0069] Step 2: Report Generation

[0070] 1. Preliminary Quality Report Generation Process: Automatically generate an independent, standardized "digital quality passport" for each grouting hole. The specific steps are as follows:

[0071] Triggering and perception;

[0072] Manual triggering: The grouting trolley operator confirms the completion of a single-hole operation on the trolley control interface or handheld terminal and clicks the "Complete Grouting" button. This operation sends a clear end instruction to the central platform.

[0073] Automatic Sensing: The system monitors the grouting data stream. When it detects that the flow rate of a certain hole is continuously zero, the pressure is stable in the shutdown state, and the preset end silence time is met, it can automatically determine that the operation of that hole is complete and trigger the report generation process. It usually adopts a dual mode of "manual confirmation as the main method and automatic sensing as the auxiliary method".

[0074] Data aggregation and contextual association;

[0075] After receiving the trigger signal, the report generation engine immediately initiates a query to the database using the hole number and the time range of this operation as the core index.

[0076] Extract time-series data for the entire process: Extract the raw data points of pressure, flow rate, and density corresponding to all timestamps within the grouting operation cycle of the borehole from the time-series database.

[0077] Related business master data: Extract all static and related data bound to this hole from the relational database, including:

[0078] Basic project information: Project name, contract section, and chainage interval.

[0079] Drilling records: designed hole depth, actual hole depth, geological strata revealed by the borehole and their description.

[0080] Material information: batch number of cement and admixtures used, and design mix proportion.

[0081] Equipment and personnel: Grouting trolley number, operator's name.

[0082] Core indicator calculation and rule determination;

[0083] Metric Calculation: The engine performs real-time calculations on the extracted raw time-series data to generate key statistical metrics:

[0084] Pressure parameters: maximum pressure, minimum pressure, average pressure, pressure stability coefficient.

[0085] Flow and Total Volume: Calculate the cumulative infusion volume and analyze the trend of flow changes.

[0086] Time indicators: total grouting time, pure grouting time.

[0087] Rule base comparison: The system calls a pre-set quality judgment rule base. The rule base is typically derived from design specifications, construction process plans, and quality standards, for example:

[0088] "If the final stable pressure does not reach 90% of the design pressure, it is judged as 'insufficient pressure'."

[0089] "If the injection volume per unit hole depth exceeds 150% of the design value, it is judged as 'abnormally high injection volume'."

[0090] "If the average slurry density exceeds the allowable fluctuation range of the mix proportion, it is judged as 'abnormal slurry mix proportion'."

[0091] The engine compares the calculated indicators with the rules one by one and automatically draws a preliminary quality judgment conclusion, such as "qualified", "pressure not up to standard", "insufficient filling volume, to be checked".

[0092] Report rendering and digital fingerprint generation

[0093] Template filling: The system will automatically fill the calculated indicators, judgment conclusions, related basic information and process curves and charts into a pre-designed standardized report template, such as a Word or PDF template.

[0094] Visualization generation: Automatically generates intuitive stress-time and flow-time graphs from raw data and embeds them into reports.

[0095] Data fingerprint generation: Before the report is finalized, the system performs a hash operation on the unique identifier set of all source data referenced in the report to generate a unique digital fingerprint. This fingerprint will be permanently bound to the report as cryptographic proof of its authenticity and integrity, preparing for subsequent on-chain evidence storage.

[0096] The generated preliminary quality report is saved to the document server in a non-editable format such as PDF.

[0097] The report's key summary (hole number, conclusion, key indicators) and access link are automatically pushed to the workbenches of relevant construction teams and technical supervisors, and the status of the hole on the digital map is updated.

[0098] 2. Comprehensive Assessment Report Generation Process

[0099] At a higher dimension (space, time, batch), multi-source information fusion analysis is performed on the pore locations of the population to provide regional and trend-based quality insights. The specific steps are as follows:

[0100] Periodic or event-based triggering

[0101] Scheduled Trigger: The system automatically starts batch analysis tasks according to a preset cycle.

[0102] Batch Trigger: When a construction unit, such as a chainage segment or a lining cycle, has completed grouting of all holes, the technical supervisor manually triggers the summary evaluation of that unit.

[0103] Conditional trigger: When the system detects that the proportion of abnormal holes exceeds the threshold, a special assessment of the area is automatically triggered.

[0104] Multi-source data aggregation and panoramic construction

[0105] Based on the trigger range, such as "all grouting holes from K100+100 to K100+200 yesterday", the engine aggregates three types of data from the database:

[0106] Group process data: A set of grouting process indicators for all boreholes within this range.

[0107] Associated geological maps: corresponding borehole columnar sections, geological sketches, or geophysical interpretation results within the range form a digital geological profile.

[0108] Design process benchmarks: Grouting design parameters for this section, such as target pressure and expected grout consumption for different geological units.

[0109] Multidimensional evaluation model analysis

[0110] Geological adaptability assessment:

[0111] The system spatially correlates the grouting results (actual pressure, grouting volume) of each borehole with the geological description in its borehole record.

[0112] The analysis model will determine whether the injection volume is generally higher in areas marked as "fractured zones" and whether the pressure is more likely to reach the design value in "intact bedrock" areas. Through cluster analysis, it will verify whether the correlation between the construction results and geological conditions is reasonable.

[0113] Process conformity assessment:

[0114] The system compares a large number of actual grouting pressure-time curves with the design process curves. It can calculate the "curve similarity" or check the compliance rate of key control points, and assess the standardization of construction operations.

[0115] Statistical Trends and Anomaly Identification:

[0116] Statistical analysis was performed on key indicators such as injection volume and maximum pressure of all holes in the region. Statistical methods were used to automatically identify discrete points and mark them.

[0117] Comprehensive analysis and report synthesis

[0118] The engine integrates the analysis results from the above three dimensions to make a comprehensive judgment:

[0119] Provide the overall quality rating: such as "The overall quality of this batch of grouting is under control, with an excellent rate of XX%".

[0120] Systemic risks are highlighted, such as "The overall injection volume in Area A is lower than expected, which may differ from geological forecasts. A re-examination is recommended."

[0121] Focus on individual anomalies: List the identified discrete borehole locations and, in conjunction with their geological and process data, provide preliminary hypotheses about the causes, such as "Borehole Y may have encountered a hidden fracture."

[0122] Report Compilation: The above conclusions, indexes of all preliminary quality reports, and various analytical charts, such as geological profile and grouting volume overlay maps, pressure distribution cloud maps, and trend statistics charts, are compiled into a "Comprehensive Assessment Report".

[0123] Step 3: Multi-party collaborative work driven

[0124] Once the "Preliminary Quality Report" is generated, the system will automatically push the report to the supervisor's "To-Do Items" list, and mark the status as "Pending Review".

[0125] At the same time, if the report automatically determines it as "abnormal", or if the hole is marked as a discrete point in the "Comprehensive Evaluation Report", the system will also generate an "Abnormal, pending confirmation" prompt on the workbench of the person in charge of the construction.

[0126] Construction technicians log into the system and view their assigned areas on their personal workbench or digital map. They can view automatically generated anomaly alerts from the system or independently identify potential problem holes using charts in the comprehensive assessment report.

[0127] Initiate an "Application for Handling Abnormal Data":

[0128] After selecting the specific abnormal hole location, click "Initiate Disposal Request", and the system will display a structured form.

[0129] Complete the application form in a structured manner:

[0130] Referenced data: The form automatically associates the hole number and preliminary report. Applicants need to select the specific anomaly type, such as "excessive filling volume" or "pressure not up to standard".

[0131] Site description: Fill in the text box to describe any relevant conditions observed on site, such as the color of the slurry returning from the borehole or water seepage from the surrounding rock surface.

[0132] Preliminary analysis: Based on professional judgment, select or fill in possible reasons from the drop-down menu, such as: "Suspected collusion with neighboring boreholes" or "Geological conditions do not match drilling findings".

[0133] Recommended solutions: Select from the preset measures library, such as: "Request to add an inspection hole next to this hole", "Request to refill once according to a special process", "Request to conduct a pressure test for verification".

[0134] Attachment upload: Upload photos and short videos taken on-site as supporting evidence to make the problem description more comprehensive.

[0135] Submission: After completing the form, submit it electronically using your personal digital certificate or password. The application status will change to "Submitted, Awaiting Supervisor's Review" and will automatically be redirected to the corresponding supervising engineer's to-do list.

[0136] The supervising engineer receives new tasks at the workbench, including "normal report approval" and "abnormal handling application".

[0137] For any abnormal handling application, the supervisor first reviews the original process data curve of the borehole for detailed verification, compares it with the description submitted by the construction party, and determines whether the application is reasonable and whether the basis is sufficient.

[0138] Make decisions and generate opinions:

[0139] Scenario 1: The application is reasonable and the problem is clear.

[0140] The supervisor fills in "review comments" on the application form, agreeing with the construction party's suggestions or providing adjusted handling opinions, such as: "Agree to re-grouting, and suggest extending the pressure stabilization time from 30 minutes to 45 minutes."

[0141] If the proposed measures are simple and clear, the supervisor has the right to approve them directly. The application form status changes to "Supervisor approved, pending implementation by the contractor" and is returned to the contractor.

[0142] Scenario 2: The problem is complex or has significant impact.

[0143] If the handling measures involve changes to the plan, increased costs, or technical disputes, the supervisor must generate a more formal "Pre-treatment Opinion Form." This form will summarize the abnormal situation, the contractor's application, the supervisor's review and analysis, and provide clear handling recommendations.

[0144] After the supervisor electronically signs the feedback form, it is submitted to the owner for approval. The status changes to "Submitted for Owner Approval".

[0145] Scenario 3: Additional information required

[0146] The supervisor can reject the application and require the construction company to conduct a certain test or provide more detailed information.

[0147] Electronic visas reported normally:

[0148] For a normal preliminary quality report with a status of "Pending Review", the supervising engineer reviews the process curves and judgment results and clicks the "Approval" button after confirming that they are correct.

[0149] The system records the signatory, the signing time, and attaches the supervisor's digital signature. The report status is permanently changed to "Supervisor has signed," and it enters the archiving process. This operation has legal effect, indicating that the supervisor approves the grouting quality of the borehole.

[0150] The owner's representative mainly receives the "Pre-processing Opinion Form" and related attachments submitted by the supervisor at the work station.

[0151] The owner reviewed the comprehensive assessment report on the issue and all the results data of the relevant areas to weigh the overall progress, cost and quality objectives of the project.

[0152] Final approval is then made on the "Pre-processing Opinion Form":

[0153] Approval: Final instructions are generated. The system status is updated to "Owner has approved, proceed according to pre-processing opinions," and the instructions are issued to the supervisor and construction team.

[0154] Rejection or Modification: Provide feedback of disagreement or revised opinions, and return the case to the supervisor for renegotiation.

[0155] Using data for strategic decision-making:

[0156] The owner can grasp the overall quality trend by regularly reviewing the comprehensive assessment report. For example, if the report shows that the grouting effect is not good under a certain type of geological conditions, the owner can decide to convene a special meeting to organize the design, construction and supervision parties to adjust the grouting design parameters or process methods for subsequent sections.

[0157] Step 4: Trusted Data Storage and Traceability Based on Blockchain

[0158] Phase 1: Construction and Integration of the Underlying Blockchain Infrastructure

[0159] Consortium blockchain network setup:

[0160] Consensus established: The owner, together with the supervision unit, the general contractor, and a third-party authoritative institution recognized by both parties, reached a consensus to jointly establish a licensed consortium blockchain network.

[0161] Node Deployment: Each participant deploys a blockchain node on its own or co-managed cloud server / data center. These nodes together form a distributed ledger network, and the notarization of any data requires the joint confirmation of a majority of nodes to be effective, ensuring that no single party can control or tamper with the ledger.

[0162] Permissions and Channel Configuration: Configure corresponding read and write permissions for each party on the blockchain. Independent channels can be established for sensitive business operations to achieve privacy isolation of data among specific participants.

[0163] Phase Two: Generation and On-Chain Storage of Key Digital Achievements' "Fingerprints"

[0164] This phase follows the efficient principle of "storing complete data off-chain and anchoring data fingerprints on-chain".

[0165] Triggering and "fingerprint" generation:

[0166] The system will automatically trigger whenever the final version of the "Preliminary Quality Report" or "Comprehensive Assessment Report" is generated.

[0167] The platform's backend uses a cryptographic hash function (such as SHA-256) to generate a fixed-length, unique "digital fingerprint" (hash value) from the core content of the report (all text, numerical, and chart data) and its associated unique file ID. This fingerprint has a key characteristic: any minor change to the report content will completely alter the fingerprint, and the original content cannot be derived in reverse.

[0168] Similarly, when each critical business operation is completed, such as when the construction party submits an application, the supervisor signs it, or the owner approves it, the system will package the information such as the operator, timestamp, operation type, and associated report ID of the operation and generate a "digital fingerprint" of the operation record.

[0169] "Fingerprint" on-chain notarization: The platform will generate a good "digital fingerprint", along with brief descriptive information such as "report type-hole number-time", and package it into a notarization transaction, which will be broadcast to the previously deployed consortium blockchain network.

[0170] Each node in the network verifies and confirms the transaction according to a pre-defined consensus mechanism, such as Byzantine Fault Tolerance (PBFT). Once enough nodes reach a consensus, the transaction containing the "digital fingerprint" is packaged into a block and linked to the previous block in chronological order, forming a perpetually growing chain.

[0171] Once this process is complete, a blockchain transaction receipt will be obtained, containing the transaction's unique location information on the chain. This receipt is then linked and stored with an off-chain report.

[0172] Phase 3: Everyday Applications – Trusted Verification and End-to-End Traceability

[0173] Scenario: The supervisor suspects that data in an archived report has been modified, or the auditor needs to verify the authenticity of a report during an inspection.

[0174] Operation: The user selects the target report in the platform and clicks the "Verify Authenticity" button.

[0175] Execute automatically in the background:

[0176] Step 1: The platform immediately recalculates the "digital fingerprint" based on the report content in the current database.

[0177] The second step: Based on the bound transaction receipt, the platform queries the blockchain network for the "digital fingerprint" recorded when the data was initially uploaded and stored on the blockchain.

[0178] Step 3: The system compares the two fingerprints.

[0179] Results feedback:

[0180] Verification passed: The fingerprints calculated in both tests are completely identical. The platform clearly demonstrates to the user: "This report has remained completely unchanged since [the date of storage], and the blockchain verification has passed." This provides cryptographic-level proof.

[0181] Verification failed: The two fingerprints do not match. The platform issued a prominent alert: "Warning! The report content does not match the blockchain evidence record and may have been tampered with!" and immediately triggered the audit log, notifying the system administrator and relevant personnel.

[0182] "Full-chain traceability" query:

[0183] Scenario: The owner wants to understand the complete handling process of a quality issue, or investigate how a key report was approved by various parties.

[0184] Operation: Users enter a key report number in the platform and select "View Full Source Tracing".

[0185] System presentation:

[0186] The platform interface visualizes the complete lifecycle of the report in the form of a timeline or flowchart.

[0187] Each key node in the process (report generation, construction party application, supervisor review, owner approval, etc.) is displayed as a "block". Each node contains operation details and is accompanied by a green blockchain verification mark.

[0188] Clicking on any node will allow you to view the on-chain evidence storage information of that node's operation records.

[0189] The above description is merely a specific embodiment of the invention, but the scope of protection of the invention is not limited thereto. Any variations or substitutions conceived without inventive effort should be included within the scope of protection of the invention. Therefore, the scope of protection of the invention should be determined by the scope defined in the claims.

Claims

1. An intelligent integrated grouting operation data management method, characterized in that: Includes the following steps: S1: Data structuring processing: Based on a multi-channel data writing strategy, the acquired grouting operation data is written into different databases according to different properties, and a structured data set lake with grouting holes as the index is constructed. S2: Report generation. In response to the completion of single-hole grouting operation, a preliminary quality report containing process parameter curves and quality judgment is generated based on the structured data set lake by calling the preset quality judgment rule base. Based on the preliminary quality reports of multiple grouting holes in the specified area, multi-source data fusion analysis is performed to generate a comprehensive evaluation report including anomaly point identification. S3: Driven by multi-party collaborative work, based on the preliminary quality report and the comprehensive evaluation report, the first party initiates an anomaly handling application with handling suggestions, the second party reviews the anomaly handling application and generates pre-processing opinions marked with anomaly level, and the third party conducts online final review of the pre-processing opinions that exceed the anomaly level threshold based on the comprehensive evaluation report, forming a closed loop and recording key operation records; S4: Based on blockchain, the data is stored and traced with trusted evidence. The preliminary quality report, the comprehensive evaluation report and the key operation records are generated into digital fingerprints and stored in a permissioned consortium blockchain jointly maintained by multiple parties. A blockchain-based verification interface is provided to verify the authenticity and integrity of the report and operation records by comparing the on-chain and off-chain digital fingerprints, and to provide full lifecycle operation traceability query.

2. The intelligent integrated grouting operation data management method according to claim 1, characterized in that: The multi-channel data writing strategy includes a dynamic data channel and a static data channel. The dynamic data channel writes real-time dynamic data of the grouting process with timestamps into a time-series database optimized for time series storage. The static data channel writes the business-related data of the grouting holes and the grouting result summary information into a relational database, and associates and binds the grouting hole position number with the real-time dynamic data of the grouting process in the time-series database.

3. The intelligent integrated grouting operation data management method according to claim 2, characterized in that: The method for generating the preliminary quality report specifically includes the following steps: Based on the hole location number of the grouting hole, the corresponding time series process data, business-related data and design parameters are indexed and aggregated from the structured data set lake; Based on a pre-set quality judgment rule library, the aggregated data is calculated and compared with the rules, and the quality judgment conclusion is automatically output. Based on the comparison results, a standardized report document containing process parameter curves including pressure-time and flow-time, as well as quality level determination, is automatically generated.

4. The intelligent integrated grouting operation data management method according to claim 3, characterized in that: The quality judgment rule base includes: Based on the quantitative threshold rules of design parameters and engineering specifications, the thresholds for the final pressure, unit injection volume and grout density of grouting are determined. An adaptive matching rule based on the geological description associated with the grouting hole is used to evaluate the consistency between actual grouting parameters and geological conditions; The morphological conformity rules based on process parameter curves are used to evaluate the degree of agreement between the actual construction curve and the design process curve. Based on the comparison results of the rules of one or more of the above dimensions, the corresponding quality level is automatically determined and output.

5. The intelligent integrated grouting operation data management method according to claim 4, characterized in that: The multi-source data fusion analysis includes: Geological adaptability analysis: The actual grouting parameters in the preliminary quality reports of each grouting hole are compared and correlated with the corresponding borehole geological records to analyze the rationality of the matching between the construction results and the geological conditions; Process compliance analysis: The process parameter curves of multiple grouting holes in the area are set together and compared with the design process requirement curve to evaluate the degree of standardization of construction operations. Statistical trend analysis: Statistical analysis is performed on the key performance indicators of all grouting holes in the region to generate parameter distribution patterns and overall quality trends.

6. The intelligent integrated grouting operation data management method according to claim 5, characterized in that: The generation of a comprehensive evaluation report that includes anomaly identification specifically includes: Based on the results of the statistical trend analysis, the preset statistical dispersion determination method is used to automatically identify grouting holes that deviate from the overall data distribution pattern as outliers. The generated comprehensive assessment report uses visual charts to mark the anomalies, and provides preliminary cause classification or risk warnings based on the corresponding geological adaptability analysis and process compliance analysis results.

7. The intelligent integrated grouting operation data management method according to claim 6, characterized in that: The method for a first party to initiate an exception handling request with handling recommendations includes the following steps: In the preliminary quality report or the comprehensive evaluation report, the first party initiates a structured application for the identified abnormal grouting holes; The structured application must cite the anomaly report, describe the on-site situation, select or fill in the preliminary cause analysis, and select one or more disposal suggestions from the pre-set measures library; The structured application supports uploading on-site photos or videos as supporting attachments, and must be submitted to the second party after being electronically authenticated by the first party.

8. The intelligent integrated grouting operation data management method according to claim 7, characterized in that: The second party reviews the anomaly handling application and generates preprocessing opinions marked with anomaly levels, specifically including: The second party reviews the process parameter curves and business data of the grouting hole associated with the anomaly handling application for verification. The second party determines an anomaly level for the anomaly handling application based on the complexity of the problem, the scope of its impact, and the handling measures. If the anomaly level does not exceed the preset threshold, the second party has the right to directly approve the handling opinion, and the process returns to the first party for execution; if it exceeds the preset threshold, a pre-processing opinion with detailed analysis and suggestions is generated and then submitted to the third party for final review.

9. The intelligent integrated grouting operation data management method according to claim 8, characterized in that: The method for generating digital fingerprints and storing them in a permissioned consortium blockchain maintained by multiple parties includes the following steps: For each of the preliminary quality report, the comprehensive evaluation report, and the key operation record to be stored, a unique digital fingerprint is calculated using a cryptographic hash function; The digital fingerprint, along with the corresponding report identifier, operation type, and timestamp information, is packaged into a single evidence-based transaction and broadcast to the permissioned consortium blockchain network. After the consortium blockchain network nodes reach a consensus, the evidence-preserving transaction is recorded on the blockchain and a transaction receipt containing its on-chain location is obtained. This receipt is then stored in association with the original off-chain file.

10. The intelligent integrated grouting operation data management method according to claim 9, characterized in that: The method for tracing the entire lifecycle of operations includes the following steps: In response to a verification request, the digital fingerprint of the off-chain target file is recalculated immediately, and the original stored digital fingerprint is retrieved from the consortium blockchain based on the associated transaction receipt. Compare the consistency of the two fingerprints. If they match, the verification is successful. If they do not match, a tampering alarm is triggered. Based on the chronologically recorded and immutable evidence-based transactions on the consortium blockchain, a visualized traceability map of the entire lifecycle, from report generation to approval operations at all levels, is provided.

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