Concrete strength early warning system and method based on edge calculation analysis

Abstract

The invention discloses a concrete strength early warning system and method based on edge calculation analysis, and relates to the technical field of civil engineering, and the method comprises the following steps: collecting standard curing room temperature and humidity data, concrete pressure test data and a digital resiliometer measurement value, carrying out unified time recording, and writing into an electronic curing machine account; and synchronously curing the retention date and the maintenance duration. According to the invention, by recording the unified time and writing the unified time into the electronic maintenance ledger, source solidification of the indwelling date and the maintenance duration is realized, a whole-process traceable data chain is formed, and the authenticity and continuity of strength data are improved. And meanwhile, 28-day strength calculation is carried out based on complete pressure test data, an alarm value is revised, three-level early warning and rectification closed loop are triggered, the concrete strength is converted from post judgment to process pre-judgment, and the quality control initiative and the closed-loop management capability are improved.

Description

Concrete Strength Early Warning System and Method Based on Edge Computing Analysis Technical Field

[0001] This invention relates to the field of civil engineering technology, and specifically to a concrete strength early warning system and method based on edge computing analysis. Background Technology

[0002] Concrete strength early warning based on edge computing analysis refers to a method that directly connects field terminals such as standard curing temperature and humidity monitoring equipment, networked pressure testing machines, and digital rebound hammers to the data network throughout the entire process of concrete strength formation. A lightweight intelligent analysis program is deployed at the construction site to process the collected curing environment data, test block strength data, and physical rebound data in real time. By comprehensively comparing the age development law, strength growth trend, and regional historical data, risk signals such as abnormal curing conditions, strength fluctuation deviations, or insufficient early strength are identified at the source stage of data generation. The identification results are simultaneously uploaded to the cloud platform to trigger multi-level early warning and rectification processes, thereby realizing an intelligent quality control method that transforms concrete strength from traditional post-test confirmation to real-time process monitoring and early intervention.

[0003] Existing technologies have the following shortcomings: Currently, construction projects commonly use pressure testing or rebound testing to determine concrete strength. However, these tests are often conducted independently offline, leaving considerable room for manipulation by testers in data recording, processing, and reporting, making it difficult to effectively guarantee the accuracy of the test data. Furthermore, data statistics and reporting are often delayed, making it difficult for management personnel to promptly grasp the actual situation on-site, easily creating blind spots in supervision. If test data is manipulated or fails to accurately reflect the strength state, substandard concrete may be mistakenly judged as qualified and enter the structural system, potentially severely impacting the safety and stability of the building structure and posing significant quality and safety hazards.

[0004] The information disclosed in the background section is only intended to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0005] The purpose of this invention is to provide a concrete strength early warning system and method based on edge computing analysis to solve the problems mentioned in the background art.

[0006] To achieve the above objectives, this invention provides the following technical solution: a concrete strength early warning method based on edge computing analysis, comprising the following steps: collecting standard curing room temperature and humidity data, concrete pressure test data, and digital rebound hammer measurements; recording these data at a unified time and writing them into an electronic curing ledger; simultaneously fixing the retention date and curing duration as the basis for calculating test nodes; calculating test nodes based on the retention date and curing duration in the electronic curing ledger, generating due date reminders and overdue warnings, and writing the test nodes into the electronic curing ledger to form a continuous test arrangement record; and adapting a networked pressure testing machine based on the test nodes in the electronic curing ledger, realizing strength assessment through a standardized data interface. Data is automatically uploaded, and the intensity data is associated with the test nodes and written into the electronic maintenance ledger to form a complete test data sequence. Based on the complete test data sequence in the electronic maintenance ledger, the first ten sets of complete test data are extracted and the intensity value at seven days of age is used to estimate the intensity at twenty-eight days of age. The intensity warning value is revised in combination with regional historical data, and the revised intensity warning value is written into the electronic maintenance ledger as a basis for early warning. The intensity warning value in the electronic maintenance ledger is compared with the real-time collected data to trigger a three-level early warning system involving the field terminal, mobile terminal, and management dashboard. This system is linked to test number deviation reminders and multi-level access control, supports the entry of rectification details and online approval tracking, and forms a closed loop for handling.

[0007] Preferably, the steps for collecting standard curing room temperature and humidity data, concrete pressure test data, and digital rebound hammer measurements, recording them in a unified time, and writing them into the electronic curing ledger are as follows: Standard curing room temperature and humidity monitoring equipment, concrete pressure test equipment, and a digital rebound hammer are deployed at the construction site to continuously collect standard curing room temperature and humidity data, concrete pressure test data, and digital rebound hammer measurements, and the collected data are recorded in a unified time. Based on the unified time record, the standard curing room temperature and humidity data, concrete pressure test data, and digital rebound hammer measurements are written into the electronic curing ledger in chronological order, and the retention date and curing duration are recorded simultaneously and bound to the time record. Based on the retention date and curing duration in the electronic curing ledger, the curing duration is continuously updated and a time chain is formed according to the unified time record, and the standard curing room temperature and humidity data are associated with the curing stage. Based on the time chain, the concrete pressure test data and digital rebound hammer measurements are associated with the corresponding retention date and curing duration and written into the electronic curing ledger, and the retention date and curing duration are solidified and stored to form a continuous time series structure.

[0008] Preferably, the unified time record uses the same time benchmark to bind the standard curing room temperature and humidity data, concrete pressure test data and digital rebound hammer measurement values ​​to time. The electronic maintenance ledger continuously writes various types of data in chronological order, and simultaneously fixes the retention date and maintenance duration each time it is written, maintaining a unidirectional progressive recording relationship in the time chain.

[0009] Preferably, the steps for calculating test pressure nodes based on the retention date and maintenance duration in the electronic maintenance log are as follows: Time series processing is performed on the retention date and maintenance duration in the electronic maintenance log. An age development timeline is formed, starting from the retention date and combining it with the maintenance duration. The maintenance duration is then mapped according to engineering management specifications to determine potential test pressure nodes. Based on the age development timeline and potential test pressure nodes, test pressure nodes are calculated for test blocks that have reached preset age nodes. The test pressure nodes are then bound to the corresponding retention date, maintenance duration, and unified time record and written into the log. Electronic maintenance ledger; based on the test nodes in the electronic maintenance ledger, due date reminders are generated according to a unified time record, and overdue warnings are generated when the maintenance duration exceeds the test node time and the corresponding intensity data is not written. The due date reminders and overdue warnings are linked to the test nodes; based on the test nodes and the linked records, the test nodes, due date reminders, and overdue warnings are written into the electronic maintenance ledger according to the unified time record, forming a continuous test arrangement record structure that includes the retention date, maintenance duration, test nodes, due date reminders, and overdue warnings.

[0010] Preferably, the age development timeline is continuously generated based on a unified time record, and the pressure test node is corresponding one-to-one with the retention date and maintenance duration. Expiration reminder information and overdue warning information are both triggered based on the pressure test node and written into the electronic maintenance ledger according to the unified time record, thereby ensuring that the pressure test node calculation, the generation of expiration reminder information and the recording of overdue warning information are continuously presented within the same time chain.

[0011] Preferably, the steps for automatically uploading and associating strength data based on the test nodes in the electronic maintenance log are as follows: With the electronic maintenance log forming a continuous test arrangement record including retention date, maintenance duration, and test nodes, test execution identification information is generated for each test node, and this information is bound to a unified time record. The test node information is then sent to the networked pressure testing machine. Based on the networked pressure testing machine, the compressive strength test of the concrete test block is completed. The strength data is automatically uploaded through a standardized data interface. The strength data includes the strength value, test time, test block identification information, and test node identification information, and remains consistent with the fields in the electronic maintenance log. Based on the test node identification information in the automatically uploaded strength data, the strength data is associating with the corresponding test node in the electronic maintenance log, and the retention date and maintenance duration are recorded simultaneously. Based on the associating results, the test nodes in the electronic maintenance log are sequentially arranged according to the unified time record, forming a complete test data sequence that starts from the retention date, increases with the maintenance duration, and writes strength data at each test node.

[0012] Preferably, the standardized data interface uses the same field names and field order as the electronic maintenance ledger for data encapsulation during the automatic upload of intensity data, and includes test node identification information, retention date and maintenance duration information in the intensity data, so as to achieve synchronous association writing of intensity data with the corresponding test node in the electronic maintenance ledger and consistent arrangement of the time chain.

[0013] Preferably, the steps for intensity estimation and intensity warning value revision based on the complete test pressure data sequence in the electronic maintenance log are as follows: Based on the complete test pressure data sequence in the electronic maintenance log, extract the first ten sets of complete test pressure data according to the time identifier of the test pressure node, and retain the test time, intensity value, maintenance duration information and related environmental data; Based on the first ten sets of complete test pressure data and the seven-day-old intensity value, combine the maintenance duration and intensity growth pattern to estimate the twenty-eight-day-old intensity; Based on the twenty-eight-day-old intensity estimation result, revise the intensity value in combination with the intensity development trend in regional historical data to form an intensity warning value; Based on the intensity warning value, write the intensity warning value into the electronic maintenance log, and use the intensity warning value as a warning basis for comparison and judgment with real-time collected data.

[0014] Preferably, the steps for comparing and judging the strength warning value in the electronic maintenance log with the real-time collected data and triggering an early warning are as follows: Based on the strength warning value in the electronic maintenance log, the real-time collected concrete strength data is compared and judged with the strength warning value of the corresponding test node; based on the comparison and judgment results, a three-level early warning is triggered on the site, mobile terminal, and management dashboard when the real-time collected data deviates from the strength warning value; based on the three-level early warning, a test number deviation reminder is generated and multi-level permission control is implemented to manage data access and rectification operations in a hierarchical manner; based on multi-level permission control, rectification details are entered and online approval is tracked, and the rectification progress record is written into the electronic maintenance log to form a closed loop of handling.

[0015] The concrete strength early warning system based on edge computing analysis includes a data acquisition and record-keeping module, a test pressure calculation module, a strength correlation module, a strength prediction and revision module, and a graded early warning closed-loop module. The data acquisition and record-keeping module collects standard curing room temperature and humidity data, concrete pressure test data, and digital rebound hammer measurements, records them at a unified time, and writes them into the electronic curing ledger, simultaneously fixing the retention date and curing duration as the basis for test pressure milestone calculation. The test pressure calculation module calculates test pressure milestones based on the retention date and curing duration in the electronic curing ledger, generates due date reminders and overdue warnings, and writes the test pressure milestones into the electronic curing ledger to form a continuous test schedule record. The strength correlation module, based on the test pressure milestones in the electronic curing ledger, adapts to a networked pressure testing machine and, through standard... The standardized data interface enables automatic uploading of intensity data and associates the intensity data with test nodes, writing it into the electronic maintenance ledger to form a complete test data sequence. The intensity prediction and revision module, based on the complete test data sequence in the electronic maintenance ledger, extracts the first ten sets of complete test data and the seven-day age-appropriate intensity value to extrapolate the twenty-eight-day age-appropriate intensity. It then revises the intensity warning value by combining regional historical data and writes the revised intensity warning value into the electronic maintenance ledger as a basis for early warning. The graded early warning closed-loop module compares and judges the intensity warning value in the electronic maintenance ledger with the real-time collected data, triggering three levels of early warning: on-site, mobile, and management dashboard. It also links test number deviation reminders and multi-level permission control, supports the entry of rectification details and online approval tracking, forming a closed-loop handling system.

[0016] In the above technical solution, the technical effects and advantages provided by this invention are as follows: This invention records the standard curing room temperature and humidity data, concrete pressure test data, and digital rebound hammer measurements in a unified time and writes them into an electronic curing ledger. This ensures that the retention date and curing duration are synchronously fixed at the source of data generation, constructing a continuous data chain covering the entire curing process. The test pressure nodes are automatically calculated and generated by the electronic curing ledger and form a one-to-one correspondence with the strength data, realizing the inherent correlation between test arrangements, data collection, and time series. This fundamentally reduces data deviations caused by manual recording and processing, giving concrete strength information a complete time trajectory and traceability attributes, and improving the authenticity and continuity of strength data.

[0017] This invention, based on a complete sequence of test data, extrapolates the strength at 28 days by combining the first ten sets of complete test data with the seven-day strength values. It then revises the strength warning value using regional historical data, and uses the revised warning value as the basis for early warning in the electronic curing log, thus shifting from result-based judgment to process-based prediction. By comparing the strength warning value with real-time collected data and triggering a three-level early warning system, while simultaneously linking rectification data entry and online approval tracking, strength anomalies can be identified at an early stage and initiated into the handling process, thereby improving the initiative in concrete strength control and the ability to manage the entire process in a closed loop. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0019] Figure 1 is a flowchart of the concrete strength early warning method based on edge computing analysis according to the present invention.

[0020] Figure 2 is a schematic diagram of the concrete strength early warning system based on edge computing analysis according to the present invention. Detailed Implementation

[0021] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, they are provided so that the description of this disclosure will be more complete and fully convey the concept of the exemplary embodiments to those skilled in the art.

[0022] Example 1: This invention provides a concrete strength early warning method based on edge computing analysis, as shown in Figure 1. The method includes the following steps: collecting standard curing room temperature and humidity data, concrete pressure test data, and digital rebound hammer measurements; recording these data using a unified time reference and writing them into an electronic curing ledger; simultaneously fixing the retention date and curing duration; and uniformly collecting, fixing, and constructing an electronic curing ledger for the original data throughout the entire process of concrete strength formation. Specifically, this is implemented according to the following steps: deploying standard curing room temperature and humidity monitoring equipment, concrete pressure testing equipment, and digital rebound hammers at the construction site. The standard curing room temperature and humidity monitoring equipment continuously collects standard curing room temperature and humidity data, the concrete pressure testing equipment outputs concrete pressure test data in real time, and the digital rebound hammer outputs digital rebound hammer measurements. All types of data are recorded using a unified time reference by the data acquisition terminal. This unified time recording uses the same time reference to timestamp and bind the standard curing room temperature and humidity data, concrete pressure test data, and digital rebound hammer measurements, ensuring that all data are identified under the same time coordinate system, so that each set of data is... A unique time identifier is used; specifically: edge-side data acquisition terminals are set up at the construction site, and these terminals establish communication connections with the standard curing room temperature and humidity monitoring equipment, concrete pressure testing equipment, and digital rebound hammer. For the standard curing room temperature and humidity monitoring equipment, the edge-side data acquisition terminals poll or subscribe to receive temperature and humidity data according to a preset sampling cycle, ensuring that the standard curing room temperature and humidity data continuously enters the edge-side data acquisition terminals during the curing process. For the concrete pressure testing equipment, after the equipment completes a single test block compression test, the edge-side data acquisition terminals receive the output strength value, test completion time, and test block identification information, ensuring that the concrete pressure test data is collected in real time upon test completion. For the digital rebound hammer, after the digital rebound hammer completes a single test area detection, the edge-side data acquisition terminals receive the output rebound measurement value, test area number, and component identification information, or read newly added measurement values ​​from the digital rebound hammer according to a preset short cycle, ensuring that the digital rebound hammer measurement values ​​are collected in real time or near real time.

[0023] After receiving standard curing room temperature and humidity data, concrete pressure test data, and digital rebound hammer measurement values ​​from the edge-side data acquisition terminal, the received data is timestamped based on a unified time record and the same time reference. The corresponding curing duration is automatically calculated in conjunction with the pre-entered retention date. Subsequently, the equipment type, equipment identification, test block identification information or component identification information, time stamp, retention date, curing duration, and corresponding collected data are written into the electronic curing ledger according to a unified field structure, so that the standard curing room temperature and humidity data, concrete pressure test data, and digital rebound hammer measurement values ​​are continuously written records under the same time coordinate system.

[0024] In the event of communication interruption or momentary device offline, the edge data acquisition terminal first caches and stores the received data, and then rewrites it into the electronic maintenance ledger according to the original unified time record order after communication is restored, so as to maintain the continuity and integrity of the time chain in the electronic maintenance ledger.

[0025] After completing the unified time recording, the standard curing room temperature and humidity data, concrete pressure test data, and digital rebound hammer measurement values ​​are written into the electronic curing ledger in chronological order. During the writing process, the test block retention date and current curing duration are entered simultaneously, and the retention date and curing duration are bound to the corresponding timestamp one by one. This ensures that each record in the electronic curing ledger contains a time identifier, retention date, curing duration, and data source information, thus forming an initial data structure with complete time logic and data source association.

[0026] After the initial data structure of the electronic maintenance log is established, the retention date and maintenance duration within the electronic maintenance log are continuously updated and solidified, so that each test block forms a continuous and progressive maintenance duration growth trajectory during the maintenance period. Specifically, as standard maintenance room temperature and humidity data are continuously written into the electronic maintenance log, the current maintenance duration is automatically calculated based on the unified time record and retention date, and the updated maintenance duration and corresponding time identifier are synchronously written into the electronic maintenance log, so that the electronic maintenance log forms a continuous time chain with the retention date as the starting point, the unified time record as the time axis, and the maintenance duration as the incrementing variable. Through this time chain, the standard maintenance room temperature and humidity data are dynamically linked with the maintenance stage corresponding to the test block, so that the electronic maintenance log not only reflects the trajectory of environmental parameter changes, but also synchronously records the time position of the test block at different maintenance stages, providing continuously traceable time data support for subsequent pressure test node estimation.

[0027] With the electronic curing ledger having established a continuous time chain and stably recording standard curing temperature and humidity data, retention dates, and curing duration, structured correlation processing is performed on concrete pressure test data and digital rebound hammer measurements. Specifically, when the concrete pressure testing equipment outputs strength data, the strength data is matched with the corresponding test block's retention date and current curing duration according to a unified time record, and written into the electronic curing ledger in chronological order, establishing a precise correspondence between the strength data and the curing stage in the time dimension. Similarly, when the digital rebound hammer measurement is generated, the rebound measurement value is correlated with the corresponding component's curing stage information according to a unified time record, allowing the electronic curing ledger to synchronously present standard curing temperature and humidity data, concrete pressure test data, and digital rebound hammer measurements on the same time axis. Through the above correlation writing method, data from different sources form a structured continuous record under the same time coordinate and retention date system, constructing a complete data sequence covering the entire curing process, providing a comprehensive data set with time and data consistency for subsequent test node estimation and strength development analysis.

[0028] After a continuous data sequence is formed in the electronic maintenance ledger, the retention date and maintenance duration in the electronic maintenance ledger are solidified and stored to maintain a stable sequential structure of the time chain. Specifically, each time data is written into the electronic maintenance ledger, the current time record, the corresponding retention date, and the corresponding maintenance duration are simultaneously solidified, so that new data can only be written sequentially at the end of the existing time chain, keeping the original time order of the records unchanged. Through this solidification method, the electronic maintenance ledger forms a continuous time series structure starting from the retention date, increasing with the maintenance duration, and growing synchronously with the standard curing room temperature and humidity data, concrete pressure test data, and digital rebound hammer measurements. This ensures that the retention date and maintenance duration maintain a stable correspondence throughout the entire maintenance cycle, and provides a complete, continuous, and traceable data support system for subsequent calculations of test nodes, strength data correlation analysis, and strength warning value judgment based on the retention date and maintenance duration.

[0029] Based on the retention date and maintenance duration in the electronic maintenance ledger, pressure test nodes are calculated, and due date reminders and overdue warnings are generated. These pressure test nodes are then written into the electronic maintenance ledger to form a continuous test arrangement record. The process of constructing pressure test node calculation and continuous test arrangement records based on the retention date and maintenance duration in the electronic maintenance ledger is implemented according to the following steps: After the electronic maintenance ledger has formed a data structure linking retention date, maintenance duration, and unified time records, the retention date corresponding to each test block is processed using time series expansion. Using the retention date as the starting point, and combined with the continuously increasing maintenance duration records in the electronic maintenance ledger, an age development timeline covering the entire maintenance process is constructed. This age development timeline uses the unified time record as the time advancement benchmark. The curing duration is an increasing variable, continuously unfolding the time evolution of the test block from the start of placement to each age stage. On this age development timeline, according to the test arrangement requirements of the engineering management specifications for seven-day, twenty-eight-day, and other age stages, the curing duration in the electronic curing ledger is mapped to intervals, so that each curing duration node corresponds to a potential pressure test node on the timeline. By embedding the potential pressure test nodes into the age development timeline, an inherent correspondence is achieved between the pressure test node and the placement date, curing duration, and unified time record. This ensures that the generation of the pressure test node is entirely based on the actual curing time progression trajectory, avoiding manually specified arrangements that deviate from the actual curing process, thereby ensuring the consistency between the pressure test node and the time chain of the electronic curing ledger.

[0030] After mapping the age development timeline to potential stress test nodes, stress test node estimation is performed on test blocks that have reached the preset age node time value based on the retention date and maintenance duration in the electronic maintenance ledger. Specifically, when the maintenance duration in the electronic maintenance ledger meets the time conditions of the corresponding age stage, the time node is determined as a stress test node, and the stress test node is bound to the corresponding retention date, maintenance duration, and unified time record and written into the electronic maintenance ledger, so that the stress test node forms an independent identification record in the time chain. While the stress test node estimation is completed, the original retention date and maintenance duration records are continuously retained for test blocks that have not yet met the age time conditions, so that the electronic maintenance ledger presents a continuous time arrangement structure starting from the retention date, increasing with the maintenance duration, and forming a stress test node identifier at a specific age position, thereby realizing the synchronous correspondence between the generation of stress test nodes and the evolution of maintenance stages.

[0031] Assuming that each pressure test node has been recorded independently in the electronic maintenance log, overdue reminders and warnings are generated around the pressure test nodes. Specifically: when the maintenance duration in the electronic maintenance log reaches the determined pressure test node time, an overdue reminder is generated based on the unified time record, and the overdue reminder is bound to the corresponding pressure test node and written into the electronic maintenance log, transforming the test arrangement from a simple time record into a triggerable reminder status; when the maintenance duration in the electronic maintenance log exceeds the pressure test node time and no corresponding intensity data record has been generated, an overdue warning is generated, and the overdue warning is associated with the corresponding pressure test node, so that the electronic maintenance log simultaneously includes the retention date, maintenance duration, pressure test node identifier, overdue reminder status, and overdue warning status in the time chain, thus forming a complete test arrangement status structure; through the above processing, the pressure test node not only undertakes the function of time identification, but also undertakes the time control function of triggering reminders and warning actions.

[0032] After generating due date reminders and overdue warnings, the test pressure nodes and their corresponding due date reminder and overdue warning statuses are written into the electronic maintenance ledger in a unified time recording order, forming a continuous test arrangement record. Specifically, each time a test pressure node is calculated, a new test pressure node record is added to the time chain of the electronic maintenance ledger, maintaining a one-to-one correspondence with the corresponding retention date and maintenance duration. When a due date reminder or overdue warning status is triggered, it is also written into the electronic maintenance ledger in a unified time recording order, so that the electronic maintenance ledger presents a continuous test arrangement record structure starting from the retention date, increasing with the maintenance duration, forming test pressure node identifiers at key age nodes, and forming reminders or warning statuses at the node times. Through this continuous writing method, the calculation of test pressure nodes, the generation of due date reminders, and the triggering of overdue warnings all rely on the retention date and maintenance duration, forming a closed logical relationship in the same time chain, providing a stable time sequence data framework for subsequent intensity data association writing and intensity warning value judgment.

[0033] Based on the test pressure nodes in the electronic maintenance log, a networked pressure testing machine is adapted to automatically upload strength data through a standardized data interface. The strength data is then associated with the test pressure nodes and written into the electronic maintenance log to form a complete test pressure data sequence. The automatic uploading and association of strength data around the test pressure nodes in the electronic maintenance log is implemented according to the following steps: Based on the existing continuous test arrangement records in the electronic maintenance log, including retention date, maintenance duration, and test pressure nodes, a corresponding test execution identifier is generated for each test pressure node in the electronic maintenance log. This test execution identifier is then bound to a unified time record, giving each test pressure node both a unique time identifier and test block identity information. The test execution identifier includes the test block identifier and corresponding retention date. The date, corresponding curing duration, and test node time and location are synchronously identified through a unified time record, making the test node an identifiable data anchor point in the time chain of the electronic curing ledger. Before the test is executed, the test node information in the electronic curing ledger is proactively sent to the networked pressure testing machine, enabling the networked pressure testing machine to directly call the test block identifier, retention date, and curing duration information corresponding to the test node during the compressive strength test. This ensures that the strength data is pre-associated with the existing test node the moment it is generated. Through this pre-binding method of test nodes based on the electronic curing ledger, the generation process of strength data is synchronously correlated with the test node in the time chain, avoiding the need for subsequent manual comparison to complete data matching and ensuring that the data association is established during the test execution phase.

[0034] After the concrete test blocks undergo compressive strength testing on the networked pressure testing machine, the strength data is automatically uploaded to the data processing terminal via a standardized data interface. This standardized data interface uses a unified data format to structurally encapsulate the strength values, test time, test block identification information, and corresponding test node identification information. It maintains consistency between field names and field order and the retention date and curing duration fields in the electronic curing log, ensuring that the uploaded data can be directly matched with the test node records in the electronic curing log without conversion upon entering the data processing terminal. The strength data retains a unified time record identifier during transmission, ensuring that the upload process remains within the same timeline. By automatically uploading strength data through the standardized data interface, the generated strength data immediately enters the timeline structure constructed by the electronic curing log, reducing intermediate interventions and maintaining the continuity of data source and time position.

[0035] After the intensity data is automatically uploaded through a standardized data interface, the corresponding test pressure node record is located in the electronic maintenance log based on the test pressure node identification information carried in the automatically uploaded data. The intensity data is then written under the corresponding test pressure node according to a unified time recording order. During the writing process, the retention date and maintenance duration corresponding to the intensity data are recorded simultaneously, so that each test pressure node in the electronic maintenance log forms a complete data unit containing intensity value, test time, retention date, maintenance duration, and time identifier. Through the above-mentioned associated writing process, a fixed correspondence is formed between the intensity data and the test pressure node, and a continuous progressive relationship is maintained in the same time chain as the previous standard maintenance room temperature and humidity data records, retention date records, and maintenance duration records, thereby constructing a complete test pressure node data structure.

[0036] After the strength data and test node association were written, all test node records in the electronic maintenance log were arranged in a unified time recording order, so that the same test block formed a continuous strength record sequence at different ages. When the seven-day age test node, the twenty-eight-day age test node, and other age test nodes generated strength data, they were all written into the electronic maintenance log according to the time position of the corresponding test node. This made the electronic maintenance log form a complete test data sequence starting from the retention date, increasing with the maintenance time, and recording strength data at each age test node. This complete test data sequence also retains the standard maintenance room temperature and humidity data, retention date information, and maintenance time information, so that the strength data of different ages are continuously presented on the same time axis, forming a strength change trajectory covering the entire maintenance process of the test block. This provides a continuous, traceable, and structured data support system for the subsequent extraction of the first ten sets of complete test data and the seven-day age strength value based on the complete test data sequence and the estimation of the twenty-eight-day age strength.

[0037] Based on the complete test pressure data sequence in the electronic maintenance log, the first ten sets of complete test pressure data and the seven-day intensity value are extracted to estimate the intensity at 28 days. The intensity warning value is then revised by combining regional historical data, and the revised intensity warning value is written into the electronic maintenance log as a basis for early warning. The specific implementation steps are as follows: Once the complete test pressure data sequence is recorded in the electronic maintenance log, the system obtains the latest test pressure data and extracts the first ten sets of complete test pressure data based on the time identifier of the test pressure node. Specifically, each test pressure node in the electronic maintenance log contains corresponding intensity data. The system binds these test pressure data to their respective test pressure nodes via a timeline and extracts the most recent ten sets of complete test pressure data in chronological order. Each set of data includes the test time, intensity value, maintenance duration information of the test pressure node, and relevant environmental data during the test. In this way, the system ensures that the extracted data not only has temporal continuity, but also ensures the correlation between the test nodes and the data, which can provide complete data support for subsequent intensity estimation.

[0038] By combining the extracted first ten sets of complete pressure test data with the intensity values ​​at seven days of age, the system can accurately predict the intensity value at twenty-eight days of age through analysis of this data. Specifically, based on the intensity growth trend in the first ten sets of pressure test data, combined with actual data on curing time and pressure test nodes, and the intensity values ​​at seven days of age, the system uses a calculation model to predict the intensity at twenty-eight days of age. This prediction is based on a large amount of historical test data, combined with the curing time and intensity growth pattern, providing a scientific basis for the prediction results. By using the intensity values ​​at seven days of age as known data input, the intensity at twenty-eight days of age is calculated, thereby achieving early prediction of future intensity values ​​and providing data support for subsequent intensity control and early warning.

[0039] After the electronic maintenance log forms a complete test data sequence, a nonlinear mapping relationship for age-related strength is constructed based on the first ten sets of complete test data and the seven-day age-related strength values. This is then combined with regional historical data to revise the strength warning value. Specifically: First, the first ten sets of complete test data and their corresponding seven-day age-related strength values ​​are extracted from the electronic maintenance log. A nonlinear mapping function for age-related growth is constructed to predict the compressive strength at 28 days of age. Let the seven-day age-related strength value be... The predicted intensity at 28 days of age is The growth mapping function is defined as follows: in, This is the growth amplification factor, used to adjust the overall magnitude of intensity growth; This is the curvature adjustment coefficient, used to adjust the degree of curvature of the growth trend; It is the natural logarithm function, used to control the smooth change of the growth rate; The intensity increment gradient factor is defined as: In the formula, The compressive strength value is the first ten complete sets of test data, i.e., the [number]th [test result]. The compressive strength value in the complete set of pressure test data, The sample size is defined as follows. The intensity increment gradient factor enhances intensity fluctuations through the form of squared difference, amplifying the changes in the growth trend; the denominator normalizes the overall intensity level, ensuring that the growth rate matches the actual intensity range. Through the above mapping function, the seven-day-old intensity value is coupled with the historical intensity growth trajectory to form a twenty-eight-day-old intensity prediction value with nonlinear characteristics, thereby enabling the advance estimation of the final compressive strength.

[0040] Secondly, in obtaining the predicted intensity value at 28 days of age Subsequently, regionalized historical data is used to revise the prediction results, and a regionally coupled revision function is constructed to generate the intensity warning value. Let the revised intensity warning value be... The regional influence coefficient is The region offset index is The revision function is defined as follows: Among them, the regional offset index Defined as: In the formula, The historical sample intensity value of the region, i.e., the first... Compressive strength values ​​of historical samples from each region. The sample size for the region. The regional offset index characterizes the degree of deviation between the predicted intensity and the historical intensity distribution of the region; the fractional structure controls the revision magnitude within a reasonable range; the regional influence coefficient... This is used to adjust the sensitivity of regional data to warning value revisions. When the difference between the predicted intensity and historical regional data increases, the regional offset index increases, and the revision function adjusts the predicted value accordingly, thereby generating an intensity warning value that matches the actual regional situation. Finally, the revised intensity warning value is written into the electronic maintenance ledger, associated with the corresponding test node, and used as the basis for early warning based on the proportion of subsequent real-time intensity data. Through the above nonlinear mapping and regional coupling revision process, the prediction conversion from seven-day intensity values ​​to twenty-eight-day intensity values ​​is realized. At the same time, a dynamically revised intensity warning value generation mechanism is constructed, so that the intensity warning is based on the dual constraints of historical data and regional characteristics, improving the stability and adaptability of intensity prediction.

[0041] After calculating the strength values ​​at seven days and twenty-eight days, the system revises these values ​​using regional historical data. The revised strength values ​​serve as warning thresholds for subsequent management. Specifically, the regional historical data includes strength development trends of similar mix proportions from past construction projects within the same region. By comparing these trends with the calculated strength values, the system revises the values ​​to a more accurate warning threshold based on the average value, standard deviation, and strength growth pattern of the regional data. This revised warning threshold considers not only the differences in material properties within the same region but also the impact of factors such as climate and curing methods on concrete strength. The revised warning threshold will serve as a benchmark for real-time monitoring and will be used for subsequent early warning triggering.

[0042] The revised strength warning values ​​are written into the electronic maintenance log as a basis for early warning. Specifically, after the update, the electronic maintenance log will include the strength warning value corresponding to each test node and compare this value with the real-time collected strength data. When the actual measured strength value deviates from the revised warning value, the system will trigger an early warning, reminding on-site personnel to conduct further inspections and handle the situation. By comparing the revised warning values ​​with real-time data, the electronic maintenance log can reflect the state of concrete strength in real time, providing timely early warning information for project managers. This helps managers take corresponding corrective measures when the concrete strength has not yet reached the predetermined standard, ensuring the quality and safety of the building structure.

[0043] The system compares the strength warning values ​​in the electronic maintenance log with real-time collected data to trigger a three-tiered early warning system across on-site, mobile, and management dashboards. This system also links test count deviation alerts with multi-level access control, supports detailed rectification data entry and online approval tracking, forming a closed-loop management system. Specifically, after the electronic maintenance log records the strength warning values ​​for each test block, the system compares these warning values ​​with the real-time collected strength data. Specifically, the system automatically compares the concrete strength data collected in real-time by on-site sensors and testing equipment with the corresponding strength warning values ​​of the test nodes in the electronic maintenance log. This comparison process is dynamic; if the real-time collected data deviates from or exceeds the set warning values, the system will immediately identify and process it. Through comparison, the system can detect anomalies as soon as the initial collected data enters the platform and determine whether the warning standard has been reached based on set thresholds. At this point, the system not only compares the specific data, but also identifies whether the data fluctuates or shows a trend of insufficient strength, ensuring that the problem is identified at the earliest stage.

[0044] After comparing intensity data and warning values ​​and confirming anomalies, the system will trigger a three-tiered early warning mechanism involving the on-site, mobile, and management dashboards. Specifically, based on different warning levels and management needs, the system simultaneously sends warning information to different ports, ensuring relevant personnel can obtain information and respond promptly. On-site warning information is primarily presented to on-site construction workers, reminding them to immediately check relevant problem areas via real-time push notifications. Mobile warning information is synchronized to the mobile phones of project managers, quality control personnel, and other relevant management personnel, facilitating simultaneous on-site and remote follow-up on issues. The management dashboard displays all warning information in a visual format, supporting real-time monitoring of multiple project progress and facilitating decision-making by senior management. This three-way linkage not only improves the efficiency of information transmission but also ensures that personnel at different levels can promptly grasp the on-site situation.

[0045] Based on the triggered early warning information, the system also integrates test count deviation alerts and multi-level access control. When an early warning is triggered, the system automatically checks whether the number of tests meets the specified requirements and generates a test count deviation alert. Specifically, the system compares the planned number of tests with the actual number of tests. If the actual number of tests is insufficient or deviates, the system automatically pushes a test count deviation alert, prompting relevant personnel to supplement or redo the tests. Simultaneously, the system implements multi-level access control for data access and rectification operations based on different management permissions. For example, on-site personnel can only view and receive preliminary early warning information and provide initial feedback, while senior managers can view more detailed early warning reports and rectification processes, and even approve rectification measures online. This multi-level access control method ensures data security while guaranteeing that managers at different levels can handle matters promptly and effectively according to their responsibilities.

[0046] After the warning information is sent and the test deviation reminder and access control are completed, the system supports the entry of rectification details and online approval tracking. Specifically, when the warning information is triggered, relevant personnel can enter rectification measures in the system, recording the rectification plan and implementation steps for the current problem. Through the built-in online approval function of the system, superiors can review and approve rectification measures in real time, ensuring the feasibility and timeliness of the rectification plan. After the rectification details are entered, the system will automatically track the rectification progress and update the rectification status in real time, ensuring that the rectification work can be carried out efficiently and transparently. Each rectification measure will form a traceable record in the system, and relevant personnel can view the rectification progress and historical records at any time, ensuring that each task can be handled in a timely manner, ultimately achieving closed-loop management from warning information to rectification action.

[0047] This invention unifies the recording of standard curing temperature and humidity data, concrete pressure test data, and digital rebound hammer measurements, and writes them into an electronic curing ledger. This ensures that the retention date and curing duration are synchronously fixed at the data generation source, constructing a continuous data chain covering the entire curing process. Test nodes are automatically calculated and generated from the electronic curing ledger, establishing a one-to-one correspondence with strength data. This achieves an inherent correlation between test scheduling, data collection, and time series, fundamentally reducing data deviations caused by manual recording and processing. It gives concrete strength information a complete timeline and traceability, improving the authenticity and continuity of strength data.

[0048] This invention, based on a complete sequence of test data, extrapolates the strength at 28 days by combining the first ten sets of complete test data with the seven-day strength values. It then revises the strength warning value using regional historical data, and uses the revised warning value as the basis for early warning in the electronic curing log, thus shifting from result-based judgment to process-based prediction. By comparing the strength warning value with real-time collected data and triggering a three-level early warning system, while simultaneously linking rectification data entry and online approval tracking, strength anomalies can be identified at an early stage and initiated into the handling process, thereby improving the initiative in concrete strength control and the ability to manage the entire process in a closed loop.

[0049] Example 2: This invention provides a concrete strength early warning system based on edge computing analysis, as shown in Figure 2. It includes a data acquisition and record-keeping module, a test pressure calculation module, a strength correlation module, a strength prediction and revision module, and a graded early warning closed-loop module. The data acquisition and record-keeping module collects standard curing room temperature and humidity data, concrete pressure test data, and digital rebound hammer measurements. After unified time recording, it writes the data into the electronic curing ledger, simultaneously fixing the retention date and curing duration as the basis for test pressure node calculation. The test pressure calculation module calculates test pressure nodes based on the retention date and curing duration in the electronic curing ledger, generating due date reminders and overdue warnings, and writes the test pressure nodes into the electronic curing ledger to form a continuous test arrangement record. The strength correlation module, based on the test pressure nodes in the electronic curing ledger, adapts to networked pressure... The force testing machine automatically uploads strength data through a standardized data interface and associates the strength data with test nodes, writing it into the electronic maintenance log to form a complete test data sequence. The strength prediction and revision module, based on the complete test data sequence in the electronic maintenance log, extracts the first ten sets of complete test data and the seven-day age strength value to extrapolate the twenty-eight-day age strength, and revises the strength warning value by combining regional historical data. The revised strength warning value is then written into the electronic maintenance log as a basis for early warning. The graded early warning closed-loop module compares and judges the strength warning value in the electronic maintenance log with the real-time collected data, triggering three levels of early warning: on-site, mobile, and management dashboard. It links test number deviation reminders and multi-level permission control, supports the entry of rectification details and online approval tracking, forming a closed-loop handling system.

[0050] The concrete strength early warning method based on edge computing analysis provided in this embodiment of the invention is implemented through the concrete strength early warning system based on edge computing analysis described above. For details of the specific methods and processes of the concrete strength early warning system based on edge computing analysis, please refer to the embodiments of the concrete strength early warning method based on edge computing analysis described above, which will not be repeated here.

[0051] The foregoing has only described certain exemplary embodiments of the present invention by way of illustration. Undoubtedly, those skilled in the art can modify the described embodiments in various ways without departing from the spirit and scope of the present invention. Therefore, the foregoing drawings and descriptions are illustrative in nature and should not be construed as limiting the scope of protection of the claims of the present invention.

Claims

1. A method for early warning of concrete strength based on edge computing analysis, characterized in that, Includes the following steps: Data on room temperature and humidity during standard curing, concrete pressure test data, and digital rebound hammer measurements are collected, recorded at a unified time, and entered into the electronic curing log, simultaneously fixing the retention date and curing duration. Based on the retention date and curing duration in the electronic curing log, test milestones are calculated, generating due date reminders and overdue warnings, and these milestones are entered into the electronic curing log to form a continuous test schedule record. Based on the test milestones in the electronic curing log, a networked pressure testing machine is adapted to automatically upload strength data through a standardized data interface, and the strength data is associated with the test milestones and entered into the electronic curing log. A complete test pressure data sequence is generated. Based on the complete test pressure data sequence in the electronic maintenance log, the first ten sets of complete test pressure data are extracted and the intensity value at seven days of age is used to estimate the intensity at twenty-eight days of age. The intensity warning value is revised in combination with regional historical data, and the revised intensity warning value is written into the electronic maintenance log as a basis for early warning. The intensity warning value in the electronic maintenance log is compared and judged with the real-time collected data to trigger a three-level early warning system of on-site terminal, mobile terminal and management dashboard. The system links test number deviation reminders and multi-level permission control, supports the entry of rectification details and online approval tracking, and forms a closed loop of disposal.

2. The concrete strength early warning method based on edge computing analysis according to claim 1, characterized in that, The steps for collecting standard curing room temperature and humidity data, concrete pressure test data, and digital rebound hammer measurements, recording them in a unified time, and writing them into the electronic curing ledger are as follows: Standard curing room temperature and humidity monitoring equipment, concrete pressure test equipment, and digital rebound hammers are deployed at the construction site to continuously collect these data and record them in a unified time. Based on the unified time record, the standard curing room temperature and humidity data, concrete pressure test data, and digital rebound hammer measurements are written into the electronic curing ledger in chronological order, simultaneously recording the retention date and curing duration and binding them to the time record. Based on the retention date and curing duration in the electronic curing ledger, the curing duration is continuously updated and a time chain is formed according to the unified time record, associating the standard curing room temperature and humidity data with the curing stage. Based on the time chain, the concrete pressure test data and digital rebound hammer measurements are associated with the corresponding retention date and curing duration and written into the electronic curing ledger, and the retention date and curing duration are solidified and stored to form a continuous time series structure.

3. The concrete strength early warning method based on edge computing analysis according to claim 2, characterized in that, The unified time record uses the same time benchmark to bind the standard curing room temperature and humidity data, concrete pressure test data and digital rebound hammer measurement values ​​to time. The electronic maintenance ledger continuously writes various types of data in chronological order, and simultaneously fixes the retention date and maintenance duration each time it is written, maintaining a unidirectional progressive recording relationship in the time chain.

4. The concrete strength early warning method based on edge computing analysis according to claim 2, characterized in that, The steps for calculating test pressure nodes based on the retention date and maintenance duration in the electronic maintenance log are as follows: First, time series processing is performed on the retention date and maintenance duration in the electronic maintenance log. Starting from the retention date, a timeline for age development is formed by combining the retention date with the maintenance duration. Then, the maintenance duration is mapped according to engineering management specifications to determine potential test pressure nodes. Based on the age development timeline and potential test pressure nodes, test pressure nodes are calculated for test blocks that have reached the preset age nodes. The test pressure nodes are then bound to the corresponding retention date, maintenance duration, and unified time record, and written into the electronic log. Maintenance log; Based on the test nodes in the electronic maintenance log, generate due date reminders according to the unified time record, and generate overdue warning information when the maintenance duration exceeds the test node time and the corresponding intensity data is not written. Link the due date reminder information and overdue warning information with the test nodes; Based on the test nodes and the linked records, write the test nodes, due date reminder information and overdue warning information into the electronic maintenance log according to the unified time record, forming a continuous test arrangement record structure that includes the retention date, maintenance duration, test nodes, due date reminder information and overdue warning information.

5. The concrete strength early warning method based on edge computing analysis according to claim 4, characterized in that, The age development timeline is continuously generated based on a unified time record. The pressure test node is associated with the retention date and maintenance duration. Expiration reminder information and overdue warning information are triggered based on the pressure test node and written into the electronic maintenance ledger according to the unified time record. This ensures that the calculation of the pressure test node, the generation of the expiration reminder information, and the recording of the overdue warning information are presented continuously within the same time chain.

6. The concrete strength early warning method based on edge computing analysis according to claim 4, characterized in that, The steps for automatically uploading and associating strength data based on the test nodes in the electronic maintenance log are as follows: With the electronic maintenance log containing continuous test schedule records including retention date, maintenance duration, and test nodes, a test execution identifier is generated for each test node, and this identifier is bound to a unified time record. The test node information is then sent to the networked pressure testing machine. The networked pressure testing machine completes the compressive strength test on concrete test blocks, and the strength data is automatically uploaded via a standardized data interface. The strength data includes the strength value, test time, test block identifier, and test node identifier, maintaining consistency with the fields in the electronic maintenance log. Based on the test node identifier in the automatically uploaded strength data, the strength data is associating with the corresponding test node in the electronic maintenance log, and the retention date and maintenance duration are recorded simultaneously. Based on the associative writing results, the test nodes in the electronic maintenance log are sequentially arranged according to the unified time record, forming a complete test data sequence that starts from the retention date, increases with the maintenance duration, and writes strength data at each test node.

7. The concrete strength early warning method based on edge computing analysis according to claim 6, characterized in that, The standardized data interface uses the same field names and field order as the electronic maintenance ledger to encapsulate data during the automatic upload of intensity data, and includes test node identification information, retention date and maintenance duration information in the intensity data.

8. The concrete strength early warning method based on edge computing analysis according to claim 6, characterized in that, The steps for intensity estimation and intensity warning value revision based on the complete test pressure data sequence in the electronic maintenance log are as follows: Based on the complete test pressure data sequence in the electronic maintenance log, extract the first ten sets of complete test pressure data according to the time identifier of the test pressure node, and retain the test time, intensity value, maintenance duration information and related environmental data; Based on the first ten sets of complete test pressure data and the seven-day age intensity value, combine the maintenance duration and intensity growth pattern to estimate the twenty-eight-day age intensity; Based on the twenty-eight-day age intensity estimation results, combine the intensity development trend in regional historical data to revise the intensity value and form the intensity warning value; Based on the intensity warning value, the intensity warning value is written into the electronic maintenance log and used as the basis for early warning judgment by comparing it with real-time collected data.

9. The concrete strength early warning method based on edge computing analysis according to claim 8, characterized in that, The steps for comparing and judging the strength warning value in the electronic maintenance log with the real-time collected data and triggering the early warning are as follows: Based on the strength warning value in the electronic maintenance log, the real-time collected concrete strength data is compared and judged with the strength warning value of the corresponding test node; based on the comparison and judgment results, if the real-time collected data deviates from the strength warning value, a three-level early warning is triggered on the site, mobile terminal and management dashboard. Based on a three-level early warning system, a test number deviation reminder is generated and multi-level access control is implemented to manage data access and rectification operations in a hierarchical manner. Based on multi-level access control, rectification details are entered and online approval is tracked, and rectification progress is recorded in the electronic maintenance ledger to form a closed-loop management system.

10. A concrete strength early warning system based on edge computing analysis, used to implement the concrete strength early warning method based on edge computing analysis as described in any one of claims 1-9, characterized in that, It includes a data acquisition and record-keeping module, a pressure test and calculation module, a strength correlation module, a strength prediction and revision module, and a graded early warning closed-loop module: The data acquisition and record-keeping module collects standard curing room temperature and humidity data, concrete pressure test data, and digital rebound hammer measurement values, records them in a unified time and writes them into the electronic curing ledger, and simultaneously solidifies the retention date and curing duration; The pressure test calculation module calculates pressure test nodes based on the retention date and maintenance duration in the electronic maintenance log, generates due date reminders and overdue warnings, and writes the pressure test nodes into the electronic maintenance log to form a continuous test arrangement record. The intensity correlation module, based on the pressure test nodes in the electronic maintenance log, adapts to the networked pressure testing machine, realizes automatic uploading of intensity data through a standardized data interface, and writes the intensity data and pressure test nodes into the electronic maintenance log to form a complete pressure test data sequence. The intensity prediction and revision module, based on the complete pressure test data sequence in the electronic maintenance log, extracts the first ten complete pressure test data sets and the seven-day age intensity value to calculate the twenty-eight-day age intensity, revises the intensity warning value by combining regional historical data, and writes the revised intensity warning value into the electronic maintenance log as the basis for early warning. The hierarchical early warning closed-loop module compares and judges the intensity warning value in the electronic maintenance log with real-time collected data, triggers three-level early warnings at the site, mobile terminal, and management dashboard, links test number deviation reminders and multi-level permission control, supports the entry of rectification details and online approval tracking, and forms a closed-loop disposal system.

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