Concrete material strength detection and analysis system

Abstract

The invention discloses a concrete material strength detection and analysis system, and relates to the technical field of constructional engineering quality detection. The system comprises a data acquisition module, a data preprocessing module, a fusion and analysis module, a fusion and analysis module and a visual report generation module. Wherein the data acquisition module is used for acquiring multi-source original data of concrete strength; the data preprocessing module is used for performing cleaning, format standardization and invalid value elimination operation on the multi-source original data and storing the multi-source original data in the central database; the fusion and analysis module is used for carrying out strength prediction in future time by adopting a dual-mode comparison prediction method, and sending warning information to detection personnel when a strength prediction value exceeds a prediction threshold value; and the visual report generation module is used for automatically generating a detection report and an analysis chart conforming to a standard format. According to the method, the analysis and evaluation of the concrete strength can be realized by fusing the multi-source detection data and the process data and utilizing a machine learning algorithm.

Description

Technical Field

[0001] This invention relates to the field of building engineering quality testing technology, and in particular to a concrete material strength testing and analysis system. Background Technology

[0002] Concrete strength is a core indicator for evaluating the safety, durability, and reliability of building structures. Currently, common methods for on-site testing of concrete strength include the rebound hammer test, ultrasonic testing, and core drilling. However, existing technologies have significant limitations:

[0003] First, the rebound method is significantly affected by the carbonation depth of the concrete surface, humidity, and the type of coarse aggregate; ultrasonic strength is affected by the distribution of reinforcing steel and internal defects. No single method can comprehensively and accurately reflect the true strength, especially for high-performance concrete or concrete with a longer curing period, where the error is more significant. Second, the processing and analysis of test data are highly dependent on the experience and skill of the testing personnel. Different personnel may interpret the data differently, leading to highly subjective results and poor repeatability. Third, traditional test reports typically only provide a single estimated strength value, lacking the ability to correlate test data with process data such as mix proportions, curing conditions, and environmental temperature and humidity, thus failing to trace and analyze the root causes of quality problems. Finally, from data recording and calculation to report generation, much relies on manual operation, resulting in low automation, long processing times, and susceptibility to human error.

[0004] Therefore, there is an urgent need for a testing system that can improve the accuracy and efficiency of concrete strength testing. Summary of the Invention

[0005] The purpose of this invention is to provide a concrete material strength testing and analysis system, which aims to solve or improve at least one of the above-mentioned technical problems.

[0006] To achieve the above objectives, the present invention provides the following solution:

[0007] A concrete material strength testing and analysis system, comprising:

[0008] The data acquisition module is used to acquire multi-source raw data on concrete strength.

[0009] The data preprocessing module is used to receive the multi-source raw data, perform cleaning, format standardization and invalid value removal operations, and then store the standardized data in the central database.

[0010] The fusion and analysis module is used to use a dual-mode comparison prediction method to predict the intensity in the future based on the data to be detected in the central database, obtain the intensity prediction value, and issue an alarm message to the detection personnel when the intensity prediction value exceeds the prediction threshold.

[0011] The visualization report generation module is used to automatically generate test reports and analysis charts in a standard format based on the report content selected by the user; the analysis charts include a test area distribution map, a data scatter plot, and an intensity distribution histogram.

[0012] Optionally, the data acquisition module specifically includes:

[0013] The interface unit is used to automatically read raw data from multiple sources;

[0014] The core drilling machine auxiliary unit is used to input or scan the core sample number and associate it with the data of the pressure testing machine;

[0015] The data entry unit is used to enter test process information, which includes the concrete design strength grade, mix proportion, pouring date, curing conditions, and ambient temperature and humidity.

[0016] Optionally, the interface unit specifically includes:

[0017] The rebound hammer interface unit communicates with the digital rebound hammer and is used to automatically read the rebound value;

[0018] The ultrasonic instrument interface unit communicates with the non-metallic ultrasonic detector and is used to automatically read the wave velocity;

[0019] The pressure testing machine interface unit communicates with the universal pressure testing machine and is used to automatically obtain the compressive strength failure load value of the core sample.

[0020] Optionally, the data preprocessing module specifically includes:

[0021] A buffer unit is used to asynchronously receive and buffer raw data from multiple sources from the data acquisition module;

[0022] An extraction unit is used to extract valid measurement data from the multi-source raw data;

[0023] The verification unit is used to perform outlier detection, duplicate data detection, logical consistency verification, and missing value handling on the extracted data to obtain a complete data stream.

[0024] Standardized units are used to convert complete data streams into uniform units and formats, perform data alignment and correlation, and obtain standardized data.

[0025] The central database storage unit is used to store the normalized data using a hybrid architecture that combines relational databases and time-series databases.

[0026] Optionally, the inspection unit specifically includes:

[0027] The outlier detection subunit is used to automatically identify, mark, and remove outlier measurement values ​​that are clearly outside the reasonable range based on the Raida criterion of statistical principles.

[0028] The duplicate data detection subunit is used to identify and remove duplicate data entries by comparing the test area number, equipment ID, and timestamp.

[0029] The logical consistency verification subunit is used to check the internal logical relationships of the data and remove data that does not meet the set logical relationships.

[0030] The missing value processing subunit is used to identify and mark missing items in the data and impute them in a corresponding manner.

[0031] Optionally, the standardized unit specifically includes:

[0032] The unit standardization subunit is used to convert all data into a set international standard unit.

[0033] The data alignment and association subunit is used to accurately match and align data from different measuring points of the rebound hammer and ultrasonic instrument using a unique detection task ID and measuring area number, forming a complete measuring area data record. At the same time, it associates the measuring area data with the entered process data.

[0034] Optionally, the fusion and analysis module specifically includes:

[0035] Traditional model calculation units have built-in calculation formulas specified in current standards, which are used to generate strength estimation values ​​based on single methods and comprehensive methods;

[0036] The machine learning intelligent analysis unit has a built-in trained concrete strength prediction model, which is used to learn and analyze the data to be tested and output the strength prediction value and the corresponding confidence interval.

[0037] The data comparison and credibility assessment unit is used to compare the output value of the traditional model calculation unit with the output value of the machine learning intelligent analysis unit. When the difference exceeds the preset threshold, an alert is issued, and the final recommendation strength value and corresponding credibility evaluation are output.

[0038] Optionally, it also includes: a user interaction module; the user interaction module is used to provide a graphical operation interface for testing personnel to start testing, view real-time data, monitor and analyze the process, and review and issue reports.

[0039] According to specific embodiments provided by the present invention, the present invention discloses the following technical effects:

[0040] This invention discloses a concrete material strength testing and analysis system. The system includes a data acquisition module, a data preprocessing module, a fusion and analysis module, and a visualization report generation module. The data acquisition module acquires multi-source raw data on concrete strength. The data preprocessing module cleans, standardizes, and removes invalid values ​​from the multi-source raw data, storing it in a central database. The fusion and analysis module uses a dual-mode comparison prediction method to predict strength over future time periods and issues an alert to testing personnel when the predicted strength exceeds a prediction threshold. The visualization report generation module automatically generates a test report and analysis charts in a standard format. This invention enables the analysis and evaluation of concrete strength by fusing multi-source test data and process data and utilizing machine learning algorithms. Attached Figure Description

[0041] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0042] Figure 1 This is a schematic diagram of the concrete material strength testing and analysis system in this embodiment;

[0043] Figure 2 This is a schematic diagram of the concrete material strength testing and analysis process in this embodiment. Detailed Implementation

[0044] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0045] The purpose of this invention is to provide a concrete material strength testing and analysis system, which aims to solve or improve at least one of the above-mentioned technical problems.

[0046] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0047] like Figures 1-2 As shown, the present invention provides a concrete material strength testing and analysis system, comprising:

[0048] The data acquisition module is used to acquire multi-source raw data on concrete strength.

[0049] The data preprocessing module receives the multi-source raw data and performs cleaning, format standardization, and invalid value removal operations, and then stores the standardized data in the central database.

[0050] The fusion and analysis module is used to use a dual-mode comparison prediction method to predict the intensity over a future time based on the data to be detected in the central database, obtain the intensity prediction value, and issue an alarm message to the detection personnel when the intensity prediction value exceeds the prediction threshold.

[0051] The visualization report generation module is used to automatically generate test reports and analysis charts in a standard format based on the report content selected by the user; the analysis charts include a test area distribution map, a data scatter plot, and an intensity distribution histogram.

[0052] User interaction module; The user interaction module is used to provide a graphical operation interface for testing personnel, enabling them to start testing, view real-time data, monitor and analyze the process, and review and issue reports.

[0053] As one specific implementation method, the data acquisition module specifically includes:

[0054] The interface unit is used to automatically read raw data from multiple sources.

[0055] The core drilling machine auxiliary unit is used to input or scan the core sample number and associate it with the data of the pressure testing machine.

[0056] The data entry unit is used to enter test process information, which includes the concrete design strength grade, mix proportion, pouring date, curing conditions, and ambient temperature and humidity.

[0057] The interface unit specifically includes:

[0058] The rebound hammer interface unit communicates with the digital rebound hammer and is used to automatically read the rebound value.

[0059] The ultrasonic instrument interface unit communicates with the non-metallic ultrasonic testing instrument and is used to automatically read the wave velocity.

[0060] The pressure testing machine interface unit communicates with the universal pressure testing machine and is used to automatically obtain the compressive strength failure load value of the core sample.

[0061] As one specific implementation method, the data preprocessing module specifically includes:

[0062] The buffer unit is used to asynchronously receive and buffer raw data from multiple sources from the data acquisition module.

[0063] An extraction unit is used to extract valid measurement data from the multi-source raw data.

[0064] The verification unit is used to perform outlier detection, duplicate data detection, logical consistency verification, and missing value handling on the extracted data to obtain a complete data stream.

[0065] Standardized units are used to convert complete data streams into uniform units and formats, perform data alignment and correlation, and obtain standardized data.

[0066] The central database storage unit is used to store the normalized data using a hybrid architecture that combines relational databases and time-series databases.

[0067] The inspection unit specifically includes:

[0068] The outlier detection subunit is used to automatically identify, mark, and remove abnormal measurement values ​​that are clearly outside the reasonable range based on the Raida criterion of statistical principles.

[0069] The duplicate data detection subunit is used to identify and remove duplicate data entries by comparing the test area number, equipment ID, and timestamp.

[0070] The logical consistency verification subunit is used to check the internal logical relationships of the data and remove data that does not meet the set logical relationships.

[0071] The missing value processing subunit is used to identify and mark missing items in the data and impute them in a corresponding manner.

[0072] Specifically, the standardized unit includes:

[0073] The unit standardization subunit is used to convert all data into a set international standard unit.

[0074] The data alignment and association subunit is used to accurately match and align data from different measuring points of the rebound hammer and ultrasonic instrument using a unique detection task ID and measuring area number, forming a complete measuring area data record. At the same time, it associates the measuring area data with the entered process data.

[0075] As a specific implementation method, the fusion and analysis module specifically includes:

[0076] Traditional model calculation units contain built-in calculation formulas specified in current national standards, used to generate strength estimation values ​​based on single methods and comprehensive methods.

[0077] The machine learning intelligent analysis unit has a built-in pre-trained concrete strength prediction model, which is used to learn and analyze the data to be tested, and output the strength prediction value and the corresponding confidence interval.

[0078] The data comparison and credibility assessment unit is used to compare the output value of the traditional model calculation unit with the output value of the machine learning intelligent analysis unit. When the difference exceeds the preset threshold, an alert is issued, and the final recommendation strength value and corresponding credibility evaluation are output.

[0079] Based on the above technical solution, the following embodiments are provided.

[0080] Taking a key construction project in a certain city as an example, its core tube wall uses C60 high-strength concrete. In order to ensure that the concrete strength meets the design requirements and to realize intelligent monitoring of strength development, the project's quality inspection department introduced this "Intelligent Concrete Strength Detection and Prediction System".

[0081] System Deployment: A system server and operating terminals were deployed in the project site laboratory, and the digital rebound hammer, non-metallic ultrasonic tester, and universal pressure testing machine were connected to the system via dedicated interfaces. Testing personnel were equipped with tablets with the system's mobile app installed for on-site data entry and viewing.

[0082] Specific application process:

[0083] 1. Task Creation and Data Acquisition (Data Acquisition Module)

[0084] A testing worker named Zhang San created a new testing task in the system.

[0085] Task information entry (entry unit): He entered the concrete design strength (C60), mix proportion number (HPB-2023-086), pouring date (2023-10-26), curing status (standard curing film coverage), and today's ambient temperature and humidity (25℃, 60%RH) for the test area through the graphical interface.

[0086] On-site non-destructive testing (interface unit):

[0087] Zhang San used a digital rebound hammer to perform rebound testing on the A-3 test area of ​​the 12th layer. After the test was completed, he clicked the "Read Rebound Data" button on the operation terminal. The rebound hammer interface unit automatically uploaded 16 rebound values ​​(e.g., 52, 54, 51, ...) to the system and associated them with the current task.

[0088] He then used a non-metallic ultrasonic testing instrument to perform ultrasonic testing on the same test area. Similarly, the ultrasonic instrument interface unit automatically read the sound time value and wave velocity (e.g., 4.52 km / s) and uploaded them to the system.

[0089] Core sampling and pressure testing (core drilling machine auxiliary unit & pressure testing machine interface unit):

[0090] For another test area, B-5, which required destructive testing, a set of three core samples were drilled. Zhang San used a tablet computer to scan the QR code on each core sample, and the system automatically recorded the core sample number (XY-1210-01 to 03).

[0091] The core sample is sent to the laboratory for pressure testing. When the universal pressure testing machine crushes the core sample, the interface unit of the pressure testing machine automatically collects the failure load value (e.g., 356.8 kN). Based on the test time and core sample number, the system automatically and accurately associates this strength value with the previously scanned and entered core sample information, eliminating the need for manual re-entry.

[0092] 2. Automated Data Processing and Storage (Data Preprocessing Module)

[0093] The collected raw data from multiple sources is sent asynchronously to the preprocessing module.

[0094] Buffering and Extraction: The buffer unit first receives all the data, and the extraction unit then extracts the valid measurement values ​​(rebound value, wave velocity, load value, etc.) from it.

[0095] Data validation (validation unit):

[0096] Outlier detection: The system found a rebound value "65" that was significantly higher than the other 15 values ​​(all between 50 and 55). According to the Raida criterion, it was marked as an outlier and automatically removed.

[0097] Duplicate data detection: The system comparison revealed that due to network fluctuations, the same set of bounce values ​​was uploaded twice. By comparing the device ID and timestamp, the duplicate data detection subunit automatically removed the duplicate entries.

[0098] Logical consistency check: The system check found that the compressive strength of a core sample was only 30 MPa, but its corresponding rebound value was very high. This does not conform to the basic logic that "low-strength core samples correspond to low rebound values". This data was marked as "logical anomaly" and requires manual review.

[0099] Missing value handling: When the environmental humidity data of a certain measurement area is lost due to sensor failure, the missing value handling subunit interpolates the data by using the average humidity of adjacent measurement areas within the same time period.

[0100] Standardization and Storage (Standardized Units & Central Database Storage Units):

[0101] Unit standardization: all force values ​​are standardized to "kilonewtons (kN)", strength is standardized to "megapascals (MPa)", and length is standardized to "millimeters (mm)".

[0102] Data alignment and association: The system successfully linked the rebound data, ultrasonic data and the entered process information of the A-3 test area through the unique "detection task ID" and "test area number", forming a complete and traceable data record.

[0103] All processed and normalized data are simultaneously stored in a relational database (for storing structured data such as task information and survey area attributes) and a time-series database (for efficiently storing and querying intensity development data generated according to time series).

[0104] 3. Intensity Prediction and Intelligent Alarm (Fusion and Analysis Module)

[0105] The system performs intensity prediction analysis on the A-3 survey area data that has been stored in the central database.

[0106] Dual-mode comparison prediction:

[0107] The traditional model calculation unit calls the national standard formula of "Rebound-Ultrasonic Integrated Method" and calculates the estimated strength value of the test area as 62.5 MPa based on the rebound value and sound velocity value.

[0108] The machine learning intelligent analysis unit compares and analyzes the current test data with massive historical data (including mix proportions, age, temperature and humidity, rebound value, wave velocity, and final core sample strength). Its built-in prediction model outputs the following result: predicted strength = 58.8 MPa, confidence interval [56.2, 61.4] MPa.

[0109] Comparison and Alerts:

[0110] The data comparison and credibility assessment unit found that the difference between the predicted values ​​of the traditional method and the AI ​​method (3.7 MPa) exceeded the preset threshold of 2.5 MPa.

[0111] The system immediately triggered an early warning mechanism, displaying a warning message on Zhang San's tablet and the laboratory's large screen: "Warning: There is a significant difference in the intensity prediction results for the A-3 test area. Core drilling verification is recommended!"

[0112] Meanwhile, the system combines the calculation results and credibility of the two methods to give a final recommended strength value of 59.5 MPa, and marks it with "credibility: to be verified".

[0113] 4. Report Generation and Deliverables (Visual Report Generation Module)

[0114] The project director needs to check the overall strength of the 12th floor.

[0115] In the report page of the system's user interaction module, he checked "Test Area Distribution Map", "Rebound Value-Intensity Scatter Plot", "Intensity Distribution Histogram" and "Detailed Data Table".

[0116] After clicking "Generate Report", the visual report generation module will start working automatically:

[0117] Data from the database was used to generate a map showing the distribution of the survey area, and the estimated intensity of each area was displayed visually using different colors.

[0118] A scatter plot of the data was generated, showing the correlation between rebound value and intensity.

[0119] A histogram of strength distribution was generated, which clearly reflects the distribution of concrete strength in this floor. It conforms to a normal distribution with a mean of 59.8 MPa.

[0120] All charts, data tables, and analysis conclusions were automatically compiled to generate a PDF inspection report that met engineering quality inspection standards. After the chief supervisor reviewed and approved the report, it was directly signed using the system's electronic signature function, and the report was immediately distributed to the construction, supervision, and owner units.

[0121] As demonstrated in this embodiment, the system successfully automates the entire process from multi-source data acquisition, intelligent cleaning, fusion analysis to report generation. It not only significantly improves detection efficiency and reduces human error, but the "dual-mode comparison prediction" mechanism employed in this embodiment also effectively enhances the scientific rigor and reliability of strength assessment, enabling early detection of potential strength deficiencies and providing robust intelligent assurance for project quality.

[0122] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. The same or similar parts between the various embodiments can be referred to each other.

[0123] This document uses specific examples to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the core ideas of the present invention. Furthermore, those skilled in the art will recognize that, based on the ideas of the present invention, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A concrete material strength testing and analysis system, characterized in that, include: The data acquisition module is used to acquire multi-source raw data on concrete strength. The data preprocessing module is used to receive the multi-source raw data, perform cleaning, format standardization and invalid value removal operations, and then store the standardized data in the central database. The fusion and analysis module is used to use a dual-mode comparison prediction method to predict the intensity in the future based on the data to be detected in the central database, obtain the intensity prediction value, and issue an alarm message to the detection personnel when the intensity prediction value exceeds the prediction threshold. The visualization report generation module is used to automatically generate test reports and analysis charts in a standard format based on the report content selected by the user; the analysis charts include a test area distribution map, a data scatter plot, and an intensity distribution histogram.

2. The concrete material strength testing and analysis system according to claim 1, characterized in that, The data acquisition module specifically includes: The interface unit is used to automatically read raw data from multiple sources; The core drilling machine auxiliary unit is used to input or scan the core sample number and associate it with the data of the pressure testing machine; The data entry unit is used to enter test process information, which includes the concrete design strength grade, mix proportion, pouring date, curing conditions, and ambient temperature and humidity.

3. The concrete material strength testing and analysis system according to claim 2, characterized in that, The interface unit specifically includes: The rebound hammer interface unit communicates with the digital rebound hammer and is used to automatically read the rebound value; The ultrasonic instrument interface unit communicates with the non-metallic ultrasonic detector and is used to automatically read the wave velocity; The pressure testing machine interface unit communicates with the universal pressure testing machine and is used to automatically obtain the compressive strength failure load value of the core sample.

4. The concrete material strength testing and analysis system according to claim 1, characterized in that, The data preprocessing module specifically includes: A buffer unit is used to asynchronously receive and buffer raw data from multiple sources from the data acquisition module; An extraction unit is used to extract valid measurement data from the multi-source raw data; The verification unit is used to perform outlier detection, duplicate data detection, logical consistency verification, and missing value handling on the extracted data to obtain a complete data stream. Standardized units are used to convert complete data streams into uniform units and formats, perform data alignment and correlation, and obtain standardized data. The central database storage unit is used to store the normalized data using a hybrid architecture that combines relational databases and time-series databases.

5. The concrete material strength testing and analysis system according to claim 4, characterized in that, The inspection unit specifically includes: The outlier detection subunit is used to automatically identify, mark, and remove outlier measurement values ​​that are clearly outside the reasonable range based on the Raida criterion of statistical principles. The duplicate data detection subunit is used to identify and remove duplicate data entries by comparing the test area number, equipment ID, and timestamp. The logical consistency verification subunit is used to check the internal logical relationships of the data and remove data that does not meet the set logical relationships. The missing value processing subunit is used to identify and mark missing items in the data and impute them in a corresponding manner.

6. The concrete material strength testing and analysis system according to claim 1, characterized in that, The standardized unit specifically includes: The unit standardization subunit is used to convert all data into a set international standard unit. The data alignment and association subunit is used to accurately match and align data from different measuring points of the rebound hammer and ultrasonic instrument using a unique detection task ID and measuring area number, forming a complete measuring area data record. At the same time, it associates the measuring area data with the entered process data.

7. The concrete material strength testing and analysis system according to claim 1, characterized in that, The fusion and analysis module specifically includes: Traditional model calculation units have built-in calculation formulas specified in current standards, which are used to generate strength estimation values ​​based on single methods and comprehensive methods; The machine learning intelligent analysis unit has a built-in trained concrete strength prediction model, which is used to learn and analyze the data to be tested and output the strength prediction value and the corresponding confidence interval. The data comparison and credibility assessment unit is used to compare the output value of the traditional model calculation unit with the output value of the machine learning intelligent analysis unit. When the difference exceeds the preset threshold, an alert is issued, and the final recommendation strength value and corresponding credibility evaluation are output.

8. The concrete material strength testing and analysis system according to claim 1, characterized in that, Also includes: User interaction module; The user interaction module is used to provide a graphical operation interface for testing personnel, enabling them to start testing, view real-time data, monitor and analyze the process, and review and issue reports.

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