High-performance concrete detection method

Abstract

The invention discloses a high-performance concrete detection method, and relates to the technical field of concrete detection. Comprising the following steps: sampling: performing segmented sampling and uniform mixing in an unloading process, acquiring image information of a sample, analyzing and pre-judging risks, generating a unique electronic tag for the sample, and binding related information of the batch of high-performance concrete; and fresh mixing performance testing: monitoring discharge rheological parameters in real time, automatically testing integrated slump, expansion degree, volume weight and gas content of the sample, judging workability and deciding pouring. According to the method, the solid curing test piece is manufactured and cured in the environment which is completely the same as the solid structure, the measured strength can more accurately reflect the actual development condition of solid concrete, the strength of the solid concrete is compared with the strength of the standard curing test piece, and the field curing effect is scientifically evaluated; the problem of high-performance concrete or the problem of field maintenance conditions can be better judged, and the accuracy of a detection result is improved.

Description

Technical Field

[0001] This invention relates to the field of concrete testing technology, specifically a high-performance concrete testing method. Background Technology

[0002] High-performance concrete, due to its superior properties such as high strength, high durability, and high workability, is widely used in major projects such as high-rise buildings, long-span bridges, and undersea tunnels. However, these very high-performance characteristics bring unprecedented challenges to its quality inspection and control. Traditional concrete testing methods exhibit many limitations when dealing with high-performance concrete, such as large errors and low efficiency.

[0003] For example, invention patent CN117890384A discloses a concrete quality inspection robot and a concrete inspection method, including a base, support, measuring ruler, image acquisition device, and controller. The controller operates the measuring ruler and rebound hammer to perform concrete inspection, saving labor costs. The multi-functional quality inspection robot comprehensively inspects the levelness, verticality, strength, and appearance quality of vertical concrete components. This invention improves the efficiency of concrete quality inspection and solves the problem that existing construction projects rely entirely on on-site inspections by supervisors, resulting in significant structural errors.

[0004] However, the above-mentioned technical solutions lack direct means of measuring the true strength of concrete entities and rely on indirect non-destructive testing technology such as rebound hammers, which may lead to errors and disputes in strength judgment; and lack the ability to assess the level of construction and maintenance, making it impossible to determine whether the insufficient strength of the entity structure is due to poor concrete quality or inadequate on-site maintenance, making it difficult to define quality responsibility. Summary of the Invention

[0005] The purpose of this invention is to provide a high-performance concrete testing method to solve the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a method for testing high-performance concrete, comprising:

[0007] Sampling: During the unloading process, samples are taken in segments and mixed evenly. Sample image information is collected, analyzed and risks are predicted, and a unique electronic tag is generated for each sample to bind relevant information of this batch of high-performance concrete.

[0008] Fresh Mix Performance Testing: Real-time monitoring of unloading rheological parameters, and integrated automatic testing of slump, spread, bulk density and air content of samples to determine workability and make casting decisions;

[0009] Test piece production and curing: After the approval of pouring, production of labeled curing test pieces and physical curing test pieces, and generation of electronic tags for test pieces; Place the test pieces in the corresponding curing conditions for curing to the specified age;

[0010] Hardening performance test: Test the strength of standard curing test pieces and physical curing test pieces at the same time to obtain strength data;

[0011] Data processing and report generation: Integrate the whole process data, automatically generate quality detection data and diagnostic prediction data, and comprehensively evaluate the detection data of the batch of high-performance concrete.

[0012] Further, the sampling method comprises:

[0013] Collect at least three sub-samples at the beginning, middle and end of the unloading process;

[0014] Pour the collected several sub-samples on a steel plate and stir them evenly to obtain a freshly mixed sample;

[0015] Image acquisition is performed on the freshly mixed sample to analyze its apparent uniformity and predict segregation and bleeding risk;

[0016] Subdivide the freshly mixed sample without segregation and bleeding risk to the required amount for testing to obtain a subdivided sample;

[0017] Generate a unique electronic tag for each batch of samples and associate it with the relevant information of the batch of high-performance concrete.

[0018] Further, the method for testing the performance of the freshly mixed sample comprises:

[0019] During the unloading process of the high-performance concrete, the yield stress and plastic viscosity of the high-performance concrete are monitored and recorded in real time;

[0020] Put the subdivided sample into a slump cone according to the standard method, insert and smooth it, and perform a slump and spread test, automatically measure the slump height and two perpendicular direction spread diameter data, and calculate the average value;

[0021] Put the subdivided sample into a known volume of bulk density bucket according to the standard method, and vibrate and smooth it, automatically calculate and record the bulk density;

[0022] Divide the subdivided sample into layers and put it into the bowl of the air content measuring device, and vibrate and smooth it, automatically read the pressure change value, calculate and record the air content;

[0023] Comprehensively analyze the test data to determine whether the workability of the batch of high-performance concrete is qualified; if qualified, approve pouring; if not qualified, stop immediately and perform return processing; and associate the test data and judgment result with the unique electronic tag of the sample.

[0024] Further, the method for manufacturing and maintaining the test piece comprises:

[0025] In the pouring of qualified high-performance concrete, the temperature and humidity change data inside the solid structure are continuously monitored to obtain the internal environment data baseline;

[0026] The standard curing test piece and the solid curing test piece are made by using the split sample, and the electronic tag is generated for the test piece, the internal environment data baseline is bound, and the internal environment data baseline is associated with the unique electronic tag of the sample;

[0027] The standard curing test piece is placed in the standard curing room for curing to the specified age, and the solid curing test piece is placed in the programmable environment curing box, and the monitored internal environment data baseline is synchronously input into the curing box, and the curing is performed to the specified age.

[0028] Further, the method for testing the hardening performance comprises:

[0029] The test pieces that have reached the specified curing age are taken out from the standard curing room and the programmable environment curing box, respectively;

[0030] The appearance of the test piece is checked, the flat side is selected as the pressure bearing surface, the pressure is applied to the test piece until the test piece is damaged, and the damage load value is automatically recorded;

[0031] According to the recorded damage load value and the pressure bearing area of the test piece, the compressive strength of the test piece is calculated and associated with the electronic tag of the test piece.

[0032] Further, the method for processing data and generating a report comprises:

[0033] All data of the sampling step to the hardening performance testing step are integrated to obtain the whole-process data;

[0034] According to the strength data of the standard curing test piece, the quality detection data is automatically generated, and according to the whole-process data, the diagnostic prediction data is obtained by diagnostic analysis, the diagnostic prediction data includes: based on the strength comparison between the standard curing test piece and the solid curing test piece, the on-site curing condition is quantitatively evaluated, and the potential risk is warned; based on the whole-process data, the long-term durability of the batch of high-performance concrete is predicted;

[0035] The quality detection data and the diagnostic prediction data are comprehensively evaluated to obtain the high-performance concrete detection data.

[0036] Further, the diagnostic analysis includes that when the high-performance concrete has a quality problem, the whole-process data can be automatically traced back to locate the problem source.

[0037] Compared with the prior art, the beneficial effects of the present application are:

[0038] A high-performance concrete detection method, by generating a unique electronic tag for each batch of high-performance concrete, and automatically associating online rheological data, fresh performance data, hardened strength data and other full-chain information, when quality problems occur, automatically trace back to analyze each link, locate the problem source, and improve the diagnosis efficiency; by monitoring the rheological parameters in real time at the discharge port and combining the automatic testing and intelligent judgment of fresh concrete, the workability of high-performance concrete is judged in time, the quality hidden danger after pouring is reduced, and the rework loss is reduced.

[0039] At the same time, by making entity curing test pieces, which are placed in the same environment as the entity structure for curing, the measured strength can more accurately reflect the actual development of the entity concrete, and by comparing the strength with the standard curing test piece strength, the on-site curing effect is scientifically evaluated, and it is better to judge whether the problem of high-performance concrete itself or the problem of on-site curing condition, and the accuracy of the detection result is improved. BRIEF DESCRIPTION OF DRAWINGS

[0040] Figure 1 A high-performance concrete detection method of the present application is shown in the figure;

[0041] Figure 2 A sampling method of the present application is shown in the figure;

[0042] Figure 3 A fresh performance test method of the present application is shown in the figure;

[0043] Figure 4 A test piece making and curing method of the present application is shown in the figure. DETAILED DESCRIPTION

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

[0045] As shown in the figure, Figure 1 The present application provides a technical solution: a high-performance concrete detection method, comprising:

[0046] Sampling: segment sampling during the discharging process and mixing uniformly, collecting sample image information, analyzing and predicting risks, and generating a unique electronic tag for the sample, and binding the related information of the batch of high-performance concrete.

[0047] As shown in the figure, Figure 2 The present application provides a sampling method;

[0048] Specifically,

[0049] At the beginning, middle and end of the unloading process, collect at least three sub-samples;

[0050] Pour the collected several sub-samples on a steel plate and stir them evenly to obtain a freshly mixed sample;

[0051] Collect images of the freshly mixed sample and analyze its apparent uniformity to predict the risk of segregation and bleeding;

[0052] Subdivide the freshly mixed sample without segregation and bleeding risk to the required amount for testing to obtain a subdivided sample;

[0053] Generate a unique electronic tag for each batch of sample and associate it with the relevant information of the batch of high-performance concrete.

[0054] It should be noted that during the unloading process of the mixing truck, strictly follow the standard requirements and use a dedicated sampling shovel to collect at least three sub-samples at the 1 / 4, 1 / 2 and 3 / 4 stages of the total unloading amount. Each sub-sample should be at least 0.5 cubic meters, and the sampling time interval should be uniform.

[0055] Pour the obtained multiple sub-samples quickly on a clean, flat, non-absorbing steel plate and stir them quickly and evenly. Ensure that the bottom concrete is completely turned over each time during the mixing process, and repeat the operation until the color is uniform.

[0056] Use a 1080P high-definition industrial camera to collect image information of the mixed sample from multiple angles. The video stream is transmitted in real time to the local server through the edge computing gateway. Use a target detection algorithm based on deep learning (such as the YOLOv5 model) to analyze the aggregate distribution and particle size in the image. Through methods such as calculating the area ratio of aggregate to paste and identifying the water light reflection characteristics of the paste surface, automatically output the segregation risk and bleeding risk level, which includes no risk, low risk and high risk. The evaluation results are immediately stored in the cloud database.

[0057] Subdivide the sample that is evaluated as no risk or low risk using the standard four-part method. First, pile the sample into a conical shape, flatten it, and divide it into four equal parts using a cross plate. Take the diagonally opposite two parts as the test sample, repeat the operation until the required amount for testing is obtained, usually 20-30L. The subdivision process should be completed within 5 minutes to prevent loss of workability.

[0058] A unique UHF RFID tag is generated for each batch of samples, and the key information of the batch of high-performance concrete is directly written into the chip storage area of the RFID tag through a handheld UHF reader with a working frequency of 860-690MHz; the key information includes the mixing station name, the mixing ratio number, the design strength grade, the sampling time, the sampler, and the transport vehicle number. At the same time, the handheld reader transmits all the information together with the collected geographic position data to the cloud database through the built-in 4G / 5G module. Then the RFID tag with the written information is pasted on a conspicuous position of the sample container.

[0059] Fresh performance test: real-time monitoring of unloading rheological parameters, automatic testing of integrated slump, spread, bulk density and air content of the sample, judgment of workability and decision of pouring.

[0060] As shown in Figure 3 , the application provides a fresh performance test method;

[0061] Specifically:

[0062] During the unloading process of the high-performance concrete, the yield stress and plastic viscosity data of the high-performance concrete are monitored and recorded in real time;

[0063] The subsample is loaded into a slump cone according to the standard method, and is inserted and smoothed, and the slump and spread tests are performed, the slump height and two perpendicular direction spread diameter data are automatically measured, and the average value is calculated;

[0064] The subsample is loaded into a known volume of bulk density barrel according to the standard method, and is vibrated and smoothed, and the bulk density is automatically calculated and recorded;

[0065] The subsample is loaded into the bowl of the air content measuring device in layers, and is vibrated and smoothed, the pressure change value is automatically read, and the air content is calculated and recorded;

[0066] The test data are comprehensively analyzed to determine whether the workability of the batch of high-performance concrete is qualified; if qualified, pouring is approved; if not qualified, pouring is immediately stopped, and return processing is performed; and the test data and the judgment result are associated with the unique electronic tag of the sample.

[0067] It should be noted that the online rheometer measuring unit is installed at the discharge port of the mixer truck, the measuring unit adopts a coaxial cylinder structure, and the rotating speed of the inner cylinder can be accurately adjusted in the range of 0.1-100 rpm. When the high-performance concrete flows through the measuring unit, a high-precision torque sensor monitors the rotating resistance in real time, and a temperature sensor synchronously records the material temperature. A group of data is collected every 10 seconds, and the torque, rotating speed, temperature and other raw data are transmitted to the cloud platform through the 4G / 5G DTU module. The platform calculates and updates the yield stress and plastic viscosity values in real time based on the Bingham fluid model, and uploads them to the cloud database.

[0068] The slump and spread are tested by using a full-automatic slump tester. When the slump cylinder is lifted, the two-dimensional laser scanning array at the top immediately scans the high-performance concrete pile, obtains three-dimensional coordinate data of not less than 1000 points through the triangulation principle, and then automatically fits the upper surface profile by using plane fitting based on random sampling consistency and combining with Z-axis projection extreme point detection. Then, the slump height and the spread diameters in two perpendicular directions are calculated, the measurement accuracy is ±1 mm, and the data are uploaded to the cloud database.

[0069] An intelligent electronic scale that has passed metrological verification is used, the accuracy is 0.1% FS, and an RS485 communication interface is provided as standard. The volume of the container barrel is pre-calibrated and recorded in the intelligent electronic scale, then the vibrated and smoothed container barrel is placed on the scale platform, the container weight value is automatically calculated, and the data are uploaded to the cloud database.

[0070] A digital air content tester is used, the instrument integrates a high-precision pressure sensor with an accuracy of 0.1% FS and a miniature air pump. After the sealed water injection is completed, the test key is pressed, and the instrument automatically completes the processes of pressurizing to the initial pressure point (usually 0.1 MPa), pressure balancing and data acquisition. The built-in processor automatically calculates the air content value according to the Boyle's law, and uploads it to the cloud database.

[0071] After the cloud database receives all the test data, the built-in quality judgment engine performs real-time judgment according to the preset threshold rules, such as C50 concrete spread ≥550 mm and air content 4.0%-6.0%. If qualified, the pouring instruction is sent to the on-site terminal; if not qualified, it is immediately stopped, and a return processing sheet is automatically generated. All operation logs are stored in association with the sample RFID tag.

[0072] After the pouring is approved, the curing test pieces and the entity curing test pieces are made, and the electronic tags are generated for the test pieces; the test pieces are placed in the corresponding curing conditions for curing to the specified age.

[0073] As shown in Figure 4 , the present application provides a test piece making and curing method;

[0074] Specifically:

[0075] In the process of pouring qualified high-performance concrete, the temperature and humidity data inside the solid structure are continuously monitored to obtain the internal environment data baseline.

[0076] Standard curing test pieces and solid curing test pieces are made from the split samples, and electronic tags are generated for the test pieces, binding the internal environment data baseline and associating with the unique electronic tag of the sample.

[0077] The standard curing test pieces are placed in a standard curing room for curing to the specified age; the solid curing test pieces are placed in a programmable environmental curing box, and the monitored internal environment data baseline is input into the curing box in synchronization, and cured to the specified age.

[0078] It should be noted that in the process of pouring high-performance concrete, the packaged LoRa wireless temperature and humidity sensor node is buried in the core part of the solid structure. The sensor collects data every 15 minutes and uploads it to the cloud database to form the internal environment data baseline of the part.

[0079] At least two groups of standard test pieces are synchronously made under standard conditions, and the production process should be completed quickly to ensure the homology of all test pieces. A unique RFID tag is bound for each test piece, and the following information is associated with the tag and written into the cloud database through a handheld reader: the unique RFID tag of the sample associated with its mother; one group of test pieces is identified as standard curing test pieces; another group of test pieces is identified as solid curing test pieces and associated with the internal environment data baseline.

[0080] The standard curing test pieces are placed in a standard curing room until the specified curing age (such as 28 days). The environmental conditions of the standard curing room are strictly controlled to be temperature 20±2℃ and humidity ≥95%. The solid curing test pieces are placed in a programmable environmental curing box, and the control system of the curing box obtains the associated internal environment data baseline from the cloud database in real time through the API interface. The curing box dynamically adjusts the environment in the box through the built-in high-precision temperature and humidity sensor and PID control algorithm, so that the temperature and humidity change is highly synchronized with the internal environment data baseline, thereby reproducing the real curing conditions of the solid structure until the specified curing age (such as 28 days).

[0081] Hardening performance test: the strength of the standard curing test pieces and the solid curing test pieces is tested simultaneously to obtain the strength data.

[0082] The method of the hardening performance test comprises:

[0083] The test pieces that have reached the specified curing age are taken out from the standard curing room and the programmable environmental curing box, respectively;

[0084] Check the appearance of the test piece, select the flat side as the bearing surface, apply pressure to the test piece until it fails, and automatically record the failure load value;

[0085] According to the recorded failure load value and the bearing area of the test piece, the compressive strength of the test piece is calculated and associated with the electronic tag of the test piece.

[0086] It should be noted that after reaching the specified curing age, the standard curing test piece and the entity curing test piece are taken out and the surface of the test piece is scanned with a 200 million pixel industrial camera. The two flattest and defect-free opposite surfaces are automatically identified and determined as the bearing surfaces by image algorithm. A 3D structured light sensor is used to test the flatness of the test piece, and the thickness of the pad is automatically selected. The press adopts a servo control system, and the loading rate is controlled at 0.5-0.8 MPa; through high-precision force value sensors (accuracy 0.5 level) and linear displacement sensors, real-time acquisition of load and displacement data is realized, and load-displacement curve is obtained. The peak load is identified from the curve, and the compressive strength is automatically calculated according to the bearing area of the test piece; compressive strength = peak load / bearing area, and uploaded to the cloud database and associated with the RFID information of the test piece.

[0087] Data processing and report generation: integrate all process data to automatically generate quality detection data and diagnostic prediction data, and comprehensively evaluate the detection data of high-performance concrete of this batch.

[0088] The method of data processing and report generation comprises:

[0089] Integrate all data from the sampling step to the hardened performance test step to obtain the whole process data;

[0090] According to the strength data of the standard curing test piece, quality detection data is automatically generated; and according to the whole process data, diagnostic analysis is carried out to obtain diagnostic prediction data, which includes: based on the strength comparison between the standard curing test piece and the entity curing test piece, the on-site curing condition is quantitatively evaluated, and potential risks are warned; based on the whole process data, the long-term durability of the high-performance concrete of this batch is predicted;

[0091] Comprehensively evaluate the quality detection data and diagnostic prediction data to obtain the detection data of high-performance concrete.

[0092] The diagnostic analysis includes automatically tracing back the whole process data when the high-performance concrete has quality problems to locate the root cause.

[0093] It should be noted that the whole process data from sampling, fresh performance testing, test piece making and curing to hardened performance testing is integrated through the cloud database.

[0094] According to the unique UHF RFID tag of the batch sample, all the associated compressive strength data of the standard curing specimens are automatically retrieved and extracted from the cloud database. Based on the quality judgment engine, the average value and standard deviation of the compressive strength are calculated, and the compressive strength standard value = compressive strength average value - 1.645 compressive strength standard value is calculated accordingly. The calculated compressive strength standard value is compared with the design strength grade of high-performance concrete. According to the compliance rules built-in the engine, the judgment conclusion of "qualified" or "unqualified" is automatically generated. The ratio of standard deviation to average value is calculated to evaluate the uniformity and stability of the production of the batch of high-performance concrete, and the evaluation level is output according to the preset threshold, such as ratio < 5% is excellent, ratio < 10% is good, and ratio > 10% is poor, to obtain the quality detection data.

[0095] The entity curing strength ratio (%) = (entity curing specimen compressive strength / standard curing specimen compressive strength) x 100% is calculated, and the absolute strength difference (MPa) = standard curing specimen compressive strength - entity curing specimen compressive strength is calculated. Then, all the strength data of the standard curing specimens and all the strength data of the entity curing specimens are subjected to t-test as two independent sample sets, and the p value is automatically calculated; if P value < 0.05, it indicates that the difference between the two groups of strength data is statistically significant, and the field curing condition indeed has a substantial impact on the strength development. Then, the quantitative indicators and the preset engineering threshold and statistical results are combined to automatically evaluate and grade the effectiveness of the field curing effect: when the strength ratio ≥ 95% and the p value ≥ 0.05, it means that the field curing condition is almost as good as the standard curing room, the temperature and humidity control of the entity structure is ideal, and the strength development is sufficient; when 90% ≤ strength ratio ≤ 95%, it means that the field curing condition is not as good as the standard curing room, but the strength loss is within the acceptable range of engineering, and the curing condition is basically qualified; when the strength ratio < 90% and the p value < 0.05, it means that the field curing condition is seriously insufficient, such as early water loss, too low or too high temperature, which leads to significant lag and insufficient strength development of high-performance concrete, and immediately issues a warning of insufficient field curing condition. Based on the whole process data, a durability prediction model (such as random forest) is trained to predict the long-term durability indicators of the batch of high-performance concrete, such as carbonation depth and chloride ion diffusion coefficient, and output the risk level.

[0096] When the quality determination engine has a quality problem, the RFID tag of the standard curing test piece where the problem occurs is automatically used as the root key to load the full-process data related to the batch of high-performance concrete from the cloud database. The quality determination engine sorts and correlates the full-process data along the time axis, automatically scans whether there are abnormal points deviating from the preset threshold in each link. If the strength is insufficient, the load-displacement curve form of the hardening performance test link is first checked to exclude test abnormalities. Then, the curing link is traced back, and the strength difference between the physical curing test piece and the standard curing test piece is compared. If both are significantly low, the problem may be from the previous steps; if only the physical curing test piece is low, the associated internal environment data baseline is automatically focused on to check whether the temperature and humidity meet the standard requirements in the early stage. If there is no abnormality in the curing link, the new-mixing performance test data is continued to trace back to analyze the rheological parameters, air content, etc. to determine whether the workability is poor. If the new-mixing performance data still has no clear abnormalities, the sampling and image analysis data are finally traced back; the historical images of the batch of samples are retrieved and recalculated to check whether the initial aggregate distribution uniformity analysis results have false positive errors, and the root cause of the problem is obtained.

[0097] The quality detection data and diagnostic prediction data are integrated to generate high-performance concrete detection data, which includes basic information, test results and compliance judgment of each link, strength comparison analysis and curing effectiveness evaluation, long-term durability prediction and risk warning, and problem tracing.

[0098] Now we simulate five different working conditions of C60 high-performance concrete batches: Batch 1, good quality, good curing; Batch 2, good quality, but water shortage in field curing; Batch 3, actual strength deficiency (mixing ratio problem); Batch 4, severe surface carbonization; Batch 5, bleeding segregation, low surface strength. Each batch uses the present invention and existing technology for strength detection and curing quality evaluation, and the results are shown in Table 1.

[0099] Table 1 High-performance concrete detection data table of the present invention and existing technology

[0100]

[0101] Existing technology error evaluation: Batch 1, the strength value measured by the rebound method is low, with an error of about -5.7%, misjudged as qualified; Batch 2, due to the loose surface of the concrete caused by water loss, the rebound value is seriously low, with a strength value error of -23.1%, misjudged as unqualified; Batch 3, the strength error is about -9.7%, judged as unqualified, but it cannot be determined whether it is a material itself problem or a curing condition problem; Batch 4, the increase in surface hardness causes the rebound value to be artificially high, with a strength error of about -6.6%, masking the risk of insufficient real strength; Batch 5, due to the poor surface condition of the concrete, the rebound value is extremely distorted, with an error of -21.1%.

[0102] Therefore, the prior art is greatly disturbed by the concrete surface state, carbonization, bleeding and other factors, the measurement value is unreliable, and misjudgment is easily caused. Through the destructive test of the entity curing test piece, the strength data closer to the entity structure can be obtained, and the pros and cons of the field curing condition are quantified through the entity curing strength ratio, so that the strength loss is directly indicated to be caused by improper curing instead of the concrete itself problem (batch 3: 100.5%).

[0103] Although embodiments of the present application have been shown and described, it is to be understood that various modifications, substitutions, replacements and changes can be made to these embodiments without departing from the principles and spirit of the present application, and the scope of the present application is defined by the appended embodiments and their equivalents.

Claims

1. A method for testing high-performance concrete, characterized in that, include: Sampling: During the unloading process, samples are taken in segments and mixed evenly. Sample image information is collected, analyzed and risks are predicted, and a unique electronic tag is generated for each sample to bind relevant information of this batch of high-performance concrete. Fresh Mix Performance Testing: Real-time monitoring of unloading rheological parameters, and automatic testing of slump, spread, bulk density and air content of samples to determine workability and make decisions on pouring; Specimen preparation and curing: After the pouring is approved, prepare specimens for marked curing and solid curing, and generate electronic tags for the specimens; place the specimens under the corresponding curing conditions and cure them to the specified age; Hardening performance test: The strength of both standard cured specimens and solid cured specimens is tested simultaneously to obtain strength data; Data processing and report generation: Integrate data from the entire process, automatically generate quality inspection data and diagnostic prediction data, and comprehensively evaluate to obtain the test data for this batch of high-performance concrete.

2. The method for testing high-performance concrete according to claim 1, characterized in that: The sampling method includes: S1. Collect at least three sub-samples during the pre-, mid-, and post-unloading stages; S2. Pour the collected sample onto a steel plate and stir evenly to obtain a freshly mixed sample; S3. Acquire images of freshly mixed samples, analyze their apparent uniformity, and predict the risk of segregation and bleeding; S4. Reduce the amount of freshly mixed sample that has no risk of segregation or bleeding to the amount required for the test to obtain the reduced sample. S5. Generate a unique electronic tag for each batch of samples and associate it with relevant information about that batch of high-performance concrete.

3. The method for testing high-performance concrete according to claim 1, characterized in that: The method for testing the performance of freshly mixed soil includes: M1. During the unloading process of high-performance concrete, monitor and record the yield stress and plastic viscosity data of high-performance concrete in real time; M2. The reduced sample is loaded into the slump cylinder according to the standard method, tamped and smoothed, and slump and spread tests are carried out. The slump height and spread diameter data in two vertical directions are automatically measured and the average value is calculated. M3. Pack the reduced sample into a known volume bulk density container using standard methods, and compact and smooth it. The bulk density is automatically calculated and recorded. M4. Pack the reduced sample into the container of the gas content measuring device in layers, and shake and smooth it. Automatically read the pressure change value, calculate and record the gas content. M5. Analyze the test data to determine whether the workability of this batch of high-performance concrete is up to standard; if it is up to standard, approve the pouring; if it is not up to standard, stop immediately and return the goods; and associate the test data and judgment results with the unique electronic tag of the sample.

4. The method for testing high-performance concrete according to claim 1, characterized in that: The methods for preparing and curing the specimens include: N1. During the pouring of qualified high-performance concrete, continuously monitor the temperature and humidity changes inside the solid structure to obtain the baseline of the internal environment data. N2. Use the reduced sample to make standard curing specimens and solid curing specimens, generate electronic tags for the specimens, bind the internal environmental data baseline, and associate them with the unique electronic tag of the sample. N3. Place the standard curing specimens in the standard curing room and cure them to the specified age; place the solid curing specimens in the programmable environmental curing chamber and synchronously input the monitored internal environmental data baseline into the curing chamber, and cure them to the specified age.

5. The method for testing high-performance concrete according to claim 1, characterized in that: The method for testing the hardening performance includes: P1. Take out the specimens that have reached the specified curing age from the standard curing room and the programmable environmental curing chamber respectively; P2. Inspect the appearance of the specimen, select a flat side as the bearing surface, apply pressure to the specimen until the specimen fails, and automatically record the failure load value. P3. Based on the recorded failure load value and the bearing area of ​​the specimen, calculate the compressive strength of the specimen and associate it with the electronic tag of the specimen.

6. The method for testing high-performance concrete according to claim 1, characterized in that: The data processing and report generation methods include: Q1. Integrate all data from the sampling step to the hardening performance test step to obtain full-process data; Q2. Based on the strength data of standard cured specimens, automatically generate quality inspection data; and based on the full-process data, perform diagnostic analysis to obtain diagnostic prediction data. The diagnostic prediction data includes: based on the strength comparison between standard cured specimens and solid cured specimens, quantitatively evaluate the on-site curing conditions and warn of potential risks; based on the full-process data, predict the long-term durability of this batch of high-performance concrete. Q3. By comprehensively evaluating the quality testing data and diagnostic prediction data, high-performance concrete testing data is obtained.

7. The method for testing high-performance concrete according to claim 6, characterized in that: The diagnostic analysis includes the ability to automatically trace back the entire process data and pinpoint the root cause of quality problems when high-performance concrete has quality issues.

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