Automatic detection and feedback control system for fluidity of fluidized solidified soil

Abstract

The application discloses a flow state solidified soil flow degree automatic detection and feedback control system and belongs to the technical field of automatic detection and control of civil engineering material production. In view of the problems of low artificial detection efficiency, extensive adjustment mode and difficulty in considering flow degree and hardening shrinkage in the prior art, the system comprises a sampling and homogenizing module, a flow degree detection module, a flow degree calculation module, a main control module in which a flow degree-shrinkage coupling model is stored and a feedback execution module, the system adjusts the admixture content preferentially and ensures that the total water addition amount does not exceed the allowed maximum total water addition amount, the system utilizes an automatic lifting barrel, image acquisition and closed-loop feedback control, and maintains the machine outlet flow degree in the target range on the premise of controlling the hardening shrinkage. The application is mainly used for the automatic production of flow state solidified soil, realizes accurate flow degree detection, intelligent decision and shrinkage collaborative optimization.

Description

Technical Field

[0001] This invention belongs to the field of automated testing and control technology for civil engineering material production, specifically relating to an automatic detection and feedback control system for the fluidity of solidified fluid. Background Technology

[0002] During the preparation of fluidized solidified soil, the flowability upon exiting the mixer must be controlled to ensure its workability. Currently, production sites commonly use manual sampling and slump expansion tests with a flowability cylinder, measuring the expansion diameter with a steel ruler to assess flowability. This method has a long testing cycle, limited sampling frequency, and the test results are easily affected by operator technique and reading deviations. Furthermore, it cannot provide real-time feedback of test data to the mixing control system. When the flowability deviates from the target range, operators typically increase the amount of mixing water to quickly improve it. However, excessive water addition significantly increases the hardening shrinkage rate of the solidified soil, leading to shrinkage cracking in the backfill or solidified layer, affecting project quality and durability. On the other hand, while increasing the dosage of admixtures, such as water-reducing agents, can achieve the desired flowability with a smaller water volume, the admixture dosage has complex interactions with soil, cement, water, and other materials. There is a lack of methods for quickly determining the appropriate dosage on-site, and operators often adjust based on experience, easily resulting in insufficient or excessive adjustments. Furthermore, the raw materials used in solidified soil, especially on-site soil or industrial solid waste, exhibit significant batch-to-batch fluctuations. Different batches of raw materials have varying soil sensitivities, resulting in marked differences in flowability response under the same admixture dosage. This makes it difficult to maintain stable flowability by relying on fixed proportions or empirical adjustments. Simultaneously, the flowability of the slurry decreases over time and under environmental conditions after transportation from the mixer to the construction site. Current technology cannot anticipate this loss during the production stage, often resulting in situations where the slurry meets flowability standards at the factory but fails to self-level on-site. These issues lead to a lack of coordination between flowability control and shrinkage control. During production, the pursuit of flowability requirements may lead to neglecting shrinkage risks, or excessive control of shrinkage may result in substandard flowability; both are difficult to balance. Summary of the Invention

[0003] This invention provides an automatic detection and feedback control system for the fluidity of solidified soil. It can automatically complete slurry sampling, fluidity detection, and fluidity value calculation. Based on the built-in fluidity-shrinkage rate coupling model, under the constraint of the preset maximum allowable shrinkage rate, it prioritizes the adjustment of admixture dosage and coordinates the control of water addition to achieve closed-loop feedback regulation of the outgoing fluidity. At the same time, it pre-compensates for the fluidity attenuation during transportation through a fluidity loss model, thereby ensuring that the outgoing fluidity and the on-site fluidity stably meet the construction requirements while ensuring that the hardening shrinkage rate does not exceed the limit.

[0004] To achieve these objectives and other advantages of the present invention, an automatic detection and feedback control system for the fluidity of solidified fluid is provided, comprising: The sampling homogenization module has its feed end connected to the mixing equipment and its discharge end connected to the flowability cylinder. It is used to extract the slurry and inject it into the flowability cylinder after secondary homogenization and mixing. The flowability detection module includes a detection platform, a flowability cylinder, a lifting mechanism, a vibrator, a timing unit, and a camera device. The lifting mechanism is connected to the flowability cylinder to lift the cylinder filled with slurry, causing the slurry to collapse and expand. The vibrator acts on the detection platform to apply vibration and expel air bubbles. The timing unit is electrically connected to the lifting mechanism and the camera device, and is used to trigger the camera device to acquire an expanded image after a preset stabilization time following the completion of the cylinder lifting action. The flowability calculation module has its input end connected to the camera device and its output end connected to the main control module. It is used to calculate the flowability value based on the image and transmit it to the main control module. The main control module, whose output is communicatively connected to the feedback execution module, stores a fluidity-shrinkage rate coupling model. When generating adjustment commands, it determines the maximum allowable total water addition and the minimum allowable total admixture dosage to meet the shrinkage rate requirement based on the preset maximum allowable shrinkage rate. It prioritizes adjusting the admixture dosage to meet the fluidity requirement while ensuring that the total water addition does not exceed the maximum allowable total water addition and that the total admixture dosage is not lower than the minimum allowable total admixture dosage, so as to control the hardening shrinkage rate within the allowable range. The feedback execution module is connected to the mixing water pipeline and the admixture pipeline. It automatically adjusts the water volume or admixture dosage according to the adjustment command to maintain the flowability of the machine outlet within the target range while controlling the hardening shrinkage rate.

[0005] Preferably, the fluidity-shrinkage coupling model specifically includes: A structured data mapping group is adopted, with the target fluidity and the maximum allowable shrinkage rate as inputs and the maximum allowable total water addition as outputs. The structured data mapping group includes fluidity-shrinkage rate-water addition response surfaces pre-established under different admixture type correction coefficients and different soil sensitivity indices. The main control module automatically updates the model parameters in the following way: when the raw material batch changes, the sampling and homogenizing module injects a fixed volume of the current raw material batch slurry sample into the homogenizing mixing tank, performs a stepped speed mixing test, obtains the dynamic torque at different speeds through the built-in torque sensor, and generates a torque-speed rheological curve; the main control module extracts the low-speed torque value, torque nonlinearity index and torque decay rate as feature parameters from the torque-speed rheological curve, inputs them into the pre-calibrated rheology-shrinkage sensitivity mapping library, calculates the soil sensitivity index and admixture type correction coefficient of the current raw material batch, and writes them into the response surface.

[0006] Preferably, the main control module also stores a flowability loss model over time. This flowability loss model is a set of multi-condition attenuation relationships established in advance through orthogonal experimental design or response surface methodology. It takes slurry temperature, ambient temperature, current admixture dosage, and soil sensitivity index of the current raw material batch calculated based on the stepped speed stirring test as input conditions, and time as the attenuation process variable, and outputs the predicted value of flowability under the corresponding conditions. The main control module obtains the slurry temperature and current ambient temperature of the discharged slurry in real time through the slurry temperature sensor and the ambient temperature sensor, respectively. It obtains the elapsed time of the discharged slurry from the discharge timer of the mixing equipment, and receives the estimated transportation time through the human-machine interface or communication interface. When the main control module receives the production instruction for the next production tank, it invokes the fluidity loss model over time. It takes the slurry temperature of the discharged slurry, the current ambient temperature, the soil sensitivity index of the current raw material batch, and the total duration of the elapsed time and the estimated transportation time as inputs to obtain the predicted fluidity value of the slurry when the next production tank arrives at the site. When the predicted fluidity value is lower than the preset lower limit of allowable fluidity for construction, the main control module calculates the required upward adjustment of the discharge fluidity and determines the corresponding water addition increment based on the mapping relationship between fluidity and water addition. This water addition increment is then added to the current water addition setting as a temporary target water addition, and the module checks whether this temporary target water addition exceeds the maximum allowable total water addition. If it does not exceed the limit, the water addition setting is updated with the temporary target water addition. If it does exceed the limit, the water addition setting is locked to the maximum allowable total water addition, and an admixture dosage adjustment instruction is triggered to compensate for the excess.

[0007] Preferably, the fluidity loss over time model uses a library of loss curves with time as the sequence dimension, which is jointly indexed by the soil sensitivity index range, slurry temperature range, ambient temperature range and admixture dosage gradient. Each curve represents a set of discrete data points where the fluidity value decays over time under specific fixed conditions. When retrieving the curve, the main control module calculates the soil sensitivity index of the current raw material batch based on the stepped speed stirring test, the real-time slurry temperature, ambient temperature, and the range and gradient of the admixture dosage of the current production tank, matches the closest time loss curve from the curve library, and then reads the flowability value corresponding to the sum of the elapsed time and the expected transportation time along the time axis of the curve as the predicted value. The instruction to increase the admixture dosage is generated by the compensation solver built into the main control module. The compensation solver determines the increase amount based on the correspondence between the required compensation amount for fluidity and the admixture ratio and water reduction rate, and sends it to the feedback execution module to adjust the admixture pipeline.

[0008] Preferably, the timing unit and the camera device are configured such that: after the lifting action is completed and a first preset time has elapsed, the camera device continuously acquires extended images at a speed of not less than 5 frames / second; the flowability calculation module uses an edge detection algorithm to extract the slurry edge of each frame image, calculates the displacement rate of the edge points, and determines that the expansion has reached stability when the maximum displacement rate is less than 0.1 mm / s, and selects the image at that moment to calculate the flowability value; if it is still not stable after a second preset time, an alarm is issued and the flowability is calculated using the image at the last moment and marked.

[0009] Preferably, the exciter is a broadband exciter, an accelerometer is fixed to the outer wall of the flow cylinder, and a vibration pickup is fixed to the detection platform; After the flowability detection is started, the main control module controls the wideband exciter to output a sweep frequency excitation, and simultaneously collects the vibration response signal of the slurry in the cylinder detected by the accelerometer and the vibration response signal of the platform detected by the vibration pickup. The slurry resonance frequency is identified by comparing the amplitude ratio peak value and phase difference reversal point of the two signals. The main control module also determines whether aggregate settlement has occurred based on the changing characteristics of the amplitude ratio curve and phase difference curve during the frequency sweep process: when the amplitude ratio shows an abnormal decrease due to non-resonance reasons and the decrease exceeds a preset threshold in a certain continuous frequency range, or when the phase difference shows a non-monotonic jump and the jump amplitude exceeds a preset threshold, the frequency range is determined to be a segregation sensitive frequency band, and the starting frequency of the range is recorded as the lower limit of the segregation sensitive frequency band; if the above phenomenon does not occur during the entire frequency sweep, it is read from the pre-stored default lower limit value; Then, a frequency that is simultaneously lower than the upper limit of the working frequency and the lower limit of the segregation sensitive frequency band is selected as the selected working frequency, and the broadband exciter is driven to vibrate at the selected working frequency. During the vibration, the expansion diameter is calculated based on the expansion image sequence acquired by the camera device. When the incremental rate of the expansion diameter is lower than the preset threshold, the broadband exciter is controlled to gradually reduce the amplitude until the expansion stabilizes and then the vibration stops.

[0010] Preferably, the sampling and homogenization module includes a multi-point sampling system. This subsystem consists of three or more sampling tubes of different radial positions and lengths extending into the mixing equipment, solenoid valves on each pipeline, and a material collection buffer tank. The main control module controls the solenoid valves to open alternately in a cycle, so that the slurry at different positions flows into the material collection buffer tank for mixing in a timed manner. The mixed slurry then enters the homogenization mixing tank. The homogenization mixing tank is equipped with a variable frequency stirring motor and a torque sensor. The main control module adjusts the stirring speed and time according to the torque feedback to ensure that the shear strength of the secondary stirring is consistent with the production stirring state.

[0011] Preferably, the feedback execution module includes a first mass flow meter and a first proportional regulating valve installed on the mixing water pipeline, and a second mass flow meter and a second proportional regulating valve installed on the admixture pipeline. The main control module has a built-in PID controller, whose input is the deviation between the target value of the outlet flow rate and the current detection value, and whose output is the set value of the water flow rate and the admixture flow rate. The feedback signals from the first mass flow meter and the second mass flow meter are used to form a closed-loop control.

[0012] Preferably, the main control module is also equipped with a vibration parameter memory unit, which is used to associate and store the raw material electronic tag, the lower limit of the separation sensitive frequency band, and the corresponding frequency sweep status mark. The main control module is configured to: when the raw material electronic tag appears for the first time or changes, use the pre-stored default lower limit value as the lower limit of the segregation sensitive frequency band, skip the frequency sweep judgment, mark the frequency sweep status of the electronic tag as "to be swept" and write it into the vibration parameter memory unit, and at the same time complete the flow detection and feedback adjustment of the current production tank according to the original process. When the same raw material electronic tag is put into production again, the main control module reads the sweep frequency status flag corresponding to the electronic tag in the vibration parameter memory unit. If it is "to be swept", the sampling and homogenization module is controlled to collect an additional independent sample to perform a sweep frequency determination, obtain the lower limit of the segregation sensitive frequency band corresponding to the electronic tag and store it in the vibration parameter memory unit, and at the same time update the sweep frequency status flag of the electronic tag to "sweeped". If it is "sweeped", the lower limit of the segregation sensitive frequency band stored in the vibration parameter memory unit is directly called, skipping the sweep frequency determination step, and only performing resonance frequency identification to select the working frequency. If an expansion anomaly or a significant drift in the resonant frequency is detected during vibration, the main control module clears the stored parameters associated with the electronic tag in the vibration parameter memory unit, and reverts the frequency sweep status to "pending frequency sweep". Production continues using the default lower limit value, and the frequency sweep determination is re-executed when the same tag is produced again.

[0013] Preferably, it also includes an alarm, a non-volatile storage unit, and a timestamp module; the alarm is electrically connected to the output of the main control module, and the non-volatile storage unit and the timestamp module are communicatively connected to the main control module; the main control module is configured to: start timing after the self-lifting cylinder action is completed and delayed for a first preset time; if no stability determination signal is received from the flowability calculation module when the accumulated timing reaches a second preset time, then output a trigger signal to the alarm, and combine the flowability value calculated by the flowability calculation module based on the image at the last moment, the current time data provided by the timestamp module, and a preset unstable state identifier code into a data record, and write it into the non-volatile storage unit.

[0014] The present invention has at least the following beneficial effects: First, this invention achieves fully automated detection and feedback control of the fluidity of solidified soil, eliminating the need for manual intervention and thus eradicating human error and detection lag. By incorporating a fluidity-shrinkage rate coupling model into the main control module, the system can calculate the maximum allowable total water addition and the minimum allowable total admixture dosage based on the preset maximum allowable shrinkage rate when generating adjustment commands. It employs an intelligent coordination strategy of "prioritizing admixture dosage adjustment and controlling the total water addition to keep it within limits," ensuring that the outflow fluidity meets target requirements while strictly controlling the hardening shrinkage rate within allowable ranges, effectively preventing cracking caused by excessive water addition. The system's feedback execution module is directly connected to the water and admixture pipelines, enabling automatic and precise adjustment of water and admixture dosages based on adjustment commands. This achieves synergistic optimization of fluidity and shrinkage rate control, improving the production quality stability and engineering durability of the solidified soil.

[0015] Secondly, this invention solves the problem of model mismatch caused by raw material batch fluctuations by designing an automatically updatable fluidity-shrinkage rate coupled model. When the raw material batch changes, the system automatically controls the sampling and homogenization module to inject small samples into the homogenizing mixing tank, performs a stepped speed mixing test, and uses a torque sensor to acquire dynamic torque and generate a torque-speed rheological curve. The main control module extracts three characteristic parameters from this curve: low-speed torque value, torque nonlinearity index, and torque decay rate. These parameters are input into a pre-calibrated rheology-shrinkage sensitivity mapping library, automatically calculates the soil sensitivity index and admixture type correction coefficient for the current batch, and writes them into the response surface. This process requires no manual experimental intervention and can quickly complete the online adaptive update of model parameters, greatly improving the system's adaptability and control accuracy to different soil types, different admixture types, and raw material batch fluctuations.

[0016] Third, this invention extends flowability control from the "discharge time" to the "arrival time" by introducing a flowability loss model, achieving full-process flowability management. The system acquires the slurry temperature, ambient temperature, and elapsed time since discharge in real time, and receives the estimated transportation time through a human-machine interface. This data is then fed into the pre-established loss model to predict the flowability upon arrival at the construction site. When the predicted value is lower than the lower limit allowed for construction, the system automatically calculates the required increase in discharge flowability, prioritizing increasing the water addition to improve it. Simultaneously, it checks whether the temporary target water addition exceeds the maximum allowable total water addition. If it does, the water addition is locked at the maximum allowable value, and the excess is compensated by generating an admixture dosage adjustment command. This strategy ensures that even with long transportation times or unfavorable environmental conditions, the arrival flowability still meets construction requirements, while preventing excessive shrinkage due to over-watering.

[0017] Fourth, this invention employs a time-loss curve library based on a joint interval-gradient index to store the fluidity decay patterns under multiple conditions, avoiding the resource consumption of complex real-time calculations. The main control module quickly matches the closest time-loss curve from the curve library based on the interval and gradient of the current slurry temperature, ambient temperature, and admixture dosage. Then, it reads the predicted fluidity value corresponding to the total duration along the time axis. This fast response and high accuracy make it highly suitable for production sites. Simultaneously, the built-in compensation solver can accurately determine the admixture adjustment amount based on the required fluidity compensation and the corresponding relationship between the admixture's increase rate and water reduction rate, and sends this information to the feedback execution module for execution.

[0018] Fifth, this invention achieves automatic monitoring and stability determination of the flowability expansion process by configuring the linkage logic between the timing unit and the camera device. The camera device starts after a first preset time delay following the completion of the lifting action, continuously acquiring expansion images at a rate of no less than 5 frames per second. The flowability calculation module uses an edge detection algorithm to extract the slurry edge of each frame and calculates the displacement rate of the edge points. When the maximum displacement rate is less than 0.1 mm / s, the expansion is determined to have reached stability, and the image at that moment is selected to calculate the flowability value. This dynamic determination method is more objective and accurate than manual visual inspection or single-shot photography, eliminating human error. Simultaneously, if stability is not achieved after a second preset time, the system will issue an alarm and force the calculation of flowability using the image at the last moment, marking it to avoid infinite waiting. It also prompts the operator to check for segregation or other abnormalities in the slurry, improving the robustness and anomaly handling capability of the detection system.

[0019] Sixth, this invention employs a multi-point sampling system with three or more sampling tubes of varying lengths extending radially into the mixing equipment. The main control module controls solenoid valves to open alternately and periodically, allowing slurry from different locations to flow into the collection buffer tank for mixing at different times. This effectively solves the problem of insufficient representativeness in single-point sampling, ensuring that the sampled slurry accurately reflects the overall state of the slurry within the mixing equipment. After the mixed slurry enters the homogenizing tank, the system dynamically adjusts the mixing speed and time via a variable frequency mixing motor based on the torque value fed back by the torque sensor. This ensures that the shear strength of the secondary mixing is consistent with the production mixing state, avoiding the problem of improper secondary mixing altering the internal structure of the slurry and affecting the accuracy of the detection.

[0020] Other advantages, objectives and features of the present invention will become apparent in part from the following description, and in part from those skilled in the art through study and practice of the invention. Attached Figure Description

[0021] Figure 1 This is a flowchart illustrating the automatic detection and feedback control system for the fluidity of solidified soil according to the present invention. Detailed Implementation

[0022] The present invention will now be described in further detail so that those skilled in the art can implement it based on the description.

[0023] It should be understood that terms such as “having,” “comprising,” and “including” as used herein do not exclude the presence or addition of one or more other elements or combinations thereof.

[0024] It should be noted that, unless otherwise specified, the experimental methods described in the following embodiments are conventional methods, and the reagents and materials mentioned are commercially available. In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "setting" should be interpreted broadly. For example, they can refer to fixed connection or setting, detachable connection or setting, or integral connection or setting. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances. The terms "lateral," "longitudinal," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, and are only for the convenience of describing this invention and simplifying the description. They do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of this invention.

[0025] like Figure 1 As shown, this invention provides an automatic detection and feedback control system for the fluidity of solidified fluid, comprising: a sampling homogenization module whose inlet end is connected to a mixing device; when fluidity detection is required, the system extracts a certain amount of fresh slurry from the mixing device. Since the extracted slurry may undergo slight segregation or air bubble entrainment during transportation or temporary storage, the sampling homogenization module is equipped with a secondary homogenization and mixing device to re-mix the extracted slurry, restoring it to a uniform and stable state. After the secondary homogenization and mixing is completed, the outlet end of the sampling homogenization module is connected to a fluidity cylinder, precisely injecting the processed slurry into the fluidity cylinder until it is full.

[0026] The flowability testing module includes a stable testing platform to support the entire testing device. The flowability cylinder, an open-top and bottom cylindrical container, is placed at the center of the testing platform, filled with slurry, and allowed to settle. A lifting mechanism is mechanically connected to the flowability cylinder. Its function is to lift the cylinder smoothly and vertically upwards after the slurry has settled and its internal stress has been relieved, allowing the slurry, originally confined within the cylinder, to collapse and expand outwards under its own gravity. A vibrator is installed on or in contact with the testing platform. Its function is to apply controllable vibration to the testing platform before, during, or after lifting the cylinder. This vibration energy is transferred to the slurry, causing air bubbles to rise and be expelled, thus eliminating interference from air bubbles in the flowability measurement. A timing unit is electrically connected to the lifting mechanism and the camera device. Its operating logic is as follows: the timing unit starts timing the instant the lifting mechanism completes the cylinder lifting action. After a preset settling time, the camera device is triggered. This settling time allows the slurry to complete the main process of rapid collapse under gravity, avoiding image acquisition during periods of vigorous slurry movement. The stabilization time can be set according to the viscosity of the slurry: two to five seconds for slurries with good fluidity, and five to ten seconds for viscous slurries. As a preferred value for reference, three seconds is generally used. After the timing ends, the timing unit sends a trigger signal to the camera device. The camera device is installed directly above the detection platform and immediately begins acquiring a top-down view image of the expanded slurry upon receiving the trigger signal.

[0027] The flowability calculation module is connected to the camera device via a communication line. After the camera device acquires the expanded image, it transmits the image data to the flowability calculation module in real time. The flowability calculation module integrates image processing algorithms to preprocess the received image, including grayscale conversion, noise reduction, and binarization. Then, it uses edge detection algorithms to extract the edge contours of the expanded slurry. Commonly used edge detection operators include the Canny edge detection operator and the Sobel operator. Since the flowability cylinder is circular, the expanded slurry typically forms an approximate circle after collapse. The flowability calculation module calculates the expansion diameter by fitting the edge contours; this diameter value is the flowability value. The calculated flowability value is packaged into a data packet and transmitted to the main control module through the output terminal.

[0028] The main control module is the decision-making core of the entire system, internally storing a pre-established fluidity-shrinkage rate coupling model. This model describes the quantitative relationship between the fluidity of the solidified soil, total water addition, total admixture dosage, and hardening shrinkage rate. When the main control module receives the current fluidity detection value from the fluidity calculation module, it compares this value with a preset target fluidity range. If the current fluidity value deviates from the target range, the main control module initiates an adjustment command generation process. When generating the adjustment command, the main control module first reads the preset maximum allowable shrinkage rate. This preset maximum allowable shrinkage rate is pre-set by the engineering designers based on the project's crack resistance requirements; for example, it can be set to 0.05% for general backfill projects and 0.02% for projects with strict crack resistance requirements. Then, the main control module calls the fluidity-shrinkage rate coupling model, using the current target fluidity (e.g., the desired expansion diameter of 200 mm to 220 mm) and the maximum allowable shrinkage rate as input parameters. The fluidity-shrinkage coupling model outputs two key constraint values ​​after calculation: the maximum allowable total water addition and the minimum allowable total admixture dosage. The maximum allowable total water addition refers to the upper limit of the total mixing water that the system can use in production, provided it does not exceed the maximum allowable shrinkage rate. The minimum allowable total admixture dosage refers to the lower limit of the minimum total amount of admixtures that the system must add, provided it does not exceed the maximum allowable shrinkage rate. When determining specific adjustment strategies, the main control module follows the principle of prioritizing the adjustment of admixture dosage. Specifically, if the current fluidity is low (i.e., the slurry is too thick), the system first considers increasing the admixture dosage to improve fluidity, because admixtures, especially water-reducing agents, can effectively improve fluidity without significantly increasing water consumption, and have a relatively small negative impact on shrinkage. Only when the admixture dosage has reached or exceeded the minimum allowable total admixture dosage, and further increasing the admixture still cannot meet the fluidity requirements, will the system consider increasing the total water addition. Regardless of the adjustment method used, the main control module monitors the current total water addition in real time, ensuring that it never exceeds the maximum allowable total water addition calculated from the model, while simultaneously ensuring that the total admixture dosage is not lower than the minimum allowable total admixture dosage. In this way, the adjustment commands generated by the main control module can meet the fluidity requirements while strictly controlling the hardening shrinkage rate within the allowable range.

[0029] The feedback execution module's execution ends are connected to both the mixing water pipeline and the admixture pipeline. When the main control module generates an adjustment command, it sends this command to the feedback execution module. The feedback execution module contains actuators such as electric regulating valves, metering pumps, or flow control valves. Based on the adjustment command, the feedback execution module automatically adjusts the opening of the water pipeline to change the total flow rate of the mixing water, or adjusts the opening of the admixture pipeline to change the total dosage of the admixture, or both simultaneously. For example, when the adjustment command requires an increase in the admixture dosage, the feedback execution module will appropriately open the regulating valve on the admixture pipeline, increasing the amount of admixture flowing into the mixing equipment per unit time; when the adjustment command requires a limit on the total water addition, the feedback execution module will close the regulating valve on the water pipeline. The entire process requires no manual intervention, achieving automatic, continuous, and precise adjustment. Through this closed-loop control system, the final goal is to maintain the outflow fluidity within the target range while effectively controlling the hardening shrinkage rate.

[0030] Traditional methods rely on manual operation, resulting in long testing cycles, limited sampling frequency, and significant deviations in test results due to differences in operator experience and techniques, making it difficult to detect fluidity fluctuations in a timely manner. This invention automates the entire process from sampling and testing to adjustment, greatly shortening the testing feedback cycle and enabling rapid responses to fluidity changes during production. More importantly, in traditional production, operators often tend to add excessive water to achieve acceptable fluidity. While this may immediately improve fluidity, it leads to a sharp increase in shrinkage after the solidified soil hardens, causing severe shrinkage cracking and compromising the long-term durability of the project. This invention, by incorporating a fluidity-shrinkage coupling model into the main control module and employing an intelligent coordination strategy that prioritizes adjusting the admixture dosage and strictly controls the total water addition, fundamentally avoids sacrificing shrinkage to meet fluidity requirements. This solution allows the system to actively limit the hardening shrinkage within acceptable limits while ensuring acceptable fluidity, effectively suppressing the cracking tendency of the solidified soil. Furthermore, due to the variability of soil types and admixtures, traditional empirical methods are insufficient to determine the optimal dosage. This invention uses a fluidity-shrinkage coupling model to guide the adjustment, making the ratio of admixtures and water more scientific and reasonable, reducing material waste and side effects caused by excessive adjustment.

[0031] In another technical solution, the fluidity-shrinkage rate coupling model of the present invention is specifically implemented in the form of a structured data mapping group. The structured data mapping group refers to a set of data mapping relationships with the target fluidity and the maximum allowable shrinkage rate as inputs and the maximum allowable total water addition as the output. This mapping group includes pre-established fluidity-shrinkage rate-total water addition response surfaces under different admixture type correction coefficients and different soil sensitivity indices. The response surface is a three-dimensional surface, where two dimensions represent fluidity and shrinkage rate, respectively, and the third dimension represents total water addition. Through this response surface, given the target fluidity and the maximum allowable shrinkage rate, the system can retrieve the corresponding maximum allowable total water addition. The admixture type correction coefficient reflects the differences in the influence of different types of admixtures on fluidity and shrinkage rate; for example, the correction coefficients for high-efficiency water-reducing agents and ordinary water-reducing agents are different. The soil sensitivity index reflects the sensitivity of the soil itself to changes in moisture; the higher the sensitivity of the soil, the faster the shrinkage rate increases after water addition. These two parameters are important adjustment factors in the response surface, enabling the fluidity-shrinkage coupling model to adapt to different materials and proportions.

[0032] To obtain the admixture type correction coefficient and soil sensitivity index of the current batch of raw material slurry, the system acquires the low-speed torque value, torque nonlinearity index, and torque decay rate through stepped speed mixing tests. These characteristic parameters are then input into a pre-established mapping model. This mapping model is built based on limited basic experimental data and can be adaptively expanded online using production data to calculate the correction coefficient applicable to the current batch of raw materials, which is then written into the response surface.

[0033] It should be noted that, regarding the establishment of this mapping model, this system does not require coverage of all possible soil types and admixture combinations. Instead, it adopts an engineering-feasible method of limited calibration plus adaptive expansion. First, for the major soil types commonly encountered in engineering practice, such as silty clay, sandy silt, bentonite, red clay, and typical representatives of engineering waste soil, typically no more than five to eight types are included, along with two to three commonly used admixtures, such as ordinary water-reducing agents, high-efficiency water-reducing agents, and retarding water-reducing agents. Rheological and shrinkage rate tests are conducted through orthogonal experiments, with a total of several dozen to 100 test groups. This workload is within the capabilities of professional R&D institutions. A preliminary mapping model is established based on the experimental data and fixed in the main control module. Second, the system has online adaptive capabilities: when encountering an uncovered material type, the system accumulates the rheological parameters and production measurement data for that batch. Once the data volume is sufficient, it automatically expands or corrects the mapping model. In this way, the mapping model can be gradually improved with use, without the need for unrealistic universal calibration beforehand.

[0034] The main control module of this invention has the ability to automatically update model parameters, specifically achieved through the following method: When the system detects a change in the raw material batch, such as a change in the soil source or the use of a new batch of industrial solid waste, the main control module will actively control the sampling and homogenizing module to inject a fixed volume of the current batch of slurry sample into the homogenizing mixing tank. This fixed volume can be set to 1 liter, 2 liters, or 5 liters, etc., determined according to actual needs; generally, 2 liters is recommended as the standard sample volume. Subsequently, the main control module instructs the homogenizing mixing tank to perform a stepped speed mixing test, that is, to gradually increase the mixing speed according to a pre-set speed sequence, for example, starting from 100 revolutions per minute, increasing by 50 revolutions every 30 seconds, until reaching 300 revolutions per minute. During the mixing process, the built-in torque sensor acquires the dynamic torque value at different speeds in real time, thereby generating a curve of torque versus speed, i.e., a torque-speed rheological curve. The main control module extracts three key characteristic parameters from the curve: the low-speed torque value, which refers to the torque measured at the lowest rotational speed, reflects the static yield stress of the slurry; the torque nonlinearity index, which refers to the degree of nonlinearity of torque as rotational speed increases, reflects the shear thinning or thickening characteristics of the slurry; and the torque decay rate, which refers to the ratio of torque decay at high rotational speed to torque decay at low rotational speed, reflects the thixotropy of the slurry. These three parameters are input into a pre-calibrated rheology-shrinkage sensitivity mapping library. This mapping library is trained using a large amount of experimental data from different soil types and admixtures, and can back-calculate the soil sensitivity index and admixture type correction coefficient for the current batch based on the rheological parameters. After the calculation is completed, the main control module writes these two new parameters into the corresponding positions on the response surface, thereby enabling the fluidity-shrinkage coupling model to automatically adapt to the material properties of the new batch.

[0035] Through the aforementioned structure, the various technical features work together to achieve online adaptive updates of the model. The sampling and homogenization module provides standardized test samples, the homogenizing tank and torque sensor provide rheological data acquisition methods, and the mapping library and response surface in the main control module constitute the data mapping and update mechanism. The entire process requires no manual intervention. When the raw material batch changes, the system can automatically complete sample testing and model parameter updates during normal production intervals. For example, during the production of a batch of slurry, the system automatically initiates an update process at regular intervals or whenever a change in the raw material silo is detected, which takes approximately 3 to 5 minutes to complete. The updated response surface is immediately used to generate subsequent adjustment commands, ensuring that control decisions are always based on the true characteristics of the current batch of raw materials.

[0036] Compared to existing technologies that rely on fixed models or periodic manual calibration, this invention achieves online adaptive updating of the fluidity-shrinkage rate coupled model parameters. When soil quality or admixture batches fluctuate, traditional systems often suffer from fluidity control deviations or shrinkage rate exceedances due to model mismatch. This invention, however, can quickly capture changes in the rheological properties of raw materials and automatically adjust the response surface parameters. By extracting three physically meaningful characteristic parameters—low-speed torque value, torque nonlinearity exponent, and torque decay rate—and using a pre-calibrated mapping library for calculation, the system can accurately obtain the soil sensitivity index and admixture type correction coefficient without relying on complex chemical analysis. This ensures the fluidity-shrinkage rate coupled model maintains good predictive accuracy, improves the control system's adaptability to different raw material batches, and reduces product quality instability caused by raw material fluctuations.

[0037] In another technical solution, the main control module of this invention also additionally stores a fluidity loss model over time. This fluidity loss model is a set of multi-condition attenuation relationships pre-established through orthogonal experimental design or response surface methodology. Orthogonal experimental design is an efficient multi-factor experimental method that reduces the number of experiments by selecting representative test points; response surface methodology can establish continuous functional relationships. The fluidity loss model uses slurry temperature, ambient temperature, current admixture dosage, and the soil sensitivity index of the current raw material batch calculated in real time based on the aforementioned stepped speed stirring test as input conditions, and time as the attenuation process variable, outputting the predicted value of fluidity under the corresponding conditions. Specifically, in the stage of establishing the fluidity loss model over time, the fluidity decay curve over time is measured for different raw material batches based on soil sensitivity index ranges (e.g., low, medium, and high sensitivity), different slurry temperatures (e.g., 10°C, 20°C, and 30°C), different ambient temperatures (e.g., 5°C, 15°C, and 25°C), and different admixture dosages (e.g., 0.5 kg, 1.0 kg, and 1.5 kg per cubic meter). These data are then fitted or interpolated to form the model. In practice, the system substitutes the measured slurry temperature, ambient temperature, admixture dosage, and the soil sensitivity index of the current raw material batch to obtain the predicted function for fluidity changes over time.

[0038] It should be noted that establishing the fluidity loss over time model does not require full-factor combination experiments. This invention employs a method combining semi-empirical mathematical models with fitting of finite experimental data to construct the model. First, based on the hydration dynamics and rheology theory of fluidized solidified soil, a basic form of the fluidity decay function over time is established. For example, the predicted fluidity value equals the initial fluidity multiplied by a decay coefficient, which is an exponential or power-law function of time, slurry temperature, ambient temperature, and admixture dosage. This function includes several undetermined parameters, such as the temperature influence factor and the admixture water-reducing efficiency decay constant. Then, through methods such as central composite design or orthogonal design, representative combinations of slurry temperature, ambient temperature, and admixture dosage are selected for experiments. The total number of experimental groups is usually controlled between 30 and 50 groups, and the fluidity values ​​at different time points under each group condition are measured. Finally, using a multivariate nonlinear regression method, the experimental data are fitted to a pre-defined function form to determine the specific values ​​of each undetermined parameter, thereby obtaining a continuous and extrapolable time-loss model. This fluidity loss model can quickly calculate the corresponding fluidity prediction value based on any input slurry temperature, ambient temperature, admixture dosage, and time. Moreover, the preliminary experimental workload is moderate, making it entirely feasible in engineering.

[0039] The main control module acquires the real-time temperatures of the slurry from the previous production batch and the current ambient temperature using slurry temperature sensors and ambient temperature sensors, respectively. The slurry temperature sensors, which can be installed at the discharge port of the mixing equipment or in the sampling homogenization module, are thermocouples or resistance temperature detectors (RTDs) with an accuracy requirement within ±0.5 degrees Celsius. The ambient temperature sensors are installed in the mixing plant control room or in a shaded outdoor location to avoid direct sunlight. Simultaneously, the mixing equipment's discharge timer records the elapsed time since the slurry from the previous production batch was discharged. This timer resets and starts counting each time discharge begins. The main control module also receives the estimated transport time via a human-machine interface or communication interface. This time is manually entered by the operator based on the transport distance and traffic conditions, or automatically issued by the production management system, for example, an estimated 30 minutes, 60 minutes, or 90 minutes.

[0040] When generating the production instruction for the next production tank, the main control module invokes the fluidity loss over time model. It takes the slurry temperature from the previous production tank, the current ambient temperature, the current admixture dosage, and the total elapsed time plus the estimated transportation time as input to obtain a predicted fluidity value for the slurry arriving at the construction site. If this predicted value is lower than the preset allowable lower limit for flowability at the construction site, the main control module determines that an upward adjustment of the outflow fluidity is needed. It first calculates the required upward adjustment amount, which is the difference between the allowable lower limit and the predicted value, plus a safety margin, for example, 5 to 10 millimeters. Then, based on a pre-established mapping relationship between fluidity and water addition (usually a linear or near-linear relationship obtained through experiments), it determines the corresponding water addition increment. This water addition increment is then added to the current water addition setpoint as a temporary target water addition amount, where the current water addition setpoint is the baseline mix water addition amount. Next, the main control module verifies whether the temporary target water addition exceeds the maximum allowable total water addition, which is calculated by the fluidity-shrinkage rate coupling model based on the preset maximum allowable shrinkage rate. If it does not exceed the limit, the temporary target water addition is directly updated to the new water addition setting value; if it does exceed the limit, it means that simply adding water will exceed the shrinkage rate limit. In this case, the water addition setting value is locked to the maximum allowable total water addition, and an admixture dosage adjustment command is triggered to compensate for the remaining fluidity deficiency using the admixture. The compensated production parameters will be used for the next production tank cycle, thereby achieving feedforward pre-compensation for transportation attenuation.

[0041] The various technical features work together to achieve pre-compensation for fluidity transport losses. The slurry temperature sensor, ambient temperature sensor, discharge timer, and human-machine interface provide the input parameters required for the fluidity loss over time model. The loss over time model in the main control module is responsible for prediction, while the water addition and admixture adjustment mechanisms perform compensation. For example, assuming the outflow fluidity of the slurry from the previous production batch was 200 mm and its elapsed time was 30 minutes, and the estimated transport time for the next production batch is 60 minutes, the total duration is 90 minutes. The predicted on-site fluidity is only 180 mm, while the lower allowable limit for construction is 190 mm. Therefore, the system calculates an upward adjustment of 10 mm. According to the mapping relationship, every additional 1 liter of water increases the fluidity by 5 mm, requiring an additional 2 liters of water. If the current baseline water addition is 180 liters per cubic meter, and the maximum allowable total water addition is 182 liters per cubic meter, then the temporary target water addition of 182 liters per cubic meter does not exceed the maximum allowable total water addition and is executed directly. If the maximum permissible total water addition is only 181 liters per cubic meter, then the water addition setting will be locked at 181 liters per cubic meter, and the insufficient fluidity will be compensated by increasing the amount of admixture. The entire decision-making process is completed before the start of the next production tank, and adjustments are immediately implemented to ensure that the slurry leaving the factory meets the construction requirements even after long-term transportation.

[0042] Compared to traditional techniques that only control the flowability at the discharge point, this invention introduces a mechanism for predicting and compensating for flowability degradation during transportation. Traditional methods often result in materials passing factory inspections but failing to self-level upon arrival at the construction site, necessitating secondary processing or even material scrapping. This solution, by real-time monitoring of the temperature of the slurry discharged from the previous batch and the ambient temperature, combined with the estimated transportation time, can accurately predict the flowability of the slurry from the next batch and make adjustments in advance. More importantly, the adjustment process also considers shrinkage constraints, prioritizing the use of water addition increments and only employing admixtures for compensation when water addition may exceed limits. This ensures on-site construction performance without sacrificing hardening shrinkage. This improves the overall quality controllability of the fluidized solidified soil from the mixing plant to the construction site and reduces quality risks caused by fluctuations in transportation time.

[0043] In another technical solution, the fluidity loss over time model of the present invention employs a data structure that facilitates rapid querying, namely, a library of time-loss curves with time as the sequence dimension, using slurry temperature range, ambient temperature range, and admixture dosage gradient as joint indexes. The time-loss curve library is a multi-dimensional table or database. First, the slurry temperature is divided into several ranges, for example, every 5 degrees Celsius: 0 to 5 degrees Celsius, 5 to 10 degrees Celsius, 10 to 15 degrees Celsius, and so on up to above 40 degrees Celsius. Similarly, the ambient temperature is also divided into similar or identical ranges. The admixture dosage is divided according to gradients, for example, every 0.2 kg per cubic meter is a gradient: 0 to 0.2, 0.2 to 0.4, up to above 2.0. Each combined index corresponds to a time-loss curve, which is a discrete set of data points with time as the horizontal axis and fluidity value as the vertical axis, recording the measured value of fluidity decaying over time under specific fixed conditions. For example, under the combination of slurry temperature of 15 to 20 degrees Celsius, ambient temperature of 10 to 15 degrees Celsius, and admixture dosage of 0.8 to 1.0 kg per cubic meter, the curve includes flowability values ​​corresponding to time points of 0 minutes, 10 minutes, 30 minutes, 60 minutes, 90 minutes, and 120 minutes. These data points can be interpolated to obtain predicted values ​​at intermediate times. It should be noted that establishing such a comprehensive curve library requires a large number of preliminary experiments. As an alternative, a semi-empirical mathematical model can be used in conjunction with a limited number of experimental data points for parameter fitting to reduce the workload of experiments.

[0044] The main control module's workflow when retrieving curves is as follows: First, based on the real-time slurry temperature collected for the current production tank, it determines the temperature range it belongs to. For example, if the slurry temperature for this production tank is 18 degrees Celsius, it falls into the 15-20 degree Celsius range. Similarly, if the ambient temperature is 12 degrees Celsius, it falls into the 10-15 degree Celsius range; and if the admixture dosage for the current production tank is 0.9 kg / m³, it falls into the 0.8-1.0 gradient. Then, it matches the time loss curve that best matches these three conditions from the curve library. If a perfectly matching curve exists, it is used directly; otherwise, a near-nearest neighbor or interpolation method can be used to synthesize an approximate curve from adjacent curves. Next, it reads the predicted flowability value corresponding to the total duration along the time axis of the curve. The total duration is the sum of the elapsed time of the previous production tank and the estimated transport time of the next production tank. For example, if the estimated transport time is 60 minutes, the flowability value corresponding to 60 minutes is found on the curve as the predicted value. When compensation is required, the compensation solver built into the main control module generates an admixture dosage increase command. This compensation solver internally stores the correspondence between the required fluidity compensation and the admixture's specific water reduction rate. The specific water reduction rate refers to the increase in water reduction rate or fluidity resulting from each additional unit of admixture dosage. For example, it is known that under current conditions, an increase of 0.1 grams per kilogram in admixture dosage can increase fluidity by approximately 5 millimeters. The compensation solver calculates the required admixture dosage increase by dividing the required fluidity difference by the specific water reduction rate, then generates an increase command and sends it to the feedback execution module. The latter adjusts the valves or pumps in the admixture pipeline to achieve a precise increase in the admixture dosage.

[0045] This curve library structure based on interval-gradient joint indexing, combined with the compensation solver, achieves efficient and accurate prediction and compensation. The curve library discretizes the continuous multidimensional input space into a finite number of intervals and gradients, significantly reducing the amount of data that needs to be stored and queried. Furthermore, each curve is stored at discrete time points, requiring only a simple time axis index for querying, eliminating the need for complex nonlinear regression calculations, resulting in extremely fast response times suitable for real-time control requirements in industrial settings. The compensation solver utilizes a linear approximation of the admixture's water reduction ratio, making the calculation of compensation amounts simple and reliable. Combined, the main control module can complete the prediction and compensation calculation within milliseconds of receiving the production command for the next production tank and immediately drive the actuators.

[0046] Compared to methods that use complex mathematical models to calculate flowability decay online, the discrete curve library approach of this invention reduces computational resource consumption and response latency, making it more suitable for the real-time operating environment of embedded industrial controllers. Furthermore, since the curve library is based on actual experimental data, its prediction accuracy is unaffected by model assumption biases, resulting in higher reliability. The compensation solver is specifically optimized for the admixture adjustment stage, making the calculation of admixture adjustment intuitive and accurate, avoiding waste and fluctuations caused by repeated trial and error. Overall, this approach makes pre-compensation for flowability loss over time fast, stable, and easy to implement, effectively improving the system's practicality in actual production.

[0047] In another technical solution, the present invention finely configures the collaborative operation of the timing unit and the camera device. Specifically, the camera device does not begin acquiring images immediately after the lifting action, but rather after a first preset time delay. The purpose of the first preset time is to allow the slurry to complete a rapid initial collapse, avoiding the capture of blurry images during vigorous movement. This time can be set according to the typical flow characteristics of the slurry; for example, for ordinary fluidized solidified soil, it can be 1 to 3 seconds, and as a preferred reference, 2 seconds is recommended. After the delay, the camera device continuously acquires extended images at a rate of no less than 5 frames per second, that is, at least one photo is taken every 0.2 seconds. Such a high frame rate can completely record the entire process of the slurry from rapid expansion to slow creep until it stops completely.

[0048] The flowability calculation module performs edge detection processing on each acquired image frame sequentially. It employs edge detection algorithms, such as the Canny or Sobel algorithms, to extract the edge contour of the slurry in each frame. Since the slurry expands to approximately a circle, edge detection yields a closed contour line. The flowability calculation module further selects multiple feature points from the contour line, calculates the displacement of these feature points between adjacent frames, and divides this displacement by the inter-frame time interval to obtain the displacement rate of each edge point. The maximum displacement rate among all edge points is taken as an indicator of the expansion activity. When this maximum displacement rate is less than 0.1 mm / s, it indicates that the slurry has almost stopped flowing, and the expansion has reached a stable state. At this point, the flowability calculation module determines that the expansion is stable and selects the image corresponding to that moment to calculate the final flowability value, for example, by fitting a circle to calculate the diameter. If, during continuous acquisition, the maximum displacement rate is not detected to be below the threshold after a second preset time has elapsed since the first camera trigger, it indicates that the slurry may not be able to stabilize normally due to segregation, excessive bleeding, or other abnormal reasons. The second preset time can be set from 30 to 90 seconds, depending on the viscosity of the slurry; 60 seconds is generally recommended. If the timeout is exceeded, the system immediately issues an alarm signal, notifying the on-site operator to check the slurry status. Simultaneously, it forces the calculation of the flowability value using the image acquired at the last moment and specially marks the test result, for example, by adding an "unstable" flag to the data record, for differentiation and handling during subsequent quality analysis.

[0049] In the above configuration, the timing unit provides delayed triggering and timeout timing functions, the camera device provides high temporal resolution image sequences, and the flowability calculation module achieves automatic identification of stable states through edge detection and rate judgment. These three components work together to automate the stability assessment of flowability detection. For example, after the lifting action is completed, the timing unit waits for 2 seconds, then starts the camera device to continuously capture images at a rate of 5 frames per second. The calculation module processes each frame and finds that the maximum displacement rate rapidly decreases from 5 mm / s in the first 5 seconds, then drops to 0.5 mm / s after the 5th second, and further to 0.08 mm / s at the 12th second, which is less than the threshold of 0.1 mm / s. Therefore, it is determined to be stable, and the flowability is calculated using the image from the 12th second. The entire process requires no manual visual inspection, and the judgment criteria are objective and consistent. If the slurry is abnormal and remains unstable for more than 60 seconds, the system alarms and forcibly records the data, preventing the detection process from being suspended indefinitely.

[0050] Compared to manually judging the moment of expansion cessation by visual observation or using single-timed photography, the technical solution of this invention significantly improves the repeatability and objectivity of flowability detection. Manual judgment is easily influenced by personal experience and subjective factors, and different operators may arrive at different results; single-timed photography cannot guarantee that the shooting time is exactly at a stable moment. This solution, through continuous frame rate acquisition and displacement rate threshold determination, can accurately capture the true stable state, eliminating human error and timing deviations. Simultaneously, timeout alarms and forced recording mechanisms ensure system robustness under abnormal conditions, preventing detection failure or data loss due to slurry abnormalities. This provides more reliable and traceable flowability data for subsequent feedback control and quality management.

[0051] In another technical solution, the vibrator in this invention is a wideband vibrator, that is, a vibrator capable of outputting continuously varying vibration signals from low to high frequencies, for example, a frequency range from 10 Hz to 200 Hz. An accelerometer is fixed to the outer wall of the flowability cylinder to detect the response acceleration of the slurry inside the cylinder under vibration; simultaneously, a vibration pickup is fixed to the detection platform to detect the platform's own vibration response. After the flowability detection is initiated, the main control module controls the wideband vibrator to output a frequency sweep excitation, that is, to gradually scan the vibration frequency from the lower limit to the upper limit, for example, linearly increasing from 20 Hz to 150 Hz, with a sweep time of 10 to 30 seconds. During the frequency sweep, the main control module synchronously acquires the vibration response signals from the accelerometer and the vibration pickup. By comparing the amplitude ratio of the accelerometer signal and the vibration pickup signal, the vibration amplification factor of the slurry relative to the platform at different frequencies can be obtained. Simultaneously, by comparing the phase difference between the two, it can be determined whether the slurry vibration lags behind the platform. Typically, when the excitation frequency approaches the natural frequency of the slurry, the amplitude ratio will show a peak, while the phase difference will jump sharply from near 0 degrees to near -180 degrees. This phase reversal point can serve as an identification marker for the resonant frequency. The main control module uses these characteristics to automatically identify the resonant frequency of the slurry.

[0052] The main control module is also responsible for determining the segregation-sensitive frequency band. During frequency sweeping, if the aggregate in the slurry settles within a certain frequency range, it will cause changes in the internal structure of the slurry, thus affecting the vibration transmission characteristics. Specifically, this manifests as follows: within a certain continuous frequency range, the amplitude ratio curve shows an abnormal decrease due to non-resonance reasons, and this decrease exceeds a preset threshold, for example, a decrease exceeding 20%; or the phase difference curve shows a non-monotonic jump, that is, the phase difference does not follow a smooth change but jumps suddenly, and the jump amplitude exceeds a preset threshold, for example, a jump exceeding 30 degrees. When any of the above phenomena are detected, the main control module determines that the frequency range is a segregation-sensitive frequency band and records the starting frequency of the range as the lower limit of the segregation-sensitive frequency band. If no abnormal phenomena occur during the entire frequency sweep, it indicates that the slurry stability of the current production batch is good and vibration-induced segregation is unlikely to occur. At this time, the system reads a safe value from the pre-stored default lower limit value, for example, the default lower limit value can be set to 30 Hz or 50 Hz, and this default value is based on experience or typical material tests. After determining the segregation-sensitive frequency band, the main control module then selects the actual operating frequency. This requires establishing an upper limit for the operating frequency, determined by two factors: the rated frequency range of the wideband exciter and the mechanical resonance frequency of the testing platform and the fixed structure. Specifically, the main control module pre-stores the exciter's rated maximum safe frequency and identifies the structural resonance initiation frequency through a rapid frequency sweep or pre-test modal analysis. 80% of this resonance frequency is taken as the structural safety upper limit. The lower of the exciter's rated frequency and the structural safety upper limit is then taken as the upper limit of the operating frequency. For example, assuming the exciter's rated maximum frequency is 180 Hz and the structural resonance initiation frequency is 150 Hz, the structural safety upper limit is 120 Hz, and the upper limit of the operating frequency is 120 Hz. After selecting the upper limit, the main control module selects a frequency that is simultaneously lower than this upper limit and lower than the lower limit of the segregation-sensitive frequency band as the selected operating frequency, thus avoiding high-frequency regions that easily induce segregation while ensuring that harmful resonances are not excited in the equipment. For example, if the lower limit of the separation sensitive frequency band is 70 Hz and the upper limit of the operating frequency is 120 Hz, then the selected operating frequency can be 60 Hz or 65 Hz, as long as it is lower than 70 Hz.

[0053] After selecting the operating frequency, the main control module drives the wideband vibrator to vibrate continuously at that frequency. During vibration, the camera continuously acquires images of the expansion, and the flowability calculation module calculates the expansion diameter based on the image sequence, and further calculates the rate of increase of the expansion diameter, i.e., the increase in diameter per unit time. When the rate of increase of the expansion diameter is lower than a preset threshold, for example, lower than 0.5 mm per second, it indicates that the slurry expansion is nearing its end, and it is no longer necessary to maintain the original vibration amplitude. Therefore, the main control module controls the wideband vibrator to gradually reduce the amplitude, for example, by 10% each time, while continuing to monitor the rate of increase, until the expansion is completely stable and then the vibration stops. This graded amplitude reduction method avoids the residual stress effects caused by abruptly stopping vibration. Through the above process, frequency sweep identification of resonant frequency, determination of segregation-sensitive frequency band, selection of operating frequency, and graded amplitude reduction together constitute an intelligent vibration control scheme that ensures the effectiveness of vibration while preventing vibration-induced segregation.

[0054] Compared to conventional vibration methods that use a fixed frequency or simply sweep the frequency, this invention can adaptively select the optimal vibration frequency based on the actual characteristics of the slurry. It not only finds the resonant frequency to improve air venting efficiency but also actively identifies and avoids dangerous frequency bands that may cause aggregate settling, thus effectively eliminating air bubbles without disrupting the slurry's homogeneity. By monitoring the rate of diameter expansion and gradually reducing the amplitude, excessive vibration is avoided from interfering with the already nearly stable slurry. These measures significantly improve the scientific rigor and safety of the vibration process in flowability testing, reducing deviations in test results caused by improper vibration, especially for fluidized solidified soils containing coarse aggregates or prone to segregation.

[0055] In another technical solution, the sampling and homogenization module of the present invention includes a multi-point sampling system. This subsystem consists of three or more sampling tubes extending into the mixing equipment at different radial positions, each tube having a different length. For example, for a cylindrical mixing equipment, three sampling tubes can be arranged along the diameter of the equipment sidewall: the first is shorter, extending close to the inner wall of the equipment; the second is of medium length, extending to half the radius; and the third is longer, extending near the center of the equipment. Each sampling tube is equipped with a solenoid valve to control its opening and closing. The rear ends of all sampling tubes are connected to a collection buffer tank. The main control module controls the solenoid valves to open alternately according to a preset control logic. For example, a sampling cycle of 10 seconds can be set, with the first tube open for 3 seconds, the second tube open for 3 seconds, and the third tube open for 3 seconds, with a 1-second interval in between. Through this alternating opening method, slurry from different radial positions flows into the collection buffer tank at different times and mixes naturally in the buffer tank, forming a mixed sample that integrates slurry from different areas within the mixing equipment. This design is more representative of the actual state of the entire mixing batch than single-point sampling. However, it should be noted that this method mainly addresses radial non-uniformity and has limitations for axial stratification or circumferential non-uniformity, which can be improved by combining it with mixing process optimization.

[0056] After being discharged from the aggregate buffer tank, the mixed slurry enters the homogenizing tank. The homogenizing tank is equipped with a variable frequency stirring motor and a torque sensor. The variable frequency stirring motor can change its speed and direction of rotation as needed, while the torque sensor measures the torque output by the motor in real time during the stirring process. To quantify and match shear strength, this invention first installs a calibration torque sensor on the main shaft of the production stirring equipment. Under normal production conditions, it operates at a fixed stirring speed and time, recording the torque-speed curve during the production stirring process, which is stored as a standard template in the main control module. This standard template reflects the stirring shear work required for the slurry to reach a homogeneous state under the current proportions and processes. When secondary homogenizing stirring is performed, the main control module controls the variable frequency stirring motor to operate according to the same speed sequence as the production stirring, and compares the torque value fed back by the current torque sensor with the torque value at the corresponding speed in the standard template in real time. If the measured torque value is significantly higher than the template value, it indicates insufficient shear strength during secondary mixing, resulting in high slurry viscosity or incomplete structural disruption. In this case, the main control module will appropriately extend the mixing time or slightly increase the rotation speed. Conversely, if the measured torque value is significantly lower than the template value, it indicates excessive shear strength, potentially damaging the slurry's flocculation structure. In this case, the mixing time or rotation speed will be reduced accordingly. This feedback adjustment based on torque-speed curve fitting ensures that the cumulative shear work of secondary mixing matches the production mixing state, thereby guaranteeing that the microstructure of the slurry after secondary homogenization is identical to that of the production slurry and ensuring the accuracy of subsequent flowability test results.

[0057] The multi-point sampling and homogenization processes work in close coordination. The multi-point sampling system ensures spatial representativeness of the samples, avoiding sampling errors caused by inhomogeneities within the mixing equipment. The homogenization tank uses torque feedback to match shear strength, ensuring that the secondary treatment's impact on the slurry structure is consistent with the production process. For example, when producing a batch of slurry, the main control module periodically activates three sampling tubes, with each cycle lasting 10 seconds, collecting a sufficient volume of mixed sample over three cycles. This sample is then discharged into the homogenization tank, and the variable frequency motor is started to agitate at the same speed and torque as the production mixing. The torque is monitored in real time by a torque sensor. Once the torque reaches the target range and remains stable for 30 seconds, the secondary homogenization is considered complete. The treated slurry is then injected into a flowability testing cylinder to ensure that the test results accurately reflect the actual flowability of the produced slurry.

[0058] Compared to traditional single-point sampling methods, the multi-point alternating sampling of this invention improves sample representativeness and reduces detection deviations caused by localized inhomogeneities. Simultaneously, by controlling the shear intensity of the secondary stirring through torque feedback, the state of the slurry after secondary processing is highly consistent with the production state, avoiding additional errors introduced by improper secondary stirring. These two improvements collectively enhance the accuracy and reliability of flowability detection, enabling the detection values ​​to truly reflect the overall performance of the slurry within the stirring equipment. This provides a more credible basis for feedback control, thereby contributing to improved quality stability of the final product.

[0059] In another technical solution, the feedback execution module of the present invention includes a first mass flow meter and a first proportional regulating valve installed on the mixing water pipeline, and a second mass flow meter and a second proportional regulating valve installed on the admixture pipeline. The main control module has a built-in strategy decision unit and a PID controller, which work together to achieve hierarchical control from macro-control strategy to specific flow regulation. The strategy decision unit is a software functional module in the main control module responsible for high-level decision-making. When the main control module receives the current flowability detection value from the flowability calculation module, the strategy decision unit first calculates the deviation between the current flowability and the target flowability, then calls the flowability-shrinkage rate coupling model and the flowability time loss model, and makes a decision based on the principle of prioritizing the adjustment of the admixture dosage while ensuring that the total water addition does not exceed the maximum allowable total water addition. Specifically, the strategy decision unit first determines whether, under the current operating conditions, increasing or decreasing the admixture dosage is sufficient to bring the flowability back to the target range without causing the shrinkage rate to exceed the limit; if so, it generates a target value for the admixture dosage, while keeping the target value for the water addition at the current allowable value. The strategy decision unit only considers adjusting the water dosage when the admixture's adjustment capacity is insufficient or deemed infeasible by the model. In this case, it calculates the required water increment based on the fluidity deviation and verifies whether this increment exceeds the maximum allowable water increment calculated by the fluidity-shrinkage coupling model. If it does not exceed this limit, a target water dosage value is generated; if it does, the target water dosage value is locked at the maximum allowable total water dosage, and an upward adjustment target value for the admixture dosage is generated based on the remaining insufficient fluidity compensation. Through this decision-making process, the strategy decision unit outputs not the original fluidity deviation signal, but two independent target values ​​with physical meaning and satisfying the shrinkage constraint: the admixture dosage target value and the water dosage target value.

[0060] The main control module's built-in PID controller is actually divided into two independent control loops: an admixture flow PID loop and a water addition flow PID loop. The setpoint for the admixture flow PID loop is derived from the admixture dosage target value output by the strategy decision unit. This value is converted by the main control module into the instantaneous flow setpoint of the admixture pipeline based on the production cycle. The feedback signal of the loop is provided in real-time by a second mass flow meter installed on-site. The PID controller continuously adjusts the opening of the second proportional control valve based on the deviation between the setpoint and the feedback value until the actual admixture flow accurately tracks the setpoint. The setpoint for the water addition flow PID loop is derived from the water addition target value output by the strategy decision unit, which is also converted into the instantaneous flow setpoint of the water addition pipeline. The feedback signal is provided by the first mass flow meter. The PID controller adjusts the opening of the first proportional control valve accordingly to achieve precise closed-loop control of the water addition. The two PID loops operate independently and in parallel without interference. When the target value of either loop is updated, the corresponding PID controller automatically starts a new tracking process. Through the aforementioned hierarchical control architecture, the main control module automatically transforms the macroscopic materials science strategy of prioritizing the adjustment of admixtures and limiting the amount of water added into precise flow regulation of both admixtures and mixing water. This ensures that the outflow flowability remains stable within the target range while meeting shrinkage constraints. In actual production, operators only need to set the target flowability range and the maximum allowable shrinkage rate through the human-machine interface, and the system can automatically complete the aforementioned decision-making and execution process.

[0061] Compared to manual adjustment or simple open-loop adjustment, the hierarchical closed-loop feedback control system of this invention significantly improves the response speed and accuracy of flowability adjustment. Traditional manual adjustment often suffers from severe lag and is prone to overshoot or undershoot, resulting in large fluctuations in flowability. In this solution, the strategy decision unit of the main control module first calculates the target values ​​for admixture dosage and water addition that satisfy the shrinkage rate constraint based on the flowability deviation, combined with the flowability-shrinkage rate coupling model and the strategy of prioritizing admixture adjustment. Subsequently, two independent PID loops quickly and accurately track the above target values ​​based on the precise feedback from the mass flow meter, thereby stabilizing the outflow flowability within a small tolerance range. This not only improves the product qualification rate but also reduces material waste and waiting time caused by repeated debugging, thus improving production efficiency.

[0062] In another technical solution, the main control module of the present invention is further configured with a vibration parameter memory unit. This vibration parameter memory unit can be a non-volatile memory, such as flash memory or EEPROM, characterized by data retention after power failure. Before each segregation sensitive frequency band determination, the main control module first controls the sampling homogenization module to collect an additional slurry sample independent of the flowability test sample. This independent sample is dedicated to frequency sweep excitation. The main control module only performs frequency sweep determination on this independent sample to obtain the lower limit of the segregation sensitive frequency band, thereby protecting the flowability test sample from the destructive effects of full-band frequency sweep during the expansion process and ensuring the authenticity of the flowability test results for this production tank. After completing the segregation sensitive frequency band determination, the main control module associates the raw material electronic tag used in the current raw material batch with the measured lower limit of the segregation sensitive frequency band and stores them together in the vibration parameter memory unit. The raw material electronic tag can be an RFID tag, barcode, or batch number entered by the operator; it uniquely identifies a group of raw materials, such as the same batch of soil transported from a certain material yard on a certain day. The lower limit of the segregation-sensitive frequency band is a value obtained through frequency sweep determination, representing the lower limit of frequencies that should be avoided under the current raw material ratio. It is important to emphasize that the reuse mechanism of the vibration parameter memory unit is strictly bound to the consistency of the raw material electronic tags. When the main control module detects that the raw material electronic tag for the current batch is inconsistent with the historical storage record, it indicates that the soil source or ratio has changed. At this time, the lower limit of the segregation-sensitive frequency band for the old raw material batch is no longer of reference value. The main control module automatically clears all stored parameters associated with the old tag and forcibly triggers a complete frequency sweep determination process to re-acquire the lower limit of the segregation-sensitive frequency band for the new raw material batch slurry. Only when the electronic tags are completely matched will the system allow the recall of historical stored parameters to shorten the detection cycle. Through this mechanism of "same tag reuse, different tag rescan," it is ensured that the vibration parameters always match the actual segregation sensitivity of the current raw material batch slurry, preventing vibration-induced segregation due to parameter misuse even under production conditions with frequent soil fluctuations.

[0063] When the same raw material electronic tag is used in production again, for example, if the same batch of soil is used again after 3 days, the main control module will first look up the historical record corresponding to the electronic tag in the vibration parameter memory unit. If the stored lower limit of the segregation sensitive frequency band is found, the main control module directly calls that value, skipping the time-consuming frequency sweep determination step. However, the resonant frequency still needs to be identified, because the resonant frequency may vary slightly due to changes in slurry temperature, moisture content, etc. Therefore, the main control module still performs the resonant frequency identification process, that is, controls the vibrator to perform a rapid frequency sweep, only identifying the amplitude ratio peak and phase difference reversal point, without performing a full scan of the segregation sensitive frequency band. Then, combining the stored lower limit of the segregation sensitive frequency band and the currently identified resonant frequency, the operating frequency is selected. It should be noted that this scheme assumes that the segregation sensitivity characteristics of the slurry remain stable under the same raw material electronic tag. If the raw material storage conditions or moisture content change significantly, it may cause the sensitive frequency band to drift. In this case, it can be corrected by periodic sampling or triggering a re-sweep when the test results are abnormal.

[0064] In this way, the single detection cycle can be significantly shortened, for example, from the original 30-second frequency sweep to 5-second rapid resonance identification. At the same time, since a wide-range frequency sweep across the entire frequency band is avoided, the exciter's losses are also reduced accordingly.

[0065] The vibration parameter memory unit works in conjunction with the main control module's storage and retrieval logic to reuse empirical parameters. For example, for a fixed-formulation fluidized solidified soil, a complete frequency sweep determination was performed during the initial production run, determining the lower limit of the segregation-sensitive frequency band to be 65 Hz, and this value was associated with the raw material batch number "soil-20231101" and stored. Subsequently, when soil from the same raw material batch is used again, the system directly retrieves 65 Hz, finding the resonant frequency (e.g., 80 Hz) in just 5 seconds, and then selects a working frequency below 65 Hz, such as 60 Hz. The entire process saves approximately 25 seconds compared to the initial detection. If the raw material batch changes, the system will execute the complete process again and update the storage.

[0066] Compared to schemes that perform a complete frequency sweep judgment for each test, the memory reuse mechanism of the vibration parameter memory unit in this invention shortens the time for repeated tests and improves production efficiency. For scenarios involving continuous production of the same formula, the accumulated time savings are considerable. Simultaneously, by reducing the number of large-scale frequency sweeps of the exciter, the equipment's lifespan is effectively extended, reducing maintenance costs. This memory method based on raw material electronic tags can automatically identify and reuse parameters without manual intervention, representing an intelligent optimization approach, particularly suitable for production environments where raw materials are relatively stable but require frequent testing.

[0067] In another technical solution, the system of the present invention further includes an alarm, a non-volatile storage unit, and a timestamp module. The alarm is electrically connected to the output of the main control module and can be an audible and visual alarm, such as a buzzer combined with a red flashing light. The non-volatile storage unit and the timestamp module are communicatively connected to the main control module. The non-volatile storage unit is used to store data for a long time and will not lose it even if power is lost; the timestamp module can provide accurate current date and time and can be a real-time clock chip or obtained from a time server via a network. The main control module is configured with dedicated exception handling logic: after a first preset time delay following the completion of the self-lifting cylinder's action, timing begins; if a stability determination signal from the flowability calculation module is still not received after a second preset time, the detection is determined to have timed out and not stabilized.

[0068] Upon timeout, the main control module immediately sends a trigger signal to the alarm, which then issues an audible and visual alarm to alert on-site operators to potential anomalies in the slurry. Simultaneously, the main control module requests the flowability value calculated from the last frame of the image from the flowability calculation module. The flowability calculation module processes the last frame of the image according to its normal procedure and calculates the flowability value, which, although potentially inaccurate, serves as a reference. The main control module also reads the current time data from the timestamp module and generates a preset unstable state identifier code, such as the number "999" or the letter "UNSTABLE". The main control module combines these three pieces of information into a single data record: flowability value, time data, and unstable state identifier code. This record is then written to non-volatile storage. This record is permanently stored and can be consulted for subsequent quality traceability, data analysis, or production improvement.

[0069] The coordination of the above components enables a complete process of anomaly detection, alarm, and data recording. For example, in one detection, the flowability calculation module failed to detect a displacement rate below the threshold for 60 seconds after the drum was lifted. This was likely due to severe slurry segregation, with aggregate settling and surface water rising to the surface, causing the segregation to continue. Upon the timeout, the alarm sounded and a red light flashed, prompting operators to investigate. Simultaneously, the system automatically recorded this anomaly: time 10:32:15 AM on May 20, 2026, flowability measurement value 245 mm, and identification code "unstable." In future analysis, this record can be retrieved, combined with the production log to find the amount of admixtures and water used at that time, to determine if the proportions were incorrect, thereby optimizing the formula.

[0070] All the hardware components of this invention can be implemented using existing equipment. Specifically, the solenoid valves, stirring motors, and torque sensors in the sampling homogenization module; the electric cylinders, vibrators, accelerometers, and industrial cameras in the flowability detection module; and the programmable controllers or industrial computers, mass flow meters, and proportional control valves on which the main control module depends are all commercially available components commonly used in the field of industrial automation. Those skilled in the art can directly select, purchase, and assemble them according to actual needs. The inventiveness of this invention does not lie in the novelty or special customization of these hardware components themselves, but in the collaborative working method between the modules, the signal interaction process, the control strategy based on multi-model fusion, and the automatic detection and feedback adjustment logic designed for the specific material of fluidized solidified soil. Therefore, any system built according to the functional module connection relationship and control process defined in this invention falls within the protection scope of this invention, and is not limited by specific hardware models.

[0071] The number of devices and processing scale described herein are for the purpose of simplifying the description of the invention. Applications, modifications, and variations of the invention will be readily apparent to those skilled in the art.

[0072] Although the embodiments of the present invention have been disclosed above, they are not limited to the applications listed in the specification and embodiments. They can be applied to various fields suitable for the present invention. For those skilled in the art, other modifications can be easily made. Therefore, without departing from the general concept defined by the claims and their equivalents, the present invention is not limited to the specific details.

Claims

1. An automatic detection and feedback control system for the fluidity of solidified fluid, characterized in that, include: The sampling homogenization module has its feed end connected to the mixing equipment and its discharge end connected to the flowability cylinder. It is used to extract the slurry and inject it into the flowability cylinder after secondary homogenization and mixing. The flowability detection module includes a detection platform, a flowability cylinder, a lifting mechanism, a vibrator, a timing unit, and a camera device. The lifting mechanism is connected to the flowability cylinder to lift the cylinder filled with slurry, causing the slurry to collapse and expand. The vibrator acts on the detection platform to apply vibration and expel air bubbles. The timing unit is electrically connected to the lifting mechanism and the camera device, and is used to trigger the camera device to acquire an expanded image after a preset stabilization time following the completion of the cylinder lifting action. The flowability calculation module has its input end connected to the camera device and its output end connected to the main control module. It is used to calculate the flowability value based on the image and transmit it to the main control module. The main control module has its output terminal connected to the feedback execution module. The main control module stores a fluidity-shrinkage rate coupling model. When generating adjustment instructions, it determines the maximum allowable total water addition and the minimum allowable total admixture dosage to meet the shrinkage rate requirement based on the preset maximum allowable shrinkage rate. The dosage of admixtures is adjusted first to meet the fluidity requirements, while ensuring that the total water addition does not exceed the maximum allowable total water addition and the total admixture dosage is not lower than the minimum allowable total admixture dosage, so as to control the hardening shrinkage rate within the allowable range. The feedback execution module is connected to the mixing water pipeline and the admixture pipeline. It automatically adjusts the water volume or admixture dosage according to the adjustment command to maintain the flowability of the machine outlet within the target range while controlling the hardening shrinkage rate.

2. The automatic detection and feedback control system for the fluidity of solidified soil as described in claim 1, characterized in that, The fluidity-shrinkage coupling model specifically includes: A structured data mapping group is adopted, with the target fluidity and the maximum allowable shrinkage rate as inputs and the maximum allowable total water addition as outputs. The structured data mapping group includes fluidity-shrinkage rate-water addition response surfaces pre-established under different admixture type correction coefficients and different soil sensitivity indices. The main control module automatically updates the model parameters in the following way: when the raw material batch changes, the sampling and homogenizing module injects a fixed volume of the current raw material batch slurry sample into the homogenizing mixing tank, performs a stepped speed mixing test, obtains the dynamic torque at different speeds through the built-in torque sensor, and generates a torque-speed rheological curve; the main control module extracts the low-speed torque value, torque nonlinearity index and torque decay rate as feature parameters from the torque-speed rheological curve, inputs them into the pre-calibrated rheology-shrinkage sensitivity mapping library, calculates the soil sensitivity index and admixture type correction coefficient of the current raw material batch, and writes them into the response surface.

3. The automatic detection and feedback control system for the fluidity of solidified soil as described in claim 2, characterized in that, The main control module also stores a fluidity loss model over time. This fluidity loss model is a set of multi-condition attenuation relationships established in advance through orthogonal experimental design or response surface methodology. It takes slurry temperature, ambient temperature, current admixture dosage, and soil sensitivity index of the current raw material batch calculated based on the stepped speed stirring test as input conditions, and time as the attenuation process variable, and outputs the predicted value of fluidity under the corresponding conditions. The main control module obtains the slurry temperature and current ambient temperature of the discharged slurry in real time through the slurry temperature sensor and the ambient temperature sensor, respectively. It obtains the elapsed time of the discharged slurry from the discharge timer of the mixing equipment, and receives the estimated transportation time through the human-machine interface or communication interface. When the main control module receives the production instruction for the next production tank, it calls the fluidity loss model over time. It takes the slurry temperature of the discharged slurry, the current ambient temperature, the soil sensitivity index of the current raw material batch, and the total duration of the elapsed time and the estimated transportation time as inputs to obtain the predicted fluidity value of the slurry when the next production tank arrives at the site. When the predicted fluidity value is lower than the preset lower limit of allowable fluidity for construction, the main control module calculates the required upward adjustment of the discharge fluidity and determines the corresponding water addition increment based on the mapping relationship between fluidity and water addition. This water addition increment is then added to the current water addition setting as a temporary target water addition, and the module verifies whether this temporary target water addition exceeds the maximum allowable total water addition. If the limit is not exceeded, the water addition setting will be updated to the temporary target water addition value. If the amount exceeds the limit, the water addition setting will be locked to the maximum allowable total water addition, and an instruction to increase the admixture dosage will be triggered to compensate for the excess.

4. The automatic detection and feedback control system for the fluidity of solidified soil as described in claim 3, characterized in that, The fluidity loss over time model uses a library of time loss curves with soil sensitivity index range, slurry temperature range, ambient temperature range and admixture dosage gradient as joint indexes and time as the sequence dimension. Each curve represents a set of discrete data points where the fluidity value decays over time under specific fixed conditions. When retrieving the curve, the main control module calculates the soil sensitivity index of the current raw material batch based on the stepped speed stirring test, the real-time slurry temperature, ambient temperature, and the range and gradient of the admixture dosage of the current production tank, matches the closest time loss curve from the curve library, and then reads the flowability value corresponding to the sum of the elapsed time and the expected transportation time along the time axis of the curve as the predicted value. The instruction to increase the admixture dosage is generated by the compensation solver built into the main control module. The compensation solver determines the increase amount based on the correspondence between the required compensation amount for fluidity and the admixture ratio and water reduction rate, and sends it to the feedback execution module to adjust the admixture pipeline.

5. The automatic detection and feedback control system for the fluidity of solidified soil as described in claim 1, characterized in that, The timing unit and the camera device are configured such that: after the lifting action is completed and a first preset time has elapsed, the camera device continuously acquires extended images at a speed of not less than 5 frames / second; the flowability calculation module uses an edge detection algorithm to extract the slurry edge of each frame image, calculates the displacement rate of the edge point, and determines that the expansion has reached stability when the maximum displacement rate is less than 0.1mm / s, and selects the image at that moment to calculate the flowability value; if it has not stabilized after a second preset time, an alarm is issued and the flowability is calculated using the image at the last moment and marked.

6. The automatic detection and feedback control system for the fluidity of solidified soil as described in claim 1, characterized in that, The exciter is a wideband exciter, an accelerometer is fixed to the outer wall of the flow cylinder, and a vibration pickup is fixed to the detection platform; After the flowability detection is started, the main control module controls the wideband exciter to output a sweep frequency excitation, and simultaneously collects the vibration response signal of the slurry in the cylinder detected by the accelerometer and the vibration response signal of the platform detected by the vibration pickup. The slurry resonance frequency is identified by comparing the amplitude ratio peak value and phase difference reversal point of the two signals. The main control module also determines whether aggregate settlement has occurred based on the changing characteristics of the amplitude ratio curve and phase difference curve during the frequency sweep process: when the amplitude ratio shows an abnormal decrease due to non-resonance reasons and the decrease exceeds a preset threshold in a certain continuous frequency range, or when the phase difference shows a non-monotonic jump and the jump amplitude exceeds a preset threshold, the frequency range is determined to be a segregation sensitive frequency band, and the starting frequency of the range is recorded as the lower limit of the segregation sensitive frequency band; if the above phenomenon does not occur during the entire frequency sweep, it is read from the pre-stored default lower limit value; Then, a frequency that is simultaneously lower than the upper limit of the working frequency and the lower limit of the segregation sensitive frequency band is selected as the selected working frequency, and the broadband exciter is driven to vibrate at the selected working frequency. During the vibration, the expansion diameter is calculated based on the expansion image sequence acquired by the camera device. When the incremental rate of the expansion diameter is lower than the preset threshold, the broadband exciter is controlled to gradually reduce the amplitude until the expansion stabilizes and then the vibration stops.

7. The automatic detection and feedback control system for the fluidity of solidified soil as described in claim 1, characterized in that, The sampling and homogenization module includes a multi-point sampling system. The subsystem consists of three or more sampling tubes of different radial positions and lengths extending into the mixing equipment, solenoid valves on each pipeline, and a material collection buffer tank. The main control module controls the solenoid valves to open alternately in a cycle, so that the slurry at different positions flows into the material collection buffer tank for mixing in a timed manner. The mixed slurry then enters the homogenization mixing tank. The homogenization mixing tank is equipped with a variable frequency stirring motor and a torque sensor. The main control module adjusts the stirring speed and time according to the torque feedback to ensure that the shear strength of the secondary stirring is consistent with the production stirring state.

8. The automatic detection and feedback control system for the fluidity of solidified soil as described in claim 1, characterized in that, The feedback execution module includes a first mass flow meter and a first proportional regulating valve installed on the mixing water pipeline, and a second mass flow meter and a second proportional regulating valve installed on the admixture pipeline. The main control module has a built-in PID controller, whose input is the deviation between the target value of the outlet flow rate and the current detection value, and whose output is the set value of the water flow rate and the admixture flow rate. It also uses the feedback signals from the first mass flow meter and the second mass flow meter to form a closed-loop control.

9. The automatic detection and feedback control system for the fluidity of solidified soil as described in claim 6, characterized in that, The main control module is also equipped with a vibration parameter memory unit, which is used to associate and store the raw material electronic tag, the lower limit of the separation sensitive frequency band and the corresponding frequency sweep status mark. The main control module is configured to: when the raw material electronic tag appears for the first time or changes, use the pre-stored default lower limit value as the lower limit of the segregation sensitive frequency band, skip the frequency sweep judgment, mark the frequency sweep status of the electronic tag as "to be swept" and write it into the vibration parameter memory unit, and at the same time complete the flowability detection and feedback adjustment of the current production tank according to the original process. When the same raw material electronic tag is put into production again, the main control module reads the sweep frequency status flag corresponding to the electronic tag from the vibration parameter memory unit. If it is "to be swept", the sampling and homogenization module is controlled to collect an additional independent sample to perform a sweep frequency determination, obtain the lower limit of the segregation sensitive frequency band corresponding to the electronic tag and store it in the vibration parameter memory unit, and at the same time update the sweep frequency status flag of the electronic tag to "sweeped". If it is "sweeped", the lower limit of the segregation sensitive frequency band stored in the vibration parameter memory unit is directly called, skipping the sweep frequency determination step, and only performing resonance frequency identification to select the working frequency. If an expansion anomaly or a significant drift in the resonant frequency is detected during vibration, the main control module clears the stored parameters associated with the electronic tag in the vibration parameter memory unit, and reverts the frequency sweep status to "pending frequency sweep". Production continues using the default lower limit value, and the frequency sweep determination is re-executed when the same tag is produced again.

10. The automatic detection and feedback control system for the fluidity of solidified soil as described in claim 5, characterized in that, It also includes an alarm, a non-volatile storage unit, and a timestamp module; the alarm is electrically connected to the output of the main control module, and the non-volatile storage unit and the timestamp module are communicatively connected to the main control module; the main control module is configured to: start timing after the self-lifting cylinder action is completed and delayed by the first preset time; if the accumulated timing reaches the second preset time and no stability determination signal is received from the flowability calculation module, then output a trigger signal to the alarm, and combine the flowability value calculated by the flowability calculation module based on the image at the last moment, the current time data provided by the timestamp module, and a preset unstable state identifier code into a data record, and write it into the non-volatile storage unit.

Images