A smart casting device for precast concrete inspection wells and its processing method

Abstract

The application discloses a prefabricated concrete inspection well intelligent pouring device and a processing method thereof, and belongs to the technical field of prefabricated concrete member intelligent manufacturing. The prefabricated concrete inspection well intelligent pouring device comprises a well mold assembly, a collaborative vibration and support part, a pouring execution mechanism and a main controller. The well mold assembly is used for surrounding a concrete pouring cavity and comprises an inner mold and an outer mold which are sleeved with each other. A distributed temperature measurement array is arranged on the inner wall of the inner mold. An ultrasonic receiving and transmitting matrix is arranged between the inner mold and the outer mold. A partitioned temperature control unit is arranged on the outer wall of the outer mold. The collaborative vibration and support part is used for bearing the well mold assembly and applying vibration and comprises a bearing support platform used for placing the well mold assembly. A weighing sensor is arranged on the bearing support platform. A partitioned vibrator group is further fixed on the outer wall of the outer mold of the well mold assembly. The application provides real-time volume and quality data of poured concrete for the main controller.

Description

Technical Field

[0001] This invention relates to the field of intelligent manufacturing of precast concrete components, specifically to an intelligent casting device and processing method for precast concrete inspection wells. Background Technology

[0002] In the production of precast concrete manholes, traditional pouring processes mainly rely on workers' on-site experience. This method has significant limitations, namely, it cannot perceive and monitor the physical state of the concrete inside the mold in real time, such as density and curing temperature. Due to the lack of effective process monitoring and data feedback, the entire pouring process becomes an open and uncontrollable process, resulting in poor quality uniformity of the finished manholes.

[0003] The aforementioned situation and shortcomings mainly stem from the limitations of sensing methods and control technologies. Traditional processes cannot obtain key process parameters inside the casting cavity, and when defects such as air bubbles and voids appear inside the concrete, managers cannot detect them in time and take targeted measures. In addition, the global and indiscriminate vibration method cannot accurately apply vibration energy to the areas that are truly needed, and the heat of hydration during the curing process cannot be effectively managed. These factors together lead to potential quality hazards in the final product, affecting production efficiency and the pass rate of finished products.

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

[0005] The purpose of this invention is to provide an intelligent pouring device and processing method for precast concrete inspection wells, so as to solve the problems mentioned in the background art.

[0006] The technical solution of the present invention includes a well mold assembly, a coordinated vibration and support unit, a pouring execution mechanism, and a main controller;

[0007] The well mold assembly is used to form a concrete pouring cavity. It includes an inner mold and an outer mold that are nested together. The inner wall of the inner mold is provided with a distributed temperature measurement array. An ultrasonic transceiver matrix is ​​provided between the inner mold and the outer mold. The outer wall of the outer mold is provided with a zoned temperature control unit.

[0008] The coordinated vibration and support unit is used to support the well mold assembly and apply vibration. It includes a load-bearing support platform for placing the well mold assembly, a weighing sensor is provided on the load-bearing support platform, and a zoned vibrator group is fixed on the outer wall of the outer mold of the well mold assembly.

[0009] The pouring actuator is used to transport and inject concrete. It spans across the well formwork assembly in a gantry structure. The pouring actuator is equipped with a liftable pouring hose and a pumping metering unit for measuring the concrete flow rate.

[0010] The main controller is electrically connected to the distributed temperature measurement array, the ultrasonic transceiver matrix, the zoned temperature control unit, the weighing sensor, the zoned vibrator group, and the pouring actuator.

[0011] Preferably, the pouring execution mechanism includes a gantry-type moving frame, a lifting pouring hose, and a pumping metering unit. The gantry-type moving frame includes a horizontal moving mechanism driven by a servo motor. The lifting pouring hose is suspended on the horizontal moving mechanism and its lifting and lowering are controlled by a winch. The outlet of the pumping metering unit is connected to the lifting pouring hose.

[0012] Preferably, the ultrasonic transceiver matrix includes a first transducer group disposed on the inner wall of the outer mold and a second transducer group disposed on the outer wall of the inner mold. The transducers in the first transducer group and the transducers in the second transducer group are arranged opposite to each other along the radial direction of the mold, together forming a grid-like detection area covering the casting cavity.

[0013] Preferably, the coordinated vibration and the partitioned vibrator group on the support part includes multiple variable frequency vibration motors grouped together along the annular and height directions of the outer mold; the weighing sensor on the load-bearing support platform is a resistance strain gauge pressure sensor, used to measure the total weight of the well mold assembly and the internal concrete in real time.

[0014] A smart casting and processing method for precast concrete inspection wells includes the following steps:

[0015] In the step of establishing a filling model, the main controller collects the concrete flow rate provided by the pumping metering unit and the total weight provided by the weighing sensor, and defines the concrete flow rate and total weight data as a pouring process data list. The main controller establishes a filling state model to characterize the filling state of the concrete in the cavity based on the pouring process data list.

[0016] In the compactness diagnosis step, the main controller drives the ultrasonic transceiver matrix to acquire ultrasonic signals of the poured area according to the filling state model and defines them as a compactness characterization dataset. Based on the analysis results of the compactness characterization dataset, defective areas with substandard compactness are identified.

[0017] In the adaptive control step, the main controller drives the zoned vibrator group corresponding to the defect area to vibrate, and after the vibration is completed, it drives the distributed temperature measurement array to collect temperature data to define the curing process temperature dataset. Then, based on the curing process temperature dataset, it drives the corresponding zoned temperature control unit to guide the curing process uniformly.

[0018] Preferably, a sensor self-calibration step is included before performing the compactness diagnosis step;

[0019] The sensor self-calibration step is used to define the moment when the main controller determines that the pouring of a certain area has been completed as the diagnostic start time node after the main controller determines that the pouring has been completed. The main controller first collects static ultrasonic attenuation data once at the diagnostic start time node, and then instructs the corresponding zoned vibrator group of the area to apply a preset vibration pulse, and collects dynamic ultrasonic attenuation data once during the vibration. The main controller determines the validity of the data of the corresponding probe in the ultrasonic transceiver matrix by comparing the static and dynamic ultrasonic attenuation data, and uses the valid data or the data estimated by interpolation based on the valid data for subsequent defect area identification.

[0020] Preferably, in the step of establishing the filling model, the main controller also collects the current horizontal position information of the pouring nozzle provided by the gantry-type moving frame of the pouring execution mechanism, and the height information provided by the lifting pouring hose; the main controller combines the pouring process data list with the position and height information of the pouring nozzle to calculate the theoretical filling height and distribution state of the concrete in the mold cavity in real time in the digital model, so as to establish the filling state model.

[0021] Preferably, in the adaptive control step, the main controller identifies temperature anomaly areas where the curing process is uneven by calculating the spatial temperature gradient between different measuring points in the curing process temperature data set and the temporal temperature gradient of a single measuring point over time; the main controller instructs the zoned temperature control unit corresponding to the temperature anomaly area to start micro-cooling or micro-heating functions until the spatial temperature gradient and the temporal temperature gradient are restored to the preset process range.

[0022] This invention provides an improved intelligent casting device and its processing method for precast concrete inspection wells, which has the following improvements and advantages compared with the prior art:

[0023] 1. By integrating a distributed temperature measurement array and an ultrasonic transceiver matrix into the well mold assembly, the device can acquire real-time information on the curing temperature and cross-sectional density of the concrete inside the casting cavity. The ultrasonic transceiver matrix, through transducer groups positioned opposite each other on the inner and outer walls of the outer mold, forms a grid-like detection area covering the casting cavity. This allows for cross-sectional scanning to identify the specific spatial locations of defects such as air bubbles and voids, providing precise target guidance for targeted defect removal. The casting execution mechanism adopts a gantry structure, and its combination of a horizontal moving mechanism and a lifting casting hose enables the casting outlet to move along a preset trajectory in three-dimensional space. This design allows the concrete to be gently and layered in designated locations, rather than being poured from a single high point, effectively reducing the separation of concrete aggregate and mortar, laying the foundation for a uniform and dense concrete structure. Simultaneously, the pumping metering unit and the weighing sensors on the load-bearing support platform work together to provide the main controller with real-time volume and mass data of the poured concrete.

[0024] 2. The zoned vibrator group for the coordinated compaction and support consists of multiple variable frequency vibration motors grouped along the outer mold ring and height direction. The main controller can independently drive the corresponding vibration motor in the defect area identified by the ultrasonic transceiver matrix to perform supplementary compaction. This targeted micro-intervention precisely applies vibration energy to the required area, avoiding indiscriminate global vibration of the entire mold, thereby efficiently eliminating local defects. The zoned temperature control unit on the outer wall of the mold assembly can actively intervene in the curing process based on the internal temperature data collected by the distributed temperature measurement array. By calculating the spatial temperature gradient between different measuring points and the temporal temperature gradient of a single measuring point over time, the main controller can identify temperature anomaly areas with uneven curing process and drive the corresponding temperature control unit for micro-cooling or micro-heating, thereby ensuring uniform curing of concrete, reducing internal stress caused by uneven temperature, and helping to prevent the formation of cracks later.

[0025] 3. By collecting the flow rate of the pumping metering unit, the total weight of the weighing sensor, and the three-dimensional spatial coordinates of the pouring nozzle, a precise filling state model is established to characterize the concrete filling state within the cavity. This model not only includes the macroscopic total filling volume but also calculates the theoretical filling height and distribution of concrete within the mold in real time. This allows the main controller to accurately judge the pouring process and provides a basis for timely initiation of subsequent compaction diagnosis. Before performing compaction diagnosis, this method innovatively sets up a sensor self-calibration step. By comparing the static and dynamic ultrasonic attenuation data before and after applying a preset vibration pulse, the main controller can determine the validity of the ultrasonic probe data. This aims to avoid signal distortion caused by the adhesion of solidified slurry to the probe surface, ensuring the accuracy of the diagnostic results and serving as a prerequisite for subsequent precise control.

[0026] 4. A complete closed-loop process of diagnosis-control-re-diagnosis was constructed. After identifying defective areas where the density did not meet the standard, the main controller drove the corresponding vibrator group to vibrate and simultaneously used an ultrasonic transceiver matrix to continuously monitor the area until the density reached the preset qualified standard before stopping the vibration. This adaptive control based on real-time data feedback ensured that the pouring quality of each local area met the process requirements. Attached Figure Description

[0027] The present invention will be further explained below with reference to the accompanying drawings and embodiments:

[0028] Figure 1 This is a schematic diagram of the overall structure of the device;

[0029] Figure 2 This is a schematic diagram of the pouring actuator;

[0030] Figure 3 This is a structural schematic diagram of the coordinated vibration and support components;

[0031] Figure 4 This is a structural schematic diagram of the well mold assembly;

[0032] Figure 5 This is a schematic diagram of the method flow of the present invention;

[0033] In the diagram: 100, well mold assembly; 110, inner mold; 120, outer mold; 130, distributed temperature measurement array; 140, ultrasonic transceiver matrix; 150, zoned temperature control unit; 200, pouring execution mechanism; 210, gantry-type moving frame; 220, lifting pouring hose; 230, pumping metering unit; 300, coordinated vibration and support unit; 310, load-bearing support platform; 320, zoned vibrator group; 400, main controller. Detailed Implementation

[0034] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to specific embodiments.

[0035] Example 1

[0036] Please see Figure 1-4 The present invention provides an intelligent pouring device for precast concrete inspection wells, comprising: well formwork assembly 100, co-vibration and support part 300, pouring execution mechanism 200 and main controller 400.

[0037] The well mold assembly 100 is used to form a concrete pouring cavity. It includes an inner mold 110 and an outer mold 120 nested together. A distributed temperature measurement array 130 is provided on the inner wall of the inner mold 110. An ultrasonic transceiver matrix 140 is provided between the inner mold 110 and the outer mold 120. A zoned temperature control unit 150 is provided on the outer wall of the outer mold 120.

[0038] The co-vibration and support unit 300 is used to support the well mold assembly 100 and apply vibration. It includes a load-bearing support platform 310 for placing the well mold assembly 100. The load-bearing support platform 310 is equipped with a weighing sensor. A partitioned vibrator group 320 is also fixed on the outer wall of the outer mold 120 of the well mold assembly 100.

[0039] The pouring actuator 200 is used to transport and inject concrete. It spans the well formwork assembly 100 in a gantry structure. The pouring actuator 200 is equipped with a liftable pouring hose and a pumping metering unit 230 for measuring the concrete flow rate.

[0040] The main controller 400 is electrically connected to the distributed temperature measurement array 130, the ultrasonic transceiver matrix 140, the zoned temperature control unit 150, the weighing sensor, the zoned vibrator group 320, and the pouring actuator 200.

[0041] This embodiment provides an intelligent pouring device for precast concrete inspection wells, aiming to solve the problems of existing technologies where concrete pouring relies on manual experience, cannot perceive internal quality status in real time, and has poor uniformity of finished products. This intelligent pouring device utilizes multi-dimensional sensors integrated in the well mold assembly 100, combined with the precise operation of the coordinated vibration and support unit 300 and the pouring execution mechanism 200, all uniformly scheduled by the main controller 400. The well mold assembly 100 serves as the forming foundation, and its built-in distributed temperature measurement array 130 and ultrasonic transceiver matrix 140 provide the physical basis for obtaining information on the internal curing temperature and density of the concrete. The weighing sensor on the vibration and support unit 300 and the zoned vibrator group 320 are used to acquire macroscopic data on the total amount of concrete poured and to apply microscopic interventions for local vibration, respectively. The pouring execution mechanism 200 controls the amount and position of concrete injection through its pumping metering unit 230 and movable pouring hose. The main controller 400, such as a Siemens S7-1200 series PLC, links these sensing and execution components, transforming the pouring process from an open and uncontrollable process into a data-driven and controllable manufacturing process, which makes it possible to improve the overall quality and production efficiency of precast inspection wells.

[0042] The pouring execution mechanism 200 includes a gantry-type moving frame 210, a lifting pouring hose 220, and a pumping metering unit 230. The gantry-type moving frame 210 includes a horizontal moving mechanism driven by a servo motor. The lifting pouring hose 220 is suspended on the horizontal moving mechanism and its lifting and lowering are controlled by a winch. The outlet of the pumping metering unit 230 is connected to the lifting pouring hose 220.

[0043] The pouring execution mechanism 200 in this embodiment aims to achieve precise concrete placement within the pouring cavity. The design of the gantry-type moving frame 210 allows the working range of the pouring execution mechanism 200 to completely cover the well formwork assembly 100 below. The horizontal moving mechanism on the gantry-type moving frame 210 can be specifically composed of a ball screw pair and driven by a servo motor. This configuration allows the suspended lifting pouring hose 220 to be precisely positioned on the horizontal plane. Simultaneously, the vertical height of the lifting pouring hose 220 is controlled by a winch, such as a wire rope drum driven by a self-locking brake motor. In this way, the outlet of the pouring hose can move in three-dimensional space according to a preset trajectory. This allows the concrete to be gently and layeredly placed in designated locations according to the pouring process, rather than being poured from a single high point. This helps reduce the separation of concrete aggregate and mortar, laying the foundation for obtaining a uniform and dense concrete structure.

[0044] The ultrasonic transceiver matrix 140 includes a first transducer group disposed on the inner wall of the outer mold 120 and a second transducer group disposed on the outer wall of the inner mold 110. The transducers in the first transducer group and the transducers in the second transducer group are arranged opposite each other along the radial direction of the mold, together forming a grid-like detection area covering the casting cavity.

[0045] The ultrasonic transceiver matrix 140 in this embodiment aims to acquire cross-sectional density information of the concrete inside the casting cavity. The first and second transducer groups of the ultrasonic transceiver matrix 140 are respectively installed on the outer mold 120 and the inner mold 110, and are arranged in a one-to-one correspondence along the radial direction of the mold, i.e., the thickness direction. This layout allows each pair of transducers to form an independent ultrasonic detection path. When all the detection paths are combined, a grid-like detection area is formed within the annular space of the casting cavity; its function is to enable cross-sectional scanning of the internal state of the concrete, rather than single-point or single-line measurement. When defects such as air bubbles and voids exist in the concrete, the ultrasonic signal attenuation in this area will increase significantly. By analyzing the signal attenuation data of each path in this grid, the main controller 400 can identify the specific spatial location of the defect, providing accurate target guidance for subsequent targeted defect removal.

[0046] The zoned vibrator group 320 on the co-vibration and support section 300 includes multiple variable frequency vibration motors grouped in the annular and height directions along the outer mold 120; the weighing sensor on the load-bearing support platform 310 is a resistance strain gauge pressure sensor, used to measure the total weight of the well mold assembly 100 and the concrete inside in real time.

[0047] The purpose of the coordinated vibration and support unit 300 in this embodiment is to provide precise vibration energy and monitor the total amount of material in real time. The zoned vibrator group 320 consists of multiple variable frequency vibration motors, which are divided into several independent areas along the circumference and height of the outer mold 120. The use of variable frequency vibration motors allows the main controller 400 to independently adjust the vibration frequency and start / stop of each motor, which means that vibration energy can be precisely applied to the required area, rather than performing indiscriminate global vibration on the entire mold. The weighing sensor on the load-bearing support platform 310, specifically multiple sets of parallel resistance strain gauge pressure sensors, is used to measure the total weight of the mold assembly 100 and the internal concrete in real time and continuously. Subtracting the known empty weight of the mold from this total weight data yields the real-time mass of the poured concrete, providing basic data for the main controller 400 to establish the filling model.

[0048] Example 2

[0049] Please see Figure 5 A smart casting and processing method for precast concrete inspection wells includes the following steps:

[0050] In the step of establishing the filling model, the main controller 400 collects the concrete flow rate provided by the pumping metering unit 230 and the total weight provided by the weighing sensor, and defines the concrete flow rate and total weight data as the pouring process data list. The main controller 400 establishes a filling state model to characterize the filling state of the concrete in the cavity based on the pouring process data list.

[0051] In the compactness diagnosis step, the main controller 400 drives the ultrasonic transceiver matrix 140 to collect ultrasonic signals from the poured area according to the filling state model and defines them as a compactness characterization dataset. Based on the analysis results of the compactness characterization dataset, defective areas with substandard compactness are identified.

[0052] The adaptive control step is executed. The main controller 400 drives the partitioned vibrator group 320 corresponding to the defect area to vibrate. After the vibration is completed, the distributed temperature measurement array 130 is driven to collect temperature data to be defined as the curing process temperature dataset. Then, based on the curing process temperature dataset, the corresponding partitioned temperature control unit 150 is driven to guide the curing process uniformly.

[0053] This embodiment provides a method for processing precast concrete inspection wells, aiming to transform the pouring process into a perceptible and controllable workflow. The step of establishing a filling model allows the main controller 400 to monitor the concrete filling status within the mold in real time. The main controller 400 obtains the volume of injected concrete through a pumping metering unit 230, such as an electromagnetic flowmeter, and simultaneously obtains the injected mass through a weighing sensor. These two data points constitute a pouring process data list. Based on this list, the main controller 400 can calculate the real-time density of the current batch of concrete and establish a filling state model describing the concrete filling status within the cavity. The compaction diagnosis step actively checks for defects within the concrete after pouring. When the filling state model indicates that a certain area has been poured, the main controller 400 drives the ultrasonic transceiver matrix 140 to scan that area. The obtained ultrasonic signals are defined as a compaction characterization dataset. By analyzing the signal attenuation in this dataset, defective areas caused by insufficient vibration can be identified.

[0054] The identification here is based on a preset density qualification standard, which is a judgment threshold quantified according to the attenuation characteristics of ultrasonic waves propagating in concrete. The value is based on ultrasonic testing experiments on standard concrete test blocks with known good density, or on the ultrasonic signal characteristics of high-quality finished products in historical production data, and is pre-calibrated and stored in the main controller 400. During the diagnosis process, the main controller 400 compares the real-time collected ultrasonic attenuation value with the preset threshold point by point. When the attenuation value of a certain area exceeds the threshold, it is judged as a defective area with insufficient density, and as a logic trigger signal, it drives the main controller 400 to perform subsequent targeted supplementary vibration on the area.

[0055] The adaptive control step is designed to specifically eliminate defects and guide the curing process. Based on the density diagnosis results, the main controller 400 drives the corresponding zoned vibrator group 320 to perform supplementary vibration in the defective area. During this supplementary vibration, the main controller 400 again drives the ultrasonic transceiver matrix 140 to scan the area and compares the acquired new density characterization data with the preset acceptable standard until the density of the area reaches the acceptable standard, at which point vibration stops. After confirming that the density of all areas is acceptable, and after vibration is complete, to manage the heat of hydration of the concrete, the main controller 400 uses the distributed temperature measurement array 130 to collect temperature data, forming a curing process temperature dataset. Based on this dataset, it drives the corresponding zoned temperature control unit 150 to perform fine-tuning to achieve uniform guidance of the curing process. The purpose is to reduce internal stress caused by uneven temperature, thereby improving the durability of the finished product.

[0056] Before performing the compactness diagnostic step, a sensor self-calibration step is also included;

[0057] The sensor self-calibration step is used to define the moment when the main controller 400 determines that the pouring of a certain area has been completed as the diagnostic start time node. The main controller 400 first collects static ultrasonic attenuation data once at the diagnostic start time node, and then instructs the corresponding zoned vibrator group 320 to apply a preset vibration pulse, and collects dynamic ultrasonic attenuation data once during the vibration. By comparing the static and dynamic ultrasonic attenuation data, the main controller 400 determines the validity of the data of the corresponding probe in the ultrasonic transceiver matrix 140, and uses the valid data or the data estimated by interpolation based on the valid data for subsequent defect area identification.

[0058] The sensor self-calibration step in this embodiment aims to ensure the reliability of the data source used for compaction diagnosis. In a concrete environment, the surface of the ultrasonic probe may be coated with slurry and solidify, causing signal distortion. Therefore, before performing the compaction diagnosis step, the main controller 400 first performs a data validity query. The process is as follows: at the start of the diagnosis, the main controller 400 first records static ultrasonic attenuation data when the vibration stops. Then, it instructs the vibrator in that area to apply a brief vibration pulse, recording dynamic ultrasonic attenuation data simultaneously. The judgment logic is that if the probe is working properly, the internal structure of the fluid concrete will undergo slight changes under vibration, resulting in a significant difference between the dynamic and static data. Conversely, if the probe is covered by solidified slurry, the vibration cannot affect the received signal, and the two data will be very close. By comparing the difference between these two data, the main controller 400 can determine the validity of the probe data, which avoids incorrect defect judgments due to invalid data, thereby ensuring the accuracy of subsequent adaptive control.

[0059] In the step of establishing the filling model, the main controller 400 also collects the current horizontal position information of the pouring nozzle provided by the gantry moving frame 210 of the pouring actuator 200, and the height information provided by the lifting pouring hose 220; the main controller 400 combines the pouring process data list with the position and height information of the pouring nozzle to calculate the theoretical filling height and distribution state of the concrete in the mold cavity in real time in the digital model, so as to establish the filling state model.

[0060] The calculation process is as follows: The main controller 400 pre-constructs a three-dimensional digital twin model that is completely consistent with the actual pouring cavity. This model is divided into fine mesh units and voxels. After the pouring begins, the controller accumulates the concrete volume measured by the pumping metering unit 230 within the corresponding time interval into the voxel directly below it, based on the real-time three-dimensional coordinates of the pouring hose nozzle. At the same time, the model has a built-in simplified algorithm based on a preset angle of repose or viscosity coefficient to simulate the natural flow and spreading process of the newly injected concrete to the adjacent voxels under the action of gravity, thereby dynamically generating the theoretical concrete distribution surface. To ensure the accuracy of the model, the main controller 400 also obtains the theoretical total mass by multiplying the total injected volume and the concrete density in real time, and continuously compares it with the actual total mass measured by the weighing sensor. The difference is used to correct the model, forming a high-precision real-time filling state model.

[0061] This embodiment refines the steps for establishing the filling model, aiming to construct a more accurate filling state model. A list of pouring progress data only provides a macroscopic filling amount and cannot describe the distribution of concrete within the mold. Therefore, while collecting weight and volume data, the main controller 400 also obtains the real-time three-dimensional spatial coordinates of the pouring nozzle from the pouring execution mechanism 200, namely the horizontal position information provided by the gantry-type moving frame 210 and the height information provided by the lifting pouring hose 220. The main controller 400 combines this position information with the pouring progress data list and, through calculation, can depict the theoretical filling height and surface distribution of concrete within the mold cavity in real time in the digital model. This more refined filling state model allows the main controller 400 to more accurately determine when and where pouring has been completed, enabling more timely and precise initiation of subsequent compaction diagnostics and improving the overall efficiency of the processing method.

[0062] During the adaptive control step, the main controller 400 identifies temperature anomaly areas where the curing process is uneven by calculating the spatial temperature gradient between different measuring points in the curing process temperature data and the temporal temperature gradient of a single measuring point over time. The main controller 400 instructs the zoned temperature control unit 150 corresponding to the temperature anomaly area to start the micro-cooling or micro-heating function until the spatial temperature gradient and the temporal temperature gradient are restored to the preset process range.

[0063] This embodiment refines the curing guidance process in the adaptive control step, aiming to achieve precise management of the concrete hydration heat reaction process. Concrete releases heat during curing; uneven heat dissipation can lead to internal temperature stress. The main controller 400 analyzes the temperature dataset of the curing process to calculate two key indicators: the temperature difference between different measuring points, i.e., the spatial temperature gradient; and the rate of temperature change at a single measuring point over time, i.e., the temporal temperature gradient. An excessively large spatial temperature gradient indicates overheating or undercooling at a certain location, while an excessively large temporal temperature gradient indicates that the hydration reaction is too vigorous at a certain location. Using these two gradient values, the main controller 400 can accurately identify abnormal temperature areas where the curing process is uneven.

[0064] The preset process range upon which the identification and control here are based refers to the allowable fluctuation range of the spatial temperature gradient and temporal temperature gradient during the concrete curing process, which is preset by the main controller 400. The purpose of setting this range is to control the internal and external temperature difference and cooling rate caused by the heat of hydration within a safe level that will not generate harmful thermal stress. The upper and lower limits are determined by thermodynamic simulation calculation and experimental verification after comprehensively considering the concrete mix ratio, manhole wall thickness, cement thermophysical properties and relevant industry standards. Once any gradient value calculated by the main controller 400 exceeds this range, the corresponding zoned temperature control unit 150 is triggered to start the micro-cooling or micro-heating function until the temperature gradient of the area returns to within the preset process range.

[0065] The main controller 400 instructs the zoned temperature control unit 150 corresponding to the abnormal area, such as the Peltier semiconductor cooling and heating module, to perform targeted micro-cooling or micro-heating. The purpose is to actively intervene in local heat in this way, maintain the spatial and temporal temperature gradient within a small preset process range, ensure the overall uniform curing of concrete, help prevent the generation of cracks in the later stage, and thus ensure the long-term structural stability of the final product.

[0066] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A precast concrete inspection well with intelligent pouring device, characterized in that: The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application relates to a prefabricated concrete inspection well intelligent pouring device and an intelligent pouring processing method thereof. The application 2. The precast concrete inspection well intelligent pouring device according to claim 1, characterized in that, The pouring execution mechanism (200) comprises a gantry movable frame (210), a lifting pouring hose (220) and a pumping metering unit (230), the gantry movable frame (210) comprises a horizontal moving mechanism driven by a servo motor, the lifting pouring hose is hung on the horizontal moving mechanism and its lifting is controlled by a winch, and the outlet of the pumping metering unit (230) is communicated with the lifting pouring hose (220).

3. The precast concrete inspection well intelligent pouring device according to claim 1, characterized in that, The ultrasonic transceiving matrix (140) comprises a first transducer group arranged on the inner wall of the outer mold (120) and a second transducer group arranged on the outer wall of the inner mold (110), the transducers in the first transducer group and the transducers in the second transducer group are oppositely arranged along the radial direction of the mold, and together form a grid-shaped detection area covering the pouring cavity.

4. The precast concrete inspection well intelligent pouring device according to claim 1, characterized in that, The partitioned vibrator group (320) on the collaborative vibration and support part (300) comprises a plurality of variable-frequency vibration motors arranged in groups along the annular and height directions of the outer mold (120); and the load sensor on the load-bearing support platform (310) is a resistance strain pressure sensor, which is used to measure the total weight of the well mold assembly (100) and the internal concrete in real time.

5. The precast concrete inspection well intelligent pouring device according to claim 1, characterized in that, Before the compactness diagnosis step is performed, a sensor self-calibration step is further included; The sensor self-calibration step is used to define the time point when the main controller judges that the pouring is completed as a diagnosis starting time node after the main controller (400) judges that the pouring in a certain area is completed; the main controller (400) first collects static ultrasonic attenuation data at the diagnosis starting time node, then instructs the partitioned vibrator group (320) corresponding to the area to apply a preset vibration pulse, and collects dynamic ultrasonic attenuation data when the vibration acts; the main controller (400) determines the data validity of the corresponding probe in the ultrasonic transceiving matrix (140) by comparing the static and dynamic ultrasonic attenuation data, and uses the effective data or the data estimated by interpolation based on the effective data for subsequent defect area identification.

6. The precast concrete inspection well intelligent pouring device according to claim 1, characterized in that, In the step of establishing the filling model, the main controller (400) further collects the current horizontal position information of the pouring nozzle provided by the gantry movable frame (210) of the pouring execution mechanism (200) and the height information provided by the lifting pouring hose (220); the main controller (400) combines the pouring progress data list with the position and height information of the pouring nozzle, and calculates the theoretical filling height and distribution state of the concrete in the mold cavity in real time in the digital model to establish the filling state model.

7. The precast concrete inspection well intelligent pouring device according to claim 1, characterized in that, In the step of performing adaptive regulation, the main controller (400) identifies temperature abnormal areas of uneven curing process by calculating the spatial temperature gradient between different measuring points in the curing process temperature data set and the time temperature gradient of a single measuring point changing with time; the main controller (400) instructs the partitioned temperature control unit (150) corresponding to the temperature abnormal area to start the micro-cooling or micro-heating function until the spatial temperature gradient and the time temperature gradient return to the preset process range.

Images