Cast-in-place continuous section concrete layered vibration control system and method

Abstract

The invention discloses a cast-in-place continuous section concrete layered vibration control system and method, and belongs to the technical field of building engineering construction. The control system comprises an intelligent vibrator management and control module for realizing accurate positioning of the spatial position of the vibrator and self-adaptive optimization control of vibration parameters; the concrete state sensing module is configured to collect key state parameters of concrete in real time and dynamically evaluate the quality state of the concrete; the hierarchical control decision module is used for automatically generating a dynamic hierarchical vibration strategy based on the concrete rheological characteristic rule base and implementing quality early warning and control decision in combination with construction data; the collaborative operation scheduling module is used for realizing collaborative operation control, path planning optimization and task dynamic allocation management of the multi-vibrator equipment; and the intelligent early warning protection module automatically realizes equipment abnormity early warning and operation safety protection management.

Description

Technical Field

[0001] This application relates to the field of building construction technology, and more specifically, to a control system and method for layered vibration compaction of cast-in-place continuous concrete. Background Technology

[0002] In the construction of cast-in-place concrete structures, vibration is a crucial step in ensuring the density, uniformity, and overall performance of the concrete. Its quality directly impacts the mechanical properties and durability of the structure. This is especially true in continuous concrete structures such as bridges, tunnels, and large-volume foundations, where the large size of components, long pouring times, and complex construction environments present numerous challenges. On one hand, concrete experiences rapid slump changes and its hardening time is greatly affected by the environment. If vibration is not timely or performed improperly, quality defects such as honeycomb, pitting, voids, and slag inclusions can easily occur. On the other hand, traditional manual methods rely on operator experience, making it difficult to precisely control the vibration depth, time, and frequency, resulting in inconsistent local density of the concrete and making it difficult to uniformly control construction quality.

[0003] To improve construction efficiency and vibration quality, some projects have introduced electric or hydraulic vibratory compactors. However, most of these devices are still primarily manually controlled, lacking real-time sensing capabilities of the concrete's condition and the ability to dynamically adjust operating parameters based on different pouring stages and material states. Furthermore, the issues of multi-point synchronous vibration and path optimization in complex structures have not been effectively resolved, easily leading to over- or under-vibration in certain areas and increasing the risk of rework. Simultaneously, a systematic early warning and management mechanism has not been established for equipment malfunctions, vibration blind spots, and safety hazards during the vibration process, hindering the improvement of overall construction quality and safety levels.

[0004] In summary, how to achieve integrated and coordinated control of vibration operation status perception, parameter self-adjustment, path optimization and safety protection in cast-in-place continuous concrete construction has become an urgent technical problem to be solved. Summary of the Invention

[0005] In order to overcome a series of defects in the existing technology, the purpose of this application is to provide a layered vibration control system for cast-in-place continuous concrete, which includes the following modules: The intelligent vibrator control module integrates multi-parameter sensors and vibration fingerprint recognition to achieve precise spatial positioning of the vibrator and adaptive optimization control of vibration parameters. The concrete condition sensing module is configured to collect key concrete condition parameters in real time and dynamically evaluate the concrete quality status. The layered control decision module responds to the quality assessment signal output by the concrete state perception module, automatically generates a dynamic layered vibration strategy based on the concrete rheological property rule library, and implements quality early warning and control decisions in conjunction with construction data. The collaborative operation scheduling module, based on the operation instructions output by the hierarchical control decision module, realizes collaborative operation control, path planning optimization and dynamic task allocation management of multiple vibratory equipment. The intelligent early warning and protection module responds to the collaborative operation scheduling module and equipment status information, and automatically realizes equipment anomaly early warning and operation safety protection management. Among them, the intelligent vibrator control module, concrete status perception module, hierarchical control decision module, collaborative operation scheduling module and intelligent early warning and protection module work together to solve the problems of insufficient positioning accuracy, uneven vibration quality and high safety risks in the process of vibrating cast-in-place continuous concrete.

[0006] Preferably, the multi-parameter sensor includes a triaxial accelerometer, an angular velocity sensor, a laser rangefinder, and a temperature compensation sensor, wherein: the triaxial accelerometer has a measurement range of ±16g and a sampling frequency of not less than 1000Hz; the angular velocity sensor has a measurement accuracy of ±0.1° / s and is used to detect changes in the vibrator's posture; the laser rangefinder is used for precise positioning, with a measurement accuracy of ±5mm and an effective distance measurement range of 50m; and the temperature compensation sensor has an operating range of -40℃ to +85℃.

[0007] Preferably, the adaptive optimization control of the vibration parameters includes three dimensions: amplitude adjustment, frequency adjustment, and phase adjustment. Specifically: the amplitude adjustment range is 30% to 100% of the rated amplitude, with an adjustment accuracy of ±3%; the frequency adjustment range is 8000-12000 rpm, with an adjustment step size of 100 rpm, and frequency stability is better than ±2%; phase adjustment is used for synchronous control when multiple vibrators work together, with a phase difference control accuracy of ±10°; the adaptive optimization is based on fuzzy PID control theory, automatically adjusting the control parameters according to the current state parameters of the concrete, with a response time controlled within 800 milliseconds.

[0008] Preferably, the key state parameters of the concrete include five core parameters: internal temperature, humidity, density, flowability index, and hardening degree. Among them: temperature measurement adopts distributed fiber optic temperature sensing technology with a measurement accuracy of ±0.5℃ and a spatial resolution of 1m; humidity measurement is achieved through a capacitive humidity sensor with a measurement range of 0%~100%RH and an accuracy of ±3%RH; density is measured by ultrasonic testing technology with a detection frequency of 40kHz and a penetration depth of 1.5m; flowability index is obtained through vibration response spectrum analysis with a sampling frequency of not less than 1500Hz.

[0009] Preferably, the dynamic layered vibration strategy includes four elements: layer depth determination, vibration sequence planning, vibration parameter setting, and quality control standards. Specifically: the layer depth is dynamically calculated based on concrete slump, aggregate size, and vibrator diameter, using the formula: layer depth = 1.25 × vibrator radius of action + maximum aggregate size × 0.3, with single-layer thickness controlled within the range of 20cm-40cm; the vibration sequence adopts a spiral or grid-like path planning to ensure that the vibration coverage rate of the main areas reaches over 95%, while corner areas are supplemented by manual vibration, with overlapping areas controlled within 15%–25%; vibration parameters include vibration time, vibration depth, and vibration intensity, which are adjusted in real-time according to the concrete quality status.

[0010] The purpose of this application is also to provide a method for controlling the layered vibration compaction of cast-in-place continuous concrete, which is based on the above-mentioned layered vibration compaction control system for cast-in-place continuous concrete, and includes the following steps: Acquire the pouring status information and construction data of the concrete components to be vibrated in the construction area, and collect the initial spatial position information and vibration state parameters of each intelligent vibrator; Based on the intelligent vibrator control module, the spatial positioning and vibration parameters of each vibrator are adaptively optimized and controlled through multi-parameter sensor acquisition and vibration fingerprint recognition. The concrete state sensing module collects key state parameters of the target concrete component in real time, constructs a concrete health index, and assesses its current vibration adaptability. Using the layered control decision module, combined with the current health index of the concrete, a layered vibration strategy suitable for the target component is dynamically generated, and construction process data is called simultaneously to form quality early warning and control decision instructions. According to the control decision command, each intelligent vibrator is controlled to carry out vibration operation in layers, while monitoring the vibration depth, frequency and duration parameters. With the help of the collaborative operation scheduling module, the spatial distribution, task priority and path planning information of multiple vibrators are integrated to realize multi-device collaborative control, path optimization and dynamic task allocation; During the vibration operation, the intelligent early warning and protection module is invoked to identify equipment malfunctions and operational risks, and to automatically adjust the vibration strategy or suspend the operation as needed. When the target concrete component has been vibrated in layers and meets the preset quality standards, the corresponding vibration task ends and the intelligent vibrator is dispatched to the next vibration target.

[0011] Preferably, the pouring status information includes five aspects: concrete pouring time, pouring temperature, pouring thickness, concrete mix proportions, and environmental parameters. Specifically: the pouring time is recorded to the minute level for calculating the initial setting time and suitable vibration time window; the pouring temperature is measured using an infrared thermometer with an accuracy of ±1℃, covering the entire pouring surface; the pouring thickness is measured using a laser rangefinder with an accuracy of ±2mm; the concrete mix proportions include cement content, aggregate ratio, admixture type and dosage, and water-cement ratio; and the environmental parameters include ambient temperature, humidity, wind speed, and rainfall.

[0012] Preferably, the multi-parameter sensor acquisition and vibration fingerprint recognition steps adopt a layered data processing architecture: the first layer is the raw data acquisition layer, which is responsible for the real-time acquisition and preprocessing of sensor data, including data filtering, outlier removal, and data calibration; the second layer is the feature extraction layer, which extracts statistical features through time domain analysis, frequency domain features through frequency domain analysis, and time-frequency features through time-frequency analysis; the third layer is the pattern recognition layer, which uses a deep learning algorithm for vibration fingerprint matching. The network structure is a three-layer convolutional neural network with a kernel size of 3×3, max pooling in the pooling layer, a learning rate of 0.001, and at least 200 training epochs.

[0013] Preferably, the process of constructing a concrete health index by real-time acquisition of key state parameters of the target concrete component through the concrete state sensing module includes the following steps: Based on the collected temperature-time curves, resistivity change data, concrete mix proportion information, as well as the viscosity coefficient, yield stress and thixotropic index of concrete, combined with the temperature change trend, the vibratory compaction window period of concrete is dynamically evaluated. By utilizing the rate of temperature rise, the rate of resistivity increase, and the change in surface hardness, an evaluation index for the degree of hydration is established to quantify the transformation process of concrete from a plastic to a hardened state, and to determine the optimal vibration timing and remaining workable time. Based on the changing trends of the internal void distribution of concrete, the degree of aggregate segregation, and the quality of interfacial bonding, calculate the current density index and uniformity coefficient, and assess whether additional vibration or adjustment of vibration parameters is needed. By combining the rheological properties, hydration degree, density, and temperature uniformity parameters of concrete, a concrete health index with a scale of 0-100 is constructed to quantify the overall adaptability of concrete under the current construction conditions.

[0014] Preferably, the layered control decision module, combined with the current health index of the concrete, dynamically generates a layered vibration strategy suitable for the target component, and simultaneously calls construction process data to form quality early warning and control decision instructions, including the following steps: Based on the geometric characteristics of the component, the density of the reinforcement arrangement, and the spatial distribution characteristics of the concrete health index, the target component is divided into multiple vibration control units, and an independent vibration priority and initial quality control standard are set for each unit. Based on the health index level of each layered area, a personalized vibration strategy is dynamically generated, including vibration frequency range, insertion depth sequence, duration window and movement trajectory planning. At the same time, a multi-parameter cross-validation mechanism is used to ensure that each area obtains the most suitable combination of vibration parameters to optimize construction quality. Simultaneously access construction process data, assess the impact of external environment and construction factors on vibration effect, and dynamically adjust the time nodes, parameter intensity and operation sequence in the layered vibration strategy; Establish a three-level early warning mechanism based on the rate of change of health index, the deviation of vibration parameters, and the matching of construction progress to achieve progressive quality risk identification and graded response; The generated layered vibration strategy, quality early warning information, and parameter adjustment suggestions are integrated into standardized control commands and sent to each intelligent vibrator in real time.

[0015] Preferably, according to the control decision command, each intelligent vibrator is controlled to perform vibration operation in layers, while monitoring the vibration depth, frequency, and duration parameters, including the following steps: Each intelligent vibrator automatically adjusts the working frequency, amplitude, and power output of the vibrating head to the preset value according to the received layered vibration strategy instructions, and moves precisely to the starting coordinate point of the corresponding layered area to complete the initial positioning; The intelligent vibrator controls the downward speed and final insertion depth of the vibrating head according to the set insertion depth sequence, while monitoring the changes in insertion resistance and depth in real time, and recording the depth attainment status of each insertion point. Within the set vibration frequency range, combined with the real-time feedback signal of the concrete, the intelligent vibrator precisely controls the vibration frequency through the frequency regulator, while monitoring the transmission efficiency of vibration energy and the response characteristics of the concrete, and dynamically fine-tunes the frequency parameters according to the phased compaction assessment results to maintain the best vibration effect. Based on the time window set by the layered strategy, the vibration duration of each point is automatically controlled, and the concrete air bubble discharge and surface flatness changes are detected in real time. When the preset quality standard is reached or the maximum allowable vibration time is exceeded, the operation is automatically stopped and the operation is moved to the next point. During the vibration process, the vibration depth, frequency stability, duration accuracy, and equipment power consumption parameters are monitored simultaneously to evaluate the vibration quality and equipment performance in real time, and to automatically generate operation records containing timestamps, location coordinates, and parameter values.

[0016] Compared with the prior art, this application has the following beneficial effects: This application achieves collaborative operation and path optimization of multiple vibrators by real-time sensing of key state parameters of concrete and constructing a health index, dynamically generating a layered vibration strategy, and combining fuzzy PID adaptive adjustment of vibration parameters and a three-level quality early warning mechanism. It comprehensively solves the problems of insufficient positioning accuracy of concrete vibration, uneven vibration quality and high construction safety risks, thereby significantly improving the level of intelligence and automation of vibration efficiency and concrete construction quality. Attached Figure Description

[0017] Figure 1 This is a communication timing diagram, which describes the interaction flow between various modules of a cast-in-place continuous concrete layered vibration control system disclosed in an embodiment of this application.

[0018] Figure 2 This is a flowchart illustrating a method for controlling the layered vibration of cast-in-place continuous concrete as disclosed in an embodiment of this application. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of the embodiments of this invention will be described in more detail below with reference to the accompanying drawings. In the drawings, the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The described embodiments are some embodiments of this invention, but not all embodiments.

[0020] Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0021] The embodiments and directional terms described below with reference to the accompanying drawings are exemplary and intended to explain the present invention, and should not be construed as limiting the present invention.

[0022] Figure 1 This is a communication timing diagram, which describes the interaction flow between various modules of a cast-in-place continuous concrete layered vibration control system disclosed in an embodiment of this application.

[0023] like Figure 1 As shown, a layered vibration control system for cast-in-place continuous concrete includes the following modules: The intelligent vibrator control module integrates multi-parameter sensors and vibration fingerprint recognition to achieve precise spatial positioning of the vibrator and adaptive optimization control of vibration parameters. The concrete condition sensing module is configured to collect key concrete condition parameters in real time and dynamically evaluate the concrete quality status. The layered control decision module responds to the quality assessment signal output by the concrete state perception module, automatically generates a dynamic layered vibration strategy based on the concrete rheological property rule library, and implements quality early warning and control decisions in conjunction with construction data. The collaborative operation scheduling module, based on the operation instructions output by the hierarchical control decision module, realizes collaborative operation control, path planning optimization and dynamic task allocation management of multiple vibratory equipment. The intelligent early warning and protection module responds to the collaborative operation scheduling module and equipment status information, and automatically realizes equipment anomaly early warning and operation safety protection management. Among them, the intelligent vibrator control module, concrete status perception module, hierarchical control decision module, collaborative operation scheduling module and intelligent early warning and protection module work together to solve the problems of insufficient positioning accuracy, uneven vibration quality and high safety risks in the process of vibrating cast-in-place continuous concrete.

[0024] In summary, this cast-in-place continuous concrete layered vibration control system integrates modules such as intelligent vibrator management, concrete state perception, layered control decision-making, collaborative operation scheduling, and intelligent early warning and protection. It constructs an integrated intelligent control system with multi-dimensional perception, dynamic decision-making, and collaborative execution, significantly improving the positioning accuracy of the vibrator and the adaptive optimization capability of vibration parameters. It realizes dynamic quality assessment and intelligent generation of layered strategies during the concrete vibration process, effectively ensuring vibration uniformity and construction quality, reducing equipment operation risks and operational safety hazards, thereby comprehensively improving the level of intelligence and engineering quality control capabilities of cast-in-place continuous concrete construction.

[0025] Preferably, the multi-parameter sensor includes a triaxial accelerometer, an angular velocity sensor, a laser rangefinder, and a temperature compensation sensor, wherein: the triaxial accelerometer has a measurement range of ±16g and a sampling frequency of not less than 1000Hz; the angular velocity sensor has a measurement accuracy of ±0.1° / s and is used to detect changes in the vibrator's posture; the laser rangefinder is used for precise positioning, with a measurement accuracy of ±5mm and an effective distance measurement range of 50m; and the temperature compensation sensor has an operating range of -40℃ to +85℃.

[0026] In summary, by integrating high-precision triaxial accelerometers, angular velocity sensors, laser rangefinders, and temperature compensation sensors, multi-dimensional and accurate perception of the vibrator's attitude, spatial position, and ambient temperature is achieved. This ensures high-frequency, stable, and reliable acquisition of the vibrator's motion status and positioning information in complex construction environments, thus providing solid data support for subsequent vibration control optimization and precise operations.

[0027] Preferably, the adaptive optimization control of the vibration parameters includes three dimensions: amplitude adjustment, frequency adjustment, and phase adjustment. Specifically: the amplitude adjustment range is 30% to 100% of the rated amplitude, with an adjustment accuracy of ±3%; the frequency adjustment range is 8000-12000 rpm, with an adjustment step size of 100 rpm, and frequency stability is better than ±2%; phase adjustment is used for synchronous control when multiple vibrators work together, with a phase difference control accuracy of ±10°; the adaptive optimization is based on fuzzy PID control theory, automatically adjusting the control parameters according to the current state parameters of the concrete, with a response time controlled within 800 milliseconds.

[0028] In summary, this vibration parameter adaptive optimization control technology achieves high-precision control of amplitude within the range of 30% to 100%, stable frequency adjustment between 8000 and 12000 rpm, and high-precision coordination of phase synchronization among multiple vibrators by precisely adjusting the amplitude, frequency, and phase dimensions. Combined with an adaptive algorithm based on fuzzy PID control, it can quickly and dynamically adjust control parameters according to the real-time state of the concrete (response time not exceeding 800 milliseconds), significantly improving the response speed of the vibration process and the uniformity and coordination of the vibration effect, thereby ensuring the quality of concrete vibration and construction efficiency.

[0029] Preferably, the key state parameters of the concrete include five core parameters: internal temperature, humidity, density, flowability index, and hardening degree. Among them: temperature measurement adopts distributed fiber optic temperature sensing technology with a measurement accuracy of ±0.5℃ and a spatial resolution of 1m; humidity measurement is achieved through a capacitive humidity sensor with a measurement range of 0%~100%RH and an accuracy of ±3%RH; density is measured by ultrasonic testing technology with a detection frequency of 40kHz and a penetration depth of 1.5m; flowability index is obtained through vibration response spectrum analysis with a sampling frequency of not less than 1500Hz.

[0030] In summary, by employing a variety of high-precision sensing technologies, such as distributed fiber optic temperature sensing, capacitive humidity sensing, ultrasonic density detection, and high-frequency vibration response spectrum analysis, real-time, multi-dimensional, and high-precision monitoring of five key state parameters of concrete—temperature, humidity, density, fluidity, and hardening degree—was achieved. This ensures comprehensive perception and accurate assessment of the physical and mechanical state of concrete during construction, providing a solid data foundation for dynamic quality control and intelligent vibration strategies.

[0031] Preferably, the concrete rheological property rule base adopts a four-layer architecture: a basic data layer, a feature extraction layer, a rule reasoning layer, and an application decision layer. The basic data layer includes a material property database, an environmental condition database, and a historical project database. The material property database covers key parameters. The feature extraction layer calculates yield stress and plastic viscosity in real time through rheological parameter calculations. The formula for calculating yield stress is: τ0 = A0 × (W / C) α ×exp(β×T 拌合 )×(1+γ×t)×(1+δ×SP), where τ0 is the yield stress, representing the minimum stress required for concrete to begin flowing; A0 is the reference yield stress coefficient, ranging from 50 to 2000 Pa; W is the mass of water; C is the mass of cement; W / C represents the water-cement ratio; α is the water-cement ratio influence index, representing the degree of influence of the water-cement ratio on the yield stress, ranging from -1.2 to -0.8; β is the temperature influence coefficient, representing the exponential influence of temperature on the yield stress, ranging from 0.02 to 0.08 / ℃; T 拌合 η is the temperature of the concrete mixture; γ is the time influence coefficient, representing the increasing trend of yield stress with the settling time of the mixture; t is the settling time after mixing; δ is the admixture correction coefficient, reflecting the influence of admixture dosage on yield stress; SP is the admixture dosage; the formula for calculating plastic viscosity is: η p =B0×[Φ / (Φ m -Φ)] n ×exp(E / RT)×(1+λ×t m ), where η p Φ is the plastic viscosity, representing the internal resistance of concrete during sustained flow after yielding; B0 is the reference viscosity coefficient, ranging from 0.1 to 10 Pa·s; Φ is the actual solid volume fraction, ranging from 0.65 to 0.85; Φ m The maximum filler volume fraction is given by λ; n is the viscosity growth exponent, representing the degree of influence of volume fraction change on viscosity; E is the apparent activation energy; R is the gas constant; T is the absolute temperature; λ is the time effect coefficient, reflecting the rate of influence of aging or hydration reaction on viscosity; t m This refers to the mixing time or mixing age, which is the duration from mixing to measurement.

[0032] In summary, this concrete rheological property rule library adopts a four-layer architecture design, realizing systematic management from basic data accumulation, real-time calculation of characteristic parameters, rule reasoning to application decision-making. By accurately modeling the variation law of concrete yield stress and plastic viscosity, and comprehensively considering key factors such as water-cement ratio, temperature, settling time and admixture dosage, it dynamically reflects the minimum stress required for the start of concrete flow and the internal resistance characteristics during the flow process. It provides scientific rheological parameter support for vibration control strategies and effectively improves the quality prediction and intelligent control capabilities in the concrete construction process.

[0033] Preferably, the dynamic layered vibration strategy includes four elements: layer depth determination, vibration sequence planning, vibration parameter setting, and quality control standards. Specifically: the layer depth is dynamically calculated based on concrete slump, aggregate size, and vibrator diameter, using the formula: layer depth = 1.25 × vibrator radius of action + maximum aggregate size × 0.3, with single-layer thickness controlled within the range of 20cm-40cm; the vibration sequence adopts a spiral or grid-like path planning to ensure that the vibration coverage rate of the main areas reaches over 95%, while corner areas are supplemented by manual vibration, with overlapping areas controlled within 15%–25%; vibration parameters include vibration time, vibration depth, and vibration intensity, which are adjusted in real-time according to the concrete quality status.

[0034] In summary, this dynamic layered vibration strategy scientifically determines the layer depth and controls the thickness of each layer within a reasonable range by combining concrete slump, aggregate particle size, and vibrator size. It adopts a spiral or grid-style path planning to achieve a high-coverage vibration sequence, effectively ensuring the uniformity and integrity of vibration in key areas. At the same time, by adjusting parameters such as vibration time, depth, and strength in real time, it achieves dynamic response and precise control of concrete quality, thereby significantly improving the uniformity of concrete vibration quality and construction efficiency.

[0035] Preferably, the multi-vibrator collaborative operation control adopts a master-slave distributed control architecture, where the master controller is responsible for task allocation, path planning and status monitoring, and the slave controller is responsible for executing specific vibration tasks and providing feedback on the execution status. The collaborative operation requires that the positional error of each vibrator be controlled within ±15cm and the time synchronization accuracy reach ±200 milliseconds to ensure the coordination and consistency of the vibration operation.

[0036] In summary, this multi-vibrator collaborative operation control adopts a master-slave distributed control architecture, which realizes centralized management of task allocation, path planning and status monitoring by the master controller, and precise execution of vibration tasks by the slave controller and real-time feedback of status, ensuring that the position error of each vibrator is controlled within ±15cm and the time synchronization accuracy reaches ±200 milliseconds. This effectively improves the coordination and consistency of multi-equipment collaborative operation, and ensures the high efficiency and accuracy of vibration operation and the stability of construction quality.

[0037] Preferably, the path planning optimization adopts a hybrid optimization method combining genetic algorithm and ant colony algorithm; the genetic algorithm is used for global path search, with a population size of 80 individuals, an evolutionary generation of no less than 150 generations, a crossover probability of 0.7, and a mutation probability of 0.15; the ant colony algorithm is used for local path optimization, with an initial pheromone value of 1.0, a pheromone volatility coefficient of 0.1, and the number of ants being 1.5 times the number of vibrators; the path planning result must meet three objectives: a vibration coverage rate of over 95% in the main area, the shortest total path length, and the optimal vibration time, with the optimization calculation time controlled within 60 seconds to ensure the practicality and executability of the path planning.

[0038] In summary, this path planning optimization technology integrates the global search capability of genetic algorithms with the local optimization advantages of ant colony algorithms. By using reasonable parameter settings, it achieves efficient and accurate planning of vibration paths, ensuring that the coverage rate of the main vibration areas reaches more than 95%. At the same time, it minimizes the total path length and vibration time, effectively improving the efficiency and coverage quality of vibration operations. Moreover, the optimization calculation time is controlled within 60 seconds, ensuring the real-time performance and practicality of the path planning scheme, and significantly enhancing the intelligent scheduling capability of the construction process.

[0039] Preferably, the collaborative operation scheduling module integrates operation progress monitoring and efficiency evaluation functions, wherein: progress monitoring generates an overall construction progress report by collecting information on the operation position, completion rate and remaining task of each vibrator in real time, and the progress is updated every 10 minutes; efficiency evaluation adopts multi-dimensional evaluation indicators, including four dimensions: vibration area per unit time, energy consumption efficiency, equipment utilization rate and quality pass rate, and each dimension is set with corresponding evaluation standards and weight coefficients.

[0040] In summary, this collaborative operation scheduling module achieves dynamic monitoring and timely updates of the overall construction progress by collecting the operating location, completion rate, and remaining workload of each vibrator in real time. Combined with multi-dimensional evaluation indicators such as vibration area per unit time, energy efficiency, equipment utilization rate, and quality pass rate, it conducts a comprehensive efficiency assessment, scientifically quantifies construction progress and resource utilization, thereby improving the transparency and accuracy of construction management and promoting efficient collaboration and quality assurance in vibration operations.

[0041] Figure 2 This is a flowchart illustrating a method for controlling the layered vibration of cast-in-place continuous concrete as disclosed in an embodiment of this application.

[0042] like Figure 2 As shown, a method for controlling the layered vibration of cast-in-place continuous concrete includes the following steps: Acquire the pouring status information and construction data of the concrete components to be vibrated in the construction area, and collect the initial spatial position information and vibration state parameters of each intelligent vibrator; Based on the intelligent vibrator control module, the spatial positioning and vibration parameters of each vibrator are adaptively optimized and controlled through multi-parameter sensor acquisition and vibration fingerprint recognition. The concrete state sensing module collects key state parameters of the target concrete component in real time, constructs a concrete health index, and assesses its current vibration adaptability. Using the layered control decision module, combined with the current health index of the concrete, a layered vibration strategy suitable for the target component is dynamically generated, and construction process data is called simultaneously to form quality early warning and control decision instructions. According to the control decision command, each intelligent vibrator is controlled to carry out vibration operation in layers, while monitoring the vibration depth, frequency and duration parameters. With the help of the collaborative operation scheduling module, the spatial distribution, task priority and path planning information of multiple vibrators are integrated to realize multi-device collaborative control, path optimization and dynamic task allocation; During the vibration operation, the intelligent early warning and protection module is invoked to identify equipment malfunctions and operational risks, and to automatically adjust the vibration strategy or suspend the operation as needed. When the target concrete component has been vibrated in layers and meets the preset quality standards, the corresponding vibration task ends and the intelligent vibrator is dispatched to the next vibration target.

[0043] In summary, this method for controlling the layered vibration of cast-in-place continuous concrete achieves precise positioning of the vibrator and adaptive optimization of vibration parameters through multi-parameter sensing and vibration fingerprint recognition of the intelligent vibrator. Combined with the concrete state sensing module to construct a health index, it dynamically generates layered vibration strategies and implements quality warnings, effectively guiding the fine control of vibration depth, frequency, and time. The multi-vibrator collaborative operation scheduling module optimizes path planning and task allocation to ensure coordinated and efficient operation. At the same time, the intelligent early warning and protection module monitors equipment status and risks in real time and dynamically adjusts operation strategies, comprehensively improving the intelligent management level, construction quality, and safety assurance capabilities of the concrete vibration process.

[0044] Preferably, the pouring status information includes five aspects: concrete pouring time, pouring temperature, pouring thickness, concrete mix proportions, and environmental parameters. Specifically: the pouring time is recorded to the minute level for calculating the initial setting time and suitable vibration time window; the pouring temperature is measured using an infrared thermometer with an accuracy of ±1℃, covering the entire pouring surface; the pouring thickness is measured using a laser rangefinder with an accuracy of ±2mm; the concrete mix proportions include cement content, aggregate ratio, admixture type and dosage, and water-cement ratio; and the environmental parameters include ambient temperature, humidity, wind speed, and rainfall.

[0045] In summary, this concrete pouring status information acquisition technology comprehensively covers concrete pouring time, temperature, thickness, mix proportion, and environmental parameters. Utilizing high-precision infrared temperature measurement and laser ranging sensors, it achieves accurate monitoring of the pouring surface temperature and thickness. Combined with detailed mix proportion data and environmental conditions, it provides a scientific basis for accurately calculating the initial setting time of concrete and the appropriate vibration window, enhancing the ability to control the concrete status in real time during construction and effectively supporting the dynamic adjustment of vibration strategies and the refined management of construction quality.

[0046] Preferably, the initial spatial position information is represented by a three-dimensional coordinate system and a precise correspondence is established with the construction drawings; the vibration state parameters include vibration frequency, amplitude, power, current, voltage, and temperature, wherein: the vibration frequency measurement range is 8000-12000 rpm, and the measurement accuracy is ±20 rpm; the amplitude measurement adopts the acceleration integration method, and the measurement accuracy is ±0.2 mm; the power measurement accuracy is ±2%, and the current and voltage measurement accuracy are both ±1%; the temperature measurement includes motor temperature and vibrating head temperature, and the measurement accuracy is ±2℃.

[0047] In summary, by using a three-dimensional coordinate system to accurately represent the initial spatial position of the vibrator and achieving precise correspondence with the construction drawings, combined with high-precision measurements of vibration frequency, amplitude, power, current, voltage, and motor and vibrating head temperatures, comprehensive real-time monitoring of the vibrating equipment status is achieved. This provides solid data support for precise control of the vibration process and safe equipment operation, and improves the accuracy of construction positioning and the reliability of vibration parameters.

[0048] Preferably, the multi-parameter sensor acquisition and vibration fingerprint recognition steps adopt a layered data processing architecture: the first layer is the raw data acquisition layer, which is responsible for the real-time acquisition and preprocessing of sensor data, including data filtering, outlier removal, and data calibration; the second layer is the feature extraction layer, which extracts statistical features through time domain analysis, frequency domain features through frequency domain analysis, and time-frequency features through time-frequency analysis; the third layer is the pattern recognition layer, which uses a deep learning algorithm for vibration fingerprint matching. The network structure is a three-layer convolutional neural network with a kernel size of 3×3, max pooling in the pooling layer, a learning rate of 0.001, and at least 200 training epochs.

[0049] In summary, this multi-parameter sensor acquisition and vibration fingerprint recognition adopts a hierarchical data processing architecture, which realizes efficient collaboration from real-time data acquisition and preprocessing, comprehensive feature extraction (time domain, frequency domain, and time-frequency domain), to high-precision vibration fingerprint matching based on deep learning. With the help of a three-layer convolutional neural network structure and sufficient training, the accuracy and robustness of vibration state recognition are significantly improved.

[0050] Preferably, the process of constructing a concrete health index by real-time acquisition of key state parameters of the target concrete component through the concrete state sensing module includes the following steps: Based on the collected temperature-time curves, resistivity change data, concrete mix proportion information, as well as the viscosity coefficient, yield stress and thixotropic index of concrete, combined with the temperature change trend, the vibratory compaction window period of concrete is dynamically evaluated. By utilizing the rate of temperature rise, the rate of resistivity increase, and the change in surface hardness, an evaluation index for the degree of hydration is established to quantify the transformation process of concrete from a plastic to a hardened state, and to determine the optimal vibration timing and remaining workable time. Based on the changing trends of the internal void distribution of concrete, the degree of aggregate segregation, and the quality of interfacial bonding, calculate the current density index and uniformity coefficient, and assess whether additional vibration or adjustment of vibration parameters is needed. By combining the rheological properties, hydration degree, density, and temperature uniformity parameters of concrete, a concrete health index with a scale of 0-100 is constructed to quantify the overall adaptability of concrete under the current construction conditions.

[0051] In summary, by collecting key parameters such as temperature-time curves, resistivity, mix proportions, and rheological properties in real time, the vibratory window period and hydration process of concrete are dynamically evaluated. Combined with density and uniformity indicators, the transformation of concrete from plastic to hardened state is comprehensively reflected. Thus, a concrete health index quantified on a 0-100 scale is constructed to accurately measure the comprehensive adaptability of concrete under the current construction conditions.

[0052] Preferably, the layered control decision module, combined with the current health index of the concrete, dynamically generates a layered vibration strategy suitable for the target component, and simultaneously calls construction process data to form quality early warning and control decision instructions, including the following steps: Based on the geometric characteristics of the component, the density of the reinforcement arrangement, and the spatial distribution characteristics of the concrete health index, the target component is divided into multiple vibration control units, and an independent vibration priority and initial quality control standard are set for each unit. Based on the health index level of each layered area, a personalized vibration strategy is dynamically generated, including vibration frequency range, insertion depth sequence, duration window and movement trajectory planning. At the same time, a multi-parameter cross-validation mechanism is used to ensure that each area obtains the most suitable combination of vibration parameters to optimize construction quality. Simultaneously access construction process data, assess the impact of external environment and construction factors on vibration effect, and dynamically adjust the time nodes, parameter intensity and operation sequence in the layered vibration strategy; Establish a three-level early warning mechanism based on the rate of change of health index, the deviation of vibration parameters, and the matching of construction progress to achieve progressive quality risk identification and graded response; The generated layered vibration strategy, quality early warning information, and parameter adjustment suggestions are integrated into standardized control commands and sent to each intelligent vibrator in real time.

[0053] In summary, by combining the concrete health index with the geometry of the components and the layout of the reinforcing bars, the vibration control units are finely divided and prioritized, and personalized vibration strategies are dynamically generated, covering vibration parameters and trajectory planning. Furthermore, multi-parameter cross-validation ensures optimal vibration results. Simultaneously, construction process data is integrated, and vibration parameters and work sequences are adjusted in real time. A three-level quality early warning mechanism is constructed to achieve graded identification and response to quality risks. Finally, the optimized vibration strategies and early warning information are standardized into control commands, which are then issued to the intelligent vibrator in real time, effectively improving the intelligence level and precise control capabilities of construction quality management.

[0054] Preferably, according to the control decision command, each intelligent vibrator is controlled to perform vibration operation in layers, while monitoring the vibration depth, frequency, and duration parameters, including the following steps: Each intelligent vibrator automatically adjusts the working frequency, amplitude, and power output of the vibrating head to the preset value according to the received layered vibration strategy instructions, and moves precisely to the starting coordinate point of the corresponding layered area to complete the initial positioning; The intelligent vibrator controls the downward speed and final insertion depth of the vibrating head according to the set insertion depth sequence, while monitoring the changes in insertion resistance and depth in real time, and recording the depth attainment status of each insertion point. Within the set vibration frequency range, combined with the real-time feedback signal of the concrete, the intelligent vibrator precisely controls the vibration frequency through the frequency regulator, while monitoring the transmission efficiency of vibration energy and the response characteristics of the concrete, and dynamically fine-tunes the frequency parameters according to the phased compaction assessment results to maintain the best vibration effect. Based on the time window set by the layered strategy, the vibration duration of each point is automatically controlled, and the concrete air bubble discharge and surface flatness changes are detected in real time. When the preset quality standard is reached or the maximum allowable vibration time is exceeded, the operation is automatically stopped and the operation is moved to the next point. During the vibration process, the vibration depth, frequency stability, duration accuracy, and equipment power consumption parameters are monitored simultaneously to evaluate the vibration quality and equipment performance in real time and automatically generate work records containing timestamps, location coordinates, and parameter values. In summary, by controlling the intelligent vibrator to precisely implement vibration operations based on a layered strategy, the vibration frequency, amplitude, power, and insertion depth are automatically adjusted and dynamically optimized. Combined with real-time feedback signals and compaction assessment results, the frequency is continuously adjusted to maintain the optimal vibration state. Within a set time window, the system intelligently identifies the expulsion of air bubbles and changes in surface flatness, ensuring that the vibration operation automatically terminates and switches points once the quality requirements are met. The entire process synchronously monitors key parameters such as vibration depth, frequency stability, and energy consumption, forming a complete spatiotemporal positioning operation record, effectively improving the intelligence, precision, and traceability of the vibration operation.

[0055] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A layered vibration control system for cast-in-place continuous concrete, characterized in that, Includes the following modules: The intelligent vibrator control module integrates multi-parameter sensors and vibration fingerprint recognition to achieve precise spatial positioning of the vibrator and adaptive optimization control of vibration parameters. The concrete condition sensing module is configured to collect key concrete condition parameters in real time and dynamically evaluate the concrete quality status. The layered control decision module responds to the quality assessment signal output by the concrete state perception module, automatically generates a dynamic layered vibration strategy based on the concrete rheological property rule library, and implements quality early warning and control decisions in conjunction with construction data. The collaborative operation scheduling module, based on the operation instructions output by the hierarchical control decision module, realizes collaborative operation control, path planning optimization and dynamic task allocation management of multiple vibratory equipment. The intelligent early warning and protection module responds to the collaborative operation scheduling module and equipment status information, and automatically realizes equipment anomaly early warning and operation safety protection management. Among them, the intelligent vibrator control module, concrete status perception module, hierarchical control decision module, collaborative operation scheduling module and intelligent early warning and protection module work together to solve the problems of insufficient positioning accuracy, uneven vibration quality and high safety risks in the process of vibrating cast-in-place continuous concrete.

2. The layered vibration control system for cast-in-place continuous concrete as described in claim 1, characterized in that, The multi-parameter sensor includes a triaxial accelerometer, an angular velocity sensor, a laser rangefinder, and a temperature compensation sensor. Specifically: the triaxial accelerometer has a measurement range of ±16g and a sampling frequency of no less than 1000Hz; the angular velocity sensor has a measurement accuracy of ±0.1° / s and is used to detect changes in the vibrator's attitude; the laser rangefinder is used for precise positioning, with a measurement accuracy of ±5mm and an effective distance range of 50m; and the temperature compensation sensor operates within a range of -40℃ to +85℃. The adaptive optimization control of the vibration parameters includes three dimensions: amplitude adjustment, frequency adjustment, and phase adjustment. Specifically: the amplitude adjustment range is 30% to 100% of the rated amplitude, with an adjustment accuracy of ±3%; the frequency adjustment range is 8000-12000 rpm, with an adjustment step size of 100 rpm, and frequency stability is better than ±2%; phase adjustment is used for synchronous control when multiple vibrators work together, and the phase difference control accuracy reaches ±10°; the adaptive optimization is based on fuzzy PID control theory, which automatically adjusts the control parameters according to the current state parameters of the concrete, and the response time is controlled within 800 milliseconds.

3. The layered vibration control system for cast-in-place continuous concrete as described in claim 1, characterized in that, The key state parameters of the concrete include five core parameters: internal temperature, humidity, density, flowability index, and hardening degree. Among them: temperature measurement adopts distributed fiber optic temperature sensing technology with a measurement accuracy of ±0.5℃ and a spatial resolution of 1m; humidity measurement is achieved through a capacitive humidity sensor with a measurement range of 0%~100%RH and an accuracy of ±3%RH; density is measured by ultrasonic testing technology with a detection frequency of 40kHz and a penetration depth of 1.5m; flowability index is obtained through vibration response spectrum analysis with a sampling frequency of not less than 1500Hz.

4. The layered vibration control system for cast-in-place continuous concrete as described in claim 1, characterized in that, The dynamic layered vibration strategy includes four elements: layer depth determination, vibration sequence planning, vibration parameter setting, and quality control standards. Specifically: the layer depth is dynamically calculated based on concrete slump, aggregate size, and vibrator diameter, using the formula: layer depth = 1.25 × vibrator radius of action + maximum aggregate size × 0.3, with single-layer thickness controlled within the range of 20cm-40cm; the vibration sequence adopts a spiral or grid-like path planning to ensure that the vibration coverage rate of the main areas reaches over 95%, while corner areas are supplemented by manual vibration, with overlapping areas controlled within 15%–25%; vibration parameters include vibration time, vibration depth, and vibration intensity, which are adjusted in real time according to the concrete quality status.

5. A method for controlling the layered vibration of cast-in-place continuous concrete, implemented based on the layered vibration control system for cast-in-place continuous concrete as described in any one of claims 1-4, characterized in that... Includes the following steps: Acquire the pouring status information and construction data of the concrete components to be vibrated in the construction area, and collect the initial spatial position information and vibration state parameters of each intelligent vibrator; Based on the intelligent vibrator control module, the spatial positioning and vibration parameters of each vibrator are adaptively optimized and controlled through multi-parameter sensor acquisition and vibration fingerprint recognition. The concrete state sensing module collects key state parameters of the target concrete component in real time, constructs a concrete health index, and assesses its current vibration adaptability. Using the layered control decision module, combined with the current health index of the concrete, a layered vibration strategy suitable for the target component is dynamically generated, and construction process data is called simultaneously to form quality early warning and control decision instructions. According to the control decision command, each intelligent vibrator is controlled to carry out vibration operation in layers, while monitoring the vibration depth, frequency and duration parameters. With the help of the collaborative operation scheduling module, the spatial distribution, task priority and path planning information of multiple vibrators are integrated to realize multi-device collaborative control, path optimization and dynamic task allocation; During the vibration operation, the intelligent early warning and protection module is invoked to identify equipment malfunctions and operational risks, and to automatically adjust the vibration strategy or suspend the operation as needed. When the target concrete component has been vibrated in layers and meets the preset quality standards, the corresponding vibration task ends and the intelligent vibrator is dispatched to the next vibration target.

6. The method for controlling layered vibration of cast-in-place continuous concrete according to claim 5, characterized in that, The pouring status information includes five aspects: concrete pouring time, pouring temperature, pouring thickness, concrete mix proportions, and environmental parameters. Among them: the pouring time is recorded to the minute level and is used to calculate the initial setting time and suitable vibration time window of the concrete; the pouring temperature is measured by an infrared thermometer with a measurement accuracy of ±1℃ and the measurement range covers the entire pouring surface; the pouring thickness is measured by a laser rangefinder with a measurement accuracy of ±2mm; the concrete mix proportions include cement dosage, aggregate ratio, admixture type and dosage, and water-cement ratio; the environmental parameters include ambient temperature, humidity, wind speed, and rainfall.

7. The method for controlling layered vibration compaction of cast-in-place continuous concrete according to claim 5, characterized in that, The multi-parameter sensor acquisition and vibration fingerprint recognition steps adopt a layered data processing architecture: the first layer is the raw data acquisition layer, which is responsible for the real-time acquisition and preprocessing of sensor data, including data filtering, outlier removal, and data calibration; the second layer is the feature extraction layer, which extracts statistical features through time domain analysis, frequency domain features through frequency domain analysis, and time-frequency features through time-frequency analysis; the third layer is the pattern recognition layer, which uses a deep learning algorithm for vibration fingerprint matching. The network structure is a three-layer convolutional neural network with a kernel size of 3×3, max pooling in the pooling layer, a learning rate of 0.001, and at least 200 training epochs.

8. The method for controlling layered vibration of cast-in-place continuous concrete according to claim 5, characterized in that, The concrete health index is constructed by real-time acquisition of key state parameters of the target concrete component through the concrete state sensing module, including the following steps: Based on the collected temperature-time curves, resistivity change data, concrete mix proportion information, as well as the viscosity coefficient, yield stress and thixotropic index of concrete, combined with the temperature change trend, the vibratory compaction window period of concrete is dynamically evaluated. By utilizing the rate of temperature rise, the rate of resistivity increase, and the change in surface hardness, an evaluation index for the degree of hydration is established to quantify the transformation process of concrete from a plastic to a hardened state, and to determine the optimal vibration timing and remaining workable time. Based on the changing trends of the internal void distribution of concrete, the degree of aggregate segregation, and the quality of interfacial bonding, calculate the current density index and uniformity coefficient, and assess whether additional vibration or adjustment of vibration parameters is needed. By combining the rheological properties, hydration degree, density, and temperature uniformity parameters of concrete, a concrete health index with a scale of 0-100 is constructed to quantify the overall adaptability of concrete under the current construction conditions.

9. The method for controlling layered vibration of cast-in-place continuous concrete according to claim 5, characterized in that, Using the aforementioned layered control decision module, combined with the current health index of the concrete, a layered vibration strategy suitable for the target component is dynamically generated, and construction process data is simultaneously invoked to form quality early warning and control decision instructions, including the following steps: Based on the geometric characteristics of the component, the density of the reinforcement arrangement, and the spatial distribution characteristics of the concrete health index, the target component is divided into multiple vibration control units, and an independent vibration priority and initial quality control standard are set for each unit. Based on the health index level of each layered area, a personalized vibration strategy is dynamically generated, including vibration frequency range, insertion depth sequence, duration window and movement trajectory planning. At the same time, a multi-parameter cross-validation mechanism is used to ensure that each area obtains the most suitable combination of vibration parameters to optimize construction quality. Simultaneously access construction process data, assess the impact of external environment and construction factors on vibration effect, and dynamically adjust the time nodes, parameter intensity and operation sequence in the layered vibration strategy; Establish a three-level early warning mechanism based on the rate of change of health index, the deviation of vibration parameters, and the matching of construction progress to achieve progressive quality risk identification and graded response; The generated layered vibration strategy, quality early warning information, and parameter adjustment suggestions are integrated into standardized control commands and sent to each intelligent vibrator in real time.

10. The method for controlling layered vibration compaction of cast-in-place continuous concrete according to claim 5, characterized in that, According to the control decision command, each intelligent vibrator is controlled to perform vibration operation in layers, while monitoring the vibration depth, frequency, and duration parameters, including the following steps: Each intelligent vibrator automatically adjusts the working frequency, amplitude, and power output of the vibrating head to the preset value according to the received layered vibration strategy instructions, and moves precisely to the starting coordinate point of the corresponding layered area to complete the initial positioning; The intelligent vibrator controls the downward speed and final insertion depth of the vibrating head according to the set insertion depth sequence, while monitoring the changes in insertion resistance and depth in real time, and recording the depth attainment status of each insertion point. Within the set vibration frequency range, combined with the real-time feedback signal of the concrete, the intelligent vibrator precisely controls the vibration frequency through the frequency regulator, while monitoring the transmission efficiency of vibration energy and the response characteristics of the concrete, and dynamically fine-tunes the frequency parameters according to the phased compaction assessment results to maintain the best vibration effect. Based on the time window set by the layered strategy, the vibration duration of each point is automatically controlled, and the concrete air bubble discharge and surface flatness changes are detected in real time. When the preset quality standard is reached or the maximum allowable vibration time is exceeded, the operation is automatically stopped and the operation is moved to the next point. During the vibration process, the vibration depth, frequency stability, duration accuracy, and equipment power consumption parameters are monitored simultaneously to evaluate the vibration quality and equipment performance in real time, and to automatically generate operation records containing timestamps, location coordinates, and parameter values.

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