Intelligent monitoring system for bridge cantilever pouring construction based on bim and digital twinning

Abstract

The application relates to the technical field of bridge construction monitoring, and discloses a bridge cantilever pouring construction intelligent monitoring system based on BIM and digital twinning, which comprises a physical perception and execution layer for acquiring field temperature and humidity and coordinate parameters and constructing a global state matrix; a computer-aided management and core algorithm layer for predicting absolute time nodes based on the global state matrix; a linear programming production scheduling module for comparing a benchmark scheduling and triggering a progress scheduling program to lock an optimal idle production scheduling time window; a reverse thermodynamics solving module for deducing a target temperature curve and generating a compliance intervention scheduling plan; and a building information model engine for executing four-dimensional space topology intersection operation based on the compliance intervention scheduling plan; and when the interference detection result is zero, a resource scheduling matrix work order containing a physical hardwiring interlocking instruction is issued. The application solves the problems of cross-operation timing conflict and concrete over-period maintenance, and realizes the overall control of time and space scheduling and component quality.

Description

Technical Field

[0001] This invention relates to the field of bridge construction monitoring technology, specifically to an intelligent monitoring system for bridge cantilever casting construction based on BIM and digital twins. Background Technology

[0002] The construction of cantilever bridges typically involves multiple work surfaces and the parallel and overlapping operations of specialized equipment such as tower cranes and concrete placing booms. In existing construction scheduling models, on-site production scheduling relies on manual experience and pre-set baseline plans. Faced with multiple parallel processes, traditional scheduling schemes lack a global temporal and spatial perspective, and when overlapping spatial resource occupancy occurs, a postponement strategy is usually adopted. This scheduling method leads to idle equipment and project delays, failing to effectively resolve spatial resource timing conflicts during overlapping operations.

[0003] When work schedules are disrupted due to temporal interference, existing construction management systems struggle to dynamically adapt to changes in physical work periods and component material quality. Concrete strength evolution is influenced by both microenvironmental temperature and curing time. If existing natural curing or fixed temperature control strategies are continued when construction is delayed, the accumulated maturity of the concrete will deviate from project expectations by the time the new schedule window arrives, leading to overdue curing. The lack of underlying hydrothermal dynamic intervention mechanisms to reverse-engineer based on schedule deviations, coupled with insufficient synchronized temperature control, can cause internal thermal stress concentration and shrinkage cracking, reducing the overall quality of bridge components.

[0004] Furthermore, for the safety management of multiple special equipment operating simultaneously in the same airspace, existing monitoring methods are mostly limited to three-dimensional anti-collision simulation in upper-level software or single spatial distance alarms. These monitoring systems fail to link production scheduling instructions with dynamic physical space in a four-dimensional topology and lack a control mechanism that maps from software parsing to the underlying programmable logic controller (PLC). When field equipment intrudes into a dangerous area due to human error or mechanical failure, existing systems cannot directly trigger hard-wired power-off intervention at the physical and electrical level. This disconnect between upper-level anti-collision simulation and lower-level power cut-off prevents closed-loop control from being formed when spatial operational interference occurs at the construction site, increasing the risk of mechanical equipment collisions. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides an intelligent monitoring system for bridge cantilever casting construction based on BIM and digital twins. This system solves the spatial resource timing conflicts caused by multi-source parallel and cross-operations in traditional bridge cantilever casting construction, as well as the quality problems of excessive concrete curing and thermal stress cracking caused by passively delaying and waiting.

[0006] To achieve the above objectives, the present invention provides the following technical solution: an intelligent monitoring system for bridge cantilever casting construction based on BIM and digital twins, comprising: The physical sensing and execution layer acquires on-site temperature, humidity, and coordinate parameters, which are then transmitted via the edge transmission layer to the computer-aided management and core algorithm layer to construct a global state matrix. The computer-aided management and core algorithm layer initiates an integral calculation program based on the global state matrix to predict the absolute time node for reaching the required intensity. The linear programming scheduling module receives the absolute time node, compares it with the baseline schedule, and triggers the progress scheduling program to lock the optimal idle scheduling time window. The inverse thermodynamics solution module derives the target temperature curve based on the optimal idle production time window, performs physical specification verification, and generates a compliant intervention scheduling plan. The building information modeling engine receives the compliance intervention scheduling plan, performs a four-dimensional spatial topology intersection operation, and outputs the spatial topology interference detection result. When the spatial topology interference detection result is zero, the system issues a resource scheduling matrix work order containing underlying physical hard-wired interlock instructions.

[0007] Preferably, the physical sensing and execution layer acquires multi-source heterogeneous data streams containing on-site temperature, humidity, and coordinate parameters; the edge computing gateway of the edge transmission layer receives the multi-source heterogeneous data streams, performs zero-order sample-keeping alignment and network packet encapsulation, and transmits standard transmission control protocol messages; the computer-aided management and core algorithm layer receives the standard transmission control protocol messages, uses the global state matrix aggregation formula to calculate, and constructs a global state matrix that spans the environmental physical domain and the mechanical operation domain, forming a unified data base.

[0008] The principle is to establish a unified mathematical foundation that spans the physical domain of the environment and the mechanical operation domain, and to use the global state matrix aggregation formula to align the time sections of asynchronous multi-source heterogeneous data to avoid data misalignment.

[0009] Preferably, the computer-aided management and core algorithm layer performs dimensionality reduction extraction based on the global state matrix, and inputs it into the integral calculation program to generate historical microenvironment temperature data; the Nurse-Saul maturity calculation formula is used to calculate the cumulative maturity of the historical microenvironment temperature data, and combined with external meteorological data to infer the future microenvironment temperature evolution sequence to form a predicted maturity data chain; the predicted maturity data chain is mapped to the compressive strength approximation rate using the hyperbolic evolution model of concrete strength maturity; when the compressive strength approximation rate first meets the demolding or release strength threshold requirement and simultaneously meets the minimum curing days time constraint, the corresponding physical time point is extracted, and the absolute time node for reaching the strength required by the specification is predicted; wherein, the demolding or release strength threshold is set to more than 90% of the preset compressive strength.

[0010] The principle is as follows: by introducing the equivalent age theory, using the Nurse-Saul maturity calculation formula to transform nonlinear temperature fluctuations into a unified endogenous strength measurement scale, and using the strength maturity hyperbola evolution model to achieve positive quantitative age prediction from environmental parameters to structural physical strength.

[0011] Preferably, the linear programming scheduling module receives absolute time nodes and queries preset baseline schedules, extracts the planned occupation time period data of associated special equipment before and after the absolute time nodes; combines the space operation and transfer time to deduce the planned occupation time period data along the time axis to generate the expected operation time period; based on the preset baseline schedule comparison logic, performs time domain intersection operation on the expected operation time period and the planned occupation time period data to output the intersection duration; when the intersection duration is greater than zero, it is determined that there is a time sequence overlap, the original operation plan is suspended and the progress scheduling program for the execution of space-time resource allocation is triggered.

[0012] The principle is to integrate the time consumed by spatial physical transfer with the time consumed by standard operation of the process, and objectively quantify the mutual exclusivity of equipment resources through the intersection calculation of the overlap of the time axis, so as to accurately identify the temporal interference boundary in the cross operation process.

[0013] Preferably, the scheduler calls a mixed-integer linear programming algorithm to set the optimization objective as minimizing the comprehensive time penalty cost, calculates and outputs the target cost using the comprehensive time penalty cost calculation formula, and performs iterative convergence calculation based on the target cost to traverse the equipment idle periods after conflict nodes under the constraints of special equipment resource monopoly and concrete curing time efficiency. Based on the target cost, it performs iterative convergence calculation to output the available time interval that minimizes the comprehensive time penalty cost, and locks the optimal idle production scheduling time window as a conflict-free benchmark reference boundary.

[0014] The principle is to construct a multi-objective decision-making mathematical model, take the comprehensive time penalty cost calculation formula as the objective function, find the convergent solution under the rigid boundary of physical mechanical monopoly and thermodynamic time-sensitive criticality, overcome the limitations of a single scheduling index, and output the assignment scheme with the minimum comprehensive cost.

[0015] Preferably, the inverse thermodynamics solution module calculates the remaining maturity index to be compensated based on the optimal idle production scheduling time window and the physical principle of reversibility of equivalent age integral using the inverse equivalent age compensation formula. The remaining maturity index to be compensated is then evenly and smoothly spread across the optimal idle production scheduling time window sequence, and the basic thermodynamic reference trajectory is derived in reverse. The basic thermodynamic reference trajectory is then extracted as the target temperature curve for subsequent physical specification verification.

[0016] The principle is as follows: by applying the reversible property of equivalent age integral, the physical time offset caused by scheduling intervention is converted into the expected difference of heat through the inverse equivalent age compensation formula, and the underlying hydrothermal intervention reference trajectory required to maintain the target strength of the component is derived and output.

[0017] Preferably, the target temperature curve is subjected to physical specification verification covering both the maximum temperature and the heating rate limit, and the result of the boundary node judgment is output. If the boundary node judgment result is true, multiple rounds of thermodynamic rebalancing iteration are performed by dynamically adjusting the temperature curve smoothing adjustment coefficient of some violation intervals, and a multi-dimensional time-series data chain that is within the multi-dimensional safety envelope throughout the entire cycle is output. The multi-dimensional time-series data chain is encapsulated and solidified to generate a compliant intervention scheduling plan for the convergence of on-site time-temperature and thermal environment intervention.

[0018] Its principle is to superimpose engineering physical safety boundary checks, use a multi-dimensional thermodynamic rebalancing iteration mechanism to perform smooth adjustment of high and low temperature amplitudes, prevent unilateral intervention to induce thermal stress concentration, and achieve integrated control of adaptive construction period and structural quality assurance.

[0019] Preferably, the building information modeling engine receives the compliance intervention scheduling plan and extracts the corresponding special equipment operation actions; based on the principle of rigid body kinematics, it uses the dynamic spatial envelope boundary calculation formula to derive the equipment occupancy space of the special equipment operation actions at each prediction time; it transforms the static equipment drawing model of the corresponding equipment occupancy space into a four-dimensional spatial envelope that dynamically extends with the time axis, and generates a three-dimensional solid envelope surface for four-dimensional spatial topology intersection operation.

[0020] The principle is that by combining the static topology matrix with the physical attitude and translation transformation of the equipment using the dynamic spatial envelope boundary calculation formula, the spatial safety buffer boundary that extends continuously over time is derived, thus eliminating rigid body sway and physical braking hysteresis errors during mechanical operation.

[0021] Preferably, the coordinate set of the boundary of the three-dimensional entity envelope surface is verified to overlap with the dynamic spatial trajectory of the other production equipment on site in a spatiotemporal manner; based on the spatiotemporal overlap verification, the separation axis theorem algorithm is used to perform polyhedral intersection calculation frame by frame along the time axis, and the interference volume parameters are accumulated to generate interference volume parameters; based on the interference volume parameters, a four-dimensional spatial topological intersection operation is performed, and the spatial topological interference detection result representing the degree of three-dimensional physical interference overlap is output.

[0022] The principle is as follows: the polyhedron separation axis theorem is introduced to quantitatively calculate the degree of physical interference, and the derived interference volume parameters are used as the exclusive basis for determining the feasibility of the time-space temperature path.

[0023] Preferably, when the spatial topological interference detection result is zero, the system extracts compliance verification data to generate a resource scheduling matrix work order; it parses the boundary contour in the resource scheduling matrix work order and converts it into the special equipment prohibited three-dimensional coordinates for anti-collision comparison; it sends the special equipment prohibited three-dimensional coordinates to the special equipment programmable logic control cabinet of the underlying industrial control execution hardware for latching and forming an electronic fence boundary; the special equipment programmable logic control cabinet compares the real-time three-dimensional absolute coordinates with the electronic fence boundary at high frequency, and when it intrudes into the preset buffer tolerance range, the system activates and sends the underlying physical hard-wired interlock command contained in the resource scheduling matrix work order to cut off the control power supply at the input end of the special equipment motor frequency converter.

[0024] The principle is as follows: the production scheduling coordinate system at the software level is parsed and mapped to the dynamic electronic fence of the underlying programmable logic controller. The high-frequency coordinate point-area projection comparison triggers the hard-wired power-off intervention at the electrical level, thus constructing a closed-loop safety control mechanism from the core algorithm deduction down to the underlying power cut-off.

[0025] This invention provides an intelligent monitoring system for bridge cantilever construction based on BIM and digital twins. It offers the following advantages: 1. This invention extracts planned time slot data before and after absolute time nodes through a linear programming scheduling module, performs temporal intersection calculations based on the spatial operation and transfer time, and calls a mixed-integer linear programming algorithm to traverse equipment idle slots when temporal overlap is detected. The algorithm outputs the available time slot that minimizes the overall time penalty cost as the optimal idle scheduling time window. This mathematical optimization mechanism based on multi-objective decision-making replaces the passive waiting and deferral of traditional manual scheduling, solving the problem of spatial resource temporal conflicts caused by multiple parallel and overlapping operations in bridge cantilever casting construction.

[0026] 2. This invention utilizes a reverse thermodynamics solution module to derive the fundamental thermodynamic reference trajectory based on the optimal idle production scheduling time window using a reverse equivalent age compensation formula. It then performs physical specification verification on the target temperature curve, covering both the maximum temperature and the heating rate, thereby generating a compliant intervention scheduling plan. This mechanism dynamically adjusts the underlying physical hydrothermal intervention strategy based on the offset of the production scheduling time window, ensuring that the intrinsic strength development process of the concrete structure remains synchronized with the actual construction period. This solves the quality problems of excessive curing and thermal stress cracking of concrete caused by scheduling delays.

[0027] 3. This invention extracts the operational actions of special equipment through a Building Information Modeling (BIM) engine and generates a dynamically expanding 3D solid envelope surface that extends over time. It then performs a 4D spatial topological intersection operation. Upon confirming no spatial interference, it issues a resource scheduling matrix work order to the programmable logic control cabinet to form an electronic fence boundary. When the real-time coordinates of the equipment intrude into the buffer tolerance range, the system directly activates the hard-wired power-off interlocking circuit at the physical and electrical level, achieving closed-loop control from the upper-level anti-collision deduction down to the lower-level power cutoff, ensuring the spatial operational safety of multiple equipment operating simultaneously. Attached Figure Description

[0028] Figure 1 This is the overall architecture diagram of the intelligent monitoring system for bridge cantilever casting construction based on BIM and digital twins of the present invention. Figure 2 This is a flowchart of the intelligent monitoring method for bridge cantilever casting construction based on BIM and digital twins according to the present invention. Figure 3 This is a comparative diagram of the multi-cycle scheduling evolution based on comprehensive time penalty cost according to the present invention; Figure 4 This is a comparative diagram of the microenvironment thermodynamic evolution based on the reverse equivalent age of the present invention. Detailed Implementation

[0029] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0030] See attached document Figure 1 This invention provides an intelligent monitoring system for bridge cantilever casting construction based on BIM and digital twins, comprising: a physical perception and execution layer, an edge transmission layer, and a computer-aided management and core algorithm layer.

[0031] The physical sensing and execution layer is deployed in the bridge cantilever casting work area and on-site special equipment. This layer includes a temperature and humidity sensor network, spatial data acquisition equipment, and industrial control execution hardware. The temperature and humidity sensor network's monitoring probes are embedded inside the cantilever casting box girder structure and within the curing membrane, continuously collecting real-time temperature data of the concrete core and surface. The spatial data acquisition equipment includes laser rangefinders installed on the running track of on-site special equipment (such as hanging baskets or concrete placing booms) and absolute encoders at the end of the hoisting motors. This equipment continuously acquires the three-dimensional absolute coordinates of the on-site special equipment. The industrial control execution hardware includes the solenoid valve group of the automatic sprinkler system, heating equipment, and the programmable logic control cabinet for special equipment. The programmable logic control cabinet for special equipment has a built-in hard-wired power-off interlock circuit, directly controlling the output of the special equipment motor frequency converter.

[0032] The edge transport layer, serving as the medium for interaction between field hardware and upper-layer systems, includes the edge computing gateway. The edge computing gateway is equipped with a multi-protocol conversion module. It parses the fieldbus protocol messages output by the industrial control execution hardware and encapsulates them into standard transmission control protocol messages for higher-layer information technology networks. The edge transport layer ensures the stability of the bidirectional interaction link between the underlying physical sensing parameters and the upper-layer scheduling commands.

[0033] The computer-aided management and core algorithm layer is deployed on the computing server, undertaking the core algorithm derivation and scheduling computation tasks of the system. This layer incorporates a building information modeling (BIM) engine. The BIM engine receives multi-source data, performs 3D structural component visualization rendering and spatial topology collision calculations, and establishes a BIM-digital twin mapping. The layer also integrates a linear programming scheduling module and an inverse thermodynamics solution module. The linear programming scheduling module outputs a time-series allocation scheme based on the on-site equipment occupancy status. The inverse thermodynamics solution module, based on specified time window node parameters, calculates the target microenvironmental temperature curve required to maintain construction progress.

[0034] See attached document Figure 2 This invention provides an intelligent monitoring system for bridge cantilever casting construction based on BIM and digital twins, comprising the following steps: S1, the physical perception and execution layer uses a network of temperature and humidity sensors and spatial data acquisition equipment to obtain on-site temperature, humidity and coordinate parameters, which are then transmitted to the computer-aided management and core algorithm layer via the edge computing gateway of the edge transmission layer to construct a global state matrix and complete on-site data process monitoring. S2, the computer-aided management and core algorithm layer, starts the integral calculation program based on the global state matrix and external meteorological data to predict the absolute time node when the intensity required by the standard is reached; S3, the linear programming scheduling module receives absolute time nodes and compares them with the baseline schedule. When it is determined that there is a time overlap, the progress scheduling program is triggered to lock the optimal idle scheduling time window. S4, the reverse thermodynamics solution module derives the target temperature curve based on the optimal idle production time window, and performs physical specification verification to complete quality control by combining thermodynamic boundary thresholds such as the highest temperature or the maximum heating rate. After the verification is passed, a compliant intervention scheduling plan containing underlying hardware adjustment instructions is generated. S5, the building information modeling engine receives the compliance intervention scheduling plan, extracts the corresponding special equipment operation actions to generate a three-dimensional entity envelope surface, performs a four-dimensional spatial topology intersection operation to output the spatial topology interference detection results, and realizes intelligent monitoring of bridge cantilever casting construction. S6, when the spatial topology interference detection result is zero, the system issues a resource scheduling matrix work order containing underlying physical hard-wired interlock instructions.

[0035] The steps of the method provided by this invention will be described in detail below.

[0036] The physical sensing and execution layer in S1 above utilizes a network of temperature and humidity sensors and spatial data acquisition equipment to obtain on-site temperature, humidity, and coordinate parameters. These parameters are then transmitted via the edge computing gateway of the edge transmission layer to the computer-aided management and core algorithm layer to construct a global state matrix and complete the specific execution steps for on-site data process monitoring. These steps are divided into the following sub-steps for detailed explanation: S101, In this embodiment, the physical sensing and execution layer synchronously senses the environmental physical parameters and mechanical position parameters of the cantilever casting site through deployed hardware sensors. As a preferred approach, the physical sensing and execution layer deploys a temperature and humidity sensor network in each cantilever casting surface area. Based on the heat release characteristics of concrete hydration, the temperature and humidity sensor network uses thermistor sensors embedded inside the cantilever box girder structure to collect the core temperature and surface temperature of the concrete structure.

[0037] The temperature difference between the core and surface is a crucial physical parameter for subsequent systems to determine the thermal stress boundary within the structure and avoid shrinkage cracks. The threshold for this temperature difference is dynamically determined based on the current concrete mix proportions and the prevailing season, typically set below 25 degrees Celsius. A temperature and humidity sensor network simultaneously deploys IoT temperature and humidity node devices on the inner wall of the concrete curing membrane to collect micro-environmental temperature and humidity within the membrane. For the data acquisition circuit architecture of the thermistor sensors and temperature and humidity node devices, those skilled in the art can use conventional analog-to-digital converters and microcontroller communication modules; the hardware signal acquisition mechanism is well-known in the field and will not be elaborated further here. The data output from the hardware sensors, with hardware clock timestamps, is converted into level signals and sent to a multi-source heterogeneous data stream.

[0038] S102, in order to comprehensively grasp the operating trajectory of special equipment on site, the physical sensing and execution layer acquires the three-dimensional dynamic position information of the special equipment on site through spatial data acquisition equipment and integrates it into a multi-source heterogeneous data stream. The spatial data acquisition equipment includes laser rangefinders deployed on the side of the special equipment's main track and trolley track, as well as absolute encoders installed on the hoisting motor shaft.

[0039] The rationale for selecting the above equipment combination is that the laser rangefinder measures the absolute X-axis and Y-axis coordinates of the special equipment, while the absolute encoder records the lifting height of the hook and converts it into the absolute Z-axis coordinates of the special equipment. The combination of these three measurements allows for a complete reconstruction of the real-time spatial activity boundaries of the mechanical equipment. Simultaneously, the system obtains the remaining task queue length of each special equipment from its programmable logic control cabinet via the application programming interface. This queue length objectively reflects the current operating load of the corresponding equipment. The system merges and encapsulates the aforementioned location information and queue length into a multi-source heterogeneous data stream.

[0040] S103, the edge transmission layer utilizes the edge computing gateway to receive multi-source heterogeneous data streams, and performs industrial control protocol parsing and standard network message encapsulation. Considering the objective differences in sampling frequencies among different types of sensors, the edge computing gateway introduces multi-source data time alignment logic after receiving fieldbus protocol messages on the downlink interface.

[0041] Specifically, based on the system's globally synchronized clock, the asynchronously arriving temperature, humidity, and coordinate data undergo zero-order hold sampling alignment. That is, before acquiring new valid sensor observations, the system maintains and reuses historical values ​​from the previous sampling period to ensure temporal consistency of data slices at the same time point and prevent data misalignment during subsequent matrix splicing. The edge computing gateway extracts the aligned fieldbus protocol messages into plaintext numbers using a built-in protocol parsing script, packages them into standard transmission control protocol messages according to a preset data structure mask, and sends them to the computer-aided management and core algorithm layer via the uplink network interface.

[0042] S104, before performing specific data processing, to achieve global coordination of the complex field environment, the system maps heterogeneous physical and mechanical states to a unified mathematical dimension based on multi-agent state space theory. The computer-aided management and core algorithm layer receives standard transmission control protocol messages and calculates the global state matrix using the global state matrix aggregation formula. The global state matrix aggregation formula is: ; in, Represents the global state matrix. Indicates the current system time. This represents the physical state vector of the first working surface at the current system time. Indicates the first The physical state vector of each working surface at the current system time. This represents the device state vector of the first special device in the current system time. Indicates the first The device state vector of a special piece of equipment at the current system time. The technical purpose of this formula is to establish a unified data base across the environmental physical domain and the mechanical operation domain, providing initial parameter support for subsequent planning and optimization.

[0043] To further clarify the data structure of the elements within the matrix, for the physical state vector of the work surface, the first... The physical state vector of the current working surface at the current system time is determined by the first working surface. The micro-environmental temperature of the work surface, the first The core temperature of the concrete structure on each working surface, the first The concrete surface temperature of the first working surface and the first The humidity inside the film covering the work surface is composed of four physical quantities combined in sequence.

[0044] For the device state vector, the first The device state vector of a special device in the current system time is determined by the first... The absolute X-axis coordinates of a special piece of equipment, the first The absolute Y-axis coordinate of a special piece of equipment, the first The absolute Z-axis coordinates of each special equipment and the first The four parameters, namely the length of the remaining task queue for each special equipment, are combined in sequence.

[0045] Based on the aforementioned mathematical mapping, the computer-aided management and core algorithm layer continuously and periodically executes steps S101 to S104, generating a dynamically updated global state matrix time series in the database. The system stores this time series as a reference parameter to complete the data process monitoring of the cross-operation environment of bridge cantilever casting.

[0046] The specific execution steps of the computer-aided management and core algorithm layer in S2 above, which initiates the integral calculation program based on the global state matrix and external meteorological data to predict the absolute time node when the intensity required by the specification is reached, are divided into the following sub-steps for detailed explanation: S201, the development of concrete's compressive strength is dominated by its internal hydration heat reaction process, and the hydration heat reaction rate is highly dependent on the cumulative effect of microenvironmental temperature during the curing period. In this embodiment, the computer-aided management and core algorithm layer extracts a global state matrix time series containing historical records from the database. Before performing prediction and inference, the system uses time-series slicing technology to reduce the dimensionality of the continuous state matrix and extract the historical microenvironmental temperature data of the corresponding working surface. This data dimensionality reduction operation aims to eliminate mechanical environmental parameters such as spatial coordinates that are not strongly correlated with the current structural strength evolution, providing a basic calculation sequence for subsequently quantifying the cumulative contribution of temperature to concrete strength.

[0047] S202, to transform nonlinear temperature fluctuations into a unified engineering evaluation index, the system introduces the equivalent age theory. Based on the acquired historical sequence, the computer-aided management and core algorithm layer uses the existing Nurse-Saul maturity calculation formula to calculate the cumulative maturity. The Nurse-Saul maturity calculation formula is as follows: ; in, Indicates the first The cumulative maturity of each task within the current system time. Indicates the work surface index number. Indicates the current system time. This represents the summation operator. Indicates the time step index number. This represents the total number of discrete time steps. Indicates the first Within the first time step Temperature of the microenvironment at the work site The reference temperature constant representing the temperature at which the hydration reaction of concrete ceases is usually pre-calibrated in a laboratory based on the type of cement and admixtures used. Indicates the first Effective hydration temperature within a time step This represents the duration of a single discrete time step. To balance the physical hysteresis characteristics of heat conduction within large concrete components with the computational power consumption of the control server, The value of this time is usually set between 0.5 and 2 hours based on practical engineering experience. The technical purpose of this formula is to establish a measure of the intrinsic strength of concrete that is not affected by fluctuations in the external environment through the dual integration of temperature and time.

[0048] S203. Merely assessing the current maturity status is insufficient to meet the pre-planning requirements of on-site procedures. As a preferred approach, the system uses an application programming interface to access data from a meteorological service platform to obtain the environmental temperature forecast curve for the area where the bridge cantilever casting construction site is located over a future period. Considering the inherent latency fluctuations or short-term data packet loss during network transmission of external meteorological data streams, and the physical continuity of environmental temperature changes in nature, the system introduces a linear interpolation algorithm to compensate for and fill in missing data points before time-series splicing, ensuring the mathematical continuity of the forward-looking sequence.

[0049] Subsequently, the system combines the predicted curve with the surface heat transfer coefficient of the concrete structure to forward deduce the microenvironment temperature evolution sequence within the corresponding future working surface. For meteorological data acquisition and structural foundation heat transfer calculation, those skilled in the art can use existing meteorological data analysis tools and finite difference heat transfer models; the underlying technical implementation methods are well-known in the field and will not be elaborated upon here. The system then substitutes the generated future microenvironment temperature evolution sequence into the aforementioned Nurse-Saul maturity calculation formula, forming a predicted maturity data chain extending towards the future timeline.

[0050] S204, combining the historical accumulation and future projection maturity data mentioned above, the computer-aided management and core algorithm layer adopts the existing hyperbolic evolution model of concrete strength maturity, mapping the predicted maturity values ​​at different discrete moments to the concrete compressive strength approximation rate at the corresponding moment.

[0051] Specifically, this hyperbolic evolution model utilizes the ultimate compressive strength and curve shape parameters pre-calibrated through standard specimen compressive strength tests. It sequentially substitutes the values ​​in the predicted maturity data chain into the hyperbolic function to calculate the predicted compressive strength for the corresponding stage. To avoid the risk of biased judgments arising from relying solely on a single numerical extreme value, the system performs traversal optimization calculations along the forward time axis and constructs a joint judgment logic based on multi-dimensional indicators.

[0052] When the approximation rate obtained from the mapping first meets the demolding or tension strength threshold requirements set by the bridge construction technical specifications, and simultaneously meets the time constraint of the minimum curing days preset for the structure, the system extracts the physical time point corresponding to this state. The strength threshold is usually set to more than 90% of the preset compressive strength. The system outputs the time limit that meets all preset physical indicators as an absolute time node, thereby completing a forward-looking progress prediction. This node will serve as the underlying logical boundary for determining whether there is a conflict in the allocation of time-series resources in subsequent scheduling algorithms.

[0053] The specific execution steps of the linear programming scheduling module in S3 above, which receives absolute time nodes, compares them with the baseline schedule, and determines that there is a time overlap, triggering the scheduler to lock the optimal idle scheduling time window, are detailed in the following sub-steps: S301, after completing the forward-looking timeliness prediction and simulation, the system enters the physical feasibility verification stage of engineering resources. In this embodiment, the linear planning scheduling module within the computer-aided management and core algorithm layer receives the absolute time node output from the preceding steps and uses it as the basic input parameter to trigger subsequent spatiotemporal resource allocation logic. To determine whether the physical node is feasible in the actual work area, the linear planning scheduling module initiates a baseline scheduling query request to the building information model engine through the internal data bus.

[0054] The Building Information Modeling (BIM) engine pre-stores baseline work schedules for various special equipment, generated based on the overall construction organization plan and site records. The linear programming scheduling module extracts the planned occupancy time periods for related special equipment before and after absolute time nodes from the baseline work schedules, based on the spatial coordinates of the work area. The purpose of this data extraction is to provide a reference background for subsequent conflict detection, preventing work instructions from being issued to machinery already occupied by other parallel processes.

[0055] S302, to transform the aforementioned physical data in the time dimension into a computable mathematical form, the system performs a time sequence comparison and conflict determination between the target time node and the baseline schedule based on the time axis overlap. Starting from the absolute time node, the system combines the standard operation time of the current work surface process with the estimated spatial operation and transfer time based on the current three-dimensional coordinates of the equipment, and generates the expected operation time period for the current work surface by forward deduction along the time axis.

[0056] As a preferred method, the aforementioned logic for obtaining the time consumption of spatial operation transition is as follows: the three-dimensional Euclidean distance between the current equipment coordinates and the target work surface coordinates is calculated and divided by the rated operating speed of the special equipment; when the system's underlying parameters are abnormal and the rated operating speed value approaches 0, the system will output the preset maximum safe transition time constant by default to ensure the robustness of the division operation program.

[0057] The technical purpose of introducing spatial operation transfer time is to eliminate spatiotemporal errors caused by the physical movement of equipment and ensure the alignment of working conditions of multi-source collaborative data. After generating the expected work time period, the system performs a temporal intersection calculation with the special equipment planned occupancy time period fed back by the Building Information Modeling (BIM) engine. When the calculated intersection duration is greater than zero, it indicates that there is a temporal overlap between the original baseline schedule and the current expected work status. This mutual exclusion of physical work space and mechanical resources in the same time dimension will directly lead to on-site construction stagnation if not intervened. Based on this temporal interference judgment, the system actively suspends the original work plan and triggers the underlying progress scheduling program.

[0058] S303. Conventional delay strategies are prone to causing concrete to exceed its curing period, leading to structural cracking and other quality risks. To address this issue, the system's scheduler invokes an existing mixed-integer linear programming algorithm to initiate a global optimization search within the production time window.

[0059] Before conducting specific planning and optimization, the system constructs a basic mathematical model based on multi-objective decision theory in operations research. Mixed-integer linear programming is an optimization method for finding the optimal solution of a linear objective function under multi-dimensional constraints involving Boolean integer variables and continuous real variables. In the business scenario of this invention, to avoid a unipolar scheduling deadlock caused by relying solely on the length of the project duration, the system's optimization objective is set to minimize the comprehensive time penalty cost incurred by scheduling adjustments. The comprehensive time penalty cost calculation formula is used to calculate this cost, which is: ; in, This indicates the combined time penalty cost. This represents the summation operator. This indicates the total number of available free time slots. This represents the weighting coefficient for time deviation penalty. This coefficient is dynamically determined based on the strength sensitivity of concrete in the later stage of hydration, and its value is usually between 0.6 and 0.8. Indicates the first The offset of the starting point of each idle time period from the absolute time node. The constant representing the penalty for equipment switching and basic idleness is used to measure the basic fixed energy consumption and depreciation costs caused by changes in the scheduling plan. It is usually taken in the range of 0.2 to 0.4. The specific fixed values ​​of the timeliness deviation penalty weighting coefficient and the penalty constant for equipment switching and basic idleness are usually determined by on-site technicians using the analytic hierarchy process based on the engineering ledgers of historical projects. Indicates the first A Boolean variable representing the device resource usage during idle time periods. The value is 1 when the time period is selected and assigned to the current work surface, and 0 otherwise.

[0060] The technical purpose of this formula is to output a multi-dimensional balanced decision scheme by weighting and balancing the quality of material maintenance and the efficiency of equipment operation, while using Boolean variables to filter out interference values ​​in the unselected intervals.

[0061] S304. To ensure the physical executability of the solution results and the safety of engineering quality, the system pre-configures multi-dimensional rigid constraint boundaries when executing the mixed-integer linear programming algorithm. These constraint boundaries encompass the exclusive resource constraint for special equipment and the critical constraint for concrete curing time. The exclusive resource constraint, based on the indivisibility of physical entities, mandates that within any given time slice, a single piece of special equipment can be assigned to at most one task queue for operation.

[0062] The critical constraint on concrete curing time limits, based on the thermodynamic properties of concrete, restricts the maximum allowable bias time span represented by continuous real-valued variables, thereby ensuring that scheduling delays do not exceed the safety margin of material strength. Furthermore, to ensure the algorithm's completeness in complex construction environments, if no feasible solution exists within the constraint space—that is, if all idle time periods exceed the critical time constraint—the system will trigger an anomaly warning intervention mechanism, sending a resource alert to the upper-level management and proactively terminating the iteration.

[0063] After setting the objective function and boundary conditions, the linear programming scheduling module calls its internal solver to traverse all idle slots of equipment following conflict nodes, performing iterative convergence calculations. The system ultimately outputs the available time interval that satisfies all hard engineering constraints and minimizes the overall time penalty. This conflict-free time interval is locked and output as the optimal idle scheduling time window. This time window not only resolves top-level scheduling conflicts but also serves as a benchmark boundary for subsequent inverse thermodynamic deduction and intervention in the underlying physical environment.

[0064] The reverse thermodynamics solution module in S4 derives the target temperature curve based on the optimal idle production time window, and performs physical specification verification to complete quality control by combining thermodynamic boundary thresholds such as the highest temperature or the maximum heating rate. After the verification is passed, a compliance intervention scheduling plan containing underlying hardware adjustment instructions is generated. The specific execution steps are divided into the following sub-steps for detailed explanation: S401, after locking the optimal idle production time window, the original absolute time node has been suspended and replaced by the system. In the event of an objective shift in the production time window, if the original on-site microenvironment temperature is used for curing, the compressive strength of the concrete will deviate from the project's expected value when it reaches the new production window. To achieve dynamic adaptation between the construction period and the structural quality, in this embodiment, the inverse thermodynamics solution module built into the computer-aided management and core algorithm layer initiates the inverse solution derivation program. Based on the physical principle of the reversibility of equivalent age integrals, the inverse thermodynamics solution module uses the inverse equivalent age compensation formula to calculate the microenvironment target temperature. The inverse equivalent age compensation formula is: ; in, Indicates the first The target temperature of the microenvironment at a future time step. The reference temperature constant that indicates when the hydration reaction of concrete stops. This represents the standard cumulative maturity at demolding as required by the specification. This value is determined by inverse algebraic calculation of the aforementioned hyperbolic evolution model of concrete strength maturity, based on a pre-set target demolding compressive strength threshold. Indicates the first The cumulative maturity of each task within the current system time. Indicates the current system time. This represents the total number of discrete time steps remaining until the optimal idle scheduling time window. This represents the duration of a single discrete time step. Indicates the first A temperature curve smoothing adjustment coefficient for a future time step is used to avoid abrupt temperature changes in the output of the actuator. This coefficient is set based on the inertial response delay characteristics of the historical actuator, and its value usually fluctuates dynamically between 0.85 and 1.15.

[0065] To further clarify the physical composition characteristics within this model, the formula... This represents the remaining maturity level to be compensated from the requirement of the specification at the current moment. This indicates the remaining physical time available for maintenance.

[0066] The technical purpose of this formula is to generate a fundamental thermodynamic reference trajectory that guides the underlying hardware actions by uniformly and smoothly spreading the remaining maturity indicators to be compensated across a new time window sequence. Simultaneously, to ensure the robustness of the division operation under extreme boundary conditions, when the system approaches the critical point of the production scheduling time window, causing the total number of remaining discrete time steps from the optimal idle production scheduling time window to approach 0, the inverse thermodynamic solution module will actively bypass the compensation formula and directly use the currently observed average ambient temperature as the output constant, avoiding overflow errors in computing resources.

[0067] S402, the target environmental temperature curve generated solely based on mathematical derivation risks deviating from actual physical limitations. To prevent internal thermal stress concentration and shrinkage cracks caused by excessive temperature rise due to the system's unilateral pursuit of timeliness, the inverse thermodynamics solution module introduces a multi-dimensional engineering thermodynamic boundary threshold comparison and verification mechanism after generating preliminary time-series temperature data.

[0068] In practice, the system extracts the estimated temperature values ​​generated by the above formula at each time step and performs dual limit checks on the maximum temperature and the heating rate. On one hand, the system verifies the... The system checks whether the target temperature of the microenvironment at each future time step exceeds the maximum temperature safety threshold boundary. This maximum temperature safety threshold is usually set to no more than 65 degrees Celsius based on the peak heat release characteristics of concrete hydration. On the other hand, the system verifies whether the temperature rise slope exceeds the maximum temperature rise rate threshold boundary by performing differential conversion on the estimated temperature of adjacent time steps. This maximum temperature rise rate threshold is usually limited to a temperature rise of no more than 15 degrees Celsius per hour according to bridge construction technical specifications.

[0069] If the system determines that a data node has crossed the aforementioned thermodynamic boundary, it outputs a true result for the boundary violation, and the inverse thermodynamic solution module will trigger an internal callback mechanism. To avoid conflicts with the time constraints output by the linear programming scheduling module, the system dynamically adjusts the first boundary of some violation intervals while keeping the total maturity compensation integral area constant. The temperature curve smoothing coefficient for each future time step is adjusted to reduce peaks and fill troughs, thereby performing multiple rounds of thermodynamic rebalancing iterations until the generated full-cycle temperature trajectory is within the multidimensional safety threshold envelope.

[0070] S403, based on the inverse solution deduction after the aforementioned multi-dimensional boundary verification, the system completes the data convergence for on-site time-temperature and thermal environment intervention. As a preferred approach, the computer-aided management and core algorithm layer encapsulates and solidifies this verified multi-dimensional time-series data chain to generate the final compliance intervention scheduling plan. Considering that the temperature curve calculated by the upper-layer software cannot directly drive the electromechanical physical devices on-site, the system needs to further perform protocol conversion of the underlying hardware adjustment commands. The system calls the existing proportional-integral-derivative control algorithm to dynamically compare the expected target temperature given in the compliance intervention scheduling plan with the real-time feedback temperature currently uploaded by the physical sensing and execution layers.

[0071] To adapt to the high inertia and thermal conductivity characteristics of large-volume concrete in cantilever box girders, the system maps the three gain parameters of the control algorithm to physical meaning: the proportional term outputs the duty cycle of foundation heating or spraying based on the instantaneous temperature deviation; the integral term is used to accumulate and eliminate steady-state errors caused by natural heat dissipation over long periods; and the derivative term intervenes in advance based on the slope of the temperature change trend, effectively suppressing heat overshoot generated when high-power heating equipment starts and stops. Based on the calculated comprehensive deviation compensation, the system uses a built-in communication protocol parsing library to convert the compensation into relay opening and closing timing and analog level output parameters that can be directly recognized by the programmable logic controller. Finally, the encapsulated standard digital message is integrated into the compliance intervention scheduling plan for temporary storage and locking. After the spatial topology interference detection in step S5 passes, the system will then send the message to the industrial control execution hardware on site via the downlink network link. The industrial control execution hardware includes an automatic sprinkler system, solenoid valve group, and heating equipment that, based on the received instruction duty cycle, coordinate to execute physical water flow spray cooling or thermal radiation heating actions, thereby achieving closed-loop two-way overall control of construction progress and the quality of the bridge cantilever components in the actual physical field.

[0072] The specific execution steps for intelligent monitoring of bridge cantilever construction construction, which involve the S5 building information modeling engine receiving compliance intervention scheduling plans, extracting corresponding special equipment operation actions to generate 3D solid envelope surfaces, performing 4D spatial topological intersection operations to output spatial topological interference detection results, are detailed below: S501, after generating the aforementioned compliance intervention scheduling plan, relying solely on time-dimensional planning and thermodynamic boundary constraints is insufficient to guarantee the operational safety of the on-site special equipment cluster. To map one-dimensional time-series scheduling instructions to a three-dimensional physical work space, in this embodiment, the building information modeling engine built into the computer-aided management and core algorithm layer receives the compliance intervention scheduling plan and extracts the corresponding special equipment operation actions from the underlying database. Before performing specific spatial simulations, the system, based on the principle of rigid body kinematics, decouples the physical movement of the equipment into an affine transformation process of rotation and translation. Based on the extracted mechanical operating parameters and the initial three-dimensional absolute coordinates continuously acquired by the spatial data acquisition equipment, the building information modeling engine initiates the three-dimensional solid envelope surface generation program. To eliminate structural sway and attitude deviations during mechanical operation, the system uses a dynamic spatial envelope boundary calculation formula to derive the equipment occupancy space at each prediction moment. The dynamic spatial envelope boundary calculation formula is: ; in, Indicates the first The set of boundary coordinates of the three-dimensional entity envelope surface at each predicted and extrapolated time point. Indicates the first The device attitude rotation matrix at each predicted and simulated moment. This represents the intrinsic geometric topology matrix of the special equipment, which is obtained by parsing the fixed node coordinates of the equipment's factory-issued building information model. This represents the preset physical safety redundancy constant matrix, used to characterize the buffer boundary that extends outward from each geometric vertex along the surface normal vector. The basic extension constant in this matrix is ​​set according to the physical product of the maximum operating speed of the special equipment and the response delay period of the braking system, and the value ranges from 0.5 meters to 1.5 meters. Indicates the first The device space translation vector at each predicted simulation time.

[0073] Before performing the matrix multiplication operation described above, the system performs the following steps: The orthogonality of the device attitude rotation matrix at each predicted time point is checked. If a drift in the matrix determinant is detected, leading to a singularity risk, the system introduces a Schmitt orthogonalization compensation algorithm for adaptive correction, thereby avoiding distortion of the geometric entity volume due to matrix degradation.

[0074] The technical purpose of this formula is to transform the original static equipment drawing model into a four-dimensional spatial envelope that dynamically extends with the time axis through matrix affine transformation and safety boundary expansion, thereby establishing a reliable mathematical reference surface for subsequent collision avoidance simulation.

[0075] S502, after acquiring the aforementioned dynamic envelope surface data, the system enters the spatiotemporal topology comparison stage for multi-source parallel operation hazard sources. To ensure the alignment of working conditions in the multi-source parallel operation data, the Building Information Modeling (BIM) engine pre-introduces a globally unified time reference and synchronously latches the prediction and extrapolation time index numbers of all special equipment and work surfaces on site, thereby eliminating asynchronous extrapolation errors caused by network transmission jitter. In bridge cantilever casting construction sites, the cross-operation of multiple special equipment or concrete placing booms in the same airspace poses a physical risk of structural collisions. The BIM engine will assign the current equipment to be scheduled the first... The coordinate set of the boundary of the three-dimensional entity envelope surface at each predicted time point is used to verify the spatiotemporal overlap with the dynamic spatial trajectory of the remaining operating or scheduled equipment on site.

[0076] For the underlying computational logic of 3D spatial collisions, those skilled in the art can use existing separating axis theorem algorithms to perform polyhedral intersection calculations. The basic principle of this algorithm lies in finding a one-dimensional projection axis (usually the normal vector of the polyhedral surface or the cross product vector of the geometric edges) that can completely separate two 3D convex hull entities. This is a well-known technique in the field and will not be elaborated further here.

[0077] To prevent spatial penetration between adjacent frames caused by excessively large discrete time steps, the Building Information Modeling (BIM) engine dynamically and adaptively reduces the time slice based on the maximum relative composite speed of each device in the scene during simulation. Within the time span corresponding to the optimal idle scheduling window, the BIM engine performs frame-by-frame calculations along the time axis using the adaptively adjusted simulation step size, accumulating the calculated interference volume parameters. During this accumulation process, the underlying system automatically performs floating-point tolerance filtering to eliminate minimum noise caused by computer precision, and finally performs a four-dimensional spatial topological intersection operation to output the spatial topological interference detection result. This detection result, in the form of a physical interference volume value, visually represents the degree of three-dimensional overlap under the current spatiotemporal slice.

[0078] S503, after completing the four-dimensional spatial topology intersection operation, the system's underlying architecture performs a veto check on the scheduling plan based on the obtained data. This mechanism executes logical branch judgments by reading the spatial topology interference detection results. If the interference volume value in the detection result is greater than zero, it indicates that although the current compliant intervention scheduling plan meets the requirements in terms of time axis and thermodynamic indicators, there is a risk of mechanical collision in the actual physical space. Based on this judgment, the system triggers a veto instruction to abolish the current scheduling plan and sends an interference signal back to the linear programming scheduling module, instructing it to re-search and lock a new available time window while avoiding the current conflict space. Conversely, when the spatial topology interference detection result is zero, the system determines that the time-space temperature paths are independent and non-interfering in the physical field, realizing intelligent monitoring of bridge cantilever casting construction. Under this safe state, the system can release the plan and issue a resource scheduling matrix work order containing underlying physical hard-wired interlocking instructions, providing underlying data and control support for the orderly conduct of on-site construction operations.

[0079] Regarding the specific execution steps of the resource scheduling matrix work order that includes underlying physical hard-wired interlock instructions when the spatial topology interference detection result is zero in S6 above, the following sub-steps are provided in detail: S601, after confirming that there are no interference conflicts in the time and spatial dimensions of the current plan, i.e., when the spatial topological interference detection result is zero, the computer-aided management and core algorithm layer encapsulates the scheduling plan that has passed compliance verification and generates a resource scheduling matrix work order. To ensure the visualization and executability of on-site construction operations, in this embodiment, the system renders the time window nodes, equipment numbers, and spatial coordinate scheduling parameters in the work order into a two-dimensional view, transforming them into visual interface data for manual operation. This data covers the expected movement trajectory and safe operating range of the equipment in three-dimensional space, and is transmitted to the vehicle-mounted terminal in the special equipment operation room or the handheld display device of the ground personnel through a wireless local area network, realizing the dispatch of the visual resource scheduling matrix work order for manual operation; at the same time, the system extracts and releases the underlying hardware adjustment instructions temporarily stored in the compliant intervention scheduling plan, triggering the underlying thermal environment physical intervention action. Based on this intuitive task issuance mechanism, on-site operators can clearly understand the electromechanical operation actions that should be performed within the current optimal idle production time window, thereby providing a human-machine collaborative scheduling basis for bridge cantilever casting operations.

[0080] In S602, while issuing visual work instructions to the manual operator, the system simultaneously initiates the special equipment restricted 3D coordinate analysis and low-level over-authorization interlocking program to form the underlying physical closed-loop control logic. The computer-aided management and core algorithm layer extracts and parses the boundary contour outside the currently permitted work area from the resource scheduling matrix work order, converting its spatial parameters into special equipment restricted 3D coordinates. To ensure the consistency of the coordinate reference between the upper and lower computers, the system performs coordinate system affine transformation alignment before sending data, thereby eliminating translation and rotation deviations between the global building information model coordinate system and the local programmable logic control coordinate system. This coordinate data is converted and encapsulated into standard industrial fieldbus protocol messages for low-level control via the edge computing gateway of the edge transmission layer, and then sent to the industrial control execution hardware in the field.

[0081] In this embodiment, the industrial control execution hardware includes a special equipment programmable logic control cabinet. The storage unit inside the control cabinet receives and latches the aforementioned three-dimensional coordinates of the special equipment's restricted area, setting them as the bottom-level electronic fence boundary for the current operation phase.

[0082] In actual on-site construction operations, the special equipment programmable logic control cabinet continuously receives real-time three-dimensional absolute coordinates of the special equipment acquired by the spatial data acquisition equipment. The control cabinet, relying on its built-in logic operation unit, performs high-frequency cyclic comparisons between these real-time three-dimensional absolute coordinates and the internally latched restricted three-dimensional coordinates of the special equipment. Since the restricted three-dimensional coordinates form polygonal boundaries in space, the distance calculation inside the control cabinet is not a simple point-to-point calculation, but rather calculates the shortest normal projection distance from the current coordinate point of the equipment to the nearest electronic fence plane. When calculating the distance from a spatial point to a plane, those skilled in the art can use existing analytical geometric point-to-plane distance formulas. The algorithm for obtaining the normal projection distance by substituting the plane equation coefficients and the current coordinates of the equipment is well-known in the field and will not be elaborated upon here.

[0083] As a preferred approach, to avoid false triggering of anti-collision measures due to relying solely on a single spatial distance threshold, the system comprehensively considers the dynamic physical kinetic energy of the equipment. The aforementioned comparison logic incorporates the real-time operating speed of the equipment to dynamically adjust the buffer tolerance range of the prohibited three-dimensional coordinate extension. The basic threshold of this range is typically set to 1.2 to 1.5 times the maximum braking distance of the special equipment under full-load conditions, thus reserving sufficient response time for the mechanical braking mechanism. Based on this multi-dimensional weighted comparison result, when the real-time three-dimensional absolute coordinates of the special equipment on site intrude into the aforementioned dynamically set buffer tolerance range, it indicates a risk of human error or mechanical slippage of the equipment.

[0084] S604, based on the aforementioned boundary-crossing trigger state, the special equipment programmable logic control cabinet takes precedence over the scheduling instructions of the upper-level software, activating its internal hard-wired power-off interlocking circuit. This circuit utilizes the normally closed state switching of physical relay contacts to directly cut off the input control power supply of the special equipment motor frequency converter or trigger a safety torque cancellation signal, causing the mechanical actuator to enter an emergency braking state. By introducing this hard-wired boundary-crossing interlocking mechanism of the underlying programmable logic controller, the system, on top of the logic anti-collision foundation of software scheduling, adds a physical and electrical layer-level power-off intervention. This mechanism directly cuts off the equipment power source in emergency situations, reducing the risk of equipment collisions during multi-source parallel operations at the bridge cantilever casting site, and realizing a complete closed-loop control from computer-aided management and core algorithm layer system deduction to physical perception and execution layer on-site response.

[0085] To aid in understanding the present invention, a specific application example is provided in conjunction with a real bridge engineering application scenario, along with experimental verification and effect comparison data based on calculations under real working conditions.

[0086] In this embodiment, the physical field is set as the construction site of a cantilever bridge spanning a river. The construction site has four cantilever work surfaces and is equipped with two large specialized pieces of equipment (such as tower cranes or concrete placing booms) for formwork transport and concrete pouring. The physical sensing and execution layer acquires the level signals from the underlying physical hardware and converts them into a multi-source heterogeneous data stream containing timestamps. Taking one monitoring cycle as an example, the temperature and humidity sensor network collects data from the embedded thermistors inside work surface number two, showing a core concrete temperature of 38 degrees Celsius and a surface concrete temperature of 35 degrees Celsius. The difference between these two values ​​is within the safe tolerance range.

[0087] To predict the time when concrete components reach the demolding standard, the system extracted historical sequence data of microenvironmental temperature and substituted it into the Nurse-Saul maturity calculation formula to calculate cumulative maturity. Here, the reference temperature constant for the cessation of hydration reaction of the special cement used was set to -10 degrees Celsius, and the duration of a single discrete time step sampled by the system was set to 1 hour. In the past time step, the average microenvironmental temperature was measured to be 25 degrees Celsius. Substituting this value into the formula, the newly generated maturity value within this discrete time step is (25 minus -10) multiplied by 1, resulting in 35 degrees Celsius per hour. After continuous multi-step integration calculations along the time axis, combined with the future temperature prediction curve obtained from the external meteorological interface, the computer-aided management and core algorithm layer predicted that the absolute time node for the concrete components of the second work surface to reach the required strength was 45 hours after the completion of pouring.

[0088] After obtaining the absolute time node, the system initiates a baseline schedule comparison. The Building Information Modeling (BIM) engine, through four-dimensional spatial simulation, discovers that within the 45th hour physical time slice, special equipment number one is planned for the overall hoisting of the steel frame on work surface number three, resulting in a conflict in spatial resource occupancy and time overlap. The system's underlying logic then suspends the original work plan and triggers the progress scheduling procedure. The linear programming scheduling module retrieves two alternative idle scheduling windows that meet the basic process requirements and performs a cost comparison using a comprehensive time penalty cost calculation formula. In this embodiment, based on historical project ledgers, the timeliness deviation penalty weight coefficient is set to 0.7, and the equipment switching and basic idle penalty constant is set to 0.3. The starting point offset of alternative time window A is 3 hours; substituting this into the formula, the calculated comprehensive time penalty cost is 0.7 multiplied by 3 plus 0.3, resulting in 2.4. The starting point offset of alternative time window B is 1 hour, and the calculated comprehensive time penalty cost is 0.7 multiplied by 1 plus 0.3, resulting in 1.0. After iterative convergence, the system locks the alternative time window B with the minimum cost as the optimal idle scheduling time window.

[0089] Because the production schedule was shifted back by one hour, to ensure that the concrete strength would not deviate from the project's expected value when the new time window arrived, the inverse thermodynamics solution module used the inverse equivalent age compensation formula to calculate the target microenvironment temperature. It was assumed that there was a 100°C·hour difference in cumulative maturity between the current time and the standard demolding time, and the total number of remaining discrete time steps before the optimal idle production window was 4. To avoid high-frequency oscillations in the hardware output, the temperature curve smoothing adjustment coefficient was set to 1.0. Substituting the relevant parameters into the formula, the new target microenvironment temperature was derived as -10 plus (100 divided by 4) multiplied by 1.0, resulting in 15°C. The system further verified this value, confirming that it did not exceed the maximum safe temperature threshold of 65°C, and that the temperature change amplitude of adjacent time sequences remained within the maximum temperature change rate of 15°C per hour. After successful verification, the industrial control hardware drove the solenoid valve group of the automatic sprinkler system according to the underlying protocol messages, performing physical space cooling intervention.

[0090] See attached document Figure 3 , Figure 3The solid black line marked with a square represents the change in the overall time penalty cost of the system of this invention, while the dark gray dashed line marked with a circle represents the change in the overall time penalty cost of traditional manual scheduling. Through extraction and analysis of bottom-level monitoring data from twenty consecutive construction cycles at the bridge cantilever casting construction site, it can be found that the traditional scheduling mode, which relies on the experience of on-site personnel, typically adopts a passive delaying strategy when encountering overlapping multiple processes. Due to the lack of a global time perspective, this mechanical delay causes the penalty cost represented by the dark gray dashed line marked with a circle to show a significant cumulative divergence trend over time. In the latter half of the work cycle, the combined value of system energy consumption and construction delay exceeds a relatively high level.

[0091] The data results output by the present invention show that after the system triggers the schedule scheduling procedure, it uses a mixed-integer linear programming algorithm to reorganize the time window, causing the black solid line marked with a square to continuously converge within a very low and stable numerical range, with the overall cost never exceeding the 2.0 limit. This comparative data precisely verifies the feasibility of the multi-objective decision-making model in this invention in resolving temporal interference of complex spatial resources, and reduces redundant engineering costs caused by the deterioration of special equipment and construction delays.

[0092] See attached document Figure 4 , Figure 4 The unmarked black solid line represents the target temperature curve of the microenvironment, the dark gray dotted line with a star mark represents the actual perceived temperature curve on site, and the light gray dashed line with a triangle mark represents the traditional natural curing temperature curve. Within the 48-hour monitoring window selected in this embodiment, the production scheduling system proactively postponed the operation time boundary due to equipment interference. In response to the change in physical time, the inverse thermodynamics solution module proactively raised the baseline of the expected heat during the hydration reaction period.

[0093] From a physical perspective, influenced by the closed-loop regulation of the system's underlying proportional-integral-derivative (PID) control algorithm and the physical intervention of the industrial control hardware, the dark gray dotted line marked with a star can overcome the large inertia and thermal damping characteristics of the bridge components, closely adhering to the unmarked black solid line for dynamic climbing and steady-state maintenance. However, the light gray dashed line marked with a triangle, detached from system control, relies solely on the component's own heat release and natural environmental heat dissipation, resulting in severe heat loss during the alternating day-night temperature cycle, rendering its accumulated maturity insufficient to support subsequent demolding operations. This experimental result directly demonstrates that the present invention possesses the technical capability to adaptively compensate for the equivalent age through underlying physical hydrothermal intervention when spatiotemporal boundaries change, achieving bidirectional coordinated control of project progress and component forming quality.

Claims

1. A smart monitoring system for bridge cantilever casting construction based on BIM and digital twins, characterized in that, include: The physical sensing and execution layer acquires on-site temperature, humidity, and coordinate parameters, which are then transmitted via the edge transmission layer to the computer-aided management and core algorithm layer to construct a global state matrix. The computer-aided management and core algorithm layer initiates an integral calculation program based on the global state matrix to predict the absolute time node for reaching the required intensity. The linear programming scheduling module receives the absolute time node, compares it with the baseline schedule, and triggers the progress scheduling program to lock the optimal idle scheduling time window. The inverse thermodynamics solution module calculates the remaining maturity index to be compensated based on the optimal idle production time window and the physical principle of reversibility of equivalent age integral using the inverse equivalent age compensation formula. The remaining maturity index to be compensated is evenly and smoothly spread into the optimal idle production time window sequence, and the basic thermodynamic reference trajectory is derived in reverse as the target temperature curve. The target temperature curve is subjected to physical specification verification covering both the maximum temperature and the heating rate limit, and the boundary node judgment result is output. If the boundary node judgment result is true, multiple rounds of thermodynamic rebalancing iteration are performed by dynamically adjusting the temperature curve smoothing adjustment coefficient of some violation intervals, and a multi-dimensional time-series data chain that is within the multi-dimensional safety envelope throughout the entire cycle is output, and the data is encapsulated and solidified to generate a compliance intervention scheduling plan. The building information modeling engine receives the compliance intervention scheduling plan, performs a four-dimensional spatial topology intersection operation, and outputs the spatial topology interference detection result. When the spatial topological interference detection result is zero, the system extracts compliance verification data to generate a resource scheduling matrix work order; it parses the boundary contour in the resource scheduling matrix work order and converts it into special equipment restricted three-dimensional coordinates for anti-collision comparison; it sends the special equipment restricted three-dimensional coordinates to the special equipment programmable logic control cabinet of the underlying industrial control execution hardware for latching and forming an electronic fence boundary; the special equipment programmable logic control cabinet compares the real-time three-dimensional absolute coordinates with the electronic fence boundary at high frequency; when it intrudes into the preset buffer tolerance range, the system activates and sends the underlying physical hard-wired interlock command contained in the resource scheduling matrix work order to cut off the control power supply at the input terminal of the special equipment motor frequency converter.

2. The intelligent monitoring system for bridge cantilever casting construction based on BIM and digital twins as described in claim 1, characterized in that, The physical sensing and execution layer acquires on-site temperature, humidity, and coordinate parameters, which are then transmitted via the edge transmission layer to the computer-aided management and core algorithm layer. The specific steps for constructing the global state matrix include: The physical sensing and execution layer acquires a multi-source heterogeneous data stream containing the on-site temperature, humidity, and coordinate parameters; The edge computing gateway of the edge transport layer receives the multi-source heterogeneous data stream, performs zero-order hold-sampling alignment and network packet encapsulation, and transmits standard Transmission Control Protocol (TCP) messages. The computer-aided management and core algorithm layer receives the standard transmission control protocol messages, uses the global state matrix aggregation formula to calculate, and constructs the global state matrix that spans the environmental physical domain and the mechanical operation domain, forming a unified data base.

3. The intelligent monitoring system for bridge cantilever casting construction based on BIM and digital twins as described in claim 1, characterized in that, The computer-aided management and core algorithm layer initiates an integral calculation program based on the global state matrix to predict the absolute time node for reaching the required strength. The specific steps include: The computer-aided management and core algorithm layer performs dimensionality reduction extraction based on the global state matrix and inputs it into the integral calculation program to generate historical microenvironment temperature data. The cumulative maturity of the historical microenvironment temperature data is calculated using the Nurse-Saul maturity calculation formula, and the future microenvironment temperature evolution sequence is inferred by combining external meteorological data to form a predicted maturity data chain. The predicted maturity data chain is mapped to the compressive strength approximation rate using a hyperbolic evolution model of concrete strength maturity; When the compressive strength approximation rate first meets the demolding or release strength threshold requirement and simultaneously meets the minimum curing days time constraint, the corresponding physical time point is extracted, and the absolute time point for reaching the strength required by the specification is predicted. The demolding or tension strength threshold is set to more than 90% of the preset compressive strength.

4. The intelligent monitoring system for bridge cantilever construction based on BIM and digital twins as described in claim 1, characterized in that, The linear programming scheduling module receives the absolute time node, compares it with the baseline schedule, and triggers the progress scheduling procedure in the following steps: The linear planning scheduling module receives the absolute time node and queries the preset baseline schedule, extracting the planned time period data of related special equipment before and after the absolute time node; The expected operation time period is generated by combining the space operation and transfer time along the time axis to extrapolate the planned occupation time period data; Based on the preset benchmark scheduling comparison logic, the expected work time period and the planned occupation time period data are subjected to time domain intersection operation to output the intersection duration; When the intersection duration is greater than zero, it is determined that there is a time sequence overlap, the original work plan is suspended, and the progress scheduling procedure for allocating time and space resources is triggered.

5. The intelligent monitoring system for bridge cantilever casting construction based on BIM and digital twins as described in claim 4, characterized in that, The specific steps of triggering the progress scheduling procedure to lock the optimal idle production time window include: The scheduler calls a mixed-integer linear programming algorithm to set the optimization objective as minimizing the comprehensive time penalty cost, and uses the comprehensive time penalty cost calculation formula to calculate and output the objective cost. Under the constraints of exclusive use of special equipment resources and critical constraints of concrete curing time, iterative convergence calculation is performed based on the target cost value after traversing the equipment idle period after conflict nodes. Based on the available time interval that minimizes the comprehensive time penalty cost, the optimal idle scheduling time window is locked as a conflict-free benchmark reference boundary, according to the output of the iterative convergence calculation.

6. The intelligent monitoring system for bridge cantilever casting construction based on BIM and digital twins as described in claim 1, characterized in that, The building information modeling engine receives the compliance intervention scheduling plan and performs a four-dimensional spatial topological intersection operation preprocessing step, which specifically includes: The building information modeling engine receives the compliance intervention scheduling plan and extracts the corresponding special equipment operation actions; Based on the principle of rigid body kinematics, the space occupied by the special equipment at each predicted moment is derived by using the dynamic spatial envelope boundary calculation formula. The static equipment drawing model corresponding to the space occupied by the equipment is transformed into a four-dimensional spatial envelope that dynamically extends with the time axis, and a three-dimensional solid envelope surface is generated for four-dimensional spatial topological intersection operation.

7. The intelligent monitoring system for bridge cantilever construction based on BIM and digital twins as described in claim 6, characterized in that, The steps for performing a four-dimensional spatial topological intersection operation based on the three-dimensional entity envelope surface and outputting the spatial topological interference detection result specifically include: The coordinate set of the boundary of the three-dimensional entity envelope surface is verified to overlap with the dynamic spatial trajectory of the other production scheduling equipment on site in a spatiotemporal manner. Based on the spatiotemporal overlap verification, the separation axis theorem algorithm is used to perform polyhedral intersection calculations frame by frame along the time axis, and the interference volume parameters are accumulated to generate the interferometric volume parameters. Based on the interference volume parameters, the four-dimensional spatial topological intersection operation is performed, and the spatial topological interference detection result, which characterizes the degree of overlap of three-dimensional physical interference, is output.

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