A construction project full life cycle resource intelligent scheduling system and method

Abstract

The present invention discloses a system and method for intelligent resource scheduling for the entire life cycle of a construction project, which belongs to the field of building management technology, and specifically comprises: in the construction phase, collecting dynamic physical parameters of the component installation process; constructing a spatiotemporal indexing engine, associating the dynamic physical parameters with the corresponding component nodes of the BIM model, and generating spatiotemporal binding data units; in the project operation and maintenance phase, monitoring the component operation status data, and when an abnormal state is identified, extracting the current spatial coordinates of the abnormal component and activating a reverse tracing channel; using the spatial coordinates of the abnormal component as a retrieval anchor point, matching the spatiotemporal binding data units with the same spatial coordinates, and obtaining a dynamic physical parameter sequence for the construction phase; comparing and mapping the dynamic physical parameter sequence with the abnormal state, generating an operation and maintenance decision instruction set with a construction defect positioning identifier, and inputting the instruction into a resource scheduling sequence; the present invention significantly improves the utilization rate of construction phase data for operation and maintenance decisions.

Description

Technical Field

[0001] The present invention relates to the technical field of building management, and in particular to a system and method for intelligent resource scheduling throughout the life cycle of a construction project. Background Art

[0002] In the full lifecycle management of construction projects, the post-completion operation and maintenance phase is a critical step in ensuring the long-term safety and performance of buildings. With the widespread adoption of BIM (Building Information Modeling) technology and IoT sensors, the construction phase has enabled the precise recording of building component geometry, equipment installation processes, and environmental data. During the operation and maintenance phase, dynamic information such as structural vibration and equipment operating status can be obtained through real-time monitoring. However, in current engineering practices, as-built BIM models and the building and equipment installation data accumulated during the construction process are often archived as static documents, creating information silos with the real-time monitoring data from the operation and maintenance phase. This results in the inability to effectively unlock the value of data throughout the entire lifecycle.

[0003] Existing O&M strategies primarily rely on real-time equipment operation data collected by IoT sensors and manual inspection results, identifying anomalies by comparing current status with preset thresholds. When a problem occurs with a building structure or equipment, technicians typically analyze it based solely on real-time data and the target status at the time of the problem, such as identifying equipment failures using vibration sensor data or assessing structural damage using crack monitors.

[0004] Although this conventional operation and maintenance method can meet basic operation and maintenance needs, it has significant limitations: on the one hand, the spatial coordinates, material properties and installation process details of the components contained in the completed BIM model, and the spatiotemporal data recorded during the construction process are not effectively activated, resulting in a lack of systematic understanding of the entire life cycle of the building in operation and maintenance decisions; on the other hand, the problem analysis is only targeted at the current status and fails to link to key data in the construction phase, making it difficult to locate the cause of the defects from the root, resulting in a lack of targeted maintenance solutions. Summary of the Invention

[0005] The purpose of the present invention is to provide a system and method for intelligent resource scheduling throughout the life cycle of a construction project to solve the following technical problems:

[0006] The BIM models and spatiotemporal data accumulated during the construction phase are dormant and have not formed a cross-phase association with the real-time monitoring data during the operation and maintenance phase. This has led to long-term reliance on manual experience for operation and maintenance decisions, making it impossible to formulate precise strategies using the digital genes formed by the building during the construction process.

[0007] The purpose of the present invention can be achieved through the following technical solutions:

[0008] A construction project full life cycle resource intelligent scheduling system and method, comprising the following steps:

[0009] During the construction phase of a building project, embedded sensors are used to collect dynamic physical parameters of the component installation process. These dynamic physical parameters include component morphology change trajectories, connector stress change curves, and environmental force time series data.

[0010] Construct a spatiotemporal indexing engine to associate the dynamic physical parameters with the corresponding component nodes of the BIM model, synchronously record the spatial coordinates and time nodes of the component nodes during the construction phase, and generate spatiotemporal binding data units;

[0011] During the engineering operation and maintenance phase, the system continuously receives component operation status data monitored by IoT terminals. When an abnormal state is identified, the current spatial coordinates of the abnormal component are extracted and the reverse traceability channel is activated.

[0012] Through the reverse tracing channel, the current spatial coordinates of the abnormal component are used as the retrieval anchor point, and the spatiotemporal binding data units with the same spatial coordinates are matched to obtain the dynamic physical parameter sequence of the abnormal component during the construction phase;

[0013] The dynamic physical parameter sequence of the construction phase is compared and mapped with the abnormal state of the operation and maintenance phase to generate an operation and maintenance decision instruction set with construction defect location identification and input it into the resource scheduling sequence.

[0014] As a further solution of the present invention: the specific process of generating the spatiotemporal binding data unit is:

[0015] Create an independent storage container for each component node in the BIM model. The storage container contains a spatial coordinate field, a time node field, and a dynamic parameter storage area.

[0016] When executing the component installation operation, the final spatial coordinates of the component are obtained in real time, and the data acquisition function of the embedded sensor is activated synchronously to obtain the instant when the component installation is completed. The dynamic physical parameters collected in the continuous time window before and after this moment are packaged at the millisecond time granularity and associated with the storage container corresponding to the component;

[0017] An environmental correction coefficient is added to the spatial coordinates in the storage container. The environmental correction coefficient is dynamically calculated based on the correction amount corresponding to the air pressure gradient during the construction phase, the correction amount corresponding to the foundation settlement rate, and the correction amount corresponding to the temperature and humidity change curve. It is used to compensate for the spatial coordinate offset caused by building deformation.

[0018] As a further solution of the present invention, the specific process of associating the dynamic physical parameters with the storage container is as follows:

[0019] The time origin is set as the moment when the component installation is completed, and the time origin is traced back to the initial moment when the installation equipment contacts the component, and extended backward to the final moment when the adjacent components are installed.

[0020] All sensor data of the target component and the contact component within the time period are intercepted and decomposed into discrete data units in chronological order; each data unit is marked with the time offset relative to the time origin and bound to the component space coordinates recorded by the positioning device to form a time-space bound data unit chain.

[0021] As a further solution of the present invention: the method of activating the reverse tracing channel is specifically:

[0022] A real-time mirror model of the building information model during the operation and maintenance phase is established. When the IoT device detects abnormal component vibration characteristics, sudden temperature distribution changes, or stress levels exceeding the limit, the component is marked as an abnormal node, the 3D spatial coordinates of the abnormal node are extracted, and the historical component nodes within the error range of the abnormal node's spatial coordinates are searched in the mirror model.

[0023] If the historical component node exists in the spatiotemporal binding data unit library of the construction phase, the reverse traceability channel is started; if the mirror model shows that the current component is a replacement part during the operation and maintenance period, the construction identification code in the replacement part installation record is retrieved, and the process jumps to the spatiotemporal binding data unit library of the historical project associated with the construction identification code to perform traceability.

[0024] As a further solution of the present invention, the process of tracing the construction identification code to the spatiotemporal binding data unit library of historical projects is as follows:

[0025] During component replacement, the identity code of the new component is read, and based on the supplier identifier in the identity code, the supply chain database is accessed to obtain the production batch code and factory parameter set of the component; the production batch code is matched with the construction company's project database, and the historical project code of the first installation of the batch of components is located. Based on the historical project code, the corresponding spatiotemporal binding data unit library is loaded to realize cross-project jump of the reverse traceability channel.

[0026] As a further solution of the present invention: the specific process of the comparison mapping is:

[0027] The physical parameters of abnormal state in the operation and maintenance stage are expanded into operation and maintenance state waveform diagrams according to the time dimension; the construction process waveform diagrams of the same type of parameters are extracted from the dynamic physical parameter sequence in the construction stage;

[0028] Dual-track alignment is performed on the two waveforms. Taking the moment when component installation is completed during the construction phase as the reference point, the moment when the operation and maintenance anomaly occurs is mapped to the equivalent time axis after the reference point. The spectral coherence coefficient of the two waveforms within the equivalent time interval is calculated. When the spectral coherence coefficient exceeds the set threshold, it is determined that the operation and maintenance anomaly is associated with the dynamic physical parameters of the construction phase.

[0029] As a further solution of the present invention, determining whether an operation and maintenance anomaly is associated with a dynamic physical parameter during the construction phase is specifically as follows:

[0030] If there is a pulse peak in the construction process waveform that coincides with the phase of the operation and maintenance abnormal waveform, and the pulse peak occurs during the deformation recovery process when the component is not fully fixed, it is marked as an installation preload defect;

[0031] If the construction process waveform shows that environmental forces continue to act on the component connection area, and the abnormal operation and maintenance waveform shows the superposition characteristics of harmonics of the same frequency, it is marked as environmental cumulative damage;

[0032] If the construction process waveform records an interference event between adjacent components after installation is completed, and the operation and maintenance abnormal waveform shows a sharp increase in the energy of the corresponding frequency band within the equivalent time interval, it is marked as a cross-component chain reaction.

[0033] As a further solution of the present invention: the operation and maintenance decision instruction set specifically includes:

[0034] For components marked with installation preload defects, a reinstallation instruction is sent to the maintenance terminal, along with the stress relief path optimization plan recorded during the construction phase;

[0035] For components marked with environmental cumulative damage, apply to the resource scheduling system for the installation of buffer devices. The design parameters of the buffer devices are generated based on the environmental force waveform during the construction phase.

[0036] For components that mark cross-component chain reactions, the detection equipment is assigned the task of scanning the interference status of adjacent components, and the scanning range is determined according to the time and space coordinates of the interference events during the construction phase.

[0037] As a further solution of the present invention: the design parameters of the buffer device are:

[0038] The time series records of environmental forces during the construction phase of abnormal components are extracted from the spatiotemporal binding data unit, and the core frequency components and amplitude fluctuation range of the environmental force waveform are identified. A hydraulic buffer with reverse vibration cancellation characteristics is designed. The frequency response characteristics of the hydraulic buffer correspond to the core frequency components of the environmental force. The stroke limit value and pressure adjustment rate of the hydraulic buffer are calculated based on the amplitude fluctuation range.

[0039] The present invention also includes a construction project full life cycle resource intelligent scheduling system for implementing the above-mentioned construction project full life cycle resource intelligent scheduling method, comprising:

[0040] A database for storing dynamic physical parameters collected during the component installation process by embedded sensors during the construction phase of a building project. The dynamic physical parameters include component morphology change trajectories, connector stress change curves, and environmental force time series data;

[0041] A spatiotemporal association module is used to build a spatiotemporal indexing engine, associate the dynamic physical parameters with the corresponding component nodes of the BIM model, synchronously record the spatial coordinates and time nodes of the construction phase of the component nodes, and generate spatiotemporal binding data units;

[0042] The operation and maintenance monitoring module is used to continuously receive component operation status data monitored by IoT terminals during the project operation and maintenance phase. When an abnormal state is identified, the current spatial coordinates of the abnormal component are extracted and the reverse traceability channel is activated;

[0043] A parameter backtracking module is used to obtain the dynamic physical parameter sequence of the abnormal component during its construction phase by matching the spatiotemporal bound data units with the same spatial coordinates through the reverse tracing channel;

[0044] The operation and maintenance decision module is used to compare and map the dynamic physical parameter sequence of the construction phase with the abnormal state of the operation and maintenance phase, generate an operation and maintenance decision instruction set with construction defect location identification, and input it into the resource scheduling sequence.

[0045] Beneficial effects of the present invention:

[0046] The present invention effectively solves the problems of dormant construction data and lack of systematic operation and maintenance decision-making in the existing technology by constructing a cross-temporal and spatial correlation mechanism between dynamic data in the construction phase and abnormal states in the operation and maintenance phase. The present invention uses embedded sensors to collect dynamic physical parameters such as morphological change trajectories and stress curves during the component installation process in real time, and uses a spatiotemporal indexing engine to accurately bind them to the BIM model component nodes. Additional environmental correction coefficients are added to compensate for building deformation, forming a spatiotemporal binding data unit containing spatial coordinates, time nodes, and full-dimensional physical parameters. This activates the static construction phase data in the completed BIM model and provides systematic data support for the entire life cycle of the building for operation and maintenance decisions. Secondly, when an operation and maintenance anomaly is identified, a reverse traceability channel is activated with the spatial coordinates of the abnormal component as the anchor point by establishing a real-time operation and maintenance mirror model. This not only matches historical construction data with the same coordinates, but also allows cross-project tracing of the original installation records of the replaced components through supply chain coding, breaking through the data barriers of a single project and achieving a leap from current status analysis to full-process causal traceability. Through deep binding of spatiotemporal data, cross-stage intelligent tracing, and automated diagnosis of defect types, the present invention significantly improves the utilization of construction phase data in operation and maintenance decisions, realizes the intelligent upgrade of resource scheduling throughout the life cycle of buildings, effectively reduces operation and maintenance costs, and improves the pertinence and efficiency of defect repair. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] The present invention will be further described below with reference to the accompanying drawings.

[0048] Figure 1This is a flow chart of a method for intelligent resource scheduling throughout the life cycle of a construction project according to the present invention;

[0049] Figure 2 It is a module schematic diagram of an intelligent resource scheduling system for the entire life cycle of a construction project according to the present invention. DETAILED DESCRIPTION

[0050] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts shall fall within the scope of protection of the present invention.

[0051] See also Figure 1 As shown, the present invention is a method for intelligent resource scheduling throughout the life cycle of a construction project, comprising the following steps:

[0052] During the construction phase, embedded sensor networks are deployed in key locations. For example, fiber grating sensors, attached to the steel structure's surface, capture in real time the structural changes of the component under load. Strain gauge sensors monitor stress curves at bolted connections and welded joints. Environmental monitoring equipment collects environmental parameters such as wind speed, temperature, humidity, and air pressure to generate time-series data on environmental forces. These sensors sample data at millisecond frequencies, and the data is pre-processed by edge computing to form a standardized data stream.

[0053] To integrate construction data with the BIM model, a spatiotemporal indexing engine was built. A dedicated storage container was created for each component node in the BIM model, containing spatial coordinates, time nodes, and dynamic parameter storage areas. Upon component installation, ultra-wideband positioning technology was used to obtain 3D coordinates. A high-precision clock was used to record the installation moment. Dynamic parameters within the preceding and following time windows were captured and associated with the corresponding storage container. Environmental correction factors were dynamically calculated based on data such as foundation settlement, temperature and humidity changes, and applied to the spatial coordinates to ensure accurate spatiotemporal data, generating spatiotemporally bound data units.

[0054] During the operation and maintenance phase, IoT terminals continuously collect operational status data such as component vibration frequency, stress, and temperature. When abnormalities are detected in the monitoring data, the 3D coordinates of the abnormal component are extracted and a reverse tracing channel is activated.

[0055] Using the spatial coordinates of the abnormal component as the retrieval anchor point, the spatiotemporal bound data units with the same coordinates are matched in the spatiotemporal index database constructed during the construction phase, and the morphological change trajectory, connector stress curve and environmental force history of the component during installation are quickly retrieved to achieve accurate association of data across stages.

[0056] The construction phase parameter sequence and operation and maintenance abnormal status data are expanded into a waveform diagram along the time dimension and aligned with the installation completion time. The feature similarity is calculated through the spectrum analysis algorithm to identify construction defects such as insufficient installation preload, environmental cumulative damage, and cross-component chain reactions. An operation and maintenance decision instruction set containing the defect type, location, and cause is generated and input into the resource scheduling system to drive the rational allocation of resources and realize the precise management of building operation and maintenance.

[0057] In a preferred embodiment of the present invention, the specific process of generating the spatiotemporal binding data unit is as follows:

[0058] When constructing a building information model, a separate storage container is created for each component node. This container serves as the fundamental unit for storing data throughout the component's lifecycle and contains three core fields. The spatial coordinate field is used to record the precise three-dimensional position of the component during the construction phase. Its data comes from the on-site real-time positioning system: ultra-wideband positioning tags are fixed to the component surface. Through signal interaction with multiple positioning base stations deployed at the construction site, the spatial coordinates X, Y, and Z are calculated with millimeter-level accuracy to ensure consistency with the component's actual installation position. The time node field uses a high-precision clock system to record the instant when the component is installed. This time point is determined through two verification processes: first, reading the end-of-operation sensor signals of construction machinery such as tower cranes and hoists, and second, manual confirmation by construction personnel on the BIM collaborative management platform to form a reliable time base. The dynamic parameter storage area is used to categorize and store various physical parameters collected during the component installation process, including morphological change trajectories, stress curves of connectors, and environmental force data.

[0059] During component installation, the positioning system first acquires the component's final spatial coordinates in real time. These coordinates serve as the component's unique location identifier within the building space and are incorporated into data management throughout its lifecycle. Simultaneously, embedded sensors pre-deployed at key component locations are activated, including fiber grating (FBG) sensors bonded to the steel structure, strain gauges installed at bolt joints, and environmental monitoring equipment. These sensors continuously collect data throughout the component installation process: FBG sensors capture the component's three-dimensional deformation trajectory under load, strain gauges record tensile, compressive, and shear stress fluctuations in connectors, and environmental sensors collect environmental parameters such as temperature, humidity, and air pressure gradients. Centered on the moment component installation is completed, a continuous time window encompassing the critical installation process is defined, with the duration adjusted based on component type and installation process. All dynamic physical parameters collected during this time window are packaged with millisecond-level granularity. Each data packet contains information such as parameter type, timestamp, and value. A unique component identifier, such as an RFID tag code or BIM component ID, is mapped to a corresponding storage container, ensuring that dynamic data during the construction phase is accurately linked to the target component node in the BIM model.

[0060] Considering that environmental factors during the construction phase may cause slight offsets in component spatial coordinates, an environmental correction mechanism is introduced to dynamically compensate for the spatial coordinates in the storage container. The environmental correction factor is calculated based on three core factors: first, air pressure gradient. A network of pressure sensors deployed on-site acquires real-time air pressure data at different altitudes. Based on the physical property of air pressure varying with altitude, the vertical component of the spatial coordinates is corrected. Second, foundation settlement rate. Leveling points on site continuously monitor foundation deformation. Time series analysis is used to predict the cumulative settlement during component installation, which is then used to linearly adjust the Z-axis coordinates. Finally, the impact of temperature and humidity fluctuations is considered. An empirical model of temperature, humidity, and component dimensional deformation is established, combining the physical properties of component materials, such as the linear expansion coefficient of steel and the shrinkage rate of concrete, to calculate the correction for the three-dimensional coordinates. These corrections are combined using a weighted fusion algorithm to create a total environmental correction factor, which is automatically appended to the spatial coordinate field of the storage container. This ensures that the recorded spatial position reflects the component's true state in real time and effectively compensates for coordinate offsets caused by building deformation.

[0061] In a preferred embodiment of the present invention, the specific process of associating the dynamic physical parameters with the storage container is as follows:

[0062] The moment when the component installation is completed is set as the time origin. With the origin as the center, the time interval is traced back to the initial moment when the installation equipment first contacts the component, such as the moment when the crane hook touches the component lifting point, and extended backward to the end moment when the installation of the adjacent component is completed, that is, the time point when the support connected to the target component is fixed, forming a time interval covering the entire installation process.

[0063] During this timeframe, all sensor data from the target component and its contact components is captured synchronously. The target component refers to the currently installed main component, such as a steel column or precast beam. The contact component includes directly load-bearing components such as support brackets and connecting bolts. Sensors deployed on the component collect data: fiber Bragg grating sensors on the target component record deformation trajectories, strain gauges monitor node stress, sensors on the contact component provide feedback on the stress state of the connection, and environmental sensors simultaneously collect parameters such as temperature and humidity, forming a continuous data stream.

[0064] Decompose the continuous data stream into discrete data units at uniform time intervals. Each unit is labeled with a time offset relative to the time origin, for example, 30 seconds before the time origin is marked as -30,000 milliseconds, and 20 seconds after the origin is marked as +20,000 milliseconds. The unit is then bound to the component's spatial coordinates (X, Y, and Z) after environmental correction. This dual identification of time offset and spatial coordinates allows the data unit to be associated with the BIM model component node.

[0065] All discrete data units are linked in chronological order to form a data unit chain, which is stored in the dynamic parameter area of ​​the BIM model. For example, during steel column installation, the data chain records the deformation curve, bolt stress growth, and temperature and humidity effects from lifting and positioning to bolt tightening. This provides complete data for timeline retrieval during the operation and maintenance phase, achieving spatiotemporal binding of the entire process from installation equipment contact to adjacent component fixation, and constructing a digital record of the mechanical transmission between components.

[0066] In another preferred embodiment of the present invention, the method of activating the reverse tracing channel is specifically:

[0067] During the operation and maintenance phase, a real-time mirror model of the building information model is constructed. This model synchronizes the spatial position, operational status, and lifecycle attributes of building components in real time, forming a digital twin that corresponds one-to-one with the physical entity. When IoT devices deployed in various areas of the building detect an abnormal component state, such as a vibration sensor detecting a deviation from the normal vibration frequency, a temperature sensor detecting a sudden change in temperature distribution, or a stress sensor detecting a stress level exceeding the design threshold, the system immediately marks the component as an abnormal node and extracts its current 3D spatial coordinates through the positioning module.

[0068] The mirror model, based on a spatial coordinate matching algorithm, searches for historical component nodes within the spatiotemporal bound data unit library established during the construction phase. This matching process allows for a certain range of coordinate errors to accommodate minor positional shifts caused by factors such as foundation settlement and material deformation during the long-term use of the building. The mirror model first converts the three-dimensional coordinates of the abnormal node into a coordinate system consistent with the construction phase. It then defines a cubic search range centered on these coordinates. The search range radius is dynamically adjusted based on the building type and age, and the spatial coordinates of all historical component nodes within the range are retrieved. If a historical component node matching the abnormal node's coordinates exists within the search range, and this node exists in the spatiotemporal bound data unit library established during the construction phase, the reverse traceability channel is directly initiated to retrieve the component's dynamic physical parameters, installation time node, and environmental impact data from the construction phase.

[0069] If the mirror model shows that the current abnormal component is a replacement part during the operation and maintenance period, that is, a component not installed during the original construction phase, a special traceability process will be triggered. Each replacement part must be entered with a construction identification code during installation. The identification code contains the component identity code, replacement time, and related historical project information. The system first reads the identity code of the replacement part, which usually contains information such as the supplier identification and production batch number. Then, based on the supplier identification, it accesses the supply chain database to obtain the production batch code and factory parameter set of the component. The factory parameter set includes material performance indicators, processing parameters, etc. By matching the production batch code with the internal project database of the construction company, the historical project code of the first installation of the batch component is located, and finally the corresponding spatiotemporal binding data unit library is loaded based on the historical project code to realize the data jump from the operation and maintenance site to the historical construction project.

[0070] In another preferred embodiment of the present invention, the process of tracing the construction identification code to the spatiotemporal binding data unit library of historical projects is as follows:

[0071] During component replacement operations, the identity code of the new component is the key link between operation and maintenance data and historical construction data. The identity code typically takes the form of an RFID tag or QR code and consists of 18 characters: the first 6 digits are the supplier identification code, the middle 8 digits are the production batch number, and the last 4 digits are the component serial number. When installing the replacement part, construction workers scan the identity code using a mobile device. The system automatically interprets the supplier ID and accesses the company's integrated supply chain database. This database stores component production information for all partner suppliers, including the raw material source, processing technology, quality inspection reports, and first-time installation project records for each batch of components.

[0072] After obtaining the production batch code, the system enters the construction company's project database for matching. The project database stores data in a three-level structure: the first level is the project code, the second level is the batch code, and the third level is the component number. The project code contains information such as region, year, and project type. By fuzzy matching the production batch code with the batch information in the project database, the system can locate the historical project code where the batch components were first used. For example, the production batch number of a replacement part is 20220815A. If it is found in the project database that the batch components were used in a commercial complex project in Shanghai in 2022, the spatiotemporal binding data unit library corresponding to the historical project will be automatically loaded.

[0073] After loading is complete, the reverse traceability channel realizes cross-project data jumps, and associates the operation and maintenance abnormality data of the current replacement part with the construction data of the same batch of components in the historical project. At this time, the system can not only retrieve the original installation parameters of the component, such as installation time, spatial coordinates, and initial stress value, but also obtain the quality data of its production stage and the historical operation and maintenance records of other components in the same batch. For example, if a batch of steel components has abnormal bolt stress problems in multiple projects, the system can quickly locate the processing technology defects or design selection problems of the batch of components through cross-project data comparison, providing a more comprehensive reference basis for operation and maintenance decisions.

[0074] In another preferred embodiment of the present invention, the specific process of the comparison mapping is:

[0075] When a component abnormality is detected during the operation and maintenance phase, the physical parameters corresponding to the abnormality (such as vibration frequency, stress value, and temperature change) are first expanded chronologically to form an operation and maintenance status waveform chart that reflects the dynamic changes in the parameters. This waveform chart uses time as the horizontal axis and the physical parameter value as the vertical axis, clearly showing the parameter fluctuation trends before, during, and after the abnormality occurs. For example, if a steel component experiences an abnormal stress overlimit, the operation and maintenance status waveform chart will show that the stress value remains above the design threshold for a specific period of time, accompanied by periodic fluctuations.

[0076] Synchronously, construction process waveforms representing similar physical parameters are extracted from spatiotemporally bound data units during the construction phase. These waveforms capture parameter changes during component installation, from equipment contact to completion. These waveforms include dynamic data such as component deformation, joint stress growth, and environmental influences. For example, for steel column installation, these waveforms can show the stress growth over time during bolt tightening, the temperature decay trajectory during weld cooling, and the impact of wind speed changes on component stability during installation.

[0077] To ensure comparability of data across phases, a dual-track alignment process was performed on the two waveforms. Using the moment of component installation completion during the construction phase as the time reference point (labeled T0), the moment the O&M anomaly occurred (labeled T1) was mapped to an equivalent timeline starting at T0. This means calculating the time difference between T1 and T0 to determine the corresponding position of the O&M anomaly on the construction timeline. For example, if the O&M anomaly occurred on the 1000th day after the building was put into use, it would be converted to the total duration from T0, forming a unified time coordinate system with T0 as the origin. This ensures that the waveforms for the construction and O&M phases are aligned in the time dimension.

[0078] In a unified time coordinate system, the spectral coherence coefficient of the two waveforms within the equivalent time interval is calculated. This coefficient reflects the correlation between the two signals at different frequency components. The analysis process first performs a Fourier transform on the waveforms, converting the time-domain signal into a frequency-domain distribution to obtain the amplitude and phase information of each frequency component. The coherence coefficient is then calculated using the cross-power spectral density function. This coefficient ranges from 0 to 1, with larger values ​​indicating a higher correlation between the frequency components of the two signals. When the spectral coherence coefficient exceeds a preset threshold (dynamically set based on component type and parameter characteristics), it is determined that there is a potential correlation between the operation and maintenance anomaly and the dynamic physical parameters of the construction phase, triggering the subsequent defect type identification process.

[0079] In a preferred embodiment of the present invention, determining whether the operation and maintenance abnormality is associated with the dynamic physical parameters of the construction phase is specifically as follows:

[0080] (1) Determination of installation preload defects

[0081] If there is a pulse peak in the construction process waveform that coincides with the phase of the operation and maintenance abnormal waveform, and this pulse peak occurs during the deformation recovery process when the component is not fully fixed (i.e., the positioning adjustment stage before the installation completion time T0), it will be marked as an installation preload defect. For example, when installing steel components, if the component rebounds due to insufficient preload after the crane is unloaded, the construction waveform will show a rebound pulse peak after the stress drops sharply during the unloading period before T0. If periodic stress anomalies occur at the same location during the operation and maintenance phase, and the pulse peak of the corresponding frequency in the waveform is consistent with the phase of the construction phase, it can be determined that the preload force during installation did not meet the standard, resulting in the component being in a non-designed stress state for a long time.

[0082] (2) Determination of Cumulative Environmental Damage

[0083] When the construction process waveform shows that environmental forces (such as long-term alternating loads, temperature and humidity cycles, and corrosive media erosion) continuously act on the component connection area, and the abnormal operation and maintenance waveform shows the superposition of harmonics of the same frequency, it is marked as environmental cumulative damage. For example, during the construction phase, a node is recorded to be subjected to long-term high-frequency vibration loads, and its construction waveform shows a continuous energy distribution in the corresponding frequency band; during the operation and maintenance phase, fatigue cracks appear at the same node, and the abnormal waveform shows a significant increase in harmonic components in the same frequency band, and the phase is consistent with the environmental force waveform during the construction phase, indicating that long-term environmental effects have caused material performance degradation and cumulative damage.

[0084] (3) Determination of cross-component chain reactions

[0085] If the construction process waveform records interference events with adjacent components after installation (after T0) (such as mechanical vibration transmission during the installation of adjacent beams, load redistribution caused by support settlement, etc.), and the abnormal operation and maintenance waveform shows a sharp increase in energy in the corresponding frequency band within the equivalent time interval, it is marked as a cross-component chain reaction. For example, during the construction phase, when a column component was installed, the hoisting of the adjacent beam caused its temporary support system to generate high-frequency vibration. The construction waveform records the abnormal vibration peak during the beam hoisting period. During the operation and maintenance phase, the column component experienced abnormal bolt loosening. The abnormal waveform shows a sudden increase in energy in the same frequency range. Combined with the construction records, it can be determined that hidden damage during the installation of adjacent components triggered a chain reaction under the action of long-term loads.

[0086] In another preferred embodiment of the present invention, the operation and maintenance decision instruction set specifically includes:

[0087] (1) Targeted repair instructions for pre-installed defects

[0088] When a component anomaly is determined to be due to a preload defect during installation, a reinstallation instruction is generated and a customized stress release path optimization solution is attached. This solution directly utilizes dynamic physical parameters recorded during the construction phase, including stress change curves, deformation trajectories, and temporary support force data during component installation. For example, a steel column experienced long-term stress anomalies due to insufficient bolt preload during installation. The strain gauge data from the construction phase fully recorded the fluctuation curve caused by the rebound after the sudden stress increase during bolt tightening. After receiving the instruction at the maintenance terminal, construction personnel adjusted the installation process based on historical data. During reinstallation, preload is applied in stages according to the optimization solution. The initial preload is applied to a certain percentage of the design value and maintained for a specific duration to release the initial component deformation. The second preload is applied to a higher percentage and the stress distribution is monitored. Finally, tightening is completed according to the design value. The component verticality is calibrated against the 3D laser scanning data from the construction phase to ensure that the stress release path conforms to the material's mechanical properties and avoid recurring defects.

[0089] (2) Buffer device configuration instructions for environmental cumulative damage

[0090] In response to cumulative environmental damage, an application is submitted to the resource scheduling system for the installation of a buffer device, whose design parameters are entirely based on the environmental force waveforms recorded during the construction phase. First, the environmental parameter sequence experienced by the abnormal component during the construction period is extracted from the spatiotemporal binding data unit, including temperature and humidity cycle curves, wind load time series data, or vibration load spectrum. Taking bridge bearings as an example, if the vibration waveform caused by high-frequency vehicle loads is recorded during the construction phase, its core frequency is concentrated in a specific range, and the amplitude fluctuation range shows certain characteristics, then the designed hydraulic buffer must have reverse vibration cancellation characteristics: after determining the core frequency through the signal processing algorithm, a hydraulic component with a matching damping coefficient and stiffness is selected so that the frequency response characteristics of the buffer form a phase difference with the core frequency of the environmental force, achieving mutual cancellation of vibration energy; the stroke limit of the buffer is calculated based on the amplitude fluctuation range and the pressure adjustment rate is set to ensure that the buffer device effectively attenuates the cumulative damage to the component caused by environmental loads during long-term service.

[0091] (3) Collaborative detection instructions for cross-component chain reactions

[0092] When a cross-component chain reaction is identified, the inspection equipment is assigned a task to scan the interference status of adjacent components. The scanning range is dynamically determined based on the spatiotemporal coordinates of the interference event during the construction phase. Historical installation records are retrieved from the BIM model to locate adjacent components that are mechanically connected or force-transmitting to the abnormal component. For example, abnormal vibration in a beam component on a certain floor stems from unrelieved welding stress at the adjacent column joint during construction. UWB positioning data from the construction phase records the precise coordinates of the column component and the thermal deformation range during welding. Inspection equipment such as 3D laser scanners and stress sensor arrays will be centered around this coordinate and expanded to a reasonable spatial range to perform multi-dimensional inspection of all associated components. The laser scanner detects the spatial position deviation of the current component, the stress sensor measures the distribution of joint connection forces, and the infrared thermal imager detects temperature anomalies in the weld area. The inspection task instructions clearly indicate the time and impact range of the interference event during the construction phase, guiding the inspection equipment to focus on scanning component nodes where the stress state suddenly changed during that period, enabling accurate detection of hidden chain damage.

[0093] In a preferred embodiment of the present invention, the design parameters of the buffer device are:

[0094] Retrieve the time series records of all environmental forces acting on the abnormal component from the time of installation to the occurrence of the operation and maintenance anomaly from the time of installation to the time of the abnormal operation and maintenance. This includes cyclical, impact, or gradual loads. Signal processing algorithms are used to identify the core frequency components in the waveform—the frequency range where the energy contribution exceeds a certain percentage—and the amplitude fluctuation range, which is the difference between the historical maximum and minimum amplitudes. For example, the environmental vibration data for a certain equipment foundation shows a prominent proportion of a specific frequency component, with amplitudes fluctuating within a certain range.

[0095] The buffer type is selected based on the core frequency. For low-frequency, high-amplitude loads, a spring-damped composite buffer is used, while for high-frequency, small-amplitude loads, a hydraulic buffer is used. Taking a hydraulic buffer as an example, its frequency response characteristics must form a resonant suppression relationship with the core frequency of the environmental force. By adjusting parameters such as the piston area and the damping orifice diameter, the buffer's amplitude-frequency characteristic curve will exhibit an attenuation peak at the core frequency. The amplitude fluctuation range directly determines the buffer's mechanical parameters. The stroke limit is set to a reasonable multiple of the historical maximum amplitude to reserve a safety margin. The pressure regulation rate is calculated based on the amplitude change gradient to ensure that the buffer remains in the effective operating range under dynamic loads.

[0096] Before installation, the designed buffer device undergoes a bench test, inputting typical environmental force waveforms recorded during the construction phase to test its vibration damping efficiency. If the test results deviate from the design expectations, the system automatically retraces the spatiotemporal data unit to retrieve higher-precision historical waveforms, and iteratively optimizes the buffer parameters until the desired vibration damping is achieved.

[0097] See also Figure 2 As shown, the present invention also includes a construction project full life cycle resource intelligent scheduling system for implementing the above-mentioned construction project full life cycle resource intelligent scheduling method, including:

[0098] A database for storing dynamic physical parameters collected during the component installation process by embedded sensors during the construction phase of a building project. The dynamic physical parameters include component morphology change trajectories, connector stress change curves, and environmental force time series data;

[0099] A spatiotemporal association module is used to build a spatiotemporal indexing engine, associate the dynamic physical parameters with the corresponding component nodes of the BIM model, synchronously record the spatial coordinates and time nodes of the construction phase of the component nodes, and generate spatiotemporal binding data units;

[0100] The operation and maintenance monitoring module is used to continuously receive component operation status data monitored by IoT terminals during the project operation and maintenance phase. When an abnormal state is identified, the current spatial coordinates of the abnormal component are extracted and the reverse traceability channel is activated;

[0101] A parameter backtracking module is used to obtain the dynamic physical parameter sequence of the abnormal component during its construction phase by matching the spatiotemporal bound data units with the same spatial coordinates through the reverse tracing channel;

[0102] The operation and maintenance decision module is used to compare and map the dynamic physical parameter sequence of the construction phase with the abnormal state of the operation and maintenance phase, generate an operation and maintenance decision instruction set with construction defect location identification, and input it into the resource scheduling sequence.

[0103] The above is a detailed description of an embodiment of the present invention. However, the content described is only a preferred embodiment of the present invention and should not be considered to limit the scope of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A method for intelligent resource scheduling throughout the life cycle of a construction project, characterized in that: The following steps are involved: During the construction phase of a building project, embedded sensors are used to collect dynamic physical parameters of the component installation process. These dynamic physical parameters include component morphology change trajectories, connector stress change curves, and environmental force time series data. Construct a spatiotemporal indexing engine to associate the dynamic physical parameters with the corresponding component nodes of the BIM model, synchronously record the spatial coordinates and time nodes of the component nodes during the construction phase, and generate spatiotemporal binding data units; During the engineering operation and maintenance phase, the system continuously receives component operation status data monitored by IoT terminals. When an abnormal state is identified, the current spatial coordinates of the abnormal component are extracted and the reverse traceability channel is activated. Through the reverse tracing channel, the current spatial coordinates of the abnormal component are used as the retrieval anchor point, and the spatiotemporal binding data units with the same spatial coordinates are matched to obtain the dynamic physical parameter sequence of the abnormal component during the construction phase; Compare and map the dynamic physical parameter sequence of the construction phase with the abnormal state of the operation and maintenance phase, generate an operation and maintenance decision instruction set with construction defect location identification, and input it into the resource scheduling sequence; The specific method of activating the reverse tracing channel is: A real-time mirror model of the building information model during the operation and maintenance phase is established. When the IoT device detects abnormal component vibration characteristics, sudden temperature distribution changes, or stress levels exceeding the limit, the component is marked as an abnormal node, the 3D spatial coordinates of the abnormal node are extracted, and the historical component nodes within the error range of the abnormal node's spatial coordinates are searched in the mirror model. If the historical component node exists in the spatiotemporal binding data unit library during the construction phase, the reverse tracing channel is started; If the mirror model shows that the current component is a replacement part during the operation and maintenance period, the construction identification code in the replacement part installation record is retrieved, and the process jumps to the spatiotemporal binding data unit library of the historical project associated with the construction identification code to perform traceability. The specific process of the comparison mapping is: The physical parameters of abnormal state in the operation and maintenance stage are expanded into operation and maintenance state waveform diagrams according to the time dimension; the construction process waveform diagrams of the same type of parameters are extracted from the dynamic physical parameter sequence in the construction stage; Dual-track alignment is performed on the two waveforms. Taking the moment when component installation is completed during the construction phase as the reference point, the moment when the operation and maintenance anomaly occurs is mapped to the equivalent time axis after the reference point. The spectral coherence coefficient of the two waveforms within the equivalent time interval is calculated. When the spectral coherence coefficient exceeds the set threshold, it is determined that the operation and maintenance anomaly is associated with the dynamic physical parameters of the construction phase.

2. A method for intelligent resource scheduling throughout the life cycle of a construction project according to claim 1, characterized in that: The specific process of generating the spatiotemporal binding data unit is as follows: Create an independent storage container for each component node in the BIM model. The storage container contains a spatial coordinate field, a time node field, and a dynamic parameter storage area. When executing the component installation operation, the final spatial coordinates of the component are obtained in real time, and the data acquisition function of the embedded sensor is activated synchronously to obtain the instant when the component installation is completed. The dynamic physical parameters collected in the continuous time window before and after this moment are packaged at the millisecond time granularity and associated with the storage container corresponding to the component; An environmental correction coefficient is added to the spatial coordinates in the storage container. The environmental correction coefficient is dynamically calculated based on the correction amount corresponding to the air pressure gradient during the construction phase, the correction amount corresponding to the foundation settlement rate, and the correction amount corresponding to the temperature and humidity change curve. It is used to compensate for the spatial coordinate offset caused by building deformation.

3. A method for intelligent resource scheduling throughout the life cycle of a construction project according to claim 2, characterized in that: The specific process of associating dynamic physical parameters with storage containers is as follows: The time origin is set as the moment when the component installation is completed, and the time origin is traced back to the initial moment when the installation equipment contacts the component, and extended backward to the final moment when the adjacent components are installed. All sensor data of the target component and the contact component within the time period are intercepted and decomposed into discrete data units in chronological order; each data unit is marked with the time offset relative to the time origin and bound to the component space coordinates recorded by the positioning device to form a time-space bound data unit chain.

4. The method for intelligent resource scheduling of a construction project throughout its life cycle according to claim 1, characterized in that: The process of tracing the construction identification code to the spatiotemporal binding data unit library of historical projects is as follows: During component replacement, the identity code of the new component is read, and based on the supplier identifier in the identity code, the supply chain database is accessed to obtain the production batch code and factory parameter set of the component; the production batch code is matched with the construction company's project database, and the historical project code of the first installation of the batch of components is located. Based on the historical project code, the corresponding spatiotemporal binding data unit library is loaded to realize cross-project jump of the reverse traceability channel.

5. The method for intelligent resource scheduling of a construction project throughout its entire life cycle according to claim 1, characterized in that: The specific method for determining whether operation and maintenance anomalies are associated with dynamic physical parameters during the construction phase is as follows: If there is a pulse peak in the construction process waveform that coincides with the phase of the operation and maintenance abnormal waveform, and the pulse peak occurs during the deformation recovery process when the component is not fully fixed, it is marked as an installation preload defect; If the construction process waveform shows that environmental forces continue to act on the component connection area, and the abnormal operation and maintenance waveform shows the superposition characteristics of harmonics of the same frequency, it is marked as environmental cumulative damage; If the construction process waveform records an interference event between adjacent components after installation is completed, and the operation and maintenance abnormal waveform shows a sharp increase in the energy of the corresponding frequency band within the equivalent time interval, it is marked as a cross-component chain reaction.

6. A method for intelligent resource scheduling throughout the life cycle of a construction project according to claim 5, characterized in that: The operation and maintenance decision instruction set specifically includes: For components marked with installation preload defects, a reinstallation instruction is sent to the maintenance terminal, along with the stress relief path optimization plan recorded during the construction phase; For components marked with environmental cumulative damage, apply to the resource scheduling system for the installation of buffer devices. The design parameters of the buffer devices are generated based on the environmental force waveform during the construction phase. For components that mark cross-component chain reactions, the detection equipment is assigned the task of scanning the interference status of adjacent components, and the scanning range is determined according to the time and space coordinates of the interference events during the construction phase.

7. A method for intelligent resource scheduling throughout the life cycle of a construction project according to claim 6, characterized in that: The design parameters of the buffer device are: The time series records of environmental forces during the construction phase of abnormal components are extracted from the spatiotemporal binding data unit, and the core frequency components and amplitude fluctuation range of the environmental force waveform are identified. A hydraulic buffer with reverse vibration cancellation characteristics is designed. The frequency response characteristics of the hydraulic buffer correspond to the core frequency components of the environmental force. The stroke limit value and pressure adjustment rate of the hydraulic buffer are calculated based on the amplitude fluctuation range.

8. A construction project full life cycle resource intelligent scheduling system, used to implement a construction project full life cycle resource intelligent scheduling method according to any one of claims 1 to 7, characterized in that: include: A database for storing dynamic physical parameters collected during the component installation process by embedded sensors during the construction phase of a building project. The dynamic physical parameters include component morphology change trajectories, connector stress change curves, and environmental force time series data; A spatiotemporal association module is used to build a spatiotemporal indexing engine, associate the dynamic physical parameters with the corresponding component nodes of the BIM model, synchronously record the spatial coordinates and time nodes of the construction phase of the component nodes, and generate spatiotemporal binding data units; The operation and maintenance monitoring module is used to continuously receive component operation status data monitored by IoT terminals during the project operation and maintenance phase. When an abnormal state is identified, the current spatial coordinates of the abnormal component are extracted and the reverse traceability channel is activated; A parameter backtracking module is used to obtain the dynamic physical parameter sequence of the abnormal component during its construction phase by matching the spatiotemporal bound data units with the same spatial coordinates through the reverse tracing channel; The operation and maintenance decision module is used to compare and map the dynamic physical parameter sequence of the construction phase with the abnormal state of the operation and maintenance phase, generate an operation and maintenance decision instruction set with construction defect location identification, and input it into the resource scheduling sequence.

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