Fabricated steel member carbon emission metering method and system

Abstract

The application provides a kind of assembled steel member carbon emission metering method and system, related to building carbon emission metering technical field, including obtaining component material, process constraint and energy consumption information, state transition diagram is constructed with carbon emission state as node, process as transfer event and binding carbon emission increment.By reachability traversal and blind node processing, a complete transition diagram is formed, the incremental accumulation is promoted along the topological order, and concurrent nodes are identified and processed to achieve unique attribution of the increment.Combined with working condition monitoring data, the trigger condition is verified and the increment is corrected.Finally, based on the updated accumulation sequence, the state increment is extracted, and the total carbon emission of the whole process is obtained by summarizing.The method realizes accurate and dynamic metering of the whole process carbon emission of assembled steel member production.

Description

Technical Field

[0001] This invention relates to the field of building carbon emission metering technology, and in particular to a method and system for measuring carbon emissions from prefabricated steel components. Background Technology

[0002] In the field of prefabricated buildings, the production and installation of steel components are significant sources of carbon emissions. To achieve accurate measurement of carbon emissions from raw materials to on-site installation of individual steel components, existing technologies typically employ a static cumulative method based on a bill of materials. The core of this method is to pre-establish a fixed carbon emission factor database for each component material and each processing, transportation, and installation step. During measurement, based on the component's bill of materials and the pre-set process route, the carbon emissions from the materials involved are linearly superimposed with the energy consumption carbon emissions from each step, thereby calculating the theoretical total carbon emissions. This method relies on standard, universal process assumptions and averaged energy consumption data; its calculation model is essentially sequential and deterministic.

[0003] However, the aforementioned conventional measurement methods have significant shortcomings in practical applications. Due to the highly dynamic and uncertain nature of the actual production and construction processes of prefabricated steel components, fixed process route models cannot accurately reflect reality. For example, the constraints between processes are complex, potentially involving parallelism, branching, or conditional triggering. Static linear accumulation models cannot handle such non-sequential, conditional state transitions, leading to incomplete measurement paths or duplicate calculations. More importantly, the execution of processes during actual construction is affected by site conditions, resource scheduling, and other factors. Whether a process is triggered and its energy consumption level change in real time. Calculation results based on fixed factors and preset paths cannot be incorporated into the verification and correction of these dynamic conditions, resulting in significant deviations between the measurement results and actual carbon emissions, making it difficult to support refined carbon management and emission reduction decisions. Summary of the Invention

[0004] This invention provides a method and system for measuring carbon emissions from prefabricated steel components, which can solve the problems in the prior art.

[0005] A first aspect of this invention provides a method for measuring carbon emissions from prefabricated steel components, comprising: Obtain information on the component materials, process constraints, and process energy consumption of the steel components to be measured; Using carbon emission accumulation status as nodes and process execution as state transition events, the triggering conditions of each process are abstracted into state transition conditions based on process constraint information. The carbon emission increment is bound to the process energy consumption and the component material to form a state transition diagram. A reachability traversal is performed on the nodes of the state transition diagram to identify untouched nodes as metering blind nodes. Based on the pre- and post-constraint relationships, the metering blind nodes are forcibly connected to the nearest reachable path to obtain the carbon emission state transition diagram. The incremental accumulation is advanced along the topological order of the carbon emission state transition diagram. Concurrent merging nodes are identified and the concurrency type is determined. Fully concurrent nodes are locked with the unique attribution of the preceding path increment by path independence verification. Conditional concurrent nodes are defined with the attribution range by the state of the trigger condition. The two are merged to form an accumulation sequence with unique carbon emission increment attribution. Collect monitoring data of operating conditions at each process node, verify the triggering conditions of corresponding state transition events, correct the carbon emission increment of events whose triggering conditions are not met, calibrate the set of nodes that depend on the increment and limit the extrapolation range within it, and update the accumulated sequence with the extrapolation results; Based on the completed re-inference of the accumulation sequence, the carbon emission increment of each carbon emission accumulation state is extracted to obtain the total carbon emission of the steel component to be measured throughout the entire process.

[0006] Using carbon emission accumulation status as nodes and process execution as state transition events, the triggering conditions of each process are abstracted into state transition conditions based on process constraint information. This is combined with the carbon emission increments tied to the process energy consumption and the component materials to form a state transition diagram, including: Extract the time constraints and resource constraints of each process from the process constraint information, map the time constraints to the arrival criteria of the preceding carbon emission accumulation state, and map the resource constraints to the satisfaction criteria of the resource occupancy state. The joint fulfillment of the arrival criteria and the satisfaction criteria is used as the state transition condition of each process. The effective energy consumption range of each process is determined based on the state transition conditions. Within the effective energy consumption range, the process energy consumption is decomposed into material response energy consumption coupled with the consumption rate of each material in the component material, and equipment operation energy consumption associated with the mechanical power trajectory of the process. Based on the carbon emission coefficient, it is converted into material response carbon emission and equipment operation carbon emission respectively. The carbon emission increment of each process is calculated, and the carbon emission increment is bound to the state transition event corresponding to each process. Using the state transition condition as the directed edge trigger criterion and the carbon emission increment as the directed edge weight, the carbon emission accumulation state nodes are sequentially connected according to the dependency topology determined by the temporal constraints and resource constraints in the process constraint information to form the state transition graph.

[0007] A reachability traversal is performed on the nodes of the state transition graph to identify unreached nodes as metering blind nodes. Based on pre- and post-constraint relationships, these metering blind nodes are forcibly connected to the nearest reachable path, resulting in a carbon emission state transition graph, including: Using the initial node of the state transition graph as the starting point of the forward traversal and all nodes without outgoing edges as the starting point of the reverse traversal, the traversal is performed along the forward and reverse directions of the directed edges respectively. Nodes not touched by either the forward or reverse traversal are marked as metering blind nodes. For each blind node in the metering process, the preceding and following constraint nodes associated with the node are extracted from the process constraint information. The nodes that are reachable are selected as the preceding and following anchor nodes, respectively. The difference in the hierarchical depth between the preceding and following anchor nodes is used as the access cost. The directed path between the preceding and following anchor nodes with the minimum access cost is determined as the target access path. Insert the metering blind node into the target access path, reconstruct the directed edge triggering criteria and weights from the preceding anchor node to each metering blind node using the state transition conditions of each metering blind node and the carbon emission increment, reconstruct the directed edge triggering criteria and weights from the metering blind node to the subsequent anchor node using the state transition conditions of the subsequent anchor node and the carbon emission increment, and remove the directed edges from the preceding anchor node directly pointing to the subsequent anchor node. After completing the access operation for all blind nodes in sequence, the state transition graph is reconstructed with the updated node connection relationship and directed edge weights to obtain the carbon emission state transition graph.

[0008] The incremental accumulation proceeds along the topological sequence of the carbon emission state transition graph, identifying concurrent merging nodes and determining the concurrency type. Fully concurrent nodes are uniquely assigned to their predecessor path increments using path independence attribution verification. Conditionally concurrent nodes have their attribution range defined by the fulfillment of trigger conditions. These are then merged to form an accumulation sequence with a unique carbon emission increment attribution, including: The process proceeds node by node according to the topological sorting result of the carbon emission state transition graph. The path state slice after incremental weight accumulation is used as the propagation unit to pass along the directed edge. The set of all predecessor path state slices received by each node constitutes the incremental accumulation intermediate state. Concurrent merging nodes are identified based on the number of incoming edges at each node. The concurrency type is determined based on the compatibility test results of the activation constraint relationship of each predecessor path. Nodes with compatible activation constraints and no mutual exclusion dependencies are classified as fully concurrent nodes, while nodes with mutual exclusion dependencies are classified as conditionally concurrent nodes. For fully concurrent nodes, slices of the predecessor path state are extracted from the incremental accumulation intermediate state. The path ownership uniqueness assertion of each slice is used as the ownership locking mechanism. The slice accumulation value of the path independent ownership verification is bound to the unique ownership identifier to form a locked ownership incremental set. For conditional concurrent nodes, extract the state slices of each predecessor path and the corresponding activation constraint expressions from the incremental accumulation intermediate states. The interval where the activation constraint is met is the effective ownership boundary. The accumulated values ​​within the interval are bound to the ownership identifier, and the accumulated values ​​outside the interval are excluded to form an ownership increment set. The locked attribution increment set and the attribution increment set are merged into the accumulation sequence according to the topological advancement order, and each entry is bound with a unique attribution identifier to obtain the accumulation sequence with unique attribution of carbon emission increment.

[0009] For fully concurrent nodes, slices of predecessor path states are extracted from the incremental accumulation intermediate states. Using the path ownership uniqueness assertion of each slice as the ownership locking mechanism, a unique ownership identifier is bound to the slice accumulation value verified by independent path ownership, forming a locked ownership increment set, including: Extract the path traversal trajectory and corresponding carbon emission increment accumulation value of each slice of the precursor path state from the incremental accumulation intermediate state, encode the path traversal trajectory into a path signature sequence, and use the path signature sequence as the slice ownership identification credential. Construct a path independence verification matrix, and represent the set of nodes passed through by each precursor path in the carbon emission state transition diagram as a Boolean vector. By calculating the logical AND operation result of the Boolean vectors corresponding to any two paths, determine that the path pairs with a logical AND result of zero vector are path independent, and determine that the path pairs with a logical AND result of non-zero vector are path coupled. For path-independent slices, a unique binding table is established between path signature sequences and cumulative carbon emission increments. A uniqueness constraint assertion is applied to each record in the binding table to prevent the same cumulative carbon emission increment from being associated with multiple path signature sequences, thus forming a lock record for the ownership of path-independent slices. For the path-coupled slices, extract the state transition event sequence of each path, and use the non-common subsequence of the state transition event sequence as the path distinguishing feature, and assign the cumulative value of carbon emission increment to the path signature sequence with a unique non-common subsequence. The ownership lock records of path-independent slices and the ownership records of path-coupled slices are aggregated to form a lock ownership increment set.

[0010] Collect monitoring data on the operating conditions of each process node, verify the triggering conditions of corresponding state transition events, correct the carbon emission increments for events whose triggering conditions are not met, calibrate the set of nodes that depend on the increments and limit the extrapolation range within it, and update the accumulated sequence with the extrapolation results, including: Data on working conditions is acquired from the data acquisition terminals at each process node. The results are verified by using the logic and results of the time-series constraint satisfaction state and the resource constraint satisfaction state as trigger conditions, and the measured energy consumption value is extracted. Identify state transition events with logically false verification results, read the carbon emissions from material response and equipment operation from the carbon emission state transition diagram, take the difference between the measured energy consumption value and the preset energy consumption value as the energy consumption deviation, allocate it according to the weight of material consumption rate and equipment power, and sum it to obtain the corrected carbon emission increment value; take the state transition event where the corrected carbon emission increment value is located as the starting edge and perform a breadth-first search of the forward influence domain to collect the nodes in the carbon emission cumulative value formula containing the corrected carbon emission increment value as the incremental dependency node set; The incrementally dependent node set is topologically layered. The carbon emission accumulation value of the predecessor node and the weight of the incoming edge are summed layer by layer from low to high level to obtain the updated carbon emission accumulation value of each node. An index structure from node identifier to updated carbon emission accumulation value is established. The accumulation sequence is traversed and the original carbon emission accumulation value is overwritten with the updated carbon emission accumulation value according to the index to complete the accumulation sequence update.

[0011] Starting with the state transition event containing the corrected carbon emission increment value as the initial edge, a breadth-first search of the forward influence domain is performed. Nodes whose carbon emission cumulative value formula contains the corrected carbon emission increment value are collected as the incremental dependency node set, including: Taking the state transition event where the corrected carbon emission increment value is located as the entry point, an incremental dependency mapping table is established with node identifier as the key and dependency path as the value. The endpoint node of the event is written into the queue to be visited, and the initial dependency path is registered for it in the incremental dependency mapping table at the same time. The set of visited node tags is initialized. Retrieve the current node from the queue to be visited, read the dependency path of the current node from the incremental dependency mapping table, substitute the incremental reference relationship of each node in the path into the carbon emission cumulative value formula of the current node to perform transitive reference chain verification, and determine whether the modified carbon emission increment value forms a valid transitive reference to the current node through the dependency path; if the verification is successful, write the current node into the incremental dependency node set, write the unvisited node pointed to by its forward outgoing edge into the queue to be visited, register the extended dependency path in the incremental dependency mapping table, and update the visited node mark set; if the verification is unsuccessful, terminate the forward path expansion through the current node. Repeat the above process of retrieving and passing the reference chain verification until the queue to be accessed is empty, and output the incremental dependency node set.

[0012] A second aspect of the present invention provides a carbon emission metering system for prefabricated steel components, comprising: The information acquisition unit is used to acquire information on the component materials, process constraints, and process energy consumption of the steel component to be measured. The state modeling unit is used to abstract the triggering conditions of each process into state transition conditions based on the process constraint information, taking the carbon emission accumulation state as the node and the process execution as the state transition event, and combining the process energy consumption with the carbon emission increment of the component material to form a state transition diagram. The blind spot elimination unit is used to perform reachability traversal on the nodes of the state transition diagram, identify untouched nodes as metering blind nodes, and force the metering blind nodes to be connected to the nearest reachable path according to the pre- and post-constraint relationships to obtain the carbon emission state transition diagram. The incremental attribution unit is used to advance incremental accumulation along the topological order of the carbon emission state transition diagram, identify concurrent merging nodes and determine the concurrency type. Fully concurrent nodes lock the unique attribution of the preceding path incremental nodes with path independence attribution verification, and conditional concurrent nodes define the attribution range with the state of triggering conditions, and merge to form an accumulation sequence with unique carbon emission incremental attribution. The operating condition correction unit is used to collect operating condition monitoring data of each process node, verify the triggering conditions of the corresponding state transition events, correct the carbon emission increment of events whose triggering conditions are not met, calibrate the set of increment dependent nodes and limit the extrapolation range within it, and update the accumulated sequence with the extrapolation results. The total emission extraction unit is used to extract the carbon emission increment of each carbon emission accumulation state based on the completed re-inference accumulation sequence, so as to obtain the total carbon emission of the steel component to be measured throughout the process.

[0013] A third aspect of the present invention provides an electronic device, comprising: processor; Memory used to store processor-executable instructions; The processor is configured to invoke instructions stored in the memory to execute the aforementioned method.

[0014] A fourth aspect of the present invention provides a computer-readable storage medium having stored thereon computer program instructions that, when executed by a processor, implement the aforementioned method.

[0015] This method enables refined and dynamic measurement of carbon emissions throughout the entire lifecycle of prefabricated steel components. By mapping component material and process constraints with energy consumption information into a state transition diagram with carbon emission accumulation status as nodes and process execution as transition events, a structured measurement logic framework is constructed. This framework transforms the complex physical production process into a computable and analyzable network model, providing a clear topological foundation for systematically tracking carbon footprints.

[0016] The state transition diagram is traversed for reachability and blind nodes are identified, ensuring that the measurement model covers all necessary production links. Based on the pre- and post-constraint relationships, blind nodes are forced to be connected to the nearest reachable path, eliminating measurement omissions caused by missing or jumping process logic, ensuring the integrity and continuity of the carbon emission accumulation path, and enabling the measurement results to truly reflect the actual production process.

[0017] By introducing operational condition monitoring data to verify and correct the triggering conditions of state transition events in real time, the metrology model gains dynamic adaptability. For events that do not meet the triggering conditions, the carbon emission increment is corrected, and the extrapolation scope is limited to a calibrated set of increment-dependent nodes, achieving online calibration and partial updating of carbon emission data based on actual production conditions.

[0018] Based on the dynamically updated complete accumulation sequence, the increments of each state are extracted and summarized, which can accurately output the total carbon emissions of the steel component to be measured throughout the entire process. This method integrates static modeling, dynamic verification and concurrent processing, and realizes closed-loop measurement driven by theoretical models and actual data. It provides an effective technical tool for accurate carbon accounting and emission reduction management in the field of prefabricated steel structures. Attached Figure Description

[0019] Figure 1 This is a schematic flowchart of a carbon emission measurement method for prefabricated steel components according to an embodiment of the present invention; Figure 2 This is a flowchart illustrating the method for generating a uniquely attributed accumulation sequence for carbon emission increments according to an embodiment of the present invention. Detailed Implementation

[0020] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of 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.

[0021] The technical solution of the present invention will be described in detail below with reference to specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments.

[0022] Figure 1 This is a schematic flowchart of a carbon emission metering method for prefabricated steel components according to an embodiment of the present invention, as shown below. Figure 1 As shown, the method includes: Obtain information on the component materials, process constraints, and process energy consumption of the steel components to be measured; Using the carbon emission accumulation state as a node and the process execution as a state transition event, the triggering conditions of each process are abstracted into state transition conditions based on the process constraint information, and the carbon emission increment is bound to the process energy consumption and the component material to form a state transition diagram. A reachability traversal is performed on the nodes of the state transition graph to identify unreached nodes as metering blind nodes. Based on the preceding and following constraints, the metering blind nodes are forcibly connected to the nearest reachable path to obtain the carbon emission state transition graph. The incremental accumulation is advanced along the topological order of the carbon emission state transition diagram. Concurrent merging nodes are identified and the concurrency type is determined. Fully concurrent nodes are locked with the unique attribution of the preceding path increment by path independence verification. Conditional concurrent nodes are defined with the attribution range by the state of the trigger condition. The two are merged to form an accumulation sequence with unique carbon emission increment attribution. Collect monitoring data of operating conditions at each process node, verify the triggering conditions of corresponding state transition events, correct the carbon emission increment of events whose triggering conditions are not met, calibrate the set of nodes that depend on the increment and limit the extrapolation range within it, and update the accumulated sequence with the extrapolation results; Based on the completed re-inference of the accumulation sequence, the carbon emission increment of each carbon emission accumulation state is extracted to obtain the total carbon emission of the steel component to be measured throughout the entire process.

[0023] Using carbon emission accumulation status as nodes and process execution as state transition events, the triggering conditions of each process are abstracted into state transition conditions based on process constraint information. This is combined with the carbon emission increments tied to the process energy consumption and the component materials to form a state transition diagram, including: Extract the time constraints and resource constraints of each process from the process constraint information, map the time constraints to the arrival criteria of the preceding carbon emission accumulation state, and map the resource constraints to the satisfaction criteria of the resource occupancy state. The joint fulfillment of the arrival criteria and the satisfaction criteria is used as the state transition condition of each process. The effective energy consumption range of each process is determined based on the state transition conditions. Within the effective energy consumption range, the process energy consumption is decomposed into material response energy consumption coupled with the consumption rate of each material in the component material, and equipment operation energy consumption associated with the mechanical power trajectory of the process. Based on the carbon emission coefficient, it is converted into material response carbon emission and equipment operation carbon emission respectively. The carbon emission increment of each process is calculated, and the carbon emission increment is bound to the state transition event corresponding to each process. Using the state transition condition as the directed edge trigger criterion and the carbon emission increment as the directed edge weight, the carbon emission accumulation state nodes are sequentially connected according to the dependency topology determined by the temporal constraints and resource constraints in the process constraint information to form the state transition graph.

[0024] Obtain information on the components, process constraints, and process energy consumption of the steel components to be measured. Component materials include steel type, specifications, and quantity, such as Q345 steel plates, H-beams, and welding materials. Process constraint information includes the timing and resource constraints of processes such as blanking, drilling, welding, and painting. Timing constraints describe the sequential execution relationship between processes, such as blanking must be performed before drilling, and painting must be performed after welding. Resource constraints include the resource conditions such as equipment, personnel, and auxiliary materials required for each process. Process energy consumption records the energy consumption data of each process, such as electricity and gas.

[0025] Extract the timing and resource constraints for each process from the process constraint information. Map the timing constraints to the criteria for reaching the preceding carbon emission accumulation state. For example, for the drilling process, the timing constraint requires that the material cutting process must be completed before it can start. This constraint is then mapped to "the carbon emission accumulation state corresponding to the material cutting process has been reached" as a necessary condition for starting the drilling process. Map the resource constraints to the criteria for satisfying the resource occupancy state. For example, the drilling process requires that the CNC drilling machine be available and the operator be in place before it can be executed. This resource constraint is then mapped to the criterion that "the CNC drilling machine is available and the designated operator is not occupied by other tasks." The joint fulfillment of the timing and resource criteria serves as the state transition condition for each process.

[0026] The effective energy consumption range for each process is determined based on state transition conditions. The effective energy consumption range refers to the energy consumption period from start to finish of the process. For welding processes, the effective energy consumption range is the electrical energy consumption from welding machine start-up to shutdown; for heat treatment processes, the effective energy consumption range is the gas and electrical energy consumption from furnace heating to cooling completion. The determination of the effective energy consumption range is based on the control signals and sensor data of the process equipment. For electrically driven equipment, the range boundaries are determined by detecting the start and stop commands of the equipment control system. For heat treatment equipment, the start point is the moment the workpiece temperature reaches the process temperature, and the end point is the moment it cools to ambient temperature. For manually operated processes, the timestamps of the workpiece entering and leaving the workstation are recorded using an RFID station identification system. The data acquisition terminal communicates with the PLC controller or SCADA system of the process equipment to automatically acquire timestamp data, ensuring the accuracy and consistency of the timing start and end points.

[0027] Within the effective energy consumption range, process energy consumption is broken down into two parts: material response energy consumption and equipment operation energy consumption. Material response energy consumption refers to the energy consumption directly related to the consumption of component materials, such as the energy required to melt welding rods during welding. Equipment operation energy consumption refers to the energy consumption required to maintain the normal operation of equipment, such as the no-load power of welding machines and the operating power of cutting machines. Material response energy consumption is coupled with the consumption rate of each material in the component materials, while equipment operation energy consumption is related to the mechanical power trajectory of the process.

[0028] Specifically, material response energy consumption is calculated based on the product of the standard energy consumption per unit of material consumption and the actual material consumption. Taking welding as an example, material response energy consumption equals the product of the electrical energy required to melt a unit of welding rod and the actual amount of welding rod used. Equipment operating energy consumption is based on the integral of the equipment power curve over operating time, including energy consumption during equipment startup, stable operation, and shutdown. The standard energy consumption per unit of material consumption refers to the theoretical energy required for a unit mass of material to complete a phase change, chemical reaction, or machining under specific process conditions. This value can be obtained through the following methods: consulting national and industry standards; obtaining it from the process parameter manual provided by the equipment manufacturer; or obtaining it through energy consumption tests under standard laboratory conditions. For example, the unit energy consumption for welding rod melting can be obtained from the welding material technical specifications, with a typical value of 3-5 kWh of electrical energy required per kilogram of welding rod. Actual material consumption is obtained in the following ways: for welding processes, the difference in electrode weight before and after welding is recorded by a weighing system; for cutting processes, the product of the cut volume and the material density is calculated; for coating processes, the flow meter readings of the paint supply system are used. Actual material consumption data is automatically collected by metering devices at the process site and uploaded to the data acquisition terminal.

[0029] Based on carbon emission coefficients, material response energy consumption and equipment operation energy consumption are converted into material response carbon emissions and equipment operation carbon emissions, respectively. These carbon emission coefficients are derived from national or industry standard carbon emission factor databases, such as electricity carbon emission factors and natural gas carbon emission factors. For example, the carbon emissions from electricity consumption equal the electricity consumption multiplied by the regional power grid's carbon emission factor; the carbon emissions from natural gas consumption equal the natural gas consumption multiplied by the natural gas carbon emission factor. In this way, the carbon emission increment for each process is calculated, and this increment is bound to the corresponding state transition event for each process. Using state transition conditions as the directed edge triggering criteria and carbon emission increments as the directed edge weights, each carbon emission accumulation state node is sequentially connected according to the dependency topology determined by the temporal and resource constraints in the process constraint information, forming a state transition graph. In the state transition graph, nodes represent carbon emission accumulation states, directed edges represent state transitions caused by process execution, and the edge weight is the carbon emission increment generated by that process.

[0030] Taking prefabricated H-shaped steel column components as an example, its processing steps include five main processes: material preparation, drilling, assembly, welding, and painting. According to the process constraints, the material preparation process has no prerequisites; the drilling process depends on the material preparation process; the assembly process depends on the drilling process; the welding process depends on the assembly process; and the painting process depends on the welding process. In terms of resource constraints, the material preparation process requires a plasma cutter and operators; the drilling process requires a CNC drilling machine and operators; the assembly process requires an assembly station and operators; the welding process requires a welding machine and welders; and the painting process requires spraying equipment and painters.

[0031] When calculating the carbon emission increment for each process, the carbon emissions from the blanking process mainly come from the power consumption of the cutting equipment; the carbon emissions from the drilling process mainly come from the operation of the drilling machine and the consumption of coolant; the carbon emissions from the assembly process mainly come from temporary fixing devices and manual operation; the carbon emissions from the welding process include the power consumption of the welding machine and the consumption of welding rod materials; and the carbon emissions from the painting process include the energy consumption of the spraying equipment and the emissions generated by paint volatilization. When constructing the state transition diagram, an initial node S0 needs to be defined to represent the carbon emission accumulation state when no process has started, with a value of 0. After the blanking process is executed, the system state transitions to S1, and the carbon emission increment is the sum of the carbon emissions from the material response of the blanking process and the carbon emissions from equipment operation. When the state transition conditions of the drilling process are met (i.e., the blanking process is completed and the drilling machine and operators are available), the system state transitions from S1 to S2, and the carbon emission increment is the carbon emissions generated by the drilling process. And so on, the system state sequentially passes through the assembly process, the welding process, and the painting process, and finally reaches the final state Sf, which represents the total carbon emission accumulation state when the steel component processing is completed.

[0032] This state transition diagram approach not only allows for precise measurement of the total carbon emissions throughout the entire steel component manufacturing process, but also enables analysis of the contribution of each process to the total carbon emissions, identification of carbon emission hotspots, and provides a basis for green design and manufacturing process optimization of steel components. Furthermore, the state transition diagram model facilitates comparisons of carbon emissions from different process routes, supporting decision-making in selecting low-carbon process solutions.

[0033] A reachability traversal is performed on the nodes of the state transition graph to identify unreached nodes as metering blind nodes. Based on pre- and post-constraint relationships, these metering blind nodes are forcibly connected to the nearest reachable path, resulting in a carbon emission state transition graph, including: Using the initial node of the state transition graph as the starting point of the forward traversal and all nodes without outgoing edges as the starting point of the reverse traversal, the traversal is performed along the forward and reverse directions of the directed edges respectively. Nodes not touched by either the forward or reverse traversal are marked as metering blind nodes. For each blind node in the metering process, the preceding and following constraint nodes associated with the node are extracted from the process constraint information. The nodes that are reachable are selected as the preceding and following anchor nodes, respectively. The difference in the hierarchical depth between the preceding and following anchor nodes is used as the access cost. The directed path between the preceding and following anchor nodes with the minimum access cost is determined as the target access path. Insert the metering blind node into the target access path, reconstruct the directed edge triggering criteria and weights from the preceding anchor node to each metering blind node using the state transition conditions of each metering blind node and the carbon emission increment, reconstruct the directed edge triggering criteria and weights from the metering blind node to the subsequent anchor node using the state transition conditions of the subsequent anchor node and the carbon emission increment, and remove the directed edges from the preceding anchor node directly pointing to the subsequent anchor node. After completing the access operation for all blind nodes in sequence, the state transition graph is reconstructed with the updated node connection relationship and directed edge weights to obtain the carbon emission state transition graph.

[0034] During the construction of the state transition diagram, due to incomplete process constraint information or isolated branches in the process definition, some nodes may be unreachable through normal traversal. To ensure the integrity of carbon emission measurement, it is necessary to identify these measurement blind nodes and integrate them into the main graph structure.

[0035] A directed edge traversal is performed starting from the initial node of the state transition graph. The initial node typically represents the initial state of steel component manufacturing, with zero carbon emissions. The forward traversal uses a depth-first search algorithm, proceeding along the directed edges from the initial node, visiting and marking reachable nodes in sequence. For example, in the manufacturing of H-shaped steel columns, starting from the initial node, the state nodes corresponding to the blanking, drilling, assembly, welding, and painting processes are visited in sequence. During the forward traversal, visited nodes are recorded in the forward visit set for subsequent determination of blind nodes in measurement.

[0036] Starting from all nodes without outgoing edges, the reverse traversal proceeds in the opposite direction of the directed edges. Nodes without outgoing edges typically represent the final state of steel component manufacturing, indicating the state after all processes are completed. The reverse traversal also uses a depth-first search algorithm, but the search direction is opposite to that of the directed edges. At each node, all incoming edges pointing to that node are searched, and the source nodes of these incoming edges are visited in reverse. For example, starting from the node where the painting process is completed, the welding process nodes are visited in reverse, then the assembly process nodes are visited in reverse, and so on. During the reverse traversal, the visited nodes are recorded in the reverse visit set, which is also used for the subsequent determination of blind nodes in measurement.

[0037] Nodes not reached by either forward or reverse traversal are marked as measurement blind nodes. Through set operations, the difference between the union of the set of all nodes in the state transition diagram and the set of forward and reverse visits is obtained to obtain the set of measurement blind nodes. Measurement blind nodes represent process states that exist in the manufacturing process but are not fully captured by the current state transition diagram, such as nodes for special process treatment, quality inspection, or rework repair. For example, some steel components need to undergo ultrasonic testing after welding, but if this inspection process is not clearly reflected in the original process constraint information, a measurement blind node will be formed.

[0038] For each metrological blind node, the preceding and following constraint nodes associated with that node are extracted from the process constraint information. The preceding constraint node is a process node that must be completed before the corresponding process of the metrological blind node in the process constraint relationship. The following constraint node is a process node that can only be started after the corresponding process of the metrological blind node is completed. For example, for the metrological blind node of ultrasonic flaw detection, its preceding constraint node is the welding process node and its following constraint node is the painting process node.

[0039] Nodes that are reachable from the preceding and following constraint nodes are selected as preceding anchor nodes and following anchor nodes, respectively. Reachable nodes refer to nodes visited in the forward or reverse traversal. Preceding anchor nodes are selected from the preceding constraint node set and following anchor nodes are selected from the following constraint node set by performing an intersection operation with the forward and reverse access sets. For ultrasonic testing nodes, if the welding node is reachable in the forward traversal, the welding node is selected as the preceding anchor node; if the painting node is reachable in the reverse traversal, the painting node is selected as the following anchor node.

[0040] The access cost is calculated as the difference in hierarchical depth between the preceding and following anchor nodes. The directed path between the preceding and following anchor nodes with the lowest access cost is determined as the target access path. Hierarchical depth refers to the shortest path length from the initial node in the state transition diagram. The lower the access cost, the more direct the connection between the preceding and following anchor nodes in the original state transition diagram, and the less impact the insertion of metering blind nodes has on the original path structure. For example, if the hierarchical depth of the welding node is three and the hierarchical depth of the painting node is four, the access cost is one, indicating that these two nodes are directly connected in the original diagram. If there are multiple combinations of preceding and following anchor nodes, the path corresponding to the combination with the lowest access cost is selected as the target access path.

[0041] Metering blind nodes are inserted into the target access path. For the identified preceding anchor nodes, metering blind nodes, and following anchor nodes, directed paths are established from the preceding anchor nodes to the metering blind nodes, and then to the following anchor nodes. For example, an ultrasonic flaw detection node is inserted between a welding node and a painting node, forming a path of "welding → flaw detection → painting". The state transition conditions and carbon emission increments of each metering blind node are used to reconstruct the directed edge triggering criteria and weights from the preceding anchor nodes to each metering blind node. The state transition conditions are extracted from the process constraint information, and the carbon emission increments are calculated based on the energy consumption data of the corresponding process of the metering blind node. For example, the state transition condition for the ultrasonic flaw detection process is "the welding process is completed and the flaw detection equipment is available", and the carbon emission increment is the carbon emission amount converted from the energy consumption of the flaw detection equipment. Based on this, directed edges are constructed from the welding node to the flaw detection node, with the triggering criteria of the edge being the aforementioned state transition conditions and the weight being the calculated carbon emission increment. The state transition conditions of the post-anchor node and the carbon emission increment are used to reconstruct the directed edge triggering criteria and weights from the blind node to the post-anchor node. For example, the original state transition condition for the painting process was "welding process completed and painting equipment ready," which is now adjusted to "flaw detection process completed and painting equipment ready," while the carbon emission increment remains unchanged. Based on this, a directed edge is constructed from the flaw detection node to the painting node, with the adjusted state transition condition as the triggering criterion and the carbon emission increment of the painting process as the weight.

[0042] Remove directed edges that point directly from preceding anchor nodes to subsequent anchor nodes. In the example above, the directed edge pointing directly from the welding node to the painting node is deleted to ensure that the state transition process passes through the flaw detection node. This operation ensures the continuity and integrity of the state transition diagram.

[0043] After sequentially completing the access operation for all metering blind nodes, the state transition graph is reconstructed using the updated node connectivity and directed edge weights to obtain a complete carbon emission state transition graph. During the reconstruction process, existing reachable nodes and their connectivity are retained, and metering blind nodes are inserted into appropriate positions using the method described above. The final generated carbon emission state transition graph includes all process nodes and their carbon emission relationships throughout the entire steel component manufacturing process, achieving comprehensive and accurate metering of carbon emissions during the prefabricated steel component manufacturing process.

[0044] Taking a practical application as an example, the original state transition diagram of an H-shaped steel column component in a steel structure building project includes five main process nodes: material preparation, drilling, assembly, welding, and painting. Through forward and reverse traversal, it was found that the quality inspection and surface treatment processes were not captured, forming blind nodes for measurement. For the quality inspection node, its preceding anchor node is the welding node, and its subsequent anchor node is the painting node; for the surface treatment node, its preceding anchor node is the drilling node, and its subsequent anchor node is the assembly node. After calculating the access cost for each node, the target access path is determined. The quality inspection node is inserted between welding and painting, and the surface treatment node is inserted between drilling and assembly. The triggering criteria and weights of each connection edge are reconstructed, and inapplicable direct connection edges are removed. Finally, a complete carbon emission state transition diagram is reconstructed, realizing accurate measurement of carbon emissions from prefabricated steel components.

[0045] Figure 2 This is a flowchart illustrating the method for generating a uniquely attributed accumulation sequence for carbon emission increments according to an embodiment of the present invention. Increment accumulation proceeds along the topological order of the carbon emission state transition graph, concurrent merging nodes are identified and their concurrency types are determined, fully concurrent nodes use path-independent attribution verification to lock the unique attribution of the preceding path increment, and conditional concurrent nodes define the attribution range based on the fulfillment of trigger conditions. These are then merged to form a uniquely attributed accumulation sequence for carbon emission increments, including: The process proceeds node by node according to the topological sorting result of the carbon emission state transition diagram. The path state slices after incremental weight accumulation are used as the propagation units to pass along the directed edges. The set of all predecessor path state slices received by each node constitutes the incremental accumulation intermediate state. The number of incoming edges of each node is used as the basis for identifying concurrent merging nodes. The results of the compatibility test of the activation constraint relationship of each predecessor path are used as the basis for determining the concurrency type. Nodes with compatible activation constraints and no mutual exclusion dependencies are judged as fully concurrent nodes, while nodes with mutual exclusion dependencies are judged as conditionally concurrent nodes. For fully concurrent nodes, slices of the predecessor path state are extracted from the incremental accumulation intermediate state. The path ownership uniqueness assertion of each slice is used as the ownership locking mechanism. The slice accumulation value of the path independent ownership verification is bound to the unique ownership identifier to form a locked ownership incremental set. For conditional concurrent nodes, extract the state slices of each predecessor path and the corresponding activation constraint expressions from the incremental accumulation intermediate states. The interval where the activation constraint is met is the effective ownership boundary. The accumulated values ​​within the interval are bound to the ownership identifier, and the accumulated values ​​outside the interval are excluded to form an ownership increment set. The locked attribution increment set and the attribution increment set are merged into the accumulation sequence according to the topological advancement order, and each entry is bound with a unique attribution identifier to obtain the accumulation sequence with unique attribution of carbon emission increment.

[0046] The incremental accumulation process is advanced node by node according to the topological sorting result of the carbon emission state transition graph. Starting from the initial node, the incremental carbon emissions and path state information of that node are encapsulated into a path state slice. This slice records attributes such as the current cumulative carbon emissions value, the node activation time, and the path source identifier. The propagation unit passes the slices along directed edges to subsequent nodes. Each subsequent node receives path state slices from all preceding nodes, and all received slices constitute the incremental accumulation intermediate state of that node. For example, a steel component welding node receives slices from the preceding cutting and grinding process nodes, forming an intermediate state set containing information from two preceding paths.

[0047] When identifying concurrent merging nodes, the number of incoming edges for each node is counted. Nodes with more than one incoming edge are identified as concurrent merging nodes. The activation constraint expressions for each predecessor path of this node are extracted, and the compatibility between the constraints is checked. If the activation constraint for predecessor path A is "temperature ≥ 800℃" and the activation constraint for path B is "pressure ≤ 5MPa", and both constraints can be satisfied simultaneously without execution order dependency, the activation constraints are considered compatible, and the node is a fully concurrent node. When the activation constraint for path C is "select quenching process" and the activation constraint for path D is "select annealing process", they are mutually exclusive, and the node is identified as a conditionally concurrent node. A fully concurrent node refers to a node where predecessor processes can be executed in parallel without mutual exclusion. For example, in steel component manufacturing, web blanking and flange blanking can be performed simultaneously without affecting each other; therefore, their corresponding assembly nodes are fully concurrent nodes. A conditionally concurrent node refers to a node where there is a mutual exclusion dependency between predecessor processes. For example, the surface treatment process of a steel component can be carried out by either sandblasting or pickling, but the two methods cannot be applied to the same component at the same time. Therefore, the subsequent painting node is a conditional concurrent node.

[0048] For fully concurrent nodes, precursor path state slices are extracted one by one from the incremental accumulation intermediate states. Path-independent attribution verification is performed to verify the uniqueness of the path source identifier for each slice, confirming that the increment is contributed only by a specific precursor path and there is no duplicate measurement. For slices that pass verification, their cumulative carbon emission value is bound to a unique path attribution identifier, which adopts the "process sequence-branch code" format. For example, "W01-A-P02" represents the contribution of the grinding process in the first branch of the welding process. In the resulting locked attribution increment set, each increment entry carries a definite attribution identifier, ensuring that carbon emissions can be traced back to a unique precursor path. For conditionally concurrent nodes, each precursor path state slice and its activation constraint expression are extracted. The valid attribution boundary is the interval where the activation constraint is valid. For example, the activation constraint for the spraying process path is "humidity 30%-60%". Only carbon emissions from processes performed within this humidity range are counted towards the path attribution. By determining the time when a constraint is valid through real-time monitoring data, the accumulated value between that time and the time when the constraint fails is bound to the path's attribution identifier. Carbon emissions from processes executed outside the interval are excluded from the attribution, thus avoiding erroneous measurement when the conditions are not met. This forms an attribution increment set, where each entry contains a triplet of "attribution identifier - effective time interval - increment value".

[0049] The lock-attribution increment set generated by fully concurrent nodes and the attribution increment set generated by conditionally concurrent nodes are inserted into the accumulation sequence in chronological order of topology advancement. Each entry in the sequence is bound to a unique attribution identifier, recording information such as the increment source path, the corresponding node position, and the accumulation time. The final result is an accumulation sequence with unique attribution for carbon emission increments. This sequence is indexed by a time axis, and the carbon emission increment corresponding to each time point can be clearly traced back to a specific process path, supporting subsequent verification and correction operations.

[0050] Taking a practical application as an example, the manufacturing of a prefabricated steel component involves multiple parallel process paths. The main path is blanking → drilling → assembly → welding → painting; simultaneously, there is an auxiliary path: blanking → cutting → surface treatment → assembly. At the assembly node, the two paths merge, forming a concurrent flow. Through activation constraint compatibility checks, it is confirmed that these two paths can be executed simultaneously without mutual exclusion dependencies; therefore, the assembly node is determined to be a fully concurrent node. State slices of two precursor paths are extracted from the incremental accumulation intermediate states of the assembly node, labeled as the main path slice and the auxiliary path slice respectively, and each is assigned a unique attribution identifier. These identifiers ensure that the carbon emission increments of the main path and the auxiliary path can be accurately distinguished and attributed during subsequent metering. Furthermore, the welding process of this steel component can choose between ordinary welding or low-carbon welding, but these two methods are mutually exclusive. The subsequent painting node receives path state slices from both welding methods, forming conditional concurrency. If low-carbon welding technology is used in a specific batch by activating the constraint expression, the carbon emission increment of that batch is attributed to the low-carbon welding path, excluding the accumulated value of the ordinary welding path. The locked attribute increment sets and attribute increment sets of all process nodes are integrated in the topology progression order to form a complete carbon emission accumulation sequence.

[0051] For fully concurrent nodes, slices of predecessor path states are extracted from the incremental accumulation intermediate states. Using the path ownership uniqueness assertion of each slice as the ownership locking mechanism, a unique ownership identifier is bound to the slice accumulation value verified by independent path ownership, forming a locked ownership increment set, including: Extract the path traversal trajectory and corresponding carbon emission increment accumulation value of each slice of the precursor path state from the incremental accumulation intermediate state, encode the path traversal trajectory into a path signature sequence, and use the path signature sequence as the slice ownership identification credential. Construct a path independence verification matrix, and represent the set of nodes passed through by each precursor path in the carbon emission state transition diagram as a Boolean vector. By calculating the logical AND operation result of the Boolean vectors corresponding to any two paths, determine that the path pairs with a logical AND result of zero vector are path independent, and determine that the path pairs with a logical AND result of non-zero vector are path coupled. For path-independent slices, a unique binding table is established between path signature sequences and cumulative carbon emission increments. A uniqueness constraint assertion is applied to each record in the binding table to prevent the same cumulative carbon emission increment from being associated with multiple path signature sequences, thus forming a lock record for the ownership of path-independent slices. For the path-coupled slices, extract the state transition event sequence of each path, and use the non-common subsequence of the state transition event sequence as the path distinguishing feature, and assign the cumulative value of carbon emission increment to the path signature sequence with a unique non-common subsequence. The ownership lock records of path-independent slices and the ownership records of path-coupled slices are aggregated to form a lock ownership increment set.

[0052] When processing fully concurrent nodes, it is necessary to extract the state slices of all predecessor paths from the incremental accumulation intermediate states. For each slice, record its complete path traversal trajectory from the initial state to the current merging node, including the identifiers of all intermediate nodes and the corresponding cumulative carbon emission increment values. Encode the path traversal trajectory into a path signature sequence according to the node access order, using an ordered connection of node identifiers. For example, the node sequence "N1→N3→N5" is encoded as the string "N1-N3-N5". The path signature sequence serves as the unique ownership identification credential of the slice and is used for subsequent incremental ownership locking operations.

[0053] When constructing the path independence verification matrix, the total number of nodes in the carbon emission state transition graph is counted, and the matrix dimension is set to be consistent with the total number of nodes. For each precursor path, all nodes it passes through are traversed. If a path passes through a node, it is marked as 1 at the corresponding position; otherwise, it is marked as 0, forming a Boolean vector representation of the path. The Boolean vectors of any two precursor paths are extracted, and a bitwise logical AND operation is performed. When all bits of the result are 0, the two paths are considered completely independent and do not pass through any nodes in common. When at least one bit of the result is 1, the two paths are considered coupled and share some node resources.

[0054] For path-independent slices, a mapping table is established between path signature sequences and cumulative carbon emission increments. Each record in the mapping table contains a path signature sequence, the corresponding cumulative carbon emission increment, and an attribution identifier field. A uniqueness constraint assertion is applied, using a database unique index or hash table mechanism, to ensure that each cumulative carbon emission increment can only be associated with a single path signature sequence. If a cumulative carbon emission increment is detected attempting to be associated with multiple path signature sequences, a constraint violation exception is triggered, and the binding operation is rejected. The attribution lock record formed through this mechanism ensures the deterministic attribution of increments for path-independent slices.

[0055] For path-coupled slices, the state transition event sequences of each path are extracted, including the corresponding process operations and triggering conditions for each state transition. The state transition event sequences between coupled paths are compared to identify common and non-common subsequences. Common subsequences are state transition events shared by multiple paths, while non-common subsequences are state transition events unique to a specific path. Non-common subsequences are used as path distinguishing features. The uniqueness of non-common subsequences for each path is calculated. When a non-common subsequence of a path appears uniquely among all coupled paths, the cumulative carbon emission increment is assigned to the path signature sequence corresponding to that path. If non-common subsequences of multiple paths overlap, the assignment priority is determined by the order of their first appearance.

[0056] The attribution lock records of path-independent slices and path-coupled slices are aggregated to form a lock attribution increment set. The lock attribution increment set is indexed by the path signature sequence and records the cumulative carbon emission increment value and attribution lock status of each slice. The attribution lock status identifiers include locked, pending adjudication, and conflict markers, which are used for attribution verification during subsequent increment extrapolation.

[0057] Collect monitoring data on the operating conditions of each process node, verify the triggering conditions of corresponding state transition events, correct the carbon emission increments for events whose triggering conditions are not met, calibrate the set of nodes that depend on the increments and limit the extrapolation range within it, and update the accumulated sequence with the extrapolation results, including: Data on working conditions is acquired from the data acquisition terminals at each process node. The results are verified by using the logic and results of the time-series constraint satisfaction state and the resource constraint satisfaction state as trigger conditions, and the measured energy consumption value is extracted. Identify state transition events with logical false verification results, read the carbon emission amount of material response and equipment operation from the carbon emission state transition diagram, take the difference between the measured energy consumption value and the preset energy consumption value as the energy consumption deviation, and sum them after allocating according to the weight of material consumption rate and equipment power to obtain the corrected carbon emission increment value. A forward influence domain breadth-first search is performed with the state transition event where the corrected carbon emission increment value is located as the starting edge, and nodes whose carbon emission cumulative value formula contains the corrected carbon emission increment value are collected as the incremental dependency node set. The incrementally dependent node set is topologically layered. The carbon emission accumulation value of the predecessor node and the weight of the incoming edge are summed layer by layer from low to high level to obtain the updated carbon emission accumulation value of each node. An index structure from node identifier to updated carbon emission accumulation value is established. The accumulation sequence is traversed and the original carbon emission accumulation value is overwritten with the updated carbon emission accumulation value according to the index to complete the accumulation sequence update.

[0058] During the actual monitoring and verification phase, operational monitoring data is read from data acquisition terminals deployed at each processing station of the steel components. These terminals include energy consumption meters, temperature sensors, displacement sensors, and RFID readers. The timing constraint fulfillment status is determined by comparing the current system clock with the preset time window for the process. If the current time falls within the time window, it is recorded as true; otherwise, it is recorded as false. The resource constraint fulfillment status is determined by querying the material inventory database and equipment occupancy table. When the required material inventory is greater than or equal to the consumption quota and the target equipment is idle, it is recorded as true. A bitwise AND operation is performed between the timing constraint fulfillment status and the resource constraint fulfillment status. The result is the verification result of the trigger condition for the state transition event. Simultaneously, the measured energy consumption value for that process node is directly extracted from the energy consumption meter, in kilowatt-hours.

[0059] When the trigger condition verification result is false, it indicates that the process was not actually executed according to the preset conditions, and its carbon emission increment needs to be corrected. The material response carbon emission and equipment operation carbon emission corresponding to the state transition event are read from the pre-constructed carbon emission state transition diagram. The material response carbon emission is obtained from the material carbon emission factor database based on the material type and consumption, while the equipment operation carbon emission is calculated based on the equipment's rated power and operating time. The energy consumption deviation is calculated as the measured energy consumption value minus the preset energy consumption value. Material consumption rate weight and equipment power weight are introduced to allocate the energy consumption deviation. The material consumption rate weight is equal to the ratio of material consumption rate to total consumption rate, and the equipment power weight is equal to the ratio of equipment power to total power. The energy consumption deviation is multiplied by these two weights to obtain the material-side deviation component and the equipment-side deviation component, which are then multiplied by their respective carbon emission factors and summed to obtain the corrected carbon emission increment value.

[0060] Using the state transition event containing the corrected carbon emission increment as the starting edge, a forward influence domain breadth-first search is performed on the carbon emission state transition graph. Specifically, the target node of the starting edge is pushed into a queue. The head node is then iteratively removed from the queue, and its carbon emission accumulation calculation formula is checked. If the formula contains the variable symbol corresponding to the corrected carbon emission increment, the node is marked as an incrementally dependent node and added to the set. Then, all its successor nodes are pushed into the queue. This process is repeated until the queue is empty, thus completing the construction of the incrementally dependent node set.

[0061] To perform topological layering on the incrementally dependent node set, the in-degree of each node needs to be calculated. Nodes with an in-degree of zero are marked as layer 0. Layer 0 nodes are removed from the graph, and the in-degree of the remaining nodes is updated. Newly generated nodes with an in-degree of zero are marked as layer 1, and so on until all nodes are layered. The nodes are traversed from low to high layer. For each node, the cumulative carbon emission values ​​of all its predecessor nodes are extracted. Simultaneously, the weight values ​​of the edges connecting the predecessor nodes and the current node are extracted, multiplied, and summed to obtain the updated cumulative carbon emission value of the current node. A hash table structure is established, using the unique node identifier as the key and the updated cumulative carbon emission value as the value. The original accumulation sequence is traversed, and the node identifier in each sequence element is read. The corresponding updated cumulative carbon emission value is searched in the hash table. If it exists, the updated value overwrites the original value, completing the dynamic update of the accumulation sequence and ensuring that the carbon emission measurement results reflect the actual working conditions.

[0062] Based on the re-evaluated accumulation sequence, the carbon emission increments for each carbon emission accumulation state are extracted. Each entry in the accumulation sequence represents a carbon emission accumulation state, including a node identifier, cumulative carbon emissions, and attribution information. The extraction process involves sequentially reading the carbon emission increment field of each entry from the accumulation sequence to form an increment set. For entries with the same attribution identifier, their carbon emission increments need to be merged to avoid double-counting. For example, if a welding process has multiple carbon emission records in different time periods but belongs to the same steel component, the carbon emission increments of these records need to be merged.

[0063] The total carbon emissions of the steel component to be measured are obtained throughout the entire process, thus completing the carbon emission measurement task. The method for calculating the total carbon emissions throughout the entire process is to sum up all carbon emission increments. The calculation formula is: the total carbon emissions throughout the entire process are equal to the sum of the carbon emission increments of all process nodes. For complex prefabricated steel components, multiple process paths and parallel processes may be involved. When calculating, it is necessary to ensure that the carbon emission increment of each process is only included once to avoid double counting or omission. The final total carbon emissions throughout the entire process are expressed in carbon dioxide equivalents, representing the carbon footprint of the steel component from raw materials to finished products throughout its entire life cycle.

[0064] Taking a practical application as an example, the manufacturing process of an H-shaped steel column includes six main steps: material preparation, drilling, assembly, welding, quality inspection, and painting. After collecting operational monitoring data, it was discovered that the welding process actually used low-carbon welding technology instead of the originally planned conventional welding process, indicating a deviation in the triggering conditions. Based on the actual energy consumption records of the welding machine and the low-carbon welding process parameters, the carbon emission increment of the welding process was corrected to 80 kg of CO2 equivalent, a reduction of 20 kg from the original estimate. The calibrated increment depends on a set of nodes, including welding, quality inspection, and painting. The carbon emission accumulation value was re-derived within this subgraph, resulting in an updated accumulation sequence. The carbon emission increments for each step were extracted from the updated accumulation sequence: material preparation 120 kg, drilling 60 kg, assembly 40 kg, welding 80 kg, quality inspection 10 kg, and painting 70 kg. Summing these up yielded a total carbon emission of 380 kg of CO2 equivalent for the entire H-shaped steel column.

[0065] Starting with the state transition event containing the corrected carbon emission increment value as the initial edge, a breadth-first search of the forward influence domain is performed. Nodes whose carbon emission cumulative value formula contains the corrected carbon emission increment value are collected as the incremental dependency node set, including: Taking the state transition event where the corrected carbon emission increment value is located as the entry point, an incremental dependency mapping table is established with node identifier as the key and dependency path as the value. The endpoint node of the event is written into the queue to be visited, and the initial dependency path is registered for it in the incremental dependency mapping table at the same time. The set of visited node tags is initialized. Retrieve the current node from the queue to be accessed, read the dependency path of the current node from the incremental dependency mapping table, substitute the incremental reference relationship of each node in the path into the carbon emission cumulative value formula of the current node to perform the transitive reference chain verification, and determine whether the corrected carbon emission incremental value forms a valid transitive reference to the current node through the dependency path. If the verification is successful, the current node is added to the incremental dependency node set, the unvisited nodes pointed to by its forward outgoing edges are added to the pending visit queue, the extended dependency path is registered in the incremental dependency mapping table, and the visited node tag set is updated; if the verification is unsuccessful, the forward path extension through the current node is terminated. Repeat the above process of retrieving and passing the reference chain verification until the queue to be accessed is empty, and output the incremental dependency node set.

[0066] When the actual working conditions deviate from the design parameters during the processing of steel components, it is necessary to correct the carbon emission increment and determine the scope of the impact of the correction on the subsequent accumulation state. The state transition event where the corrected carbon emission increment value is located corresponds to the directed edge in the graph structure. This edge connects the predecessor node and the successor node. The carbon emission increment value is recorded in the edge attribute. The goal of the forward influence domain search is to find all nodes affected by the correction value along the graph topology direction, that is, the set of nodes whose final carbon emission accumulation value depends on the correction value.

[0067] When establishing the incremental dependency mapping table, a hash table structure is used to achieve fast lookup of node identifiers to dependency paths. This mapping table uses the unique identifier of each node as the key, and the values ​​are arrays of paths containing the corrected edge and its subsequent propagation sequence. Initially, the endpoint node identifier of the state transition event where the corrected carbon emission increment value is located is obtained. The array of paths containing only the corrected edge is written into the mapping table as the initial dependency paths. The queue to be visited adopts a first-in-first-out structure, and the initial state only contains the endpoint node. The set of visited node tags uses a Boolean hash set to quickly determine the access status by the node identifier, avoiding repeated traversal caused by loops.

[0068] After retrieving the current node from the queue to be visited, the corresponding dependency path is retrieved from the incremental dependency mapping table based on the node identifier. This path records the complete propagation chain from the corrected edge to the current node. Each edge in the path is associated with a specific carbon emission increment value. When performing the propagation reference chain verification for the carbon emission accumulation formula of the current node, the carbon emission accumulation variables of all predecessor nodes and the carbon emission increment value variable of the current incoming edge are extracted from the formula. The definition expressions of these variables are traced back layer by layer, and the carbon emission increment values ​​of each edge in the dependency path are gradually substituted into the expansion. If the expanded expression contains the variable symbol corresponding to the corrected carbon emission increment value, the verification is successful, indicating that the corrected value has an effective propagation effect on the current node through this path.

[0069] When verification is successful, the current node identifier is added to the incremental dependency node set. All forward outgoing edges of the current node are retrieved by querying the carbon emission state transition graph. The endpoints of these outgoing edges constitute candidate nodes for the next layer to be visited. These candidate nodes are traversed, and the visit status is determined by querying the visited node tag set. For unvisited nodes, the dependency path of the current node is copied and the corresponding outgoing edge is appended to form a new dependency path. This new dependency path is written to the incremental dependency mapping table using the candidate node identifier as the key, and the candidate node is added to the end of the visit queue. When updating the visited node tag set, the current node identifier is written to this set to ensure that subsequent traversals skip already processed nodes.

[0070] The failure of the validation indicates that although the current node is reachable in the graph structure, the actual calculation logic of its cumulative carbon emissions is unrelated to the corrected value. A typical scenario is that the current node's cumulative carbon emissions depend only on the increment of a specific predecessor path, while the corrected value resides in other concurrent branches. In this case, subsequent paths passing through the current node are no longer expanded, the node is not added to the incremental dependency node set, and the node pointed to by its outgoing edges is not added to the visit queue. This pruning strategy prevents the cumulative carbon emissions of irrelevant nodes from being incorrectly marked as needing recalculation.

[0071] When the queue to be visited is empty, it indicates that all reachable nodes with transitive references have been traversed. The incremental dependency node set contains all affected carbon emission accumulation status nodes along the forward path, starting from the direct successor node of the correction edge. This set defines the node range for subsequent carbon emission increment recalculation. Only the nodes within this set are recalculated for carbon emission accumulation values; the remaining nodes retain their original accumulation results, ensuring the accuracy and computational efficiency of the measurement correction.

[0072] This invention also provides a carbon emission metering system for prefabricated steel components, comprising: The information acquisition unit is used to acquire information on the component materials, process constraints, and process energy consumption of the steel component to be measured. The state modeling unit is used to abstract the triggering conditions of each process into state transition conditions based on the process constraint information, taking the carbon emission accumulation state as the node and the process execution as the state transition event, and combining the process energy consumption with the carbon emission increment of the component material to form a state transition diagram. The blind spot elimination unit is used to perform reachability traversal on the nodes of the state transition diagram, identify untouched nodes as metering blind nodes, and force the metering blind nodes to be connected to the nearest reachable path according to the pre- and post-constraint relationships to obtain the carbon emission state transition diagram. The incremental attribution unit is used to advance incremental accumulation along the topological order of the carbon emission state transition diagram, identify concurrent merging nodes and determine the concurrency type. Fully concurrent nodes lock the unique attribution of the preceding path incremental nodes with path independence attribution verification, and conditional concurrent nodes define the attribution range with the state of triggering conditions, and merge to form an accumulation sequence with unique carbon emission incremental attribution. The operating condition correction unit is used to collect operating condition monitoring data of each process node, verify the triggering conditions of the corresponding state transition events, correct the carbon emission increment of events whose triggering conditions are not met, calibrate the set of increment dependent nodes and limit the extrapolation range within it, and update the accumulated sequence with the extrapolation results. The total emission extraction unit is used to extract the carbon emission increment of each carbon emission accumulation state based on the completed re-inference accumulation sequence, so as to obtain the total carbon emission of the steel component to be measured throughout the process.

[0073] A third aspect of the present invention provides an electronic device, comprising: processor; Memory used to store processor-executable instructions; The processor is configured to invoke instructions stored in the memory to execute the aforementioned method.

[0074] A fourth aspect of the present invention provides a computer-readable storage medium having stored thereon computer program instructions that, when executed by a processor, implement the aforementioned method.

[0075] This invention can be a method, apparatus, system, and / or computer program product. The computer program product may include a computer-readable storage medium having computer-readable program instructions loaded thereon for performing various aspects of the invention.

[0076] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for measuring carbon emissions from prefabricated steel components, characterized in that, include: Obtain information on the component materials, process constraints, and process energy consumption of the steel components to be measured; Using the carbon emission accumulation state as a node and the process execution as a state transition event, the triggering conditions of each process are abstracted into state transition conditions based on the process constraint information, and the carbon emission increment is bound to the process energy consumption and the component material to form a state transition diagram. A reachability traversal is performed on the nodes of the state transition graph to identify unreached nodes as metering blind nodes. Based on the preceding and following constraints, the metering blind nodes are forcibly connected to the nearest reachable path to obtain the carbon emission state transition graph. The incremental accumulation proceeds along the topological sequence of the carbon emission state transition graph, identifying concurrent merging nodes and determining the concurrency type. Fully concurrent nodes are uniquely assigned to their predecessor path increments using path independence verification. Conditionally concurrent nodes have their assignment range defined by the fulfillment of trigger conditions. These are then merged to form an accumulation sequence with a unique carbon emission increment attribution, including: The process proceeds node by node according to the topological sorting result of the carbon emission state transition diagram. The path state slice after incremental weight accumulation is used as the propagation unit to pass along the directed edge. The set of all predecessor path state slices received by each node constitutes the incremental accumulation intermediate state. Concurrent merging nodes are identified based on the number of incoming edges at each node. The concurrency type is determined based on the compatibility test results of the activation constraint relationship of each predecessor path. Nodes with compatible activation constraints and no mutual exclusion dependencies are classified as fully concurrent nodes, while nodes with mutual exclusion dependencies are classified as conditionally concurrent nodes. For fully concurrent nodes, slices of the predecessor path state are extracted from the incremental accumulation intermediate state. The path ownership uniqueness assertion of each slice is used as the ownership locking mechanism. The slice accumulation value of the path independent ownership verification is bound to the unique ownership identifier to form a locked ownership incremental set. For conditional concurrent nodes, extract the state slices of each predecessor path and the corresponding activation constraint expressions from the incremental accumulation intermediate states. The interval where the activation constraint is met is the effective ownership boundary. The accumulated values ​​within the interval are bound to the ownership identifier, and the accumulated values ​​outside the interval are excluded to form an ownership increment set. The locked attribution increment set and the attribution increment set are merged into the accumulation sequence according to the topological advancement order, and each entry is bound with a unique attribution identifier to obtain the accumulation sequence with unique attribution of carbon emission increments; Collect monitoring data on the operating conditions of each process node, verify the triggering conditions of corresponding state transition events, correct the carbon emission increments for events whose triggering conditions are not met, calibrate the set of nodes that depend on the increments and limit the extrapolation range within it, and update the accumulated sequence with the extrapolation results, including: Data on working conditions is acquired from the data acquisition terminals at each process node. The results are verified by using the logic and results of the time constraint satisfaction state and the resource constraint satisfaction state as trigger conditions, and the measured energy consumption value is extracted. Identify state transition events with logically false verification results, read the carbon emissions from material response and equipment operation from the carbon emission state transition diagram, take the difference between the measured energy consumption value and the preset energy consumption value as the energy consumption deviation, allocate it according to the weight of material consumption rate and equipment power, and sum it to obtain the corrected carbon emission increment value; take the state transition event where the corrected carbon emission increment value is located as the starting edge and perform a breadth-first search of the forward influence domain to collect the nodes in the carbon emission accumulation value formula containing the corrected carbon emission increment value as the incremental dependency node set; The incremental dependent node set is topologically layered. The carbon emission accumulation value of the predecessor node is multiplied by the weight of the incoming edge layer by layer from low to high to obtain the updated carbon emission accumulation value of each node. An index structure from node identifier to updated carbon emission accumulation value is established. The accumulation sequence is traversed and the original carbon emission accumulation value is overwritten with the updated carbon emission accumulation value according to the index to complete the accumulation sequence update. Based on the completed re-inference of the accumulation sequence, the carbon emission increment of each carbon emission accumulation state is extracted to obtain the total carbon emission of the steel component to be measured throughout the entire process.

2. The method according to claim 1, characterized in that, Using carbon emission accumulation status as nodes and process execution as state transition events, the triggering conditions of each process are abstracted into state transition conditions based on process constraint information. This is combined with the carbon emission increments tied to the process energy consumption and the component materials to form a state transition diagram, including: Extract the time constraints and resource constraints of each process from the process constraint information, map the time constraints to the arrival criteria of the preceding carbon emission accumulation state, and map the resource constraints to the satisfaction criteria of the resource occupancy state. The joint fulfillment of the arrival criteria and the satisfaction criteria is used as the state transition condition of each process. The effective energy consumption range of each process is determined based on the state transition conditions. Within the effective energy consumption range, the process energy consumption is decomposed into material response energy consumption coupled with the consumption rate of each material in the component material, and equipment operation energy consumption associated with the mechanical power trajectory of the process. Based on the carbon emission coefficient, it is converted into material response carbon emission and equipment operation carbon emission respectively. The carbon emission increment of each process is calculated, and the carbon emission increment is bound to the state transition event corresponding to each process. Using the state transition condition as the directed edge trigger criterion and the carbon emission increment as the directed edge weight, the carbon emission accumulation state nodes are sequentially connected according to the dependency topology determined by the temporal constraints and resource constraints in the process constraint information to form the state transition graph.

3. The method according to claim 1, characterized in that, A reachability traversal is performed on the nodes of the state transition graph to identify unreached nodes as metering blind nodes. Based on pre- and post-constraint relationships, these metering blind nodes are forcibly connected to the nearest reachable path, resulting in a carbon emission state transition graph, including: Using the initial node of the state transition graph as the starting point of the forward traversal and all nodes without outgoing edges as the starting point of the reverse traversal, the traversal is performed along the forward and reverse directions of the directed edges respectively. Nodes not touched by either the forward or reverse traversal are marked as metering blind nodes. For each blind node in the metering process, the preceding and following constraint nodes associated with the node are extracted from the process constraint information. The nodes that are reachable are selected as the preceding and following anchor nodes, respectively. The difference in the hierarchical depth between the preceding and following anchor nodes is used as the access cost. The directed path between the preceding and following anchor nodes with the minimum access cost is determined as the target access path. Insert the metering blind node into the target access path, reconstruct the directed edge triggering criteria and weights from the preceding anchor node to each metering blind node using the state transition conditions of each metering blind node and the carbon emission increment, reconstruct the directed edge triggering criteria and weights from the metering blind node to the subsequent anchor node using the state transition conditions of the subsequent anchor node and the carbon emission increment, and remove the directed edges from the preceding anchor node directly pointing to the subsequent anchor node. After completing the access operation for all blind nodes in sequence, the state transition graph is reconstructed with the updated node connection relationship and directed edge weights to obtain the carbon emission state transition graph.

4. The method according to claim 1, characterized in that, For fully concurrent nodes, slices of predecessor path states are extracted from the incremental accumulation intermediate states. Using the path ownership uniqueness assertion of each slice as the ownership locking mechanism, a unique ownership identifier is bound to the slice accumulation value verified by independent path ownership, forming a locked ownership increment set, including: Extract the path traversal trajectory and corresponding carbon emission increment accumulation value of each slice of the precursor path state from the incremental accumulation intermediate state, encode the path traversal trajectory into a path signature sequence, and use the path signature sequence as the slice ownership identification credential. Construct a path independence verification matrix, and represent the set of nodes passed through by each precursor path in the carbon emission state transition diagram as a Boolean vector. By calculating the logical AND operation result of the Boolean vectors corresponding to any two paths, determine that the path pairs with a logical AND result of zero vector are path independent, and determine that the path pairs with a logical AND result of non-zero vector are path coupled. For path-independent slices, a unique binding table is established between path signature sequences and carbon emission increment accumulation values. A uniqueness constraint assertion is applied to each record in the binding table to prohibit the association of the same carbon emission increment accumulation value with multiple path signature sequences, thus forming a lock record for the ownership of path-independent slices. For the path coupling slice, extract the state transition event sequence of each path, and use the non-common subsequence of the state transition event sequence as the path distinguishing feature, and assign the carbon emission increment accumulation value to the path signature sequence with a unique non-common subsequence; The ownership lock records of path-independent slices and the ownership records of path-coupled slices are aggregated to form a lock ownership increment set.

5. The method according to claim 1, characterized in that, Starting with the state transition event containing the corrected carbon emission increment value as the initial edge, a breadth-first search of the forward influence domain is performed. Nodes whose carbon emission accumulation formula contains the corrected carbon emission increment value are collected as the incremental dependency node set, including: Taking the state transition event where the corrected carbon emission increment value is located as the entry point, an incremental dependency mapping table is established with node identifier as the key and dependency path as the value. The endpoint node of the event is written into the queue to be visited, and the initial dependency path is registered for it in the incremental dependency mapping table at the same time. The set of visited node tags is initialized. Retrieve the current node from the queue to be visited, read the dependency path of the current node from the incremental dependency mapping table, substitute the incremental reference relationship of each node in the path into the carbon emission accumulation value formula of the current node to perform transitive reference chain verification, and determine whether the modified carbon emission increment value forms a valid transitive reference to the current node through the dependency path; if the verification is successful, write the current node into the incremental dependency node set, write the unvisited node pointed to by its forward outgoing edge into the queue to be visited, register the extended dependency path in the incremental dependency mapping table, and update the visited node mark set; if the verification is unsuccessful, terminate the forward path expansion through the current node. Repeat the above process of retrieving and passing the reference chain verification until the queue to be accessed is empty, and output the incremental dependency node set.

6. A carbon emission metering system for prefabricated steel components, used to implement the method as described in any one of claims 1 to 5, characterized in that, include: The information acquisition unit is used to acquire information on the component materials, process constraints, and process energy consumption of the steel component to be measured. The state modeling unit is used to abstract the triggering conditions of each process into state transition conditions based on the process constraint information, taking the carbon emission accumulation state as the node and the process execution as the state transition event, and combining the process energy consumption with the carbon emission increment of the component material to form a state transition diagram. The blind spot elimination unit is used to perform reachability traversal on the nodes of the state transition diagram, identify untouched nodes as metering blind nodes, and force the metering blind nodes to be connected to the nearest reachable path according to the pre- and post-constraint relationships to obtain the carbon emission state transition diagram. The incremental attribution unit is used to advance incremental accumulation along the topological order of the carbon emission state transition diagram, identify concurrent merging nodes and determine the concurrency type. Fully concurrent nodes lock the unique attribution of the preceding path incremental nodes with path independence attribution verification, and conditional concurrent nodes define the attribution range with the state of triggering conditions, and merge to form an accumulation sequence with unique carbon emission incremental attribution. The operating condition correction unit is used to collect operating condition monitoring data of each process node, verify the triggering conditions of the corresponding state transition events, correct the carbon emission increment of events whose triggering conditions are not met, calibrate the set of increment dependent nodes and limit the extrapolation range within it, and update the accumulated sequence with the extrapolation results. The total emission extraction unit is used to extract the carbon emission increment of each carbon emission accumulation state based on the completed re-inference accumulation sequence, so as to obtain the total carbon emission of the steel component to be measured throughout the process.

7. An electronic device, characterized in that, include: processor; Memory used to store processor-executable instructions; The processor is configured to invoke instructions stored in the memory to execute the method according to any one of claims 1 to 5.

8. A computer-readable storage medium having computer program instructions stored thereon, characterized in that, When the computer program instructions are executed by the processor, they implement the method described in any one of claims 1 to 5.

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