Intelligent duct piece production scheduling system

Abstract

The invention relates to the technical field of production scheduling, in particular to an intelligent duct piece production scheduling system, which comprises a raw material analysis module, a material distribution control module, a scheduling speed regulation module, a section judgment module and a dislocation identification module. According to the method, by quantifying the relevance between the raw material parameter difference and the processing duration, accurate regulation and control of the task rhythm are achieved, the concrete expansion rate and fluidity response relation is utilized, the discharging rate of material distribution equipment is optimized, and the dynamic adaptive capacity of the transportation process is improved by combining the space mapping of the mold load gravity center and the vehicle running path; through recognition of the surface temperature distribution state of the mold, the judgment accuracy of maintenance section switching is enhanced, and in combination with real-time judgment and compensation control of mold groove entering deviation, the response efficiency of production scheduling and the precision of path control are improved, a high-adaptability scheduling response mechanism is brought to duct piece production, and the production efficiency of duct pieces is improved. And the beat accuracy, the resource allocation rationality and the process continuity are enhanced.

Description

Technical Field

[0001] The present invention relates to the technical field of production scheduling, and particularly to an intelligent segment production scheduling system. Background Art

[0002] The technical field of production scheduling involves the orderly organization and coordination of production resources and tasks in a manufacturing system to ensure that each production link operates efficiently according to the set technological process. The core content of this technical field lies in the realization of production plan formulation, task priority ranking, dynamic matching of job tasks and production resources, and critical path management. Production scheduling involves aspects such as information collection and processing, process control, equipment operation coordination, personnel allocation, and task assignment. Relying on data collection devices, a central control unit, and execution terminals, task pushing, status feedback, and process switching are carried out among production units through preset scheduling rules or control logics, and it is applied to various industrial scenarios such as assembly manufacturing, building material prefabrication, electronic processing, and automobile manufacturing.

[0003] Among them, an intelligent segment production scheduling system refers to a scheduling control platform for a concrete segment component production line, and the technical matters it addresses cover production task information management, control of the concrete distribution sequence of segment molds, setting of temperature curves and zone switching in independent curing kilns, issuance of instructions by the central control system, path scheduling of in-out kiln mother and child vehicles, automatic recognition and positioning control of static stop positions. Specifically, it includes taking the central control system as the core, combining the sequence control logic of the concrete distributor to achieve uniform distribution of raw materials, setting the heating, constant temperature, and cooling sections by the temperature control system to control the steam curing state, driving transport vehicles through a preset path program to complete the switching of the transfer path of the molds, and real-time monitoring and recording of the states of each key link through video monitoring and sensing feedback, and carrying out logical management of the task execution sequence in the production line and distribution of scheduling commands.

[0004] Traditional segment production scheduling technologies perform static matching based on task numbers and resource allocation rules, relying on the central control platform to push tasks and feedback status according to the rules. The data correlation between each link is weak. The raw material status is only uniformly warehoused and processed through batch codes, and it is difficult to predict the dynamic duration of specific parameter differences. The cloth control depends on a fixed discharging program, and it is easy to have uneven cloth when the concrete state is abnormal. The control of the mold center of gravity is mostly executed based on a fixed path and vehicle standard speed, lacking a feedback mechanism for the real-time load state. In the curing stage, a constant temperature control curve is used for zone operation, and the actual distribution of the thermal field is not involved in the scheduling judgment, resulting in over-curing or insufficient steam curing of the molds. In the slotting control, only the positioning sensor is relied on to judge the mold in-place state, ignoring the micro-offset error caused by the change of the mold attitude, resulting in misalignment or secondary adjustment of the mold in the in-place area, increasing the overall beat time and reducing the automation control accuracy and continuous operation efficiency. Summary of the Invention

[0005] The object of the present invention is to solve the disadvantages existing in the prior art, and to propose an intelligent segment production scheduling system.

[0006] To achieve the above object, the present invention adopts the following technical solutions: An intelligent segment production scheduling system includes: The raw material analysis module obtains the data of the cement strength grade, the particle size distribution of manufactured sand, the water demand ratio of fly ash, and the water content of crushed stone for each raw material batch, analyzes the performance differences from the preset reference values, predicts the task processing duration corresponding to the raw material batch, adjusts the task arrangement list, and obtains the production task list; The concrete placing control module calls the production task list, uses the image acquisition device to identify the spreading speed of the concrete landing point in the concrete placing equipment, adjusts the discharging rate by evaluating the fluidity of the concrete, and combines with the mold number to obtain the mold status list; The scheduling speed control module calls the mold status list, calls multiple weight sensors of the mother and son vehicles, calculates the spatial offset direction and offset amplitude between the center of gravity after the mold is loaded and the center of the vehicle in real time, and adjusts the speed parameters to obtain the speed control parameters; The section judgment module, according to the speed control parameters, uses the infrared imaging device to monitor the temperature distribution image of the mold in the curing area, including the heating area, the constant temperature area, and the cooling area, extracts the temperature distribution trend in the central area of the image, the edge temperature gradient direction, and the change trend of the thermal field uniformity, calculates the time point when the mold enters the next curing area, and obtains the heat zone switching record.

[0007] As a further solution of the present invention, the production task list includes the raw material batch number, the predicted value of the task processing duration, and the task priority order. The mold status list includes the mold number, the concrete fluidity grade, and the concrete placing duration record. The speed control parameters are specifically the offset direction vector value, the offset amplitude value, and the path speed correction coefficient. The heat zone switching record includes the change trend of the central temperature of the heat map, the edge temperature difference distribution trend, and the curing area switching time point.

[0008] As a further solution of the present invention, the raw material analysis module includes: The performance difference sub-module obtains the data of the cement strength grade, the particle size distribution of manufactured sand, the water demand ratio of fly ash, and the water content of crushed stone for each raw material batch, and extracts the performance differences between each parameter and the preset reference value to generate a raw material parameter difference set; The duration prediction sub-module, based on the raw material parameter difference set, adopts the formula: ; Calculates the predicted value of the task processing cycle for each raw material and obtains the calculation result of the predicted duration; Wherein, represents the predicted value of the task processing cycle, Indicates the task reference duration corresponding to the standard raw material parameter group, Indicates the th raw material parameter value of the current batch, Indicates the th standard reference value of the raw material, Indicates the sensitivity coefficient of the parameter pair to the processing time, Indicates the raw material parameter number currently being analyzed, Indicates the total number of raw material parameters involved in the processing; The task scheduling sub-module calls the calculated result of the predicted duration, and adjusts the task scheduling list according to the required processing duration to establish a production task list.

[0009] As a further solution of the present invention, the cloth control module includes: The landing point monitoring sub-module calls the production task list, uses an image acquisition device to analyze the expansion position of the concrete landing point in the mold in consecutive frame images, extracts the expansion radius data and the corresponding timestamps of the current frame and the previous frame, and establishes an expansion speed change value; The fluidity evaluation sub-module calls the expansion speed change value, combines the standard fluidity rate and the reference discharge rate, and uses the formula: ; Calculate the discharge rate and establish a discharge rate control parameter; Wherein, represents the real-time discharge rate that the device should execute according to the current concrete fluidity, in cubic meters per second, is the reference discharge rate, in cubic meters per second, representing the target discharge rate set under standard fluidity conditions, is the concrete expansion radius in the current image frame, in meters, representing the boundary distance that the concrete expands from the landing point in the latest frame, is the concrete expansion radius in the previous image frame, in meters, representing the boundary expansion distance of the concrete in the previous frame image, is the timestamp corresponding to the current image frame, in seconds, representing the time value recorded by the system when capturing the current frame image, is the timestamp corresponding to the previous image frame, in seconds, representing the time value recorded by the system when capturing the previous frame image, is the standard concrete diffusion rate, in meters per second, representing the standard reference rate at which the concrete expansion radius changes with time under ideal conditions, is the fluidity response adjustment index, which is a dimensionless value; The rhythm recording sub-module calls the discharging rate control parameter, records the concrete placing duration of each mold, extracts the mold numbers that have completed placing, and establishes a mold status list.

[0010] As a further solution of the present invention, the scheduling speed regulation module includes: The center of gravity recognition sub-module calls the mold status list, calls multiple weight sensors of the mother and son vehicle, extracts the mass data at multiple positions and maps it to the vehicle chassis coordinate system, calculates the center of gravity position after the mold is loaded, and obtains the center of gravity coordinate data; The offset calculation sub-module calls the center of gravity coordinate data and uses the formula: ; Calculate the speed adjustment control parameter; Wherein, is the speed adjustment control parameter, is the adjusted operating speed that the vehicle should execute in the current path section, with the unit of meters per second, is the section standard speed value, is the preset basic traveling speed, with the unit of meters per second, is the coordinate value of the mold center of gravity along the transverse axis in the vehicle coordinate system, with the unit of meters, is the coordinate value of the mold center of gravity along the longitudinal axis in the vehicle coordinate system, with the unit of meters, is the coordinate value of the mold center of gravity along the vertical axis in the vehicle coordinate system, with the unit of meters, is the reference coordinate value of the vehicle track center point along the transverse axis in the vehicle coordinate system, with the unit of meters, is the reference coordinate value of the vehicle track center point along the longitudinal axis in the vehicle coordinate system, with the unit of meters, is the reference coordinate value of the vehicle track center point along the vertical axis in the vehicle coordinate system, with the unit of meters, is the boundary length value of the mold in the vehicle coordinate system, with the unit of meters, is the boundary width value of the mold in the vehicle coordinate system, with the unit of meters, is the boundary height value of the mold in the vehicle coordinate system, with the unit of meters, is the adjustment weight coefficient of the proportion of the lateral offset difference, which is a dimensionless real number, is the adjustment weight coefficient of the proportion of the longitudinal offset difference, which is a dimensionless real number, is the adjustment weight coefficient of the proportion of the vertical offset difference, which is a dimensionless real number; The speed regulation control sub-module calls the speed adjustment control parameter, sets the speed parameters at multiple positions in the mother and son vehicle path, including the operating speeds in the turning section, acceleration section and dwelling section, and establishes the traveling speed control parameter.

[0011] As a further solution of the present invention, the section judgment module includes: According to the speed control parameter, the heat map acquisition sub-module calls the infrared imaging devices in each maintenance sub-area, including the heating area, the constant temperature area, and the cooling area, to collect the temperature distribution image on the surface of the mold, and obtain the thermal image of the mold surface; The thermal field trend recognition sub-module calls the thermal image of the mold surface, divides the image into multiple grids, extracts the temperature mean sequence of each grid in the central area of the image, recognizes the temperature distribution trend in the central area, combines the temperature in the grids in the edge area of the image, calculates the edge temperature gradient direction, analyzes the change trend of the thermal field uniformity, and obtains the mold state analysis result; The partition transfer determination sub-module calls the mold state analysis result, combines the required mold state of each partition, calculates the time point for the mold to enter the next maintenance period, and obtains the hot zone switching record.

[0012] As a further solution of the present invention, the system further includes: The misalignment recognition module calls the hot zone switching record, uses the image acquisition device to recognize the positions of the two side lines of the mold, measures the angle with the track direction, detects the position offset event during the mold slotting process, and adjusts the control parameters of the mother and son vehicles according to the offset direction to obtain the segment production line management result; The segment production line management result specifically refers to the mold misalignment angle, the offset direction identifier, and the vehicle control adjustment instruction.

[0013] As a further solution of the present invention, the misalignment recognition module includes: The image acquisition sub-module calls the hot zone switching record, uses the image acquisition device to take the top view image of the mold slotting section, locates the pixel points of the two side edges of the mold in the image coordinate system, converts them into actual space coordinates, constructs the mold side line direction vector, and measures the angle with the track center reference direction to obtain the side line angle data set; The offset event determination sub-module calls the side line angle data set, detects the position offset event during the mold slotting process, including the angle offset event, the side line angle difference over-limit event, and the slotting center line offset event, and generates the slotting offset determination result; The path adjustment execution sub-module calls the slotting offset determination result, combines the offset angle direction, sets the traveling direction, traveling speed, and braking trigger value parameters of the corresponding mother and son vehicles, and obtains the segment production line management parameter set.

[0014] Compared with the prior art, the advantages and positive effects of the present invention are as follows: In the present invention, by quantifying the correlation between the differences in raw material parameters and the processing duration, precise control of the task rhythm is achieved. Utilizing the relationship between the concrete expansion rate and the fluidity response, the discharging rate of the batching equipment is optimized. Combining the spatial mapping of the center of gravity of the mold load and the vehicle operation path, the dynamic adaptability during transportation is improved. Through the identification of the surface temperature distribution state of the mold, the accuracy of the determination for switching the curing section is enhanced. Combining the real-time determination and compensation control of the mold slotting offset, the response efficiency of production scheduling and the accuracy of path control are improved, bringing a highly adaptable scheduling response mechanism for segment production, and enhancing the beat accuracy, the rationality of resource allocation, and the continuity of processes. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 is the system flowchart of the present invention; Figure 2 is the flowchart of the raw material analysis module of the present invention; Figure 3 is the flowchart of the batching control module of the present invention; Figure 4 is the flowchart of the scheduling speed regulation module of the present invention; Figure 5 is the flowchart of the section judgment module of the present invention; Figure 6 is the flowchart of the misalignment identification module of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0016] In order to make the objectives, technical solutions and advantages of the present invention clearer and more understandable, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0017] In the description of the present invention, it should be understood that the orientation or positional relationships indicated by the terms "length", "width", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc. are based on the orientation or positional relationships shown in the accompanying drawings. They are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus should not be construed as a limitation of the present invention. In addition, in the description of the present invention, "a plurality of" means two or more unless otherwise specifically defined.

[0018] Please refer to Figure 1 , an intelligent segment production scheduling system includes: The raw material analysis module obtains data on the cement strength grade, particle size distribution of manufactured sand, water demand ratio of fly ash, and water content of crushed stone for each raw material batch, analyzes the performance differences from the preset reference values, predicts the task processing duration corresponding to the raw material batch, adjusts the task scheduling list, and obtains the production task list; Particle size distribution of manufactured sand: The particle size distribution of manufactured sand refers to the mass percentage of particles with different particle sizes in the manufactured sand, which is used to evaluate the rationality of the particle size distribution of the manufactured sand. The percentage content of each particle size is extracted through a dry sieve test, and the particle size combination is used to determine the grading type of the sand and its influence on the workability and strength of concrete; The batching control module calls the production task list, uses an image acquisition device to identify the spreading speed of the concrete landing point in the concrete batching equipment, adjusts the discharge rate by evaluating the fluidity of the concrete, and combines with the mold number to obtain the mold status list; Fluidity of concrete: It is used to reflect the deformation ability of fresh concrete under the action of gravity and is an important parameter of the workability of concrete. Its common detection method is the slump test, with the unit of mm. In the video monitoring batching scenario, its fluidity trend is indirectly reflected through the time function of the spreading speed and radius of the concrete landing point, and its behavioral characteristic changes are constructed; The scheduling and speed control module calls the mold status list, calls multiple weight sensors of the mother and child vehicles, calculates the spatial offset direction and amplitude between the center of gravity after the mold is loaded and the vehicle center in real time, and adjusts the speed parameters to obtain the speed control parameters; The section judgment module, based on the speed control parameters, uses an infrared imaging device to monitor the temperature distribution image of the mold in the curing area, including the heating zone, constant temperature zone, and cooling zone, extracts the temperature distribution trend in the central area of the image, the edge temperature gradient direction, and the change trend of the thermal field uniformity, calculates the time point when the mold enters the next curing area, and obtains the heat zone switching record; Change trend of thermal field uniformity: The evaluation of thermal field uniformity is to extract the multi-period trends of indicators such as the temperature difference range and temperature distribution density between the central area and the edge area after obtaining the temperature distribution map through infrared imaging, which is used to judge whether the concrete component has completed the conversion of the heating, constant temperature, or cooling state, and serves as a reference signal for evaluating whether the curing zone switching can be carried out; The misalignment recognition module calls the heat zone switching record, uses an image acquisition device to identify the positions of the two side lines of the mold, measures the angle with the track direction, detects the position offset event during the process of the mold entering the groove, and adjusts the control parameters of the mother and child vehicles according to the offset direction to obtain the management result of the segment production line.

[0019] The production task list includes the raw material batch number, the predicted task processing duration value, and the task priority order. The mold status list includes the mold number, the concrete fluidity grade, and the concrete placing duration record. The speed control parameters are specifically the offset direction vector value, the offset amplitude value, and the path speed correction coefficient. The hot zone switching record includes the change trend of the center temperature of the heat map, the distribution trend of the edge temperature difference, and the curing zone switching time point. The segment production line management result specifically refers to the mold misalignment angle, the offset direction identifier, and the vehicle control adjustment instruction.

[0020] Please refer to Figure 2 , the raw material analysis module includes: The performance difference sub-module obtains the data of the cement strength grade, the particle size distribution of manufactured sand, the water demand ratio of fly ash, and the water content of crushed stone for each raw material batch, extracts the performance differences between each parameter and the preset reference value, and generates a set of raw material parameter differences; The performance difference sub-module collects the four key raw material parameters of the cement strength grade, the particle size distribution of manufactured sand, the water demand ratio of fly ash, and the water content of crushed stone in each raw material batch, extracts the numerical differences between these parameters and the reference values set by the system respectively, so as to form a set of raw material parameter differences. During the execution process, first set a numbered label for each batch of raw materials. For example, the current processing batch number is set to "B20240401". Read the cement strength grade of this batch as 52.5 MPa, and subtract it from the reference strength of 50.0 MPa set by the system to get a deviation value of 2.5 MPa. Then read the D60 value of the particle size distribution of manufactured sand as 0.35 mm, the standard reference value as 0.30 mm, and the difference as 0.05 mm. Next, read the water demand ratio of fly ash as 0.68, the standard ratio as 0.65, and the difference as 0.03. Then read the water content of crushed stone as 1.9%, and subtract it from the standard value of 2.0% to get a deviation of -0.1%. The above four results are respectively recorded as ΔC1 = 2.5, ΔC2 = 0.05, ΔC3 = 0.03, ΔC4 = -0.1, and form a set of parameter differences in vector form , this set is the data input directly called by the subsequent predicted processing duration module. During the entire data acquisition process, all parameters are from the real-time detection data of the raw material transportation batch by the sensor sampling system or the fixed value data obtained from quantitative laboratory analysis, ensuring that the extracted differences have the basis of raw material authenticity and processing status, and providing an effective quantitative basis for further prediction.

[0021] The duration prediction sub-module is based on the set of raw material parameter differences and uses the formula: ; Calculate the predicted value of the task processing cycle for each raw material and obtain the calculation result of the predicted duration; Among them, represents the predicted value of the task processing cycle, Indicates the task benchmark duration corresponding to the standard raw material parameter group, Indicates the th raw material parameter value in the current batch, Indicates the th standard reference value of the raw material, Indicates the sensitivity coefficient of the th parameter pair to the processing time, Indicates the current raw material parameter number being analyzed, Indicates the total number of raw material parameters participating in the processing; After the duration prediction sub-module obtains the raw material parameter difference set Set the benchmark duration to 120 minutes, substitute the four parameters for calculation respectively. Set the processing sensitivity coefficient of the first item, cement strength, to 2.0 min / MPa and perform the calculation ; The sensitivity coefficient of the second item, mechanism sand gradation, is 30.0 min / mm, calculate ; The sensitivity coefficient of the third item, water demand ratio of fly ash, is 25.0 min, calculate ; The sensitivity coefficient of the fourth item, water content of crushed stone, is 15.0 min / %, calculate , and then add all the adjustment values to the benchmark task duration to form a complete calculation expression: ; Substitute the data to perform the specific operation: ; The predicted value of the task processing cycle refers to the dynamic prediction value of the task completion time by the system based on the raw material parameter differences. The result indicates that under the current parameter conditions, the predicted value of the processing cycle for a single task is 125.75 minutes. This result will be used as the basis for determining whether to schedule and reorder in the next-stage task list adjustment. The formula starts from the task benchmark processing duration corresponding to the standard raw material parameter group, accumulatively corrects each difference between the current batch of raw material parameters and the standard parameters as an influencing factor. The weight of each difference item is determined by its corresponding time sensitivity coefficient, reflecting its response intensity to the processing duration. By summing the products of the differences of all participating parameters and their sensitivity coefficients, a set of total duration adjustment values is formed, which is superimposed on the benchmark duration. Finally, the predicted processing cycle of this batch of tasks is calculated. Its essence is to cumulatively map the time changes caused by the deviation of the raw materials from the standard ratio to the task scheduling cycle to quantify the impact of raw material performance fluctuations on the production line processing rhythm.

[0022] The task scheduling sub-module calls the predicted duration calculation result, adjusts the task scheduling list according to the required processing duration, and establishes a production task list; The task scheduling sub-module receives the predicted processing duration of 125.75 minutes transmitted from the previous module, combines it with the initial set benchmark task duration of 120 minutes for the current task number "T002" in the task list, performs a difference comparison between the predicted value and the benchmark value, sets the tolerance threshold to ±3 minutes, and the current difference is 5.75 minutes, exceeding the threshold limit. Therefore, it is judged as "requiring scheduling rearrangement". When executing the adjustment process, first extract the current task from its original position, and judge whether the condition for permuting the previous and subsequent task numbers is satisfied. If satisfied, postpone the task "T002" to two positions after the subsequent tasks. For example, if the original order is "T001→T002→T003", it is updated to "T001→T003→T002". Subsequently, update the "task duration" field of the "T002" task to "125.75", update its status field to "high-time-consuming task", and insert a record of this postponement in the scheduling record table. The system also provides the adjusted task list and the predicted cycle field for subsequent sub-modules (such as the fabric control module) for the speed control scheduling linkage module to call and process.

[0023] Table 1 Raw Material Difference and Task Scheduling Calculation Table

[0024] As shown in Table 1, the current raw material batch has varying degrees of deviation from the benchmark in various parameters, and is converted into single-item time-consuming increase and decrease values through the corresponding processing time sensitivity coefficient, finally forming a total predicted processing cycle of 125.75 minutes, exceeding the threshold standard, triggering task adjustment. The task number "T002" is re-listed at the end of the task list and the status is updated.

[0025] Please refer to Figure 3 , the fabric control module includes: The landing point monitoring sub-module calls the production task list, uses an image acquisition device to analyze the extended position of the concrete landing point in the mold in consecutive frame images, extracts the extended radius data and the corresponding timestamps of the current frame and the previous frame, and establishes the extended speed change value; The landing point monitoring sub-module calls the previously generated production task list, and performs real-time image acquisition on the mold corresponding to the current task number in the list. The industrial camera arranged directly above the concrete placing equipment acquires concrete landing point images at a frequency of 5 frames per second. The system analyzes each frame of the image, identifies the edge contour of the concrete landing point in the image, and extracts the maximum expansion radius information in the bottom area of the mold. During the execution process, the system reads the boundary position of the concrete expansion in the current frame (such as the nth frame), and calculates the distance L2 value from the center of the circle to the farthest point on the edge. For example, assume that the timestamp of the nth frame image is 8.2 seconds and the expansion radius is 0.38 meters, and the timestamp of the previous frame image (the n - 1th frame) is 8.0 seconds and the expansion radius is 0.35 meters. The system performs subtraction operations on the radius values and timestamps of these two frames, calculates the expansion radius increment ΔL = 0.38 - 0.35 = 0.03 meters, and the time interval ΔT = 8.2 - 8.0 = 0.2 seconds. Subsequently, the system calculates the expansion speed v = 0.03 / 0.2 = 0.15 meters per second through the expansion increment and the time difference, and records this speed value as the expansion speed change index at the current time point. The system stores the above calculation results in the data structure corresponding to the task and continuously iteratively updates the expansion speed data set of the subsequent image frames in the mold.

[0026] The fluidity evaluation sub-module calls the expansion speed change value, combines the standard fluidity rate and the reference discharge rate, and uses the formula: ; Calculate the discharge rate and establish the discharge rate control parameter; Among them, represents the real-time discharge rate that the equipment should execute according to the current concrete fluidity, with the unit of cubic meters per second, is the reference discharge rate, with the unit of cubic meters per second, representing the target discharge rate set under standard fluidity conditions, is the concrete expansion radius in the current image frame, with the unit of meters, representing the boundary distance that the concrete expands from the landing point to the outside in the latest frame, is the concrete expansion radius in the previous image frame, with the unit of meters, representing the boundary expansion distance of the concrete in the previous frame of the image, is the timestamp corresponding to the current image frame, with the unit of seconds, representing the time value when the system records the capture of the current frame of the image, is the timestamp corresponding to the previous image frame, with the unit of seconds, representing the time value when the system records the capture of the previous frame of the image, is the standard concrete diffusion rate, with the unit of meters per second, representing the standard reference rate at which the concrete expansion radius changes with time under ideal conditions, is the fluidity response adjustment index, which is a dimensionless value; After obtaining the increment of the expansion radius ΔL and the time interval ΔT between consecutive frames, the liquidity evaluation sub-module calculates the discharge rate control parameter Qo of the concrete at the current moment in combination with the preset standard concrete diffusion rate and the system benchmark discharge rate. In this step, the system first reads the value of the standard concrete diffusion rate Vs as 0.05 m / s, sets the benchmark discharge rate Qb of the system as 0.15 m³ / s, and sets the liquidity response adjustment index α as 1.2 (dimensionless). According to the measured increment of the expansion radius of 0.03 m and the time interval of 0.2 s, substitute them into the formula: ; where, , , , , , α = 1.2, substitute them into the formula to perform the calculation: ; This result indicates that the liquidity of the current concrete has been significantly improved. The system should perform an adjustment to increase the discharge rate, and the adjustment value is 0.5606 m³ / s, exceeding the Qb±20% threshold. The system determines that it is necessary to update the setting of the cloth feeding rate in the rhythm recording module. This formula calculates the current expansion speed through the difference in the expansion radius of the concrete landing points in consecutive frames of the image and the time difference, and then performs ratio normalization processing with the standard diffusion rate to form a dimensionless relative liquidity index. This ratio represents the deviation degree between the liquidity of the current concrete and the standard state. Subsequently, non-linear adjustment is performed through the set exponential parameter to enhance or suppress the influence amplitude of this deviation degree on the discharge rate. Finally, the adjusted result is multiplied by the benchmark discharge rate set by the system to obtain the actual discharge rate that should be executed currently, realizing the dynamic control of the cloth feeding equipment. The formula constructs a liquidity response mechanism based on visual feedback. By detecting the speed of the concrete expanding in the mold, the system can perceive the working performance state of the concrete in real time, and based on the comparison result with the standard diffusion behavior, intelligently adjust the discharge rate, enabling it to not only meet the fast cloth feeding under the high liquidity state but also appropriately slow down the discharge when the liquidity is poor to prevent accumulation and unevenness, effectively enhancing the adaptability of the system to the changes in the concrete state and realizing intelligent scheduling and precise control.

[0027] The rhythm recording sub-module calls the discharge rate control parameter, records the concrete cloth feeding duration of each mold and extracts the mold numbers that have completed cloth feeding, and establishes a mold status list; The rhythm recording sub-module receives the calculated discharge rate control parameter Qo = 0.5606 cubic meters per second and binds it to the cloth feeding process record of the current mold number "F011". During the recording process, the system counts the duration experienced by mold F011 from the starting time of the first discharge to the time when the concrete fills the entire mold cavity area. The specific process is as follows: Set the cloth feeding starting time as 8.0 seconds, and the time when the system detects that the concrete in the current frame image has covered the mold contour boundary is 9.4 seconds. Then the cloth feeding duration is 1.4 seconds. This value is the cloth feeding rhythm recording result corresponding to this mold. The system writes this duration value, the corresponding mold number, and the Qo value into the mold status list together. The subsequent module will judge whether to enter the scheduling and speed regulation link based on this. The complete data form of this record is shown in the following table: Table 2 Record Table of Mold Cloth Feeding Status Parameters

[0028] As shown in Table 2, in the current production task of mold F011, due to the abnormal increase in the expansion rate, the discharge rate needs to be increased to 0.5606 cubic meters per second, and the total cloth feeding time is 1.4 seconds. The system makes a linkage adjustment of speed and rhythm for downstream tasks based on this list.

[0029] Please refer to Figure 4 , the scheduling and speed regulation module includes: The center of gravity recognition sub-module calls the mold status list, calls multiple weight sensors of the mother and son vehicle, extracts the mass data at multiple positions and maps them to the vehicle chassis coordinate system, calculates the center of gravity position after the mold is loaded, and obtains the center of gravity coordinate data; Based on the mold status list generated by the previous module, the center of gravity recognition sub-module obtains the mold numbers marked as "cloth feeding completed" in the current task, corresponds them with the positioning module of the mother and son vehicle, allocates the mold positions to the vehicle load platform, and collects the instantaneous load-bearing data at the four support points through four groups of weight sensors arranged at the four corners of the vehicle chassis by the mother and son vehicle. Assume that the mold numbered F017 is currently in the center area of the vehicle platform, and the detection values of the front left, front right, rear left, and rear right sensors are 260 kg, 255 kg, 270 kg, and 265 kg in sequence. The system takes the origin of the vehicle coordinate system set at the center of the platform as the reference, sets the positions of each sensor as (-0.75, 1.0, 0.0), (0.75, 1.0, 0.0), (-0.75, -1.0, 0.0), (0.75, -1.0, 0.0), and then calculates the overall mass of the mold as 260 + 255 + 270 + 265 = 1050 kg according to the three-dimensional moment balance formula, and performs the center of gravity coordinate calculation for the X, Y, and Z axes. The center of gravity in the X direction is meters, and in the Y direction is In the Z direction, since the sensors are on the same plane, it is initially defined as 0.95 m. Through the above calculations, the center of gravity coordinates of the mold in the mother-daughter vehicle coordinate system are (−0.0071 m, −0.0190 m, 0.95 m), and this coordinate is the result of the center of gravity position in the current mold loading state.

[0030] The offset calculation sub-module calls the center of gravity coordinate data and uses the formula: ; Calculate the speed adjustment control parameter; Among them, is the speed adjustment control parameter, is the adjusted operating speed that the vehicle should execute in the current path section, with the unit of meters per second, is the section standard speed value, is the preset basic traveling speed, with the unit of meters per second, is the coordinate value of the mold center of gravity along the transverse axis in the vehicle coordinate system, with the unit of meters, is the coordinate value of the mold center of gravity along the longitudinal axis in the vehicle coordinate system, with the unit of meters, is the coordinate value of the mold center of gravity along the vertical axis in the vehicle coordinate system, with the unit of meters, is the reference coordinate value of the vehicle track center point along the transverse axis in the vehicle coordinate system, with the unit of meters, is the reference coordinate value of the vehicle track center point along the longitudinal axis in the vehicle coordinate system, with the unit of meters, is the reference coordinate value of the vehicle track center point along the vertical axis in the vehicle coordinate system, with the unit of meters, is the boundary length value of the mold in the vehicle coordinate system, with the unit of meters, is the boundary width value of the mold in the vehicle coordinate system, with the unit of meters, is the boundary height value of the mold in the vehicle coordinate system, with the unit of meters, is the adjustment weight coefficient of the proportion of the transverse offset difference, which is a dimensionless real number, is the adjustment weight coefficient of the proportion of the longitudinal offset difference, which is a dimensionless real number, is the adjustment weight coefficient of the proportion of the vertical offset difference, which is a dimensionless real number; After the offset calculation sub-module obtains the center of gravity coordinate data 、 、 and combines it with the reference values of the vehicle reference track center point in the coordinate system 、 、 , according to the formula: ; Execute the calculation of the speed adjustment control parameter and set the vehicle running standard speed m / s, the maximum length, width, and height of the mold accommodated by the vehicle chassis are , , , and the offset direction adjustment weights are set to be , , . Substitute all the parameters into the formula for calculation: ;

[0031] The results of the speed adjustment control parameters show that the current mold load causes a slight offset between the vehicle's center of gravity and the track center. It is necessary to slightly lower the traveling speed from the standard speed of 1.2 m / s to 1.1959 m / s to ensure the running stability of the mold's center of gravity. The main function of the speed adjustment control parameters is to dynamically adjust the speed of the transport vehicle according to the mold loading state and the real-time running condition of the vehicle to ensure safety and accuracy during the production process. The system monitors the center of gravity position of the mold and its offset relative to the vehicle center, and combines the transportation requirements of each section to automatically adjust the vehicle's speed in different path sections (such as turning sections, acceleration sections, and dwelling sections). This adaptive speed adjustment mechanism can effectively reduce stability problems caused by center of gravity offset or section change, reduce the accident risk, ensure the stability and position accuracy of the mold during transportation, and improve the running efficiency and product quality of the entire production line.

[0032] The speed regulation sub-module calls the speed adjustment control parameters, sets the speed parameters at multiple positions in the mother-daughter vehicle path, including the running speeds in the turning section, acceleration section, and dwelling section, and establishes the traveling speed control parameters; The speed regulation sub-module reads the value of the speed adjustment control parameter m / s, and calls the path section information provided by the section recording module in the current vehicle traveling path. Divide the section m / s. Section B is the main running section, taking the value equal to Vc, that is, 1.1959 m / s. Section C is the dwelling stop section, and the speed is set to 0. Finally, the system writes the speed parameters of the three sections into the vehicle path control table, marking the start and end coordinates and the bound speed values of each section for the vehicle main control system to synchronously read and execute the instructions, forming the complete traveling speed control parameters. The data record is shown in the following table: Table 3 Mother-daughter Vehicle Speed Adjustment Control Parameter Table

[0033] As shown in Table 3, when the mother-daughter vehicle is carrying mold F017, according to the offset difference of the current load center of gravity compared to the vehicle center position, calculate the adjusted running speed parameters and refine them to each paragraph of the path for subsequent precise control of the vehicle speed regulation rhythm.

[0034] Please refer to Figure 5 , the section judgment module includes: According to the speed control parameters, the thermal image acquisition sub-module calls the infrared imaging devices in each maintenance sub-area, including the heating area, the constant temperature area, and the cooling area, to collect the temperature distribution image on the surface of the mold and obtain the thermal image of the mold surface. After obtaining the vehicle speed adjustment parameter Vc, the thermal image acquisition sub-module triggers the mold current position recognition process based on this parameter, locates the mold to the sub-section of the maintenance area where it is located, and performs thermal imaging scanning by calling the infrared imaging device with the corresponding number in the current section. The infrared device collects a thermal distribution image every 2 seconds, and uses a 5×5 grid to cover the entire surface area of the mold. For example, mold F021 is currently in the constant temperature area, and the thermal map distribution collected by the infrared device is as shown in the table. Each grid represents the average temperature value per unit area of a certain local area on the mold surface, with the unit of °C. The temperature in the central area of the image is concentrated between 65°C and 66.5°C, and there are slight fluctuations and individual high and low temperature point differences in the edge area. For example, the temperature at row 1 column 4 is 68.05°C, and the temperature at row 3 column 4 is 61.17°C. The system records the acquisition timestamp of the current sampled image and the mold number, stores the acquisition result as "mold F021 - constant temperature area - image 1", continuously updates the image sequence with this number during the movement of the mold, and saves it in the thermal image storage module as the input image dataset for subsequent thermal field trend recognition. In this process, the thermal image data of the mold surface is obtained.

[0035] The thermal field trend recognition sub-module calls the thermal image of the mold surface, divides the image into multiple grids, extracts the temperature mean sequence of each grid in the central area of the image, identifies the temperature distribution trend in the central area, combines the temperatures in the grids in the edge area of the image, calculates the edge temperature gradient direction, analyzes the change trend of the thermal field uniformity, and obtains the mold status analysis result. The thermal field trend recognition sub-module calls the thermal image data of the mold surface, divides each image into 25 grid areas of 5×5, and sets the central area as nine grid areas from row 2 to row 4 and column 2 to column 4. The temperature values of each grid in the central area are extracted in turn, which are 68.16°C, 66.53°C, 64.06°C, 64.07°C, 65.48°C, 61.17°C, 62.97°C, 65.63°C, and 63.18°C. Calculate the mean sequence trend of these nine values, use the sequence standard deviation to judge the temperature fluctuation trend and identify whether it tends to be uniform. The current standard deviation of the central area is about 1.97°C. If the system sets the standard deviation fluctuation threshold to 2.5°C, then the thermal field center is determined to be "tending to be stable". At the same time, the average temperature values of a total of 16 grids on the four edges of the image are extracted as 64.18°C. Comparing with the central area mean value of 64.94°C, the temperature gradient from the edge to the center is calculated as -0.76°C. Analyzing that the direction of this gradient points to the center point of the image indicates that the heat converges from the edge to the center, and the thermal field uniformity is becoming stable. Finally, this judgment result is stored in the mold status analysis field, and the label is set as "temperature stable - mid-term state in the constant temperature area".

[0036] Table 4 Mold Thermal Distribution Grid Table

[0037] As shown in Table 4, it is the thermal image data collected by mold F021 at a certain moment in the constant temperature zone. Among them, the central grid refers to the 9 regions formed by rows 2 to 4 and columns 2 to 4, and the edge region is the 16 grids on the periphery. The table data has been accurately positioned according to the image coordinates.

[0038] The partition transfer determination sub-module calls the mold status analysis result, combines the mold status required for each partition, calculates the time point when the mold enters the next curing period, and obtains the heat zone switching record; After receiving the mold status analysis result, the partition transfer determination sub-module makes a comparison according to the stage requirements of each curing zone for the mold status. In the heating zone, it is necessary to detect that the temperature rises rapidly and the central fluctuation amplitude is greater than 3°C. In the constant temperature zone, the central fluctuation standard deviation needs to be lower than 2.5°C and maintained for 2 minutes. In the cooling zone, the central temperature drop rate needs to be less than -1°C / min for two consecutive frames. Currently, for mold F021 in the constant temperature zone, the central zone temperature fluctuation is less than 1.5°C for two consecutive frames, and the edge gradient is slowing down, meeting the constant temperature stability determination condition. At the same time, the system obtains the image acquisition timestamp from the historical record. The current image number timestamp is 14:08:00, and the previous image number timestamp is 14:06:00, indicating that the mold has been in the constant temperature stable section for more than 2 minutes. The system confirms that the mold meets the condition for entering the next cooling zone, records the transfer time point as 14:08:00, establishes a heat zone switching record item and stores it as "F021 - Constant Temperature Zone → Cooling Zone", and completes the partition switching data annotation.

[0039] Please refer to Figure 6 , the dislocation recognition module includes: The image acquisition sub-module calls the heat zone switching record, uses the image acquisition device to take a top view image of the mold slot entry section, locates the pixel points of the two side edges of the mold in the image coordinate system, converts them into actual space coordinates, constructs the mold side line direction vector, and measures the angle with the track center reference direction to obtain the side line angle data set; The image acquisition sub-module selects the image acquisition period of the corresponding mold during the slotting process according to the mold number and time node in the hot zone switching record, calls the industrial vision system deployed above the slotting area to obtain the top-down view image of the mold top. The system locates the pixel coordinates of the left and right edge points of the mold through the image processing program. For example, for the mold numbered F024, the pixel coordinates of the left edge point in its image are (122, 295), and the right edge point is (523, 297). Through the preset conversion coefficient of 1 pixel = 0.25 mm from image pixels to the actual space, the converted left edge point coordinates are (30.5 mm, 73.75 mm), and the right edge point coordinates are (130.75 mm, 74.25 mm). The system regards these two points as the starting point and the ending point of the direction vector of the mold side line. According to the construction method of the two-point vector, the direction vector is (100.25 mm, 0.5 mm). Subsequently, the reference direction vector (100 mm, 0 mm) of the track center line is called, and the direction angles of the two in the horizontal coordinate system are calculated respectively. The direction angle of the mold side line is , and the track direction angle is . The included angle between the two is 0.29°. The system adds the included angle value to the side line included angle data set, records the mold number, image number, edge point space coordinates and the calculated angle, as the input data source for subsequent offset event determination.

[0040] The offset event determination sub-module calls the side line included angle data set to detect the position offset events of the mold during the slotting process, including angle offset events, side line included angle difference over-limit events, and slotting center line offset events, and generates the slotting offset determination result; The offset event determination sub-module extracts the side line included angle values and mold direction angle information of each mold from the side line included angle data set, and performs three offset judgments by comparing the preset offset determination threshold. The first is the angle offset event judgment. If the absolute value of the deviation between the side line direction angle and the track direction angle is greater than 2°, it is judged as an angle offset event. The included angle of the current mold numbered F024 is 1.15°, which is less than 2°, so it is not judged as an angle offset event. The second is the side line included angle difference over-limit event. The system calculates the included angle difference between the extension directions of the left and right side lines. If it exceeds 3°, it is over-limit. The detected side line direction included angle of the current mold image is only 0.29°, and the difference limit is not triggered. The third is the slotting center line offset event. The midpoint coordinates of the mold edge line and the track center point coordinates are called to calculate the midpoint lateral offset distance. If it exceeds the set tolerance of ±10 mm, it is recorded as a center line offset event. The midpoint position of the F024 mold is calculated as . The track center is set to 80 mm, and the offset is 0.625 mm, which is lower than the 10 mm tolerance. The system records the offset as "normal", and the final output result is: There is no offset abnormality for mold F024, and the slotting offset determination result is "Offset status: None".

[0041] The path adjustment execution sub-module calls the in-slot offset determination result, combines the offset angle direction, sets the traveling direction, traveling speed and braking trigger value parameters of the corresponding main and sub-cars, and obtains the segment production line management parameter set; After reading the in-slot offset determination result, the path adjustment execution sub-module sets the path control parameters of the main and sub-cars in combination with the offset status and angle deviation direction in the result field. If the mold status is "offset direction to the left", the traveling angle of the main and sub-cars is set to deviate 0.5° to the right for compensation. If the offset angle is greater than 3°, the deceleration control mechanism is automatically triggered and the braking trigger value is recorded. The current mold F024 is determined to be "no offset", the standard traveling path angle is set to 0°, the speed is maintained at the standard speed value of 1.2 m / s, and the braking trigger value is set to 10%, indicating that if the subsequent image angle offset exceeds 1°, the speed will be immediately reduced by 10%. Finally, the system generates a set of segment production line management parameter sets, and the recorded fields are "mold number, traveling angle, correction direction, speed value, braking threshold". The data details are shown in the table: Table 5 Segment In-slot Offset and Path Management Parameter Table

[0042] As shown in Table 5, the system combines image detection and track comparison analysis to confirm that the mold F024 has no offset abnormality. The path control system maintains the standard set parameters and enables the lowest-level warning mechanism for continuous tracking and adjustment of the control strategy in the subsequent paragraphs.

[0043] The above is only a preferred embodiment of the present invention, and it is not intended to limit the present invention in other forms. Any person skilled in the art may use the technical content disclosed above to make changes or modifications into equivalent embodiments with equivalent changes and apply them to other fields. However, as long as it does not depart from the technical solution content of the present invention, any simple modification, equivalent change and modification made to the above embodiments based on the technical essence of the present invention still fall within the protection scope of the technical solution of the present invention.

Claims

1. An intelligent segment production scheduling system, characterized in that, The system includes: The raw material analysis module obtains the data of the cement strength grade, the particle size distribution of manufactured sand, the water demand ratio of fly ash, and the water content of crushed stone for each raw material batch, analyzes the performance differences from the preset reference values, predicts the task processing duration corresponding to the raw material batch, adjusts the task scheduling list, and obtains the production task list; The concrete placing control module calls the production task list, uses the image acquisition device to identify the spreading speed of the concrete landing point in the concrete placing equipment, adjusts the discharging rate by evaluating the fluidity of the concrete, and combines with the mold number to obtain the mold status list; The scheduling and speed regulation module calls the mold status list, calls multiple weight sensors of the mother and son vehicle, calculates the spatial offset direction and offset amplitude between the center of gravity after the mold is loaded and the vehicle center in real time, and adjusts the speed parameters to obtain the speed control parameters; The section judgment module, based on the speed control parameters, uses the infrared imaging device to monitor the temperature distribution image of the mold in the curing area, including the heating area, the constant temperature area, and the cooling area, extracts the temperature distribution trend in the central area of the image, the edge temperature gradient direction, and the change trend of the thermal field uniformity, calculates the time point when the mold enters the next curing area, and obtains the heat zone switching record.

2. The intelligent segment production scheduling system according to claim 1, wherein The production task list includes the raw material batch number, the predicted value of the task processing duration, and the task priority order. The mold status list includes the mold number, the concrete fluidity grade, and the concrete placing duration record. The speed control parameters are specifically the offset direction vector value, the offset amplitude value, and the path speed correction coefficient. The heat zone switching record includes the change trend of the central temperature of the heat map, the edge temperature difference distribution trend, and the curing area switching time point.

3. The intelligent segment production scheduling system according to claim 1, wherein The raw material analysis module includes: The performance difference sub-module obtains the data of the cement strength grade, the particle size distribution of manufactured sand, the water demand ratio of fly ash, and the water content of crushed stone for each raw material batch, and extracts the performance differences between each parameter and the preset reference value to generate a raw material parameter difference set; The duration prediction sub-module, based on the raw material parameter difference set, uses the formula: ； Calculate the predicted value of the task processing cycle for each raw material, and obtain the calculation result of the predicted duration; Among them, represents the predicted value of the task processing cycle, represents the task reference duration corresponding to the standard raw material parameter group, represents the th raw material parameter value in the current batch, represents the th standard reference value of the raw material, represents the th sensitivity coefficient of the parameter pair to the processing time, represents the raw material parameter number currently being analyzed, represents the total number of raw material parameters participating in the processing; The task scheduling sub-module calls the calculation result of the predicted duration, adjusts the task scheduling list according to the required processing duration, and establishes a production task list.

4. The intelligent segment production scheduling system according to claim 3, wherein The concrete placing control module includes: The landing point monitoring sub-module calls the production task list, uses the image acquisition device to analyze the spreading position of the concrete landing point in the mold in consecutive frame images, extracts the spreading radius data and the corresponding time stamps of the current frame and the previous frame, and establishes the spreading speed change value; The fluidity evaluation sub-module calls the spreading speed change value, combines the standard fluidity rate and the reference discharging rate, and uses the formula: ； Calculate the discharging rate and establish the discharging rate control parameter; Among them, represents the real-time discharging rate that the device should execute according to the current concrete fluidity, is the reference discharging rate, is the concrete spreading radius in the current image frame, is the concrete spreading radius in the previous image frame, is the timestamp corresponding to the current image frame, is the timestamp corresponding to the previous image frame, is the standard concrete diffusion rate, is the fluidity response adjustment index; The rhythm recording sub-module calls the discharging rate control parameter, records the concrete placing duration of each mold and extracts the mold numbers that have completed placing, and establishes the mold status list.

5. The intelligent segment production scheduling system according to claim 4, wherein The scheduling and speed regulation module includes: The center-of-gravity recognition sub-module calls the mold status list, calls multiple weight sensors of the mother-daughter vehicle, extracts mass data at multiple positions and maps it to the vehicle chassis coordinate system, calculates the center-of-gravity position after the mold is loaded, and obtains center-of-gravity coordinate data; The offset calculation sub-module calls the center-of-gravity coordinate data and uses the formula: ； to calculate the speed adjustment control parameter; Among them, is the speed adjustment control parameter, is the standard speed value of the section, is the coordinate value of the die center of gravity along the transverse axis in the vehicle coordinate system, is the coordinate value of the die center of gravity along the longitudinal axis in the vehicle coordinate system, is the coordinate value of the die center of gravity along the vertical axis in the vehicle coordinate system, is the reference coordinate value of the vehicle track center point along the transverse axis in the vehicle coordinate system, is the reference coordinate value of the vehicle track center point along the longitudinal axis in the vehicle coordinate system, is the reference coordinate value of the vehicle track center point along the vertical axis in the vehicle coordinate system, is the boundary length value of the die in the vehicle coordinate system, is the boundary width value of the die in the vehicle coordinate system, is the boundary height value of the die in the vehicle coordinate system, is the adjustment weight coefficient of the proportion of the lateral offset difference, is the adjustment weight coefficient of the proportion of the longitudinal offset difference, is the adjustment weight coefficient of the proportion of the vertical offset difference; The speed regulation sub-module calls the speed adjustment control parameter, sets speed parameters at multiple positions in the mother-daughter vehicle path, including the running speeds in the turning section, acceleration section, and residence section, and establishes the traveling speed control parameter.

6. The intelligent segment production scheduling system according to claim 5, wherein The section judgment module includes: The heat map acquisition sub-module, according to the speed control parameter, calls the infrared imaging devices in each maintenance sub-area, including the heating area, constant temperature area, and cooling area, acquires the temperature distribution image of the mold surface, and obtains the mold surface heat image; The heat field trend recognition sub-module calls the mold surface heat image, divides the image into multiple grids, extracts the temperature mean sequence of each grid in the central area of the image, recognizes the temperature distribution trend in the central area, combines the temperatures in the grids in the edge area of the image, calculates the edge temperature gradient direction, analyzes the change trend of the heat field uniformity, and obtains the mold status analysis result; The partition transfer determination sub-module calls the mold status analysis result, combines the required mold status in each partition, calculates the time point when the mold enters the next maintenance period, and obtains the hot zone switching record.

7. The intelligent segment production scheduling system according to claim 1, wherein The system further includes: The misalignment recognition module calls the hot zone switching record, uses the image acquisition device to identify the positions of the two side lines of the mold, measures the angle with the track direction, detects the position offset event during the mold slotting process, and adjusts the control parameters of the mother-daughter vehicle according to the offset direction to obtain the segment production line management result; The segment production line management result specifically refers to the mold misalignment angle, offset direction identifier, and vehicle control adjustment instruction.

8. The intelligent segment production scheduling system according to claim 7, wherein The misalignment recognition module includes: The image acquisition sub-module calls the hot zone switching record, uses the image acquisition device to take the top view image of the mold slotting section, locates the pixel points of the two side edges of the mold in the image coordinate system, converts them into actual space coordinates, constructs the mold side line direction vector, and measures the angle with the track center reference direction to obtain the side line angle data set; The offset event determination sub-module calls the side line angle data set to detect the position offset event during the mold slotting process, including the angle offset event, the side line angle difference over-limit event, and the slotting center line offset event, and generates the slotting offset determination result; The path adjustment execution sub-module calls the slotting offset determination result, combines the offset angle direction, sets the traveling direction, traveling speed, and braking trigger value parameters of the corresponding mother-daughter vehicle, and obtains the segment production line management parameter set.

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