Cloth production and transportation method, system and terminal

Abstract

The present application relates to the production transportation technical field, specifically relates to a cloth production transportation method, system and terminal, first determine the drape level of the cloth to be transported and the path complexity score of each transportation path, further execute the matching strategy on the cloth to be transported and each transportation path, to screen out the target transportation path, and dispatch the cloth to be transported along the target transportation path for conveying, while monitoring the path state of the target transportation path in real time during conveying, to re-plan a new target transportation path for dispatching conveying when triggering the preset rescheduling condition, the present application matches the drape characteristics of the cloth with the complex characteristics of the transportation path, thereby performing differentiated scheduling, avoiding the risk of wrinkle deformation of high-drape cloth due to complex road conditions such as sharp bends and vibrations, and ensuring product quality, while monitoring the path state in real time and triggering dynamic rescheduling when abnormal, to ensure the adaptive ability and production continuity of the workshop logistics.

Description

Technical Field

[0001] This invention relates to the field of production and transportation technology, specifically to a method, system, and terminal for fabric production and transportation. Background Technology

[0002] In the production and transportation of fabrics, fabrics typically undergo multiple transfer stages, including weaving, dyeing, finishing, and finished product packaging. The transportation process primarily relies on automated guided vehicles (AGVs), conveyor belts, or overhead conveyors. Existing transportation methods often use product type, production stage, or equipment status as the basis for scheduling, planning fixed or pre-set transportation routes for the fabrics.

[0003] However, this transportation planning strategy ignores the differences in the material mechanical properties of the transported fabrics: different types of fabrics have significantly different drape characteristics. When high-drape fabrics such as silk pass through complex transportation paths with multiple bends, speed changes, or strong vibrations, they are prone to irreversible wrinkles and deformation due to repeated bending and vibration, resulting in product quality loss. Furthermore, the transportation planning lacks the ability to perceive changes in the path status in real time and dynamically reschedule, leading to a disconnect between fabric characteristics and logistics decisions, and failing to meet the needs of adaptive and differentiated transportation. Summary of the Invention

[0004] To address the technical problem that existing fabric production and transportation methods cannot meet the needs of adaptive and differentiated transportation, the present invention aims to provide a fabric production and transportation method, system, and terminal. The specific technical solution adopted is as follows: A method for producing and transporting fabric, the method comprising: Extract the drape coefficient of the fabric to be transported and determine the drape level; extract the path topology information of each transport route and calculate the path complexity score. Based on the sag rating and the path complexity score, a matching strategy is executed between the fabric to be transported and each transport path to select the target transport path from all transport paths. The fabric to be transported is scheduled to be transported along the target transport path, and the path status of the target transport path is monitored in real time during the transport process. When a change in the path status is detected and a preset rescheduling condition is triggered, a new target transport path is replanned for rescheduling and transport.

[0005] By adopting the above technical solutions, the drape characteristics of the fabric are matched with the complex characteristics of the transportation path, thereby enabling differentiated scheduling. This avoids the risk of wrinkles and deformation of high-drape fabrics caused by complex road conditions such as sharp bends and vibrations, ensuring product quality. At the same time, the path status is monitored in real time and dynamic rescheduling is triggered when abnormalities occur, ensuring the adaptability of workshop logistics and production continuity.

[0006] Furthermore, the method for determining the sag level includes: Based on the sag threshold, the sag coefficient is mapped to one of three preset sag levels: low sag, medium sag, and high sag, to determine the sag level of the fabric to be transported.

[0007] By adopting the above technical solution, complex physical and mechanical indicators are transformed into discrete control strategies that are easy for computers to process and rules to execute; at the same time, the classification introduces a segmented fault-tolerant mechanism to help improve the robustness of subsequent matching decisions.

[0008] Furthermore, the method for calculating the path complexity score includes: The path topology information includes the number of curves, the radius of curvature of the curves, the number of speed change nodes, the number of vibration sources, and the total path length; the parameters in the path topology information of each transportation path are weighted and integrated to obtain a path complexity score.

[0009] By adopting the above technical solution, the multidimensional heterogeneous data is integrated into a comprehensive index to characterize the damage risk of the fabric due to path complexity.

[0010] Furthermore, a matching strategy is implemented between the fabric to be transported and each transport route, including: Extract the preset complexity upper limit corresponding to the drape level of the fabric to be transported; eliminate the transport paths whose path complexity score is greater than the preset complexity upper limit; among the remaining transport paths, calculate the comprehensive cost score by weighting the transport time of each transport path and the path complexity score, and take the optimal transport path with the smallest comprehensive cost score as the target transport path.

[0011] By adopting the above technical solution, the draping characteristics of the fabric and the complex characteristics of the transportation path are aligned in a mathematical model, thereby enabling differentiated transportation scheduling to ensure quality while taking into account workshop capacity.

[0012] Furthermore, the matching strategy also includes: When the optimal transportation route is occupied or in a faulty state, the second-lowest comprehensive cost score transportation route is automatically downgraded and selected as the target transportation route, and speed compensation is applied to the second-lowest transportation route.

[0013] Furthermore, speed compensation is applied to suboptimal transportation routes, including: If the path complexity score of the suboptimal transportation path is greater than the path complexity score of the optimal transportation path, then a speed compensation factor is calculated based on the difference between the path complexity scores corresponding to the optimal and suboptimal transportation paths, and the rated transport speed of the suboptimal transportation path is weighted and limited using the speed compensation factor to reduce the speed compensation. If the path complexity score of the suboptimal transportation path is less than or equal to the path complexity score of the optimal transportation path, then the rated transport speed of the suboptimal transportation path shall be maintained unchanged.

[0014] By adopting the above technical solutions and setting up a safety net mechanism, we can avoid waiting in place for the optimal transportation route to be released, which would affect the continuity of production, and minimize the loss of transportation efficiency while ensuring the quality of the fabric.

[0015] Furthermore, methods for replanning new target transportation routes and scheduling delivery include: The location where the path status change triggers the preset rescheduling condition is taken as the new starting point. A new transportation path is planned and the path complexity score is calculated. Then, the matching strategy is executed between the cloth to be transported and each new transportation path, and a new target transportation path is selected for scheduling and delivery.

[0016] Furthermore, the preset rescheduling conditions include: excessive vibration or the appearance of temporary obstacles on the target transportation path.

[0017] A fabric production and transportation system, the system comprising: The parameter extraction module is used to extract the sag coefficient of the fabric to be transported and determine the sag level, extract the path topology information of each transport route and calculate the path complexity score. The matching decision module is used to perform a matching strategy between the fabric to be transported and each transport path based on the sag level and the path complexity score, so as to select the target transport path from all transport paths. The scheduling and monitoring module is used to schedule the fabric to be transported to be transported along the target transport path, and to monitor the path status of the target transport path in real time during the transport process. When a change in the path status is detected and a preset rescheduling condition is triggered, a new target transport path is replanned for scheduling and transport.

[0018] A fabric production and transportation terminal, the terminal comprising: The communication unit is used to receive instructions from the dispatching terminal to transport the fabric along the target transport path, which are matched with the drape level of the fabric to be transported. A conveying execution unit is used to drive the fabric to be transported along the target transport path; The status feedback unit is used to monitor the path status of the target transportation path in real time during the transportation process, and when a change in the path status is detected that triggers a preset rescheduling condition, it sends a path anomaly feedback to the scheduling terminal for rescheduling.

[0019] The present invention has the following beneficial effects: This invention extracts the drape coefficient and determines the drape level of the fabric to be transported, clarifying its resistance to mechanical stress in a dynamic transportation environment within the workshop. Simultaneously, it extracts the path topology information of each transportation route and calculates the path complexity score, identifying the risk of wrinkle damage to the fabric during transport along that route. This provides a basis for subsequent differentiated transportation scheduling. Then, based on the drape level and path complexity score, a matching strategy is implemented between the fabric to be transported and each transportation route, aligning the drape characteristics of the fabric with the complexity characteristics of the transportation route in a mathematical model. This allows for differentiated scheduling to select the target transportation route from all available routes. Furthermore, the fabric to be transported is scheduled to travel along the target transportation route, and the route status is monitored in real time during transport. When a change in the route status triggers a preset rescheduling condition, a new target transportation route is replanned for rescheduling to address sudden road condition interruptions and interference. This invention matches the drape characteristics of the fabric with the complex characteristics of the transportation path, thereby enabling differentiated scheduling. This avoids the risk of wrinkles and deformation of high-drape fabrics caused by complex road conditions such as sharp bends and vibrations, ensuring product quality. At the same time, it monitors the path status in real time and triggers dynamic rescheduling when anomalies occur, ensuring the adaptability of workshop logistics and production continuity. Attached Figure Description

[0020] Figure 1 This is a flowchart illustrating a fabric production and transportation method according to an embodiment of the present invention. Detailed Implementation

[0021] The following description, in conjunction with the accompanying drawings, details a specific solution for a fabric production and transportation method, system, and terminal provided by the present invention.

[0022] Please see Figure 1 The diagram illustrates a flowchart of a fabric production and transportation method according to an embodiment of the present invention, specifically including: Step S1: Extract the drape coefficient of the fabric to be transported and determine the drape level; extract the path topology information of each transport path and calculate the path complexity score.

[0023] The drape coefficient is mainly used to evaluate the quality of fabrics, but it is also a mechanical indicator that measures the fabric's ability to undergo three-dimensional deformation under its own weight. The smaller the drape coefficient, the easier it is for the fabric to undergo irreversible plastic deformation when subjected to external forces. By extracting the drape coefficient of the fabric to be transported and determining the drape level, the transportation risk of the fabric to be transported can be classified, and its resistance to mechanical stress in the dynamic transfer environment of the workshop can be clarified, providing a basis for subsequent differentiated scheduling and transportation.

[0024] In one embodiment of the present invention, the drape coefficient DC of the fabric to be transported is first extracted. Considering that there are various production flow scenarios in the workshop, such as standard purchased fabrics (pre-filed) and self-woven fabrics (non-standard customization), this embodiment specifically relies on the fabric attribute entry terminal deployed at the production line entrance or material transfer station to work in concert with the drape detection station to provide an execution method that supports dual-modal acquisition. The fabric attribute entry terminal has an embedded main control MCU and connects to an external barcode / QR code scanner, RFID reader, touch screen, and local area network communication module. Through an internally created independent heartbeat task thread, it actively reports the current status information of the entry terminal (including device online status, sensor normal flag, etc.) at preset time intervals (such as every 15 seconds). When all status bits are set to 1 (normal), it can enter the entry state. For standard purchased fabrics, the batch label of the fabric to be transported is quickly scanned by the barcode scanner or RFID reader equipped on the input terminal, thereby automatically triggering the query of the drape coefficient DC of the fabric to be transported (usually a percentage, which is converted into a value ranging from 0 to 1; the smaller the value, the higher the drape and the softer the fabric). For self-woven fabrics (i.e., the drape coefficient cannot be automatically queried after scanning the code), the "New Fabric Edge Quick Test" mode is switched through the touch screen; a sample is taken from the fabric to be transported and placed in the edge drape measuring instrument integrated at the workstation, and the edge drape measuring instrument is used to automatically detect and calculate the drape coefficient of the fabric to be transported; this is a well-known technical means familiar to those skilled in the art, and will not be described in detail here.

[0025] After extracting the drape coefficient of the fabric to be transported, a format and range check is immediately performed: the data type is checked to see if it is a valid floating-point number and if the value is strictly within the range of 0-1; if the check passes (e.g., DC=0.85 is received or measured), a message "Drape coefficient successfully acquired: 0.85" will pop up on the touch screen; if the check fails (e.g., the data is detected to be empty or out of range), an anomaly is identified, an anomaly alarm message "Drape coefficient acquisition failed, please recalibrate" will pop up on the touch screen, and subsequent matching and scheduling instructions will be automatically blocked, thus ensuring the legality and reliability of the input data from the source.

[0026] Preferably, in one embodiment of the present invention, considering mapping and classifying continuous sag coefficients to preset sag levels, and setting clear and unified control boundaries and strategy thresholds for each level, complex physical and mechanical indicators can be transformed into discretized control strategies that are easy for computers to process and rules to execute; at the same time, the level division introduces a piecewise fault-tolerant mechanism, so that small fluctuations in the single sag coefficient extraction value will not cause drastic changes in the matching strategy of subsequent paths, thereby improving the robustness of subsequent matching decisions; therefore, the method for determining the sag level includes: Map the drape coefficient to one of the three preset drape grades of low drape, medium drape and high drape based on the drape threshold, and determine the drape grade of the fabric to be transported.

[0027] In one example of the present invention, a first threshold T1=0.4 and a second threshold T2=0.7 are set; the mapping rule is: if DC≤0.4, it is determined as a high drape grade, and typical fabrics include silk, rayon, chiffon, etc.; if 0.4<DC≤0.7, it is determined as a medium drape grade, and typical fabrics include cotton cloth, linen, blended fabrics, etc.; if DC>0.7, it is determined as a low drape grade, and typical fabrics include stiff fabrics such as denim, canvas, and polyester; subsequently, the drape grade of the fabric to be transported is determined as the core basis for the subsequent execution of the path matching strategy.

[0028] It should be noted that the first threshold and the second threshold are scientific critical values calibrated through a large number of textile mechanical wrinkle resistance tests and industrial field statistical data, and the calibration process is already a conventional technical means in the art, which will not be repeated here; implementers can also make fine adjustments according to practical applications.

[0029] Since the transportation paths differ not only in length, some transportation paths may be straight and open, while some may be densely packed with sharp turns, frequent speed change and connection, or even close to strong vibration sources such as large stamping presses; for high drape fabrics, if only the path distance is focused and they are sent into high-risk curved paths full of mechanical stress, severe wrinkle damage may be caused to the fabrics; Therefore, a single indicator of path length or transportation duration cannot be used to evaluate the suitability of the path; by extracting path topology information that characterizes the geometric structure features of the transportation path and the surrounding environment state, the path complexity score is comprehensively calculated; the path complexity score represents the wrinkle damage risk of the transportation path to the fabric to be transported, and provides a basis for the subsequent matching decision between fabric characteristics and transportation paths.

[0030] It should be noted that in one embodiment of the present invention, an Automated Guided Vehicle (AGV) in the workshop is used as the specific transportation device for description; those skilled in the art should understand that the transportation device can also be replaced with other automated transportation devices in the workshop, such as overhead conveyor chains, rail robots or unmanned forklifts, etc., all of which are applicable to fabric transportation scheduling.

[0031] Among them, a complete transportation road network is pre-deployed in the workshop, and the road network includes all path nodes in the workshop, based on which all transportation paths can be planned and determined; the AGV receives path instructions issued by the central scheduling system, and relies on its own LiDAR, magnetic strips or wheel speed sensors to achieve precise transportation on the specified transportation path.

[0032] Preferably, in one embodiment of the present invention, since the fabric is forced to change its direction of travel at bends, and the denser the bends and the smaller the radius of curvature (i.e., sharp bends), the fabric is more prone to in-plane compression and tensile strain. Simultaneously, during the conveying process, frequent starts, stops, braking, and acceleration / deceleration will cause inertial impact and longitudinal tensile stress on the fabric, potentially leading to permanent creases. If the conveying route passes through the influence range of large-scale stamping machines, looms, or other high-vibration equipment, continuous high-frequency mechanical vibration will cause micro-vibration friction on the surface of the soft fabric, leading to fiber fatigue or wrinkling. The longer the total path length, the greater the duration and risk of the fabric being exposed to the dynamic environment of the workshop, and the greater the risk of wrinkles. Therefore, the aforementioned external force source parameters that may cause irreversible deformation of the fabric are used as the path topology information of the conveying path. The physical dimensions of the aforementioned parameters are completely different, and their contribution to the mechanical damage to the fabric is not entirely the same. Through weighted fusion, the aforementioned multidimensional heterogeneous data can be integrated into a comprehensive index to characterize the damage risk of the fabric due to path complexity. The calculation method for the path complexity score includes: The path topology information includes at least the number of curves, the radius of curvature of the curves, the number of speed change nodes, the number of vibration sources, and the total path length. The path complexity score is obtained by weighted fusion of the parameters in the path topology information of each transportation path.

[0033] As an example, methods for obtaining path topology information include: For smart factories that have established digital twin systems, the geometric parameters (number of curves, radius of curvature of curves, total length of path), equipment parameters (number of speed change nodes), and environmental parameters (number of vibration sources) of each transportation path in the workshop have been accurately modeled in the digital twin model. The path topology information of the transportation path can be obtained directly by calling the data interface of the digital twin platform and inputting the path identifier. For factories that have not yet deployed a digital twin system, each transportation route can be measured on-site to record information such as the number of curves, the radius of curvature of each curve, the number and location of speed change nodes, the distribution and number of large vibrating equipment along the route, and the total length of the route. This information can then be entered into a database for the scheduling system to access.

[0034] For each transport route, the following route topology information is included: Number of curves N1: Represents the total number of turns in the transportation route; Curve radius Ri: Characterizes the geometric steepness of each turn (where i=1,2,...,N1); N2, the number of speed change nodes: represents the total number of nodes such as conveyor belt connection points, lifting points, and speed change points in the path; Vibration source number N3: Characterizes the number of large mechanical equipment (such as looms and other strong vibration sources) located close to the path (such as within 3 meters on both sides of the path centerline); Total path length L: Represents the physical spatial distance from the starting point to the ending point.

[0035] The parameters mentioned above are normalized to eliminate the influence of dimensions. For each transportation route, taking the number of curves as an example, the maximum and minimum values ​​are selected from the number of curves of all transportation routes. Then, the number of curves of the transportation route is normalized to the maximum and minimum. When the maximum value equals the minimum value, the normalized value is directly set to 1. The other parameters mentioned above can be normalized using the same processing method, which will not be elaborated on one by one.

[0036] The normalized parameters are then weighted and fused to obtain the path complexity score for the transportation route.

[0037] Specifically, the formula for calculating the path complexity score C is as follows: Where C is the route complexity score of the transportation route; This represents the normalized number of path curves. Let be the normalized radius of curvature of the i-th path curve; This represents the normalized number of speed-changing nodes; This represents the normalized number of vibration sources. This represents the normalized total path length; when there are no curves in the path... Set directly to 0; The smaller the radius of curvature of the curve, the greater the risk of fabric wrinkling during transportation. Therefore, the normalized radius of curvature of the curve... Perform a negative correlation mapping, specifically mapping it as the independent variable x to... In the middle, we obtained Then take the average; , , , , All values ​​are preset weights, with values ​​of 0.15, 0.25, 0.2, 0.25, and 0.15 respectively. The sum of each weight is 1. Implementers can also fine-tune these values ​​themselves. The path complexity score C ranges from (0 to 1).

[0038] It should be noted that the above-mentioned preset weights were determined through regression analysis of a large number of laboratory wrinkle resistance comparison tests of textiles, workshop physical transportation stress test data, and historical operation statistics: the "reciprocal of the sharp curvature" and "strong vibration source," which have the largest lateral centrifugal force and local shear stress and are most likely to cause irreversible creases in high-drape fabrics, were given the highest weights. and Each accounts for 0.25), to achieve accurate and sensitive identification of high-risk and damaged road sections; "speed change nodes" with frequent starts and stops are given a medium weight ( The weighting is 0.2; while the weighting of "number of bends" and "total path length", which have a smaller impact on wrinkle resistance, is relatively low. and Each accounts for 0.15), thus ensuring that the path complexity score objectively reflects the true risk of loss.

[0039] Step S2: Based on the sag level and path complexity score, a matching strategy is executed between the fabric to be transported and each transport path to select the target transport path from all transport paths.

[0040] The drape rating defines the physical tolerance limit of different fabrics against mechanical stress, bending, and shearing, while the path complexity score quantifies the potential damage risk to the fabric from each transport path. The synergistic matching of the two essentially aligns the drape characteristics of the fabric with the complexity characteristics of the transport path in a mathematical model. This allows low-drape fabrics with strong wrinkle resistance to take efficient complex paths, while avoiding high-drape fabrics with slightly weaker wrinkle resistance from being placed on high-risk complex paths. This differentiated scheduling of transport ensures both quality and workshop capacity.

[0041] Therefore, in this embodiment of the invention, a matching strategy is performed between the fabric to be transported and each transport path to select the target transport path from all transport paths. The target transport path is the optimal route for the safe transfer of the fabric to be transported.

[0042] Preferably, in one embodiment of the present invention, considering that fabrics with different drape grades correspond to different mechanical stress tolerance limits, a risk red line—an upper limit of the complexity of the transportation path—is set for each drape grade. Then, transportation paths with a complexity score greater than this upper limit are directly eliminated, thereby fundamentally preventing the possibility of high-drape fabrics entering high-risk, sharp-bend, and high-vibration sections, eliminating the risk of wrinkles. Furthermore, among the remaining transportation paths after screening, the time cost and risk cost of transportation are comprehensively considered to evaluate the overall cost score of the transportation path, thereby selecting the optimal solution corresponding to the target transportation path, avoiding the risk of wrinkles while also considering transportation efficiency. A matching strategy is executed between the fabric to be transported and each transportation path, including: Extract the preset complexity upper limit corresponding to the drape level of the fabric to be transported; eliminate transport paths with a path complexity score greater than the preset complexity upper limit; among the remaining transport paths, calculate the comprehensive cost score by weighting the transport time and path complexity score of each transport path, and select the optimal transport path with the lowest comprehensive cost score as the target transport path.

[0043] As an example, the pre-configured mapping relationship between drape level and path complexity upper limit is invoked to extract the preset complexity upper limit corresponding to the drape level of the fabric to be transported. Among them, the preset complexity upper limit corresponding to the low drape level is 0.85, which means that the fabric of this level is allowed to be optimized in the transportation path with C≤0.85; the preset complexity upper limit corresponding to the medium drape level is 0.5, which means that the fabric of this level is allowed to be optimized in the transportation path with C≤0.5; and the preset complexity upper limit corresponding to the high drape level is 0.2, which means that the fabric of this level is allowed to be optimized in the transportation path with C≤0.2.

[0044] The process of setting the mapping relationship includes: by statistically analyzing the defect rate of fabrics of different drape grades after being transferred along different transportation routes in the workshop's historical production and transportation, performing probability fitting on the road condition damage probability of different route complexity score intervals, thereby determining the critical damage path complexity score corresponding to different drape grades, determining a preset complexity upper limit for each drape grade, and constructing a mapping relationship; the above statistical analysis is a conventional technical means and will not be elaborated further; implementers can also configure the mapping relationship themselves.

[0045] After extracting the preset complexity upper limit corresponding to the drape level of the fabric to be transported, the transport paths with a path complexity score greater than the preset complexity upper limit are removed from all transport paths in order to optimize the remaining compliant transport paths; further, the pre-marked transport time of each remaining transport path is called and the transport time is normalized, specifically using maximum and minimum normalization. The maximum and minimum values ​​are determined from the transport times of all transport paths in the workshop. When the maximum value equals the minimum value, the normalization value is set to 1.

[0046] Then, the normalized values ​​of the route complexity score and the transportation time are weighted and summed with weights of 0.6 and 0.4 respectively, and the weighted sum is used as the comprehensive cost score of the transportation route. Then, the optimal transportation route with the lowest comprehensive cost score is selected from the remaining transportation routes as the target transportation route. The implementer can also fine-tune the above weights according to the priority of efficiency and quality.

[0047] It should be noted that the transportation time is the comprehensive time calibrated through actual transportation tests in the workshop. It includes the total time for turning, speed changes, and deceleration and start-stop at fixed junctions, reflecting the structural time-efficiency characteristics of the route itself. Specifically, the transportation time is the average time measured by the AGV running empty along the transportation route at least 3 times.

[0048] Considering the complex environment of multiple vehicles operating concurrently and dynamically in the workshop, the optimal transportation route may be occupied by other transportation tasks or may become unavailable due to equipment failure, temporary obstacles, or other reasons. Therefore, a fallback mechanism is needed to select the suboptimal transportation route to avoid waiting in place for the optimal transportation route to become available, which would affect the continuity of production. The suboptimal transportation route is usually slightly inferior to the optimal transportation route in terms of physical distance or road condition complexity. Detouring on the suboptimal transportation route may usually lead to an increase in transportation time or complexity. Therefore, speed compensation is also required to minimize the loss of transportation efficiency while ensuring the quality of the fabric. In a preferred embodiment of the present invention, the matching strategy further includes: when the optimal transportation path is occupied or in a fault state, automatically downgrading to select the second-lowest comprehensive cost score transportation path as the target transportation path, and performing speed compensation on the second-lowest transportation path; wherein, when the selected target transportation path (second-lowest transportation path) is still occupied or in a fault state, the next optimal transportation path can be selected in sequence, and so on, without further details on each of the various situations.

[0049] Furthermore, considering that if the path complexity score of the suboptimal transport path is greater than that of the optimal transport path, it indicates that the suboptimal transport path has a higher static risk. Without speed reduction compensation, the fabric will be subjected to greater centrifugal force at bends, variable speed impact force, and vibration excitation when passing through the suboptimal transport path at the rated speed, increasing the risk of quality damage. Therefore, it is necessary to calculate a speed compensation factor based on the path complexity score between the two transport paths, and use this factor to reduce the rated conveying speed, thereby reducing the risk of fabric wrinkling. The greater the complexity deviation, the greater the speed reduction. Conversely, if the path complexity score of the suboptimal transport path is not greater than that of the optimal transport path, it indicates that the suboptimal transport path is relatively smoother, and the original rated conveying speed can be maintained. In a preferred embodiment of the present invention, speed compensation for the suboptimal transportation path includes: If the path complexity score of the suboptimal transportation route is greater than that of the optimal transportation route, then a speed compensation factor is calculated based on the difference between the path complexity scores of the optimal and suboptimal transportation routes. The rated transport speed of the suboptimal transportation route is then weighted and limited using the speed compensation factor to compensate for the speed reduction. If the path complexity score of the suboptimal transportation path is less than or equal to the path complexity score of the optimal transportation path, then the rated transport speed of the suboptimal transportation path shall remain unchanged.

[0050] Wherein, when the path complexity score C2 of the suboptimal transportation route is greater than the path complexity score C1 of the optimal transportation route, the formula for calculating the speed compensation factor K is: ; The sensitivity adjustment weight ranges from 0 to 1 and can be dynamically adjusted. For example, it can be increased for high-drape fabrics and decreased for low-drape fabrics. Taking medium and low-drape fabrics as an example, to avoid excessively sacrificing transportation efficiency, the weight can be adjusted accordingly. Set it to a smaller value, such as 0.3; while for high-drape fabrics, in order to prioritize quality, γ can be set to a larger value, such as 0.6, to achieve a greater reduction in speed. The relative growth rate of the path complexity score, which characterizes the suboptimal transportation route, objectively reflects the relative degree of risk deterioration. This represents the risk increase ratio of taking the suboptimal transportation route. The reduction ratio of transportation speed is determined by subtracting the risk increase ratio from 1, thus realizing a negative feedback adjustment mechanism where the greater the risk, the smaller the speed compensation factor K, and the lower the transportation speed. Then, the speed compensation factor is multiplied by the rated transport speed of the suboptimal transport path and weighted to obtain the transport speed after speed reduction compensation. The rated transport speed is the path-specific operating speed curve (or segmented speed sequence) of different suspension grades of fabric that is pre-calibrated offline and stored in the road network database, which includes the speed reduction and start-stop change rules of the whole process at corners, speed changes, and connections.

[0051] For each transport route and each suspension level, the calibration method for the rated conveying speed includes: First, dividing the transport route into characteristic sections such as straight sections, curved sections, variable speed node sections, and vibration-affected sections based on the route topology information; then, conducting gradient tests for each section type—passing through the section at different speeds and detecting the rate of change in fabric flatness, and calibrating the highest speed that meets the quality requirements as the critical speed of the section, with the critical turning speed of curved sections calibrated according to the radius of curvature, and the critical acceleration / deceleration parameters of variable speed node sections calibrated; then, splicing the critical speeds of each section in the order of the route, and setting a smooth transition interval at the junction to synthesize a complete path speed curve; finally, verifying the synthesized speed curve, and fine-tuning it according to quality requirements, if it does not meet the quality requirements, lowering the speed of each section, and if it is significantly better than the threshold, gradually increasing it to approach the quality boundary, thereby obtaining the optimal dedicated operating speed curve that balances efficiency and quality.

[0052] Considering that speed compensation may calculate an excessively low or even negative speed compensation factor under extreme conditions, and that in actual engineering, excessively low transport equipment speed may lead to equipment creep, motor overheating, decreased control accuracy, or even seriously slow down production cycle, it is necessary to limit the conveying speed after speed reduction compensation to avoid excessively slow conveying speed. Specifically, when the conveying speed after speed reduction compensation is lower than half of the original rated conveying speed, it can be directly conveyed at half of the original rated conveying speed to avoid excessively low transport speed. Implementers can also adjust the limit range according to actual application.

[0053] Step S3: Schedule the fabric to be transported to be transported along the target transport path, and monitor the path status of the target transport path in real time during the transport process. When a change in the path status is detected and a preset rescheduling condition is triggered, a new target transport path is replanned for scheduling and transport.

[0054] Further scheduling of the fabric to be transported along the target transport route is required. However, during the actual transport process, unexpected situations may suddenly occur ahead (such as other transport equipment suddenly breaking down and blocking the passage or local mechanical vibration exceeding the standard). In this case, it is necessary to monitor the path status of the target transport route in real time during the transport process to deal with sudden road interruptions and physical obstacles. When a change in the path status is detected, a secondary planning mechanism can be automatically triggered to re-plan a new target transport route and schedule its use.

[0055] In a preferred embodiment of the present invention, considering that temporary obstacles such as breakdown of the preceding vehicle or falling materials can cause the transportation path to be locked, triggering dynamic rescheduling can ensure the continuous operation of the production line; and considering that high-drape fabrics are more sensitive to mechanical vibration, continuous high-frequency vibration or impact can easily cause irreversible creases and plastic deformation during transportation, triggering rescheduling when the vibration source on the path exceeds the standard can avoid the loss of crease quality; therefore, the preset rescheduling conditions include at least: the vibration exceeds the standard or a temporary obstacle appears on the target transportation path.

[0056] Once the AGV carrying the fabric to be transported officially enters the target transport path, the central dispatch system and the AGV onboard control terminal work together. The AGV onboard controller uses built-in high-precision inertial measurement unit (IMU), wheel speed encoder, and three-axis accelerometer and other onboard sensors to collect the instantaneous running speed, acceleration, and micro-vibration acceleration of the vehicle body during the journey in real time. At the same time, through onboard lidar, ultrasonic sensors, and road network base stations, it detects in real time whether there are sudden physical obstacles or serious deterioration of local road conditions (such as excessive vibration) ahead of the target transport path. Once the above situation is detected, it is determined that the preset re-dispatch conditions are met, and a re-dispatch command is directly triggered to re-plan a new target transport path.

[0057] The presence of sudden physical obstacles ahead of the target transport path can be detected by the vehicle-mounted LiDAR. The LiDAR emits a laser beam and receives the echo to construct a three-dimensional point cloud map of the path ahead. When a static obstacle with a volume exceeding a preset threshold (e.g., 0.5m × 0.5m × 0.5m) appears in the point cloud data, and the obstacle remains unchanged in position for multiple consecutive scanning cycles (e.g., 3 cycles), it is determined to be a 'sudden physical obstacle'. Whether the vibration exceeds the standard is determined by the three-axis accelerometer built into the AGV vehicle controller, which collects the effective value (RMS) of the vertical vibration acceleration of the vehicle body in real time at a preset sampling frequency (e.g., 100Hz). When the RMS value exceeds the preset vibration tolerance limit and lasts for more than 1 second, it is determined to be a vibration exceeding the standard.

[0058] It should be noted that the preset vibration tolerance upper limit is determined based on the drape level of the fabric to be transported. Each drape level of fabric corresponds to a pre-tested and calibrated preset vibration tolerance upper limit: simulated vibration tests with different amplitudes are applied to typical fabric samples of different drape levels (vibration frequency range of 10~200Hz, root mean square value of vibration acceleration range of 0.1g~2.0g), and the vibration duration simulates the actual transportation time (e.g., 5 minutes). Then, according to the industry testing standards for fabric quality, the wrinkle recovery angle or surface smoothness change rate of each sample is measured. When the smoothness change rate exceeds the preset quality qualification threshold (e.g., 3%), the root mean square value of vibration acceleration at this time is recorded. This value is the critical vibration value corresponding to the drape level. Multiplying the critical vibration value by the preset safety factor (with a value range of 0.6~0.8, which can be set by the implementer according to the production error tolerance rate), the result is the vibration tolerance upper limit corresponding to the drape level.

[0059] In a preferred embodiment of the present invention, considering that forcing the AGV to reverse back to the starting point for rescheduling would severely slow down the logistics cycle and cause channel congestion, the position where the preset rescheduling condition is triggered is taken as the new starting point, and the AGV detours to the nearest location to maintain production continuity to the greatest extent; then, a new transportation route is replanned in conjunction with the road network and a matching strategy is executed for differentiated scheduling, and a new target transportation route is selected for scheduling and delivery; the method for replanning a new target transportation route for scheduling and delivery includes: The location where the path status change triggers the preset rescheduling condition is taken as the new starting point. A new transportation path is planned and the path complexity score is calculated. Then, the matching strategy is executed between the cloth to be transported and each new transportation path, and a new target transportation path is selected for scheduling and delivery.

[0060] Specifically, when the preset rescheduling conditions are met, the path anomaly alarm signal is reported to the central dispatch system in real time. The AGV senses its position in the road network and reports it to the central dispatch system. The central dispatch system then takes the current position of the AGV (the position when the preset rescheduling conditions are triggered) as the starting point and re-traverses all candidate branches that can lead to the destination in the road network database (actively eliminating local road segments that have been locked or have malfunctioned) to determine a new set of remaining candidate paths. Then, step S2 is repeated to quickly select a new target transportation path from the remaining compliant candidate paths and issue a new navigation command to instruct the AGV to switch to the new target transportation path to continue performing the transportation task.

[0061] It should be noted that during rescheduling, the cumulative value of the path complexity score of the already traveled road segments is used as an additional constraint to appropriately tighten the upper limit of the complexity of the remaining road segments of the selected new target transportation route, thereby compensating for the stress already borne.

[0062] Based on the same inventive concept, embodiments of the present invention also provide a fabric production and transportation system, the system comprising: The parameter extraction module is used to extract the sag coefficient of the fabric to be transported and determine the sag level, extract the path topology information of each transport route and calculate the path complexity score. The matching decision module is used to perform a matching strategy between the fabric to be transported and each transport path based on the sag level and the path complexity score, so as to select the target transport path from all transport paths. The scheduling and monitoring module is used to schedule the fabric to be transported to be transported along the target transport path, and to monitor the path status of the target transport path in real time during the transport process. When a change in the path status is detected and a preset rescheduling condition is triggered, a new target transport path is replanned for scheduling and transport.

[0063] The parameter extraction module is configured to execute step S1 in the above-mentioned fabric production and transportation method, the matching decision module is configured to execute step S2 in the above-mentioned fabric production and transportation method, and the scheduling and monitoring module is configured to execute step S3 in the above-mentioned fabric production and transportation method, which will not be described in detail here.

[0064] Based on the same inventive concept, this invention also provides a fabric production and transportation terminal, which includes: The communication unit is used to receive instructions from the dispatching terminal to transport the fabric along the target transport path, which are matched with the drape level of the fabric to be transported. A conveying execution unit is used to drive the fabric to be transported along the target transport path; The status feedback unit is used to monitor the path status of the target transportation path in real time during the transportation process, and when a path status change is detected that triggers a preset rescheduling condition, it sends a path anomaly feedback to the scheduling end to perform rescheduling.

[0065] In summary, this invention extracts the drape coefficient of the fabric to be transported and determines its drape level; extracts the path topology information of each transport path and calculates the path complexity score; based on the drape level and path complexity score, a matching strategy is implemented between the fabric to be transported and each transport path to select the target transport path from all transport paths; the fabric to be transported is scheduled to be transported along the target transport path, and the path status of the target transport path is monitored in real time during the transport process. When a change in the path status is detected and a preset rescheduling condition is triggered, a new target transport path is replanned for rescheduling. This invention achieves differentiated scheduling by matching the drape characteristics of the fabric with the complexity characteristics of the transport path, avoiding the risk of wrinkles and deformation of high-drape fabrics due to complex road conditions such as sharp bends and vibrations, thus ensuring product quality; at the same time, real-time monitoring of the path status and triggering dynamic rescheduling in case of anomalies ensure the adaptability of workshop logistics and production continuity.

Claims

1. A method for producing and transporting fabric, characterized in that, The method includes: Extract the drape coefficient of the fabric to be transported and determine the drape level; extract the path topology information of each transport route and calculate the path complexity score. Based on the sag rating and the path complexity score, a matching strategy is executed between the fabric to be transported and each transport path to select the target transport path from all transport paths. The fabric to be transported is scheduled to be transported along the target transport path, and the path status of the target transport path is monitored in real time during the transport process. When a change in the path status is detected and a preset rescheduling condition is triggered, a new target transport path is replanned for rescheduling and transport.

2. The fabric production and transportation method according to claim 1, characterized in that, The method for determining the suspension grade includes: Based on the sag threshold, the sag coefficient is mapped to one of three preset sag levels: low sag, medium sag, and high sag, to determine the sag level of the fabric to be transported.

3. The fabric production and transportation method according to claim 1, characterized in that, The method for calculating the path complexity score includes: The path topology information includes the number of curves, the radius of curvature of the curves, the number of speed change nodes, the number of vibration sources, and the total path length; the parameters in the path topology information of each transportation path are weighted and integrated to obtain a path complexity score.

4. The fabric production and transportation method according to claim 1, characterized in that, A matching strategy is implemented for each transport route and the fabric being transported, including: Extract the preset complexity upper limit corresponding to the drape level of the fabric to be transported; eliminate the transport paths whose path complexity score is greater than the preset complexity upper limit; among the remaining transport paths, calculate the comprehensive cost score by weighting the transport time of each transport path and the path complexity score, and take the optimal transport path with the smallest comprehensive cost score as the target transport path.

5. The fabric production and transportation method according to claim 4, characterized in that, The matching strategy also includes: When the optimal transportation route is occupied or in a faulty state, the second-lowest comprehensive cost score transportation route is automatically downgraded and selected as the target transportation route, and speed compensation is applied to the second-lowest transportation route.

6. The fabric production and transportation method according to claim 5, characterized in that, Speed ​​compensation for suboptimal transportation routes includes: If the path complexity score of the suboptimal transportation path is greater than the path complexity score of the optimal transportation path, then a speed compensation factor is calculated based on the difference between the path complexity scores corresponding to the optimal and suboptimal transportation paths, and the rated transport speed of the suboptimal transportation path is weighted and limited using the speed compensation factor to reduce the speed compensation. If the path complexity score of the suboptimal transportation path is less than or equal to the path complexity score of the optimal transportation path, then the rated transport speed of the suboptimal transportation path shall be maintained unchanged.

7. A method for producing and transporting fabric according to claim 1, characterized in that, Methods for replanning new target transportation routes and scheduling deliveries include: The location where the path status change triggers the preset rescheduling condition is taken as the new starting point. A new transportation path is planned and the path complexity score is calculated. Then, the matching strategy is executed between the cloth to be transported and each new transportation path, and a new target transportation path is selected for scheduling and delivery.

8. The fabric production and transportation method according to claim 1, characterized in that, The preset rescheduling conditions include: excessive vibration or the appearance of temporary obstacles on the target transportation route.

9. A fabric production and transportation system, characterized in that, The system includes: The parameter extraction module is used to extract the sag coefficient of the fabric to be transported and determine the sag level, extract the path topology information of each transport route and calculate the path complexity score. The matching decision module is used to perform a matching strategy between the fabric to be transported and each transport path based on the sag level and the path complexity score, so as to select the target transport path from all transport paths. The scheduling and monitoring module is used to schedule the fabric to be transported to be transported along the target transport path, and to monitor the path status of the target transport path in real time during the transport process. When a change in the path status is detected and a preset rescheduling condition is triggered, a new target transport path is replanned for scheduling and transport.

10. A fabric production and transportation terminal, characterized in that, The terminal includes: The communication unit is used to receive instructions from the dispatching terminal to transport the fabric along the target transport path, which are matched with the drape level of the fabric to be transported. A conveying execution unit is used to drive the fabric to be transported to be conveyed along the target transport path; The status feedback unit is used to monitor the path status of the target transportation path in real time during the transportation process, and when a change in the path status is detected that triggers a preset rescheduling condition, it sends a path anomaly feedback to the scheduling terminal for rescheduling.

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