A conveying line system for a stereoscopic warehouse and a congestion control method thereof

Abstract

This invention discloses a conveyor system for automated warehouses and its congestion control method. The conveyor system includes a conveyor network module, a sensing and monitoring module, and a central control module. The conveyor network module consists of multiple interconnected conveyor segments for transferring pallets carrying goods. The sensing and monitoring module is distributed across the conveyor network to acquire real-time status information of each conveyor segment and pallet flow information. This invention proactively identifies congestion risks through flow prediction based on historical data and takes control measures before congestion actually occurs, significantly reducing system downtime. By employing a multi-conveyor-line coordinated speed control mechanism, for identified potential congestion points, not only is the speed of that point adjusted, but also the speed of its upstream and downstream related lines is coordinated, optimizing the dynamic balance of material flow across the entire network.

Description

Technical Field

[0001] This invention belongs to the field of automated logistics technology, specifically relating to a conveyor system for automated warehouses and its congestion control method. Background Technology

[0002] Automated warehouses (AS / RS) are the core of modern logistics systems. Their core functionality involves high-density storage and efficient automated retrieval of goods through high-rise racking, stacker cranes, and complex conveyor systems. The conveyor system, acting as the "arteries" connecting warehouse entrances, exits, processing stations, and racking areas, directly determines the throughput capacity of the entire AS / RS.

[0003] Currently, most common conveyor control systems adopt reactive control strategies based on local sensors. For example, photoelectric sensors or proximity switches are installed at key nodes of the conveyor line. When pallet congestion or excessive queue length is detected, the conveyor line in that section is triggered to slow down or stop to prevent physical collisions and cargo backlog. However, this control strategy has obvious limitations: (1) It only takes action after congestion occurs, resulting in a reaction lag. (2) Each conveyor line is controlled independently, lacking coordination. For example, if the main line at the front end slows down to handle slow goods, and the branch line behind it continues to transport fast goods at the original speed, it will inevitably lead to cargo backlog at the merging point; conversely, if the main line is idle while the branch line is too slow, it will result in idle resources.

[0004] Therefore, in order to address the aforementioned technical problems, it is necessary to provide a conveyor system for automated warehouses and a congestion control method thereof.

[0005] The information disclosed in this background section is intended only to enhance the understanding of the overall background of the invention and should not be construed as an admission or in any way implying that the information constitutes prior art known to those skilled in the art. Summary of the Invention

[0006] The purpose of this invention is to provide a conveyor system for automated warehouses and a congestion control method thereof, which can solve the problems mentioned in the background art.

[0007] To achieve the above objectives, a specific embodiment of the present invention provides the following technical solution: A conveyor system for automated warehouses includes a conveyor network module, a sensing and monitoring module, and a central control module. The conveyor network module consists of multiple interconnected conveyor segments for transferring pallets carrying goods. The sensing and monitoring module is distributed across the conveyor network to acquire real-time status information and pallet flow information for each conveyor segment. The central control module is communicatively connected to the sensing and monitoring module and includes a prediction unit, a congestion assessment unit, a coordinated speed control unit, and a drive execution unit. The prediction unit predicts pallet flow at key nodes over multiple future monitoring periods based on historical flow data. The congestion assessment unit incorporates a congestion prediction algorithm to calculate the congestion risk index for each conveyor segment in future time periods based on predicted pallet flow, current queue status, and dynamically adjusted congestion thresholds. The coordinated speed control unit identifies potential congestion points based on the congestion risk index and generates a coordinated speed control instruction set covering the congestion point and its upstream and / or downstream associated conveyor segments. The drive execution unit executes the coordinated speed control instruction set to adjust the speed of the corresponding conveyor segment.

[0008] In one or more embodiments of the present invention, the sensing and monitoring module includes a sensing unit and an identification unit disposed at the starting end of the conveyor line segment or a specific workstation.

[0009] In one or more embodiments of the present invention, the pallet circulation information includes weight information, cargo type information, and location and speed information.

[0010] In one or more embodiments of the present invention, the congestion prediction algorithm includes a dynamic threshold setting unit, which dynamically adjusts the maximum allowable queue length threshold of each conveyor segment based on the ratio of the predicted future pallet flow to the historical average flow.

[0011] In one or more embodiments of the present invention, the coordinated speed control instruction set includes differentiated speed control instructions for the potential congestion point itself, its upstream lines and downstream lines, wherein a stepped deceleration instruction is implemented for the upstream lines, and the deceleration magnitude is greater for the upstream lines closer to the potential congestion point, and smaller or later for the upstream lines farther away.

[0012] In one or more embodiments of the present invention, an adaptive adjustment module is further included, which is used to dynamically adjust the operating cycle of the prediction unit and the congestion assessment unit according to the rate of change of the network-wide congestion risk index.

[0013] A congestion control method for a conveyor line system in an automated warehouse includes the following steps: S1. Periodically collect pallet flow and queue status data at monitoring points on each conveyor line; S2. Based on historical data, predict the expected flow of each monitoring point in the next N periods; S3. Combining the predicted traffic flow with the current status, use dynamic thresholds to calculate the congestion risk index for each line segment in future cycles. S4. If the risk index exceeds the preset threshold, the corresponding line segment is determined to be a potential congestion point in the corresponding future period. S5. Taking the potential congestion point as the center, determine the set of associated conveyor line segments in the material flow direction; S6. Generate a set of linkage speed control instructions for the associated conveyor line segment set, and issue them for execution; S7. Update the system status based on the feedback data after the instruction is executed, and enter the next control cycle.

[0014] In one or more embodiments of the present invention, in S3, the method for calculating the dynamic threshold is as follows: Among them, L max base Based on the threshold, F pred To predict the average flow rate in the future, F hist γ represents the historical average flow rate, and γ is an adjustable sensitivity coefficient.

[0015] In one or more embodiments of the present invention, in S5, the associated conveyor segment set includes tracing back along the material flow direction to all upstream lines that directly affect the incoming material to the potential congestion point, and identifying in the forward direction along the material flow direction all downstream lines that are directly affected by the output of the potential congestion point.

[0016] In one or more embodiments of the present invention, in S6, the linkage speed regulation command set specifically includes: S601. For potential congestion points themselves, implement deceleration for at least one cycle before the risk occurs; S602. For the direct upstream lines of potential congestion points, implement step-by-step speed reduction according to the severity of the risk. S603. For upstream branch points with alternative paths, generate speed adjustment instructions to guide the diversion. S604. For the direct downstream lines of potential congestion points, assess their processing capacity and generate acceleration or coordinated speed adjustment commands.

[0017] Compared with existing technologies, the conveyor system and congestion control method for automated warehouses of the present invention can proactively identify congestion risks by predicting flow based on historical data and take control measures before congestion actually occurs, greatly reducing system downtime. By adopting a multi-conveyor-line linkage speed regulation mechanism, for the identified potential congestion points, not only is the speed of the point itself adjusted, but also the speed of its upstream and downstream related lines is coordinated and planned, thus optimizing the dynamic balance of material flow in the entire network. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a structural block diagram of a conveyor line system for an automated warehouse according to one embodiment of the present invention; Figure 2 This is a structural block diagram of the sensing and monitoring module in one embodiment of the present invention; Figure 3 This is a schematic diagram of a congestion control method for a conveyor line system in an automated warehouse according to an embodiment of the present invention. Figure 4 This is a diagram of the linkage speed control command set in one embodiment of the present invention. Detailed Implementation

[0020] To enable those skilled in the art to better understand the technical solutions in this disclosure, the technical solutions in the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this disclosure, and not all embodiments. Based on the embodiments in this disclosure, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of this disclosure.

[0021] like Figures 1 to 2As shown, an embodiment of the present invention provides a conveyor system for an automated warehouse, comprising a conveyor network module, a sensing and monitoring module, a central control module, and an adaptive adjustment module. The conveyor network module consists of multiple interconnected conveyor segments for transferring pallets carrying goods. The sensing and monitoring module is distributed across the conveyor network to acquire real-time status information and pallet flow information for each conveyor segment. The central control module is communicatively connected to the sensing and monitoring module and includes a prediction unit, a congestion assessment unit, a linkage speed control unit, and a drive execution unit. The prediction unit predicts pallet flow at key nodes over multiple future monitoring periods based on historical flow data. The congestion assessment unit incorporates a congestion prediction algorithm to calculate the congestion risk index for each conveyor segment in future time periods based on predicted pallet flow, current queue status, and dynamically adjusted congestion thresholds. The linkage speed control unit identifies potential congestion points based on the congestion risk index and generates a linkage speed control instruction set covering the congestion point and its upstream and / or downstream associated conveyor segments. The drive execution unit executes the linkage speed control instruction set to adjust the speed of the corresponding conveyor segment. The adaptive adjustment module is used to dynamically adjust the operating cycle of the prediction unit and the congestion assessment unit based on the rate of change of the network-wide congestion risk index.

[0022] In this embodiment, the conveyor network module consists of multiple interconnected or intersecting conveyor segments, forming a material flow path connecting the storage area, workstations, and inbound / outbound terminals. Each conveyor segment's operating speed is controlled by an independent drive motor. Sensing and monitoring modules are distributed at the inlets, outlets, and key branch / merging points of each conveyor segment.

[0023] The prediction unit uses a lightweight seasonal autoregressive integral moving average model as the prediction model. It is triggered every 5 minutes and uses the traffic data of each monitoring point in the past 30 minutes as input to predict the traffic in the next 2 minutes.

[0024] like Figure 2 As shown, the sensing and monitoring module includes a sensing unit and an identification unit installed at the beginning of the conveyor line or at a specific workstation. Pallet flow information includes weight information, cargo type information, and position and speed information. Through the cooperation of the weight sensing unit and the identification unit, the pallet's weight information, cargo type information, and position and speed information can be identified.

[0025] Specifically, the sensor unit includes a photoelectric sensor for measuring queue length, and the identification unit includes an RFID reader for reading tray tags.

[0026] like Figure 1As shown, the congestion prediction algorithm includes a dynamic threshold setting unit, which dynamically adjusts the maximum allowable queue length threshold for each conveyor segment based on the ratio of the predicted future pallet flow to the historical average flow.

[0027] By setting the dynamic threshold unit, the congestion judgment criteria can be adapted to different operating intensities. The threshold can be appropriately relaxed during high flow periods to improve throughput potential, while the threshold can be tightened during low flow periods to maintain the smooth operation of the conveyor system, thereby improving the overall adaptability and intelligence level of control.

[0028] like Figures 1 to 2 As shown, the coordinated speed control command set includes differentiated speed control commands for the potential congestion point itself, its upstream lines, and downstream lines. Specifically, it implements a stepped deceleration command for upstream lines, with the deceleration magnitude being greater for upstream lines closer to the potential congestion point and smaller or later for lines farther away. This stepped deceleration command creates a smooth velocity gradient buffer zone upstream of the congestion point, effectively absorbing and mitigating incoming material impact, avoiding material accumulation and pressure surges caused by direct abrupt stops, and achieving flexible flow control.

[0029] Furthermore, the linkage speed control unit also considers the substitutability of material paths when generating linkage speed control command sets. When a potential congestion point is identified, if an alternative conveying path to the same destination exists, a diversion command is generated to increase the running priority or speed of the alternative path. This configuration not only controls the flow rate through speed regulation but also changes the flow path through diversion, achieving a dynamic spatial redistribution of flow in the conveying network, further enhancing the conveyor system's ability and flexibility to resolve congestion.

[0030] like Figure 3 As shown, a congestion control method for a conveyor line system in an automated warehouse includes the following steps: S1. Periodically collect pallet flow and queue status data at monitoring points on each conveyor line; S2. Based on historical data, predict the expected flow of each monitoring point in the next N periods; S3. Combining the predicted traffic flow with the current status, use dynamic thresholds to calculate the congestion risk index for each line segment in future cycles. S4. If the risk index exceeds the preset threshold, the corresponding line segment is determined to be a potential congestion point in the corresponding future period. S5. Taking potential congestion points as the center, determine the set of associated conveyor line segments in the material flow direction; S6. Generate a set of linkage speed control instructions for the associated conveyor line segment set and issue them for execution; S7. Update the system status based on the feedback data after the instruction is executed, and enter the next control cycle.

[0031] Specifically, S3 includes the following steps: S301. Get the current queue length L curr The queue length can be estimated using photoelectric sensors; S302, Obtain the current dynamic threshold L max dynamic The dynamic threshold is calculated as follows: Among them, L max base The base threshold is 15 trays, F pred F represents the average predicted flow rate at the inlet of this line segment over the next N periods. hist γ is the historical average flow rate, and γ is the adjustable sensitivity coefficient. S303, Calculate the current load rate η curr The formula for calculating the load rate is as follows: η curr =L curr / L max dynamic ; S304. Based on the predicted inflow and outflow, calculate the predicted queue length L for each future period. pred i和预测负载率ηpred i The outflow rate can be estimated based on the condition and speed of the downstream line segment; S305. Calculate the congestion risk index R for the i-th future period. i The formula for calculating the congestion risk index is as follows: .

[0032] Furthermore, in S5, the associated conveyor segment set includes all upstream lines that directly affect incoming materials to potential congestion points by tracing back along the material flow direction, and all downstream lines that are directly affected by the output of potential congestion points by identifying forward along the material flow direction. This ensures that the coordinated speed regulation action can accurately affect lines that have a direct causal relationship with the congestion point, improving the effectiveness and economy of the control action.

[0033] like Figure 4 As shown, in S6, the linkage speed control instruction set specifically includes: S601. For potential congestion points themselves, implement deceleration at least once before the risk occurs. For example, at the beginning of the cycle before the third cycle, i.e., in the second cycle, reduce the speed from 100% to 60%. S602. For the direct upstream lines of potential congestion points, implement step-by-step speed reduction according to the severity of the risk. For example, starting from the first cycle, reduce the speed of line segment A from 100% to 80%; reduce the speed of line segment B from 100% to 85%. S603. For upstream branch points with alternative paths, generate speed adjustment instructions to guide the diversion. S604. For the direct downstream lines of potential congestion points, assess their processing capacity and generate acceleration or coordinated speed adjustment commands.

[0034] Furthermore, the congestion control method includes an adaptive adjustment step for the monitoring cycle, which calculates the rate of change of the average congestion risk index across the entire network. If the rate of change exceeds a high threshold, the control cycle is shortened; if it falls below a low threshold, the control cycle is restored or extended. This ensures that the method self-optimizes its execution frequency in a dynamic environment, enhancing its robustness and practicality under different operational scenarios.

[0035] This invention, through flow prediction based on historical data, can proactively identify congestion risks and take control measures before congestion actually occurs, greatly reducing system downtime. It employs a multi-conveyor-line coordinated speed control mechanism, adjusting not only the speed of the identified potential congestion point but also coordinating the speed planning of its upstream and downstream related lines, optimizing the dynamic balance of material flow across the entire network. The congestion prediction algorithm incorporates dynamic threshold setting and an adaptive monitoring cycle. The threshold intelligently adjusts according to the predicted flow situation, ensuring the conveyor system maintains sensitive and accurate judgment under different operating intensities. The adaptive monitoring cycle optimizes the allocation of conveyor system resources, enabling rapid response in emergencies and resource conservation during stable periods.

[0036] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0037] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0038] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0039] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0040] It will be apparent to those skilled in the art that this disclosure is not limited to the details of the exemplary embodiments described above, and that this disclosure can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered in all respects as exemplary and non-limiting, and the scope of this disclosure is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within this disclosure. No reference numerals in the claims should be construed as limiting the scope of the claims.

[0041] Furthermore, it should be understood that although this specification describes embodiments, not every embodiment contains only one independent technical solution. This narrative style is merely for clarity. Those skilled in the art should consider the specification as a whole, and the technical solutions in each embodiment can also be appropriately combined to form other embodiments that can be understood by those skilled in the art.

Claims

1. A conveyor line system for automated warehouses, characterized in that, include: A conveyor network module consists of multiple interconnected conveyor lines used to transfer pallets carrying goods. The sensing and monitoring module is deployed in a distributed manner in the conveyor network to obtain the status information and pallet circulation information of each conveyor segment in real time; The central control module is communicatively connected to the sensing and monitoring module. The central control module includes a prediction unit, a congestion assessment unit, a linkage speed control unit, and a drive execution unit. The prediction unit predicts the pallet flow of each key node in multiple future monitoring periods based on historical flow data. The congestion assessment unit has a built-in congestion prediction algorithm to calculate the congestion risk index of each conveyor segment in future time periods based on the predicted pallet flow, the current queue status, and dynamically adjusted congestion thresholds. The linkage speed control unit identifies potential congestion points based on the congestion risk index and generates a linkage speed control instruction set covering the congestion points and their upstream and / or downstream associated conveyor segments. The drive execution unit executes the linkage speed control instruction set to adjust the speed of the corresponding conveyor segment.

2. The conveyor line system for an automated warehouse according to claim 1, characterized in that, The sensing and monitoring module includes a sensing unit and an identification unit located at the beginning of the conveyor line or at a specific workstation.

3. A conveyor line system for an automated warehouse according to claim 1, characterized in that, The pallet circulation information includes weight information, cargo type information, and location and speed information.

4. A conveyor line system for an automated warehouse according to claim 1, characterized in that, The congestion prediction algorithm includes a dynamic threshold setting unit, which dynamically adjusts the maximum allowable queue length threshold for each conveyor segment based on the ratio of the predicted future pallet flow to the historical average flow.

5. A conveyor line system for an automated warehouse according to claim 1, characterized in that, The coordinated speed control command set includes differentiated speed control commands for the potential congestion point itself, its upstream lines and downstream lines. Among them, a stepped deceleration command is implemented for the upstream lines, and the deceleration magnitude is greater for the upstream lines closer to the potential congestion point, and smaller or later for the upstream lines farther away.

6. A conveyor line system for an automated warehouse according to claim 1, characterized in that, It also includes an adaptive adjustment module, which is used to dynamically adjust the operating cycle of the prediction unit and the congestion assessment unit according to the rate of change of the network-wide congestion risk index.

7. A congestion control method applied to a conveyor line system for an automated warehouse as described in any one of claims 1-6, characterized in that, Includes the following steps: S1. Periodically collect pallet flow and queue status data at monitoring points on each conveyor line; S2. Based on historical data, predict the expected flow of each monitoring point in the next N periods; S3. Combining the predicted traffic flow with the current status, use dynamic thresholds to calculate the congestion risk index for each line segment in future cycles. S4. If the risk index exceeds the preset threshold, the corresponding line segment is determined to be a potential congestion point in the corresponding future period. S5. Taking the potential congestion point as the center, determine the set of associated conveyor line segments in the material flow direction; S6. Generate a set of linkage speed control instructions for the associated conveyor line segment set, and issue them for execution; S7. Update the system status based on the feedback data after the instruction is executed, and enter the next control cycle.

8. A congestion control method for a conveyor line system in an automated warehouse according to claim 7, characterized in that, In S3, the dynamic threshold is calculated as follows: Among them, L max base Based on the threshold, F pred To predict the average flow rate in the future, F hist γ represents the historical average flow rate, and γ is an adjustable sensitivity coefficient.

9. A congestion control method for a conveyor line system in an automated warehouse according to claim 7, characterized in that, In S5, the associated conveyor line segment set includes all upstream lines that directly affect the incoming material to the potential congestion point by tracing back along the material flow direction, and all downstream lines that are directly affected by the output of the potential congestion point by identifying forward along the material flow direction.

10. A congestion control method for a conveyor line system in an automated warehouse according to claim 7, characterized in that, In S6, the linkage speed control instruction set specifically includes: S601. For potential congestion points themselves, implement deceleration for at least one cycle before the risk occurs; S602. For the direct upstream lines of potential congestion points, implement step-by-step speed reduction according to the severity of the risk. S603. For upstream branch points with alternative paths, generate speed adjustment instructions to guide the diversion. S604. For the direct downstream lines of potential congestion points, assess their processing capacity and generate acceleration or coordinated speed adjustment commands.

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