System and method for identifying and detecting multiple types of trays of stacker

Abstract

The invention provides a stacking machine multi-type tray identification and detection system and method, and the method comprises the steps that a cargo carrying table tray type identification and goods allocation position binding module receives task information of an upper computer, and analyzes the task information to obtain a task tray type and a target goods allocation position; the actual tray type identified by the sensor group on the cargo carrying table is compared with the task tray type; if yes, the task tray type and the target goods allocation position are logically bound; the multi-sensor cooperation and difference detection module collects real-time data; the PLC performs time synchronization and fusion analysis on the real-time data to obtain a fusion result; comparing the fusion result with a preset standard value to obtain a comparison result; identifying the type of the tray and the state of the tray according to the comparison result; the tray multi-dimensional detection integration module performs detection according to the tray type and position after binding of the previous tray type and the cargo position, and calls a corresponding logic block to perform detection to obtain a detection result; and determining to execute operation or alarm according to the detection result.

Description

Technical Field

[0001] This invention relates to the field of automated warehousing and logistics technology, and in particular to a multi-type pallet identification and detection system and method for stacker cranes. Background Technology

[0002] Currently, traditional stacker crane detection systems mostly use a single type of sensor (such as a limit switch or a single photoelectric sensor) to make a rough judgment on the presence or absence of pallets. While this is manageable when handling pallets of a single size, it presents the following problems when dealing with the increasingly common scenarios in modern warehousing involving multi-size pallets, mixed storage of different sizes, and complex parallel tasks: 1) Poor adaptability: The system is rigid and cannot flexibly cope with the complex storage layout of mixed pallets of different sizes and types, requiring a lot of manual pre-setting and intervention.

[0003] 2) Insufficient reliability: It relies on a single sensor. Once the sensor fails, the entire detection process will fail, resulting in a high risk of system downtime and cargo damage.

[0004] 3) Safety risks: The lack of a mechanism to verify pallet type at the initial stage of task execution makes it easy for stacker cranes to collide with shelves or pallets if the task assigned by the host computer does not match the actual items on the loading platform. Summary of the Invention

[0005] In view of this, the purpose of the present invention is to provide a multi-type pallet identification and detection system and method for stacker cranes, which can realize automated operation with high precision, high efficiency and high safety.

[0006] In a first aspect, embodiments of the present invention provide a multi-type pallet identification and detection system for stacker cranes, the system comprising: a multi-sensor collaboration and difference detection module, a pallet type identification and location binding module for loading platforms, a multi-dimensional pallet detection integration module, and a PLC; The pallet type identification and location binding module of the loading platform is used to receive task information from the host computer, parse the task information to obtain the task pallet type and the target location; compare the actual pallet type identified by the sensor group on the loading platform with the task pallet type; if they do not match, an alarm is immediately triggered and the task is terminated; if they match, the task pallet type and the target location are logically bound. The multi-sensor collaboration and difference detection module is used to collect real-time data; The PLC is used to synchronize and fuse the real-time data to obtain a fusion result; compare the fusion result with a preset standard value to obtain a comparison result; and identify the type and status of the pallet based on the comparison result. The pallet multi-dimensional detection integration module is used to perform detection based on the pallet type and location bound to the cargo location, call the corresponding logic block to perform detection, and obtain the detection result; and determine to perform an operation or alarm based on the detection result.

[0007] Furthermore, the multi-sensor collaboration and difference detection module includes an infrared sensor, a multi-point laser sensor, a distance sensor, and a through-beam sensor; The infrared sensor is used to detect the tray at close range; The multi-point laser sensor is used for detecting the tray from a distance; The distance sensor is used to detect the placement distance of the tray; The through-beam sensor is used to detect whether the tray is out of range.

[0008] Furthermore, the PLC is used to obtain the deviation based on the placement distance and the preset standard value; determine whether the deviation is within the tolerance range; if yes, determine that the state of the tray is normal; if no, determine that the state of the tray is abnormal.

[0009] Furthermore, the tray multidimensional detection integration module includes a task dimension detection logic block; The task-dimensional detection logic block is used to detect the pallets that are entering, leaving, or being transferred.

[0010] Furthermore, the tray multidimensional detection integration module also includes a type dimension detection logic block; The type dimension detection logic block is used to detect the type of the tray.

[0011] Furthermore, the pallet multidimensional detection integration module also includes a position dimension detection logic block; The position dimension detection logic block is used to detect the position of the tray.

[0012] Furthermore, the tray multidimensional detection integration module also includes a state dimension detection logic block; The state dimension detection logic block is used to detect the state of the tray.

[0013] Secondly, embodiments of the present invention provide a method for identifying and detecting multiple types of pallets on a stacker crane, applied to the stacker crane multi-type pallet identification and detection system described above. The system includes: a multi-sensor collaboration and difference detection module, a pallet type identification and location binding module for a loading platform, a pallet multi-dimensional detection integration module, and a PLC; the method includes: The pallet type identification and location binding module receives task information from the host computer, parses the task information, and obtains the task pallet type and target location. The actual pallet type identified by the sensor group on the loading platform is compared with the task pallet type; if they do not match, an alarm is immediately triggered and the task is terminated; if they match, the task pallet type and the target storage location are logically bound together. The multi-sensor collaboration and difference detection module is used to collect real-time data; The PLC performs time synchronization and fusion analysis on the real-time data to obtain a fusion result; the fusion result is compared with a preset standard value to obtain a comparison result; The type and status of the tray are identified based on the comparison results; The pallet multidimensional detection integration module performs detection based on the pallet type and location after binding the preceding pallet type with the cargo location, calls the corresponding logic block to perform detection, and obtains the detection result. The action to be taken or an alarm to be triggered will be determined based on the detection results.

[0014] Thirdly, embodiments of the present invention provide an electronic device, including a memory and a processor, wherein the memory stores a computer program that can run on the processor, and the processor executes the computer program to implement the method described above.

[0015] Fourthly, embodiments of the present invention provide a computer-readable medium having processor-executable non-volatile program code that causes the processor to perform the method described above.

[0016] This invention provides a multi-type pallet identification and detection system and method for stacker cranes. The system includes: a multi-sensor collaboration and difference detection module, a pallet type identification and location binding module for loading platforms, a multi-dimensional pallet detection integration module, and a PLC. The pallet type identification and location binding module for loading platforms receives task information from a host computer, parses the task information to obtain the task pallet type and the target location; compares the actual pallet type identified by the sensor group on the loading platform with the task pallet type; if they do not match, an alarm is immediately triggered and the task is terminated; if they match, the task pallet type and target location are linked. The system logically binds locations; a multi-sensor collaboration and difference detection module collects real-time data; a PLC synchronizes and fuses the real-time data to obtain fusion results; the fusion results are compared with preset standard values ​​to obtain comparison results; the pallet type and status are identified based on the comparison results; a pallet multi-dimensional detection integration module detects pallets based on the type and location bound to the preceding pallet type and cargo location, calls the corresponding logic blocks for detection, and obtains detection results; the system determines whether to perform an operation or issue an alarm based on the detection results; this system enables highly accurate, efficient, and safe automated operations.

[0017] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention are realized and obtained in accordance with the structures particularly pointed out in the description, claims and drawings.

[0018] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0019] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0020] Figure 1 This is a schematic diagram of the stacker crane multi-type pallet identification and detection system provided in Embodiment 1 of the present invention; Figure 2 This is a top view of a pallet arrangement within a storage compartment according to Embodiment 1 of the present invention. Figure 3 This is a side view of a pallet arrangement within a storage compartment according to Embodiment 1 of the present invention. Figure 4This is a schematic diagram of the operation of the multi-sensor collaboration and difference detection module provided in Embodiment 1 of the present invention; Figure 5 This is a flowchart of the pallet type identification and location binding module for the loading platform provided in Embodiment 1 of the present invention; Figure 6 This is a schematic diagram of the framework and dimensions of the tray multidimensional detection integrated module provided in Embodiment 1 of the present invention; Figure 7 This is a flowchart of a multi-type pallet identification and detection method for stacker cranes provided in Embodiment 2 of the present invention. Detailed Implementation

[0021] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0022] To facilitate understanding of this embodiment, the embodiments of the present invention will be described in detail below.

[0023] Example 1: Figure 1 This is a schematic diagram of a stacker crane multi-type pallet identification and detection system provided in Embodiment 1 of the present invention.

[0024] Reference Figure 1 The system includes a multi-sensor collaboration and differential detection module, a pallet type recognition and cargo location binding module, a pallet multi-dimensional detection integration module, and a PLC. The pallet type identification and location binding module of the loading platform is used to receive task information from the host computer, parse the task information to obtain the task pallet type and the target location; compare the actual pallet type identified by the sensor group on the loading platform with the task pallet type; if they do not match, an alarm is immediately triggered and the task is terminated; if they match, the task pallet type and the target location are logically bound. A multi-sensor collaboration and difference detection module is used to collect real-time data; The PLC is used to synchronize and fuse real-time data to obtain fusion results; compare the fusion results with preset standard values ​​to obtain comparison results; and identify the type and status of the pallet based on the comparison results. The pallet multi-dimensional detection integrated module is used to detect pallets based on the type and location of the preceding pallets and the bound pallet location, call the corresponding logic blocks to perform the detection, obtain the detection results, and determine the operation to be performed or an alarm to be triggered based on the detection results.

[0025] Specifically, the multi-sensor collaboration and difference detection module achieves multi-dimensional high-precision pallet identification by coordinating the types and functions of infrared sensors, laser sensors, distance sensors, and through-beam sensors, combined with difference detection technology; the pallet type identification and storage location binding module performs pallet type security verification and binds it to the storage location at the initial stage of the task to ensure the accuracy and uniqueness of task execution; and the pallet multi-dimensional detection integration module achieves unified detection of four dimensions: task, type, location, and status, through an integrated logical framework.

[0026] The multi-sensor collaboration and difference detection module comprehensively utilizes the advantages of infrared, laser, distance, and through-beam sensors to achieve comprehensive perception of the pallet through type and function collaboration. Employing difference detection technology, it compares real-time data with a preset standard model to achieve accurate identification and anomaly judgment, and features sensor redundancy design to enhance reliability.

[0027] Pallet type identification and location binding module: This adds a safety "checkpoint" at the start of the task. By identifying the type of pallet on the loading platform and comparing it with the task instructions, it eliminates type errors at the source. The binding operation ensures the independence and uniqueness of each storage location, laying the foundation for accurate subsequent detection.

[0028] The tray multi-dimensional detection integrated module employs a highly integrated software design, encapsulating complex detection logic into a unified module. This module supports rapid judgment from four dimensions: task, type, location, and status, greatly simplifying the system architecture and improving response speed, maintainability, and scalability.

[0029] This application aims to solve the technical problems of low accuracy, poor adaptability, insufficient reliability and safety hazards in the recognition of multiple types of pallets by stacker cranes in complex warehousing environments, so as to achieve high-precision, high-efficiency and high-safety automated operation.

[0030] This application presents a double-extension, double-station stacker crane application mode, simultaneously utilizing both standard large and small pallets. The double-station stacker crane handles pallet transport for two rows of racks on each side. A large storage compartment can hold three small pallets or one large pallet. That is, when a large pallet is placed in a storage compartment, no more large or small pallets can be placed there; when a small pallet is placed in a storage compartment, two more small pallets can be placed there, but no more large pallets can be placed there. A diagram illustrating pallet placement within a storage compartment is provided. Figure 2 and Figure 3 .

[0031] Furthermore, the multi-sensor collaboration and difference detection module includes an infrared sensor, a multi-point laser sensor, a distance sensor, and a through-beam sensor; Infrared sensors are used for close-range detection of the tray; Multi-point laser sensors are used for long-distance detection of trays; Distance sensor, used to detect the placement distance of the tray; Through-beam sensors are used to detect whether the tray is out of range.

[0032] Specifically, sensor types work in synergy: infrared sensors, multi-point laser sensors, distance sensors, and through-beam sensors are deployed at key detection points on the stacker crane. Infrared sensors are used for near-range pallet detection, multi-point laser sensors for long-range pallet detection, distance sensors for detecting the pallet placement distance, and through-beam sensors for detecting whether the pallet is out of range. By comprehensively utilizing the physical characteristics of different sensors, omnidirectional perception of pallets is achieved, from far to near, from outline to presence.

[0033] Sensor function collaboration: The same sensor can perform multiple functions at the same time. That is, the same sensor can be configured to perform at least two of the functions of tray type recognition, position recognition and status recognition. For example, a laser sensor can participate in both tray type recognition and position and status judgment.

[0034] Difference Detection: The system pre-stores standard characteristic data (such as standard length, standard distance, etc.) for all types of pallets under various tasks. During operation, the PLC performs time synchronization and fusion analysis on real-time data collected by multiple sensors and compares the results with preset standard values. By determining whether the deviation is within the tolerance range, the pallet type is identified and its status is judged as normal. See details [link to relevant documentation]. Figure 4 .

[0035] Redundancy design: Key detection points are covered by at least two sensors, and the system can automatically switch to the backup sensor when the main sensor fails.

[0036] Furthermore, the PLC is used to obtain the deviation based on the placement distance and the preset standard value; determine whether the deviation is within the tolerance range; if so, the pallet status is determined to be normal; if not, the pallet status is determined to be abnormal.

[0037] In the pallet type recognition and location binding module M2 of the loading platform, refer to Figure 5 The stacker crane's M2 receives the task from the host computer, parses out the task pallet type (T1) and the target storage location (P1); after picking up the goods or before placing them, it identifies the actual pallet type (T2) through the sensor group on the loading platform. Compare T2 with T1. If they match, continue execution; if they do not match, immediately issue an alarm and terminate the task to prevent type errors from the source.

[0038] After the verification is successful, the system logically binds the task pallet type (T1) with the target storage location (P1), for example, uniquely associating the "small pallet" with "location 2" in the storage compartment, laying the foundation for accurate detection in the future.

[0039] Furthermore, the tray multidimensional detection integration module includes a task dimension detection logic block; The task-dimensional detection logic block is used to detect pallets that are entering, leaving, or being transferred.

[0040] Furthermore, the tray multidimensional detection integration module also includes a type dimension detection logic block; The type dimension detection logic block is used to detect the type of the tray.

[0041] Furthermore, the pallet multidimensional detection integration module also includes a position dimension detection logic block; The position dimension detection logic block is used to detect the position of the tray.

[0042] Furthermore, the pallet multidimensional detection integration module also includes a state dimension detection logic block; The state dimension detection logic block is used to detect the state of the tray.

[0043] Specifically, refer to Figure 6 The tray multidimensional detection integration module M3 is a highly integrated software logic framework. M3 includes: task dimension detection logic block, type dimension detection logic block, position dimension detection logic block, state dimension detection logic block, and comprehensive decision and execution logic block.

[0044] M3 is activated when the stacker crane arrives at the target storage location.

[0045] Based on the type and location information bound to the preceding module, M3 automatically calls the corresponding detection logic combination.

[0046] The system performs rapid and parallel comprehensive judgment on pallets from four perspectives: task-based detection logic blocks (inbound / outbound), type-based detection logic blocks (large / small pallets), position-based detection logic blocks (position 1 / 2 / 3 / 4), and status-based detection logic blocks (center / offset / abnormal).

[0047] Ultimately, the comprehensive decision-making and execution logic block decides whether to perform an operation or issue an alarm based on the multi-dimensional detection results.

[0048] The sensor types in this system are not limited to infrared sensors, laser sensors, distance sensors, and through-beam sensors. They can also be expanded to include 3D vision sensors, RFID readers, etc., as needed to further enrich the perception dimensions.

[0049] Location binding is not limited to logical binding; it can be combined with indoor precise positioning technologies (such as UWB) to achieve real-time tracking and verification of physical location.

[0050] The design concept of the pallet multidimensional detection integrated module M3 can be extended to other detection scenarios of stacker cranes, such as cargo box size recognition and cargo shape anomaly detection, simply by updating the corresponding detection logic block.

[0051] This application is not only applicable to dual-station, dual-depth stacker cranes, but also to single-station, single-depth, or other types of aisle-type handling equipment, solving the identification problem of multiple types of carriers.

[0052] The advantages of this application are: 1) High precision and high reliability: Through multi-sensor collaboration and difference detection, centimeter-level accurate judgment of tray type and status is achieved. Redundancy design ensures that the system can still operate stably when some components fail.

[0053] 2) Strong adaptability and flexibility: It can automatically adapt to up to 16 task types and more than 50 detection situations, perfectly solving the problem of mixed operations under complex cargo layouts such as "one large and many small".

[0054] 3) Intrinsic safety: The cargo platform type identification process acts as a "safety gate," effectively preventing collisions caused by discrepancies between the task and the actual object, and greatly improving the inherent safety level of the system.

[0055] 4) High efficiency and easy maintenance: The integrated modular design makes the system logic clear and responsive. When it is necessary to maintain or expand a new tray type, only the corresponding logic needs to be modified in the integrated module, which greatly reduces maintenance costs and downtime.

[0056] Example 2: Figure 7 This is a flowchart of a multi-type pallet identification and detection method for stacker cranes provided in Embodiment 2 of the present invention.

[0057] The system, applied to the stacker crane multi-type pallet recognition and detection system described above, includes: a multi-sensor collaborative and differential detection module, a pallet type recognition and location binding module for the loading platform, a pallet multi-dimensional detection integration module, and a PLC; (Refer to...) Figure 7 The method includes the following steps: Step S101: The pallet type identification and location binding module of the loading platform receives the task information from the host computer, parses the task information, and obtains the task pallet type and the target location. Step S102: Compare the actual pallet type identified by the sensor group on the loading platform with the task pallet type; Step S103: If there is a discrepancy, immediately trigger an alarm and terminate the task; Step S104: If they match, then logically bind the task pallet type and the target storage location. Step S105: Multi-sensor collaboration and difference detection module, used to collect real-time data; Step S106: The PLC performs time synchronization and fusion analysis on the real-time data to obtain the fusion result; the fusion result is compared with the preset standard value to obtain the comparison result; Step S107: Identify the type and status of the pallet based on the comparison results; Step S108: The pallet multi-dimensional detection integration module performs detection based on the pallet type and position bound to the cargo position in the previous step, calls the corresponding logic block to perform detection, and obtains the detection result. Step S109: Determine whether to perform an operation or issue an alarm based on the detection results.

[0058] This invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of the stacker crane multi-type pallet identification and detection method provided in the above embodiments.

[0059] This invention also provides a computer-readable medium having processor-executable non-volatile program code, on which a computer program is stored. When the computer program is run by a processor, it executes the steps of the stacker crane multi-type pallet identification and detection method described above.

[0060] The computer program product provided in this embodiment of the invention includes a computer-readable storage medium storing program code. The instructions included in the program code can be used to execute the methods described in the preceding method embodiments. For specific implementation details, please refer to the method embodiments, which will not be repeated here.

[0061] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the system and apparatus described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0062] Furthermore, in the description of the embodiments of the present invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in the present invention based on the specific circumstances.

[0063] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, essentially, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0064] In the description of this invention, it should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing the invention and for simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0065] Finally, it should be noted that the above-described embodiments are merely specific implementations of the present invention, used to illustrate the technical solutions of the present invention, and not to limit it. The scope of protection of the present invention is not limited thereto. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that any person skilled in the art can still modify or easily conceive of changes to the technical solutions described in the foregoing embodiments within the technical scope disclosed in the present invention, or make equivalent substitutions for some of the technical features; and these modifications, changes, or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A multi-type pallet identification and detection system for stacker cranes, characterized in that, The system includes: a multi-sensor collaboration and difference detection module, a pallet type recognition and cargo location binding module, a pallet multi-dimensional detection integration module, and a PLC; The pallet type identification and location binding module of the loading platform is used to receive task information from the host computer, parse the task information to obtain the task pallet type and the target location; compare the actual pallet type identified by the sensor group on the loading platform with the task pallet type; if they do not match, an alarm is immediately triggered and the task is terminated; if they match, the task pallet type and the target location are logically bound. The multi-sensor collaboration and difference detection module is used to collect real-time data; The PLC is used to synchronize and fuse the real-time data to obtain a fusion result; compare the fusion result with a preset standard value to obtain a comparison result; and identify the type and status of the pallet based on the comparison result. The pallet multi-dimensional detection integration module is used to perform detection based on the pallet type and location bound to the cargo location, call the corresponding logic block to perform detection, and obtain the detection result; and determine to perform an operation or alarm based on the detection result.

2. The stacker crane multi-type pallet identification and detection system according to claim 1, characterized in that, The multi-sensor collaboration and difference detection module includes an infrared sensor, a multi-point laser sensor, a distance sensor, and a through-beam sensor; The infrared sensor is used to detect the tray at close range; The multi-point laser sensor is used for detecting the tray from a distance; The distance sensor is used to detect the placement distance of the tray; The through-beam sensor is used to detect whether the tray is out of range.

3. The stacker crane multi-type pallet identification and detection system according to claim 1, characterized in that, The PLC is used to obtain the deviation based on the placement distance and the preset standard value; determine whether the deviation is within the tolerance range; if yes, determine that the state of the tray is normal; if no, determine that the state of the tray is abnormal.

4. The stacker crane multi-type pallet identification and detection system according to claim 1, characterized in that, The tray multidimensional detection integration module includes a task dimension detection logic block; The task-dimensional detection logic block is used to detect the pallets that are entering, leaving, or being transferred.

5. The stacker crane multi-type pallet identification and detection system according to claim 1, characterized in that, The tray multidimensional detection integration module also includes a type dimension detection logic block; The type dimension detection logic block is used to detect the type of the tray.

6. The stacker crane multi-type pallet identification and detection system according to claim 1, characterized in that, The pallet multidimensional detection integration module also includes a position dimension detection logic block; The position dimension detection logic block is used to detect the position of the tray.

7. The stacker crane multi-type pallet identification and detection system according to claim 1, characterized in that, The tray multidimensional detection integration module also includes a state dimension detection logic block; The state dimension detection logic block is used to detect the state of the tray.

8. A method for identifying and detecting multiple types of pallets in a stacker crane, characterized in that, The stacker crane multi-type pallet identification and detection system according to any one of claims 1 to 7, the system comprising: a multi-sensor collaborative and differential detection module, a pallet type identification and location binding module for loading platforms, a pallet multi-dimensional detection integration module, and a PLC; the method comprising: The pallet type identification and location binding module receives task information from the host computer, parses the task information, and obtains the task pallet type and target location. The actual pallet type identified by the sensor group on the loading platform is compared with the task pallet type; if they do not match, an alarm is immediately triggered and the task is terminated; if they match, the task pallet type and the target storage location are logically bound together. The multi-sensor collaboration and difference detection module is used to collect real-time data; The PLC performs time synchronization and fusion analysis on the real-time data to obtain a fusion result; the fusion result is compared with a preset standard value to obtain a comparison result; The type and status of the tray are identified based on the comparison results; The pallet multidimensional detection integration module performs detection based on the pallet type and location bound to the cargo location, calls the corresponding logic block to perform detection, and obtains the detection result. The action to be taken or an alarm to be triggered will be determined based on the detection results.

9. An electronic device comprising a memory and a processor, wherein the memory stores a computer program executable on the processor, characterized in that, When the processor executes the computer program, it implements the method described in claim 8.

10. A computer-readable medium having processor-executable non-volatile program code, characterized in that, The program code causes the processor to execute the method described in claim 8.

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