A multi-target exception processing method and device based on a screening line and electronic equipment

Abstract

The application discloses a multi-target abnormality processing method and device based on a screening line and electronic equipment, the method comprising continuously acquiring detection data uploaded by each detection terminal on the screening line and analyzing the detection data to obtain detection result information; when there is abnormal detection result information, determining and marking a target cell corresponding to the abnormal detection result information; inputting all target carriers of the target cell to a buffer temporary storage area closest to the target cell, and outputting each target carrier in the buffer temporary storage area to an idle cell of the screening line one by one. The application realizes that when an abnormal cell with multiple packages appears, the abnormal cell will be automatically input to the buffer temporary storage area, and multiple packages will be re-output to different idle cells by the buffer temporary storage area, so that the abnormality can be automatically and timely processed when the screening line has a multiple package abnormality, and the processing efficiency of the multiple package abnormality is high.

Description

Technical Field

[0001] This application relates to the field of automatic control technology, and more specifically, to a method, apparatus, and electronic device for multi-target anomaly processing based on a screening line. Background Technology

[0002] In supermarket logistics, goods about to be packaged and shipped are transported via a sorting line of a suspended conveyor system. The sorting line consists of individual sorting chains. Normally, each sorting chain should contain only one suspended package to ensure each package is delivered to the correct packing and shipping location. However, in reality, due to errors in the hanging track structure, low sensor accuracy, and manual hanging, two or more packages may simultaneously exist in a single sorting chain, leading to subsequent package allocation errors and thread delays. Currently, multiple packages are typically only detected manually when they reach the packing and shipping personnel, making timely automatic handling of anomalies inefficient. Summary of the Invention

[0003] To address the aforementioned issues, embodiments of this application provide a method, apparatus, and electronic device for multi-target anomaly processing based on screening lines.

[0004] In a first aspect, embodiments of this application provide a multi-target anomaly processing method based on a screening line, the method comprising:

[0005] The system continuously acquires and filters the detection data uploaded by each preset online detection terminal, and parses the detection data to obtain detection result information.

[0006] When abnormal detection result information exists, the target cell corresponding to the abnormal detection result information is determined and marked;

[0007] All target vehicles of the target cell are input into the buffer storage area closest to the target cell, and each target vehicle in the buffer storage area is output to the free cell of the filter line one by one.

[0008] Preferably, the detection terminal includes a first detection sensor and a second detection sensor vertically distributed from top to bottom, and the detection data includes first detection data collected by the first detection sensor and second detection data collected by the second detection sensor;

[0009] The process of parsing the detection data to obtain detection result information includes:

[0010] The region interval corresponding to the first detection data detected twice consecutively by the same first detection sensor is defined as the detection region.

[0011] The number of the second detection data in each detection area is counted, and detection result information is generated based on the number of detections.

[0012] Preferably, the detection terminal includes a second detection sensor, and the detection data includes second detection data collected by the second detection sensor;

[0013] The process of parsing the detection data to obtain detection result information includes:

[0014] Obtain a preset statistical time period, which includes a format chain time interval and a non-format chain time interval. The format chain time interval corresponds to a format chain region, and the non-format chain time interval corresponds to a non-format chain region.

[0015] The number of detections corresponding to the second detection data in the format chain region and the non-format chain region are counted respectively, and detection result information is generated based on the number of detections.

[0016] Preferably, the detection result information includes normal detection result information and abnormal detection result information;

[0017] The generation of detection result information based on the number of detections includes:

[0018] When the number of tests is no more than one, normal test result information is generated;

[0019] When the number of detections is not less than two, abnormal detection result information is generated.

[0020] Preferably, when abnormal detection result information exists, determining and marking the target cell corresponding to the abnormal detection result information includes:

[0021] When abnormal detection result information exists, the abnormal detection data corresponding to the abnormal detection result information is determined;

[0022] The target cell corresponding to the anomaly detection data is determined based on the transport speed of the screening line and the data detection time of the anomaly detection data, and the target cell is marked.

[0023] Preferably, the step of outputting each of the target vehicles in the buffer storage area to the free cell of the filter line one by one includes:

[0024] Based on the aforementioned detection data, it is determined that there are no empty cells with suspended vehicles.

[0025] Whenever an empty cell passes through the buffer storage area, the target vehicle closest to the exit in the buffer storage area is output to the empty cell, until all the target vehicles in the buffer storage area have been output.

[0026] Secondly, embodiments of this application provide a multi-target anomaly processing device based on a screening line, the device comprising:

[0027] The acquisition module is used to continuously acquire and filter the detection data uploaded by each preset online detection terminal, and parse the detection data to obtain detection result information;

[0028] The marking module is used to determine and mark the target cell corresponding to the abnormal detection result information when abnormal detection result information exists;

[0029] The control module is used to input all target vehicles of the target cell into the buffer storage area closest to the target cell, and output each target vehicle in the buffer storage area to the free cell of the filter line one by one.

[0030] Thirdly, embodiments of this application provide an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the method provided as in the first aspect or any possible implementation of the first aspect.

[0031] Fourthly, embodiments of this application provide a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the method provided as in the first aspect or any possible implementation thereof.

[0032] The beneficial effects of this invention are: it can automatically detect and identify multiple packages in the cell during the logistics transmission process of the screening line, and for abnormal cells with multiple packages, it will automatically input them into the buffer storage area, and through the buffer storage area, multiple packages will be re-output to different idle cells. It can automatically and timely handle the abnormal situation when multiple packages occur in the screening line, and the handling efficiency of multiple package abnormal situation is high. Attached Figure Description

[0033] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0034] Figure 1A flowchart illustrating a multi-target anomaly processing method based on a screening line, provided for an embodiment of this application;

[0035] Figure 2 A schematic diagram illustrating the structure of the screening line system provided in this application embodiment;

[0036] Figure 3 A schematic diagram illustrating yet another structural example of the screening line system provided in an embodiment of this application;

[0037] Figure 4 A schematic diagram of a multi-target anomaly processing device based on a screening line provided in this application embodiment;

[0038] Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application.

[0039] 1-Detection terminal, 2-Detection sensor, 3-Support column, 4-Hanging package. Detailed Implementation

[0040] The technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings.

[0041] In the following description, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance. The following description provides multiple embodiments of this application, which can be substituted or combined with each other. Therefore, this application can also be considered to include all possible combinations of the same and / or different embodiments described. Thus, if one embodiment includes features A, B, and C, and another embodiment includes features B and D, then this application should also be considered to include embodiments containing one or more other possible combinations of A, B, C, and D, even if such embodiments are not explicitly described in the following text.

[0042] The following description provides examples and does not limit the scope, applicability, or examples set forth in the claims. Changes may be made to the function and arrangement of the described elements without departing from the scope of this application. Various processes or components may be appropriately omitted, substituted, or added to the examples. For example, the described methods may be performed in a different order than described, and various steps may be added, omitted, or combined. Furthermore, features described with respect to some examples may be combined into other examples.

[0043] See Figure 1 , Figure 1 This is a flowchart illustrating a multi-target anomaly processing method based on a screening line, provided in an embodiment of this application. In this embodiment, the method includes:

[0044] S101. Continuously acquire and filter the detection data uploaded by each preset online detection terminal, and parse the detection data to obtain detection result information.

[0045] The entity executing this application may be a cloud server.

[0046] In this embodiment of the application, multiple detection terminals will be pre-set at different positions on the screening line used to transport hanging packages that are about to be shipped. The cloud server will continuously acquire the detection data uploaded by each detection terminal, parse the acquired detection data, and generate detection result information so that it can directly determine whether there are multiple packages based on the detection result information.

[0047] In one possible implementation, the detection terminal includes a first detection sensor and a second detection sensor vertically distributed from top to bottom, and the detection data includes first detection data collected by the first detection sensor and second detection data collected by the second detection sensor.

[0048] The process of parsing the detection data to obtain detection result information includes:

[0049] The region interval corresponding to the first detection data detected twice consecutively by the same first detection sensor is defined as the detection region.

[0050] The number of the second detection data in each detection area is counted, and detection result information is generated based on the number of detections.

[0051] In this embodiment, the detection area can be understood as a cell area on the screening line used to place the hanging packages 4. To ensure that each hanging package 4 can be sorted to the correct shipping location, there should be at most one hanging package 4 in a detection area. The detection area is connected to the track by two pillars 3, and the carrier corresponding to the hanging package 4 is placed on the load-bearing column between the two pillars of the detection area.

[0052] In the embodiments of this application, such as Figure 2As shown, multiple detection sensors 2 can be vertically arranged in the detection terminal 1. These sensors 2 can be infrared sensors. Taking two sensors 2 as an example, from top to bottom, the detection terminal 1 contains a first detection sensor and a second detection sensor. The cloud server first determines the detection area based on the first detection data detected by the first detection sensor. Specifically, when the support column 3 moves to the detection terminal 1, the infrared light emitted by the first detection sensor is blocked, thus generating the first detection data. Therefore, the cloud server determines the detection area based on the time interval between consecutive detections of the first detection data. Furthermore, the second detection sensor can be used to detect the hanging package 4. When the hanging package 4 moves to the detection terminal 1, the infrared light emitted by the second detection sensor is blocked, thus generating the second detection data. Therefore, the cloud server counts the number of second detection data points obtained within the detection area, i.e., between two adjacent first detection data points corresponding to the detection area, and uses this as a benchmark to generate the detection result information.

[0053] In one possible implementation, the detection terminal includes a second detection sensor, and the detection data includes second detection data collected by the second detection sensor;

[0054] The process of parsing the detection data to obtain detection result information includes:

[0055] Obtain a preset statistical time period, which includes a format chain time interval and a non-format chain time interval. The format chain time interval corresponds to a format chain region, and the non-format chain time interval corresponds to a non-format chain region.

[0056] The number of detections corresponding to the second detection data in the format chain region and the non-format chain region are counted respectively, and detection result information is generated based on the number of detections.

[0057] In the embodiments of this application, such as Figure 3As shown, detection terminal 1 can also be equipped with only one second detection sensor for detecting the hanging package 4. This second detection sensor can be an infrared sensor. Since the lengths of the format chain region and the non-format chain region are fixed, and their distribution is regular, the format chain time interval and the non-format chain time interval can be determined by pre-setting the statistical time period based on the initial state of the screening line. For example, a statistical time period of 0.7s could mean the first 0.2s is the non-format chain time interval and the last 0.5s is the format chain time interval. Alternatively, the first 0.1s and the last 0.1s could be the non-format chain time interval, and the middle 0.5s the format chain time interval. After determining the statistical time period, the current region category can be determined directly based on the screening line's running time, and then the detection result information can be generated by combining this with the number of detections of the second detection data within that time period.

[0058] In one possible implementation, the detection result information includes normal detection result information and abnormal detection result information;

[0059] The generation of detection result information based on the number of detections includes:

[0060] When the number of tests is no more than one, normal test result information is generated;

[0061] When the number of detections is not less than two, abnormal detection result information is generated.

[0062] In this embodiment, the detection result information is divided into two types: normal detection result information and abnormal detection result information. Since under normal circumstances, there should be at most one hanging package 4 in the format chain, the detection result information generated when the number of detections is no more than one is taken as normal detection result information, and the rest is taken as abnormal detection result information.

[0063] S102. When there is abnormal detection result information, determine and mark the target cell corresponding to the abnormal detection result information.

[0064] The abnormal detection result information mentioned in this application embodiment can be understood as detection result information that characterizes abnormal results.

[0065] In this embodiment, if any abnormal detection result information is found in the detection result information obtained in the aforementioned process, it indicates that a multi-packet anomaly has occurred. In order to automate the processing of multi-packet anomalies, the cloud server needs to identify and mark the target cell containing the abnormal detection result information. The target cell can be a formatted chain area or a non-formatted chain area.

[0066] In one possible implementation, step S102 includes:

[0067] When abnormal detection result information exists, the abnormal detection data corresponding to the abnormal detection result information is determined;

[0068] The target cell corresponding to the anomaly detection data is determined based on the transport speed of the screening line and the data detection time of the anomaly detection data, and the target cell is marked.

[0069] The anomaly detection data in this embodiment can be understood as the detection data corresponding to the anomaly detection result information.

[0070] In this embodiment, since the detection result information is obtained from the detection data, and the transport speed of the screening line is also fixed and determined, the cell with the multi-package anomaly problem can be identified and marked based on the running speed of the screening line and the data detection time for collecting the anomaly detection data, so as to continuously track its location.

[0071] S103. Input all target vehicles of the target cell into the buffer storage area closest to the target cell, and output each target vehicle in the buffer storage area to the free cell of the filter line one by one.

[0072] In this embodiment, in addition to the corresponding sorting and packaging channel track, several buffer storage areas are connected to the screening line. The hanging packages are suspended on the hanging carriers. The buffer storage area can be a semi-circular track used to buffer hanging carriers with multiple package anomalies before re-transporting them back to the screening line. Specifically, the buffer storage area closest to the target cell is determined. When the target cell moves to this buffer storage area, the cloud server controls the hanging carrier in the target cell to change track to the buffer storage area. Then, the cloud server determines empty cells on the screening line without hanging carriers, and outputs the target carriers in the buffer storage area one by one to different empty cells, thereby separating multiple carriers within the same cell. This allows for autonomous handling of multiple package anomalies, ensuring that all cells ultimately output to the sorting station are normal.

[0073] In one possible implementation, the step of outputting each of the target vehicles in the buffer storage area to an empty cell of the filter line one by one includes:

[0074] Based on the aforementioned detection data, it is determined that there are no empty cells with suspended vehicles.

[0075] Whenever an empty cell passes through the buffer storage area, the target vehicle closest to the exit in the buffer storage area is output to the empty cell, until all the target vehicles in the buffer storage area have been output.

[0076] In this embodiment, as described above, each time a cell passes through, a multi-packet anomaly is determined based on the detection data. This process can also be used to determine whether a suspended vehicle exists within the cell, thereby identifying an empty cell. When an empty cell passes through the buffer storage area, the cloud server controls a target vehicle in the buffer storage area to be output to that empty cell. By repeating this process, the target vehicle can be output to different empty cells to handle multi-packet anomalies.

[0077] The following will be combined with the appendix Figure 4 This paper provides a detailed description of the multi-target anomaly processing device based on a screening line provided in the embodiments of this application. It should be noted that the appendix... Figure 4 The multi-target anomaly processing device based on the screening line shown is used to execute the present application. Figure 1 The methods shown in the embodiments are for illustrative purposes only, illustrating the parts relevant to the embodiments of this application. For specific technical details not disclosed, please refer to this application. Figure 1 The example shown.

[0078] Please see Figure 4 , Figure 4 This is a schematic diagram of the structure of a multi-target anomaly processing device based on a screening line, provided in an embodiment of this application. Figure 4 As shown, the device includes:

[0079] The acquisition module 401 is used to continuously acquire and filter the detection data uploaded by each preset online detection terminal, and parse the detection data to obtain detection result information;

[0080] The marking module 402 is used to determine and mark the target cell corresponding to the abnormal detection result information when there is abnormal detection result information;

[0081] The control module 403 is used to input all target vehicles of the target cell into the buffer storage area closest to the target cell, and output each target vehicle in the buffer storage area to the free cell of the filter line one by one.

[0082] In one possible implementation, the detection terminal includes a first detection sensor and a second detection sensor vertically distributed from top to bottom, and the detection data includes first detection data collected by the first detection sensor and second detection data collected by the second detection sensor.

[0083] The acquisition module 401 includes:

[0084] The first detection unit is used to determine the area interval corresponding to the first detection data detected twice consecutively by the same first detection sensor as the detection area;

[0085] The statistics unit is used to count the number of the second detection data in each detection area and generate detection result information based on the number of detections.

[0086] In one possible implementation, the detection terminal includes a second detection sensor, and the detection data includes second detection data collected by the second detection sensor;

[0087] The acquisition module 401 includes:

[0088] The second detection unit is used to obtain a preset statistical time period, which includes a format chain time interval and a non-format chain time interval. The format chain time interval corresponds to the format chain region, and the non-format chain time interval corresponds to the non-format chain region.

[0089] The statistics unit is used to count the number of detections corresponding to the second detection data in the format chain region and the non-format chain region respectively, and generate detection result information based on the number of detections.

[0090] In one possible implementation, the statistical unit includes:

[0091] The first generating element is used to generate normal detection result information when the number of detections is no more than one.

[0092] The second generating element is used to generate abnormal detection result information when the number of detections is not less than two.

[0093] In one possible implementation, the marking module 402 includes:

[0094] The first determining unit is used to determine the abnormal detection data corresponding to the abnormal detection result information when there is abnormal detection result information;

[0095] A marking unit is used to determine the target cell corresponding to the anomaly detection data based on the transport speed of the screening line and the data detection time of the anomaly detection data, and to mark the target cell.

[0096] In one possible implementation, the control module 403 includes:

[0097] The second determining unit is used to determine, based on the detection data, an empty cell where no suspended vehicle exists;

[0098] The output unit is used to output the target vehicle closest to the exit in the buffer area to the free cell whenever a free cell passes through the buffer area, until all the target vehicles in the buffer area have been output.

[0099] Those skilled in the art will clearly understand that the technical solutions of the embodiments of this application can be implemented by means of software and / or hardware. In this specification, "unit" and "module" refer to software and / or hardware that can independently complete or cooperate with other components to complete a specific function, wherein the hardware may be, for example, a field-programmable gate array (FPGA), an integrated circuit (IC), etc.

[0100] Each processing unit and / or module in the embodiments of this application can be implemented by an analog circuit that implements the functions described in the embodiments of this application, or by software that executes the functions described in the embodiments of this application.

[0101] See Figure 5 It shows a schematic diagram of the structure of an electronic device according to an embodiment of this application, which can be used to implement... Figure 1 The method in the illustrated embodiment. (As shown) Figure 5 As shown, the electronic device 500 may include: at least one central processing unit 501, at least one network interface 504, user interface 503, memory 505, and at least one communication bus 502.

[0102] The communication bus 502 is used to enable communication between these components.

[0103] The user interface 503 may include a display screen and a camera. Optionally, the user interface 503 may also include a standard wired interface and a wireless interface.

[0104] The network interface 504 may optionally include a standard wired interface or a wireless interface (such as a Wi-Fi interface).

[0105] The central processing unit 501 may include one or more processing cores. The central processing unit 501 connects to various parts within the electronic device 500 using various interfaces and lines. It executes various functions of the terminal 500 and processes data by running or executing instructions, programs, code sets, or instruction sets stored in the memory 505, and by calling data stored in the memory 505. Optionally, the central processing unit 501 may be implemented using at least one hardware form selected from Digital Signal Processing (DSP), Field-Programmable Gate Array (FPGA), and Programmable Logic Array (PLA). The central processing unit 501 may integrate one or more of the following: a central processing unit (CPU), a graphics processing unit (GPU), and a modem. The CPU primarily handles the operating system, user interface, and applications; the GPU is responsible for rendering and drawing the content required for display; and the modem handles wireless communication. It is understood that the modem may also be implemented as a separate chip without being integrated into the central processing unit 501.

[0106] The memory 505 may include random access memory (RAM) or read-only memory. Optionally, the memory 505 may include a non-transitory computer-readable storage medium. The memory 505 can be used to store instructions, programs, code, code sets, or instruction sets. The memory 505 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as touch function, sound playback function, image playback function, etc.), instructions for implementing the above-described method embodiments, etc.; the data storage area may store data involved in the above-described method embodiments, etc. Optionally, the memory 505 may also be at least one storage device located remotely from the aforementioned central processing unit 501. Figure 5 As shown, the memory 505, which serves as a computer storage medium, may include an operating system, a network communication module, a user interface module, and program instructions.

[0107] exist Figure 5In the illustrated electronic device 500, the user interface 503 is mainly used to provide an input interface for the user and to acquire user input data; while the central processing unit 501 can be used to call the multi-target exception handling application based on the filter line stored in the memory 505, and specifically perform the following operations:

[0108] The system continuously acquires and filters the detection data uploaded by each preset online detection terminal, and parses the detection data to obtain detection result information.

[0109] When abnormal detection result information exists, the target cell corresponding to the abnormal detection result information is determined and marked;

[0110] All target vehicles of the target cell are input into the buffer storage area closest to the target cell, and each target vehicle in the buffer storage area is output to the free cell of the filter line one by one.

[0111] This application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the above-described method. The computer-readable storage medium may include, but is not limited to, any type of disk, including floppy disks, optical disks, DVDs, CD-ROMs, microdrives, as well as magneto-optical disks, ROMs, RAMs, EPROMs, EEPROMs, DRAMs, VRAMs, flash memory devices, magnetic cards or optical cards, nanosystems (including molecular memory ICs), or any type of medium or device suitable for storing instructions and / or data.

[0112] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0113] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0114] In the several embodiments provided in this application, it should be understood that the disclosed apparatus can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some service interface; the indirect coupling or communication connection between devices or units may be electrical or other forms.

[0115] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0116] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0117] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage device (CMD). Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory 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 application. The aforementioned memory includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0118] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, which may include: a flash drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk, etc.

[0119] The foregoing description is merely an exemplary embodiment of this disclosure and should not be construed as limiting the scope of this disclosure. Any equivalent changes and modifications made in accordance with the teachings of this disclosure shall still fall within the scope of this disclosure. Those skilled in the art will readily conceive of embodiments of this disclosure upon considering the specification and practicing the disclosure herein. This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not described herein. The specification and embodiments are to be considered exemplary only, and the scope and spirit of this disclosure are defined by the claims.

Claims

1. A multi-target anomaly processing method based on a screening line, characterized in that, The method includes: The system continuously acquires and filters the detection data uploaded by each preset online detection terminal, and parses the detection data to obtain detection result information; the detection terminal includes a first detection sensor and a second detection sensor vertically distributed from top to bottom, and the detection data includes first detection data collected by the first detection sensor and second detection data collected by the second detection sensor; When abnormal detection result information exists, the target cell corresponding to the abnormal detection result information is determined and marked; All target vehicles of the target cell are input into the buffer storage area closest to the target cell, and each target vehicle in the buffer storage area is output to the free cell of the filter line one by one; The step of parsing the detection data to obtain detection result information includes: The area corresponding to the first detection data detected twice consecutively by the same first detection sensor is defined as the detection area; the detection area is a cell area on the screening line used to place hanging packages; the detection area is formed by two pillars connected to the track; when the pillars move to the detection terminal, the infrared light emitted by the first detection sensor is blocked, and the first detection data is generated; The number of second detection data in each detection area is counted, and detection result information is generated based on the number of detections. The step of outputting each of the target vehicles in the buffer storage area to the free cell of the filter line one by one includes: Based on the aforementioned detection data, it is determined that there are no empty cells with suspended vehicles. Whenever an empty cell passes through the buffer storage area, the target vehicle closest to the exit in the buffer storage area is output to the empty cell, until all the target vehicles in the buffer storage area have been output.

2. The method according to claim 1, characterized in that, The detection terminal includes a second detection sensor, and the detection data includes second detection data collected by the second detection sensor. The process of parsing the detection data to obtain detection result information includes: Obtain a preset statistical time period, which includes a format chain time interval and a non-format chain time interval. The format chain time interval corresponds to a format chain region, and the non-format chain time interval corresponds to a non-format chain region. The number of detections corresponding to the second detection data in the format chain region and the non-format chain region are counted respectively, and detection result information is generated based on the number of detections.

3. The method according to any one of claims 1 or 2, characterized in that, The detection result information includes normal detection result information and abnormal detection result information; The generation of detection result information based on the number of detections includes: When the number of tests is no more than one, normal test result information is generated; When the number of detections is not less than two, abnormal detection result information is generated.

4. The method according to claim 1, characterized in that, When abnormal detection result information exists, determining and marking the target cell corresponding to the abnormal detection result information includes: When abnormal detection result information exists, the abnormal detection data corresponding to the abnormal detection result information is determined; The target cell corresponding to the anomaly detection data is determined based on the transport speed of the screening line and the data detection time of the anomaly detection data, and the target cell is marked.

5. A multi-target anomaly processing device based on a screening line, characterized in that, The device includes: The acquisition module is used to continuously acquire and filter the detection data uploaded by each preset online detection terminal, and parse the detection data to obtain detection result information; the detection terminal includes a first detection sensor and a second detection sensor vertically distributed from top to bottom, and the detection data includes first detection data collected by the first detection sensor and second detection data collected by the second detection sensor; The marking module is used to determine and mark the target cell corresponding to the abnormal detection result information when abnormal detection result information exists; The control module is used to input all target vehicles of the target cell into the buffer storage area closest to the target cell, and output each target vehicle in the buffer storage area to the free cell of the filter line one by one; The acquisition module includes: The first detection unit is used to determine the area corresponding to the first detection data detected twice consecutively by the same first detection sensor as the detection area; the detection area is a cell area on the screening line used to place hanging packages; the detection area is formed by two pillars connected to the track; when the pillars move to the detection terminal, the infrared light emitted by the first detection sensor is blocked, and the first detection data is generated; The statistical unit is used to count the number of the second detection data in each detection area and generate detection result information based on the number of detections. The control module includes: The second determining unit is used to determine, based on the detection data, an empty cell where no suspended vehicle exists; The output unit is used to output the target vehicle closest to the exit in the buffer area to the free cell whenever a free cell passes through the buffer area, until all the target vehicles in the buffer area have been output.

6. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method as described in any one of claims 1-4.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1-4.

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