Dynamic weighing and sorting method suitable for high-speed logistics scene

Abstract

The invention relates to the technical field of logistics intelligent sorting, in particular to a dynamic weighing and sorting method suitable for a high-speed logistics scene, which comprises the following steps: acquiring shape parameters of to-be-sorted goods and a plurality of adjacent goods, and acquiring a historical goods sequence of each matched sorting port; the density and the connection condition of the to-be-sorted goods and the adjacent goods are analyzed, and the sorting priority of the to-be-sorted goods is obtained; according to the distribution of the sorting sequence and the shape parameters of all the goods in the historical goods sequence of each matched sorting opening, the stacking compactness index of each matched sorting opening is obtained; and obtaining a sorting port priority sequence of the to-be-sorted goods according to the shape parameters of the to-be-sorted goods and the stacking compactness index, and obtaining an optimal sorting port of the to-be-sorted goods according to the sorting priority of the to-be-sorted goods and the sorting port priority sequence. The invention aims to solve the problem of goods accumulation influenced by the sorting sequence in the sorting process of the power type narrow-band sorting machine, and the optimal sorting port of the to-be-sorted goods is obtained through intelligent decision.

Description

Technical Field

[0001] This invention relates to the field of intelligent sorting technology in logistics, and specifically to a dynamic weighing and sorting method applicable to high-speed logistics scenarios. Background Technology

[0002] In high-speed logistics scenarios, powered narrow-belt sorters rapidly transport packages via their continuously moving narrow belts and integrate a dynamic weighing module to obtain the precise weight of each package in real time. The system combines this weight data with order information, destination rules, and other factors as the core basis for judgment. When faced with multiple selectable sorting ports, the intelligent decision-making system can instantly calculate the optimal sorting path and then trigger the corresponding exit narrow belt, ensuring that packages are accurately and automatically diverted to the preset destination while traveling at high speed, thereby significantly improving sorting efficiency and accuracy.

[0003] During the sorting process of a powered narrow-strip sorter, in order to cope with the huge volume of goods and the sorting needs of packages of different sizes, the powered narrow-strip sorter will set up multiple sorting ports belonging to the same destination. Since the volume and weight of the goods sorted at each sorting port are almost fixed, after sorting the same volume of goods continuously, there are large gaps between the goods in the sorting box, which cannot make full use of the space of the sorting box, resulting in a decrease in sorting efficiency and an increase in transportation costs. Summary of the Invention

[0004] This invention provides a dynamic weighing and sorting method suitable for high-speed logistics scenarios to solve existing problems.

[0005] The dynamic weighing and sorting method of the present invention, applicable to high-speed logistics scenarios, adopts the following technical solution: One embodiment of the present invention provides a dynamic weighing and sorting method suitable for high-speed logistics scenarios, the method comprising the following steps: Obtain the shape parameters of the goods to be sorted and several adjacent goods, and obtain the historical goods sequence of each matching sorting port; Analyze the density and connectivity of the goods to be sorted with their neighboring goods to obtain the sorting priority of the goods to be sorted; Based on the distribution of sorting order and shape parameters of each item in the historical cargo sequence of each matching sorting point, the stacking density index of each matching sorting point is obtained. The sorting port priority sequence of the goods to be sorted is obtained based on the shape parameters of the goods to be sorted and the stacking density index. The optimal sorting port of the goods to be sorted is obtained based on the sorting priority and sorting port priority sequence of the goods to be sorted.

[0006] Preferably, obtaining the shape parameters of the goods to be sorted and several adjacent goods, and obtaining the historical goods sequence of each matching sorting port includes: Any item on the conveyor belt of the powered narrow belt sorter that passes through the scanning and identification module before the sorting section is recorded as an item to be sorted. The number of adjacent items is preset, and the number of adjacent items that have passed through the scanning and identification module before and after the item to be sorted are recorded as the adjacent items of the item to be sorted. The shape parameters of the goods to be sorted and their neighboring goods are obtained by reading the identification of the scanning and recognition module. Obtain the destination of the goods to be sorted based on the identification of the goods to be sorted, and record the sorting ports whose destinations are the same as the destinations of the goods to be sorted as the matching sorting ports of the goods to be sorted. The sequence of goods sorted to the matching sorting port is denoted as the historical goods sequence of the matching sorting port. The order of the historical goods sequence is the order in which the goods were sorted to the matching sorting port.

[0007] Preferably, the step of analyzing the density and connectivity of the goods to be sorted with their neighboring goods to obtain the sorting priority includes: Based on the time sequence in which the goods to be sorted and their adjacent goods pass through the scanning and recognition module, a scanning sequence sequence of the goods to be sorted is constructed; The average density of the goods to be sorted is the average time interval between every two adjacent goods in the scanning sequence of the goods to be sorted. Based on the average density, neighboring goods connected to the goods to be sorted are selected to construct a goods stacking sequence for the goods to be sorted; The sorting priority of the goods to be sorted is obtained based on the minimum distance between the serial number of the goods to be sorted in the goods stacking sequence and the serial numbers of the first and last serial numbers of the goods stacking sequence.

[0008] Preferably, the specific steps for obtaining the cargo stacking sequence include: In the scanning sequence of the goods to be sorted, taking the goods to be sorted as the center, if the time interval between the goods to be sorted and the previous neighboring goods is less than the average density, the previous neighboring goods of the goods to be sorted are recorded as the first preceding neighboring goods of the goods to be sorted; if the time interval between the first preceding neighboring goods of the goods to be sorted and the previous neighboring goods is less than the average density, the previous neighboring goods of the first preceding neighboring goods of the goods to be sorted are recorded as the second preceding neighboring goods of the goods to be sorted, and so on, until there exists a constant a such that the time interval between the a-th preceding neighboring goods of the goods to be sorted and the previous neighboring goods is greater than or equal to the average density, or the a-th preceding neighboring goods is the first sequence value of the scanning sequence of the goods to be sorted, and all preceding neighboring goods of the goods to be sorted are recorded as the set of preceding neighboring goods of the goods to be sorted. Centered on the goods to be sorted, the average density is used to filter the neighboring goods after the goods to be sorted in the scanning sequence of the goods to be sorted, so as to obtain the set of the next neighboring goods of the goods to be sorted. The preceding adjacent goods set and the following adjacent goods set of the goods to be sorted constitute the goods stacking sequence of the goods to be sorted in chronological order.

[0009] Preferably, obtaining the stacking density index for each matching sorting point based on the distribution of sorting order and shape parameters of each item in the historical cargo sequence of each matching sorting point includes: Record any matching sorting point as the target matching sorting point; Based on the three-dimensional shape parameters of each item in the historical cargo sequence of the target matching sorting point, calculate the volume of each item in the historical cargo sequence of the target matching sorting point. The volumes of all goods in the historical cargo sequence of the target matching sorting point are arranged in the order of the historical cargo sequence to form the historical cargo volume sequence of the target matching sorting point; Analyze the distribution of cargo volume in the historical cargo volume sequence to obtain the historical sorting rationality of the target matching sorting point; Based on the cargo volume and cargo order of the historical cargo volume sequence of the target matching sorting point, the hierarchical clustering algorithm is used to cluster the historical cargo volume sequence of the target matching sorting point to obtain several clusters, and each cluster is recorded as a unified volume segment of the target matching sorting point. Get the average volume of goods in each uniform volume segment, and get the average of the average volumes of goods in all uniform volume segments; The uniform volume segment with an average cargo volume greater than or equal to the average cargo volume is denoted as the large volume segment of the target matching sorting port, and other uniform volume segments are denoted as the small volume segments of the target matching sorting port. Based on the order of several large volume segments and several small volume segments of the target matching sorting port, obtain the stacking weight of each large volume segment and each small volume segment of the target matching sorting port. Based on the length and stacking weight of each large and small volume segment of the target matching sorting port, and combined with the historical sorting rationality, the stacking density index of the target matching sorting port is obtained.

[0010] Preferably, the specific steps for obtaining the rationality of historical sorting include: The ratio of the length of the historical cargo volume sequence of the target matching sorting point to the mean of the lengths of the historical cargo volume sequences of all other matching sorting points is denoted as the load factor of the target matching sorting point. The historical sorting rationality of the target matching sorting port is obtained. The historical sorting rationality is inversely proportional to the load coefficient and directly proportional to the distribution of cargo volume in the historical cargo volume sequence of the target matching sorting port.

[0011] Preferably, the specific steps for obtaining the stacking weights include: Obtain the number of goods from the last item in each large volume segment and each small volume segment of the target matching sorting port to the goods to be sorted; Obtain the stacking weight of each large volume segment and each small volume segment at the target matching sorting port, wherein the stacking weight is inversely proportional to the quantity of goods.

[0012] Preferably, obtaining the stacking density index of the target matching sorting port based on the length and stacking weight of each large volume segment and each small volume segment of the target matching sorting port, combined with the historical sorting rationality, includes: The product of the length of each large volume segment of the target matching sorting port and the stacking weight is denoted as the stacking contribution coefficient of each large volume segment of the target matching sorting port. The product of the length of each small volume segment of the target matching sorting port and the stacking weight is denoted as the stacking contribution coefficient of each small volume segment of the target matching sorting port. The stacking contribution coefficients of all small and large volume segments of the target matching sorting port are weighted according to the preset influence coefficients, and combined with the historical sorting rationality, to obtain the stacking density index of the target matching sorting port. The stacking density index is positively proportional to the historical sorting rationality.

[0013] Preferably, the step of obtaining the sorting port priority sequence of the goods to be sorted based on the shape parameters and the stacking density index, and obtaining the optimal sorting port of the goods to be sorted based on the sorting priority and the sorting port priority sequence, includes: Obtain the order coefficient of each matching sorting port in the sorting port priority sequence of the goods to be sorted; The difference between the order coefficient of each matching sorting point and the sorting priority of the goods to be sorted is recorded as the order priority of each matching sorting point. The first matching sorting port after reordering the product of the order priority and stacking density index of each matching sorting port in the sorting port priority sequence of the goods to be sorted according to the sorting port priority sequence is recorded as the optimal sorting port of the goods to be sorted. When the powered narrow belt sorter transports the goods to be sorted to its optimal sorting port, the belt of the powered narrow belt sorter rotates and sorts the goods into its optimal sorting port.

[0014] Preferably, the specific steps for obtaining the order coefficient include: Based on the shape parameters of the goods to be sorted, obtain the volume of the goods to be sorted; Calculate the average volume of large goods in all large volume segments and the average volume of small goods in all small volume segments for each matching sorting point; If the difference between the volume of the goods to be sorted and the average volume of the large goods at the matching sorting port is less than or equal to the difference between the average volume of the small goods at the matching sorting port, the goods to be sorted are recorded as large goods; otherwise, the goods to be sorted are recorded as small goods. When the goods to be sorted are large items, the stacking density index of the sorting port will be arranged in ascending order to form a sorting port priority sequence for the goods to be sorted. When the goods to be sorted are small items, the stacking density index of the matching sorting port is arranged in descending order to form a sorting port priority sequence for the goods to be sorted. The result of inversely normalizing the distance from each matching sorting port to the scanning and recognition module in the priority sequence of the sorting ports of the goods to be sorted is denoted as the order coefficient of each matching sorting port in the priority sequence of the sorting ports of the goods to be sorted.

[0015] The beneficial effects of the technical solution of this invention are as follows: This invention obtains the shape parameters of the goods to be sorted and several adjacent goods to acquire the historical goods sequence of each matching sorting port; analyzes the density and connection of the goods to be sorted and their adjacent goods to obtain the sorting priority of the goods to be sorted; by analyzing the density of the goods to be sorted and their adjacent goods, it selects connected adjacent goods, and obtains the sorting priority of the goods to be sorted based on the connected adjacent goods, thus avoiding the situation where connected goods are sorted first, causing other goods to be brought into the wrong sorting port; based on the historical goods sequence of each matching sorting port, the invention obtains the historical goods sequence of each matching sorting port to acquire the historical goods sequence of each adjacent goods. The sorting sequence and shape parameter distribution of goods are analyzed to obtain the stacking density index of each matching sorting port. By analyzing the historical sorting data of the matching sorting ports, the load and congestion during historical sorting processes are assessed, resulting in the stacking density index of the matching sorting ports. This index is then used to select a matching sorting port with a suitable stacking density index based on the shape of the goods to be sorted. A sorting port priority sequence for the goods to be sorted is obtained based on their shape parameters and the stacking density index. Based on the sorting priority and the sorting port priority sequence, the optimal sorting port for the goods to be sorted is determined. By selecting a matching sorting port with a suitable stacking density index based on the shape of the goods to be sorted, and combining sorting priorities, load balancing during the goods sorting process is achieved, and congestion with already sorted goods is avoided. Through intelligent decision-making on the powered narrow-strip sorter, sorting efficiency is improved. Attached Figure Description

[0016] 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 of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a flowchart illustrating the steps of the dynamic weighing and sorting method applicable to high-speed logistics scenarios according to the present invention. Detailed Implementation

[0018] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of the dynamic weighing and sorting method applicable to high-speed logistics scenarios proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0019] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0020] The following description, in conjunction with the accompanying drawings, details the specific solution of the dynamic weighing and sorting method provided by this invention, applicable to high-speed logistics scenarios.

[0021] Please see Figure 1 This document illustrates a flowchart of a dynamic weighing and sorting method for high-speed logistics scenarios provided by an embodiment of the present invention. The method includes the following steps: Step S001: Obtain the shape parameters of the goods to be sorted and several adjacent goods, and obtain the historical goods sequence of each matching sorting port when the goods to be sorted pass through the barcode recognition area.

[0022] It should be noted that when using a powered narrow-strip sorter for intelligent decision-making in goods sorting, it is first necessary to obtain information about the goods to be sorted and their corresponding sorting ports; the sorting port of the powered narrow-strip sorter is equipped with a scanning and recognition module to read the shape parameters and information of the goods.

[0023] Specifically, the method for obtaining the shape parameters of the goods to be sorted and several adjacent goods, and obtaining the historical goods sequence of each matching sorting port when the goods to be sorted pass through the barcode recognition area, is as follows: Any item on the conveyor belt of the powered narrow belt sorter that passes through the scanning and identification module before the sorting section is recorded as an item to be sorted. The number of adjacent items is preset. In this embodiment, 5 items are used as the number of adjacent items. The number of adjacent items that have passed through the scanning and identification module before and after the item to be sorted are recorded as the adjacent items of the item to be sorted. The shape parameters of the goods to be sorted and their neighboring goods are obtained by reading the identification of the scanning and recognition module. It should be noted that, in this embodiment, the identification of the goods to be sorted and their adjacent goods is a label. In this embodiment, the label is affixed to the goods in the form of a barcode. When the scanning and identification module scans the barcode, it reads the shape parameters of the goods to be sorted and their adjacent goods from the goods database based on the barcode encoding. The shape parameters include three dimensions and weight. The length of the goods can then be obtained from the three-dimensional data of the shape parameters, where the unit of length is uniformly centimeters (cm). In this embodiment, the label is affixed to a fixed position on the goods, for example, uniformly affixed to the lower left corner, so that the left width of the label overlaps with the left width of the goods. This ensures that when the scanning and identification module scans the barcode, it indicates that scanning of the goods has begun.

[0024] Furthermore, based on the identification of the goods to be sorted, the destination of the goods to be sorted is obtained, and all sorting ports whose destinations are the same as the destinations of the goods to be sorted are recorded as the matching sorting ports of the goods to be sorted. The sequence of goods sorted to the matching sorting port is denoted as the historical goods sequence of the matching sorting port. The order of the historical goods sequence is the order in which the goods were sorted to the matching sorting port.

[0025] In this embodiment, the maximum value of the historical cargo sequence is described using 100 as an example. Other embodiments may select other lengths for analysis.

[0026] Step S002: Analyze the density of the goods to be sorted and their neighboring goods to obtain the sorting priority of the goods to be sorted.

[0027] It should be noted that powered narrow-belt sorters are commonly used in the express delivery and logistics industries. Goods from different regions need to be transported from their stations to distribution centers. After the distribution center reads the identification of the goods, it uses a powered narrow-belt sorter to sort them, thereby realizing the transfer of goods. Due to the centralized transportation of goods, when the goods are piled up on the narrow belt of the powered narrow-belt sorter, the spacing between the goods is inconsistent, resulting in inconsistent stacking and spacing. When there is a stack of goods on the narrow-belt sorter, if the goods in the middle of the stack are sorted first, it will cause the surrounding goods to be pulled into the wrong sorting slot.

[0028] Based on this, this embodiment obtains the sorting priority of the goods to be sorted by analyzing the density of the goods to be sorted and the neighboring goods.

[0029] Preferably, the specific steps for analyzing the density and connectivity of the goods to be sorted with their neighboring goods to obtain the sorting priority include: The average density of the goods to be sorted is obtained based on the time interval between each pair of adjacent goods passing through the scanning and identification module. Since the length of each goods to be sorted can be obtained in step S001, the length of the goods to be sorted and the conveyor belt speed are calculated to obtain the transmission time for a complete transport of one goods to be sorted. The time interval between two adjacent goods is obtained by subtracting the transmission time of the previous goods from the time between the scanning and identification module identifying the tags of two goods.

[0030] It should be noted that the time interval between the scanning of goods by the scanning module represents the time interval between the end of the scanning of the previous goods and the start of the scanning of the next goods. Therefore, if the speed of the sorting machine remains constant, the calculated time interval between two adjacent goods can be used to represent the distance between adjacent goods to be sorted, and thus can be used to obtain the average density of the goods to be sorted.

[0031] It should be noted that the principle of a narrow belt sorter is to rotate the narrow belt to move the goods on the narrow belt, thereby achieving sorting. Therefore, different goods need to be placed on different narrow belts with a certain distance between them. If the goods are piled up together, when the same set of narrow belts is rotated, multiple goods will be involved in each other, resulting in multiple goods being sorted when a sorting command is issued. Ultimately, the goods will be sorted to the wrong sorting point. Therefore, there must be a gap between the goods.

[0032] In a preferred embodiment of the present invention, two labels can be affixed to the goods. One is a start label affixed to the lower left corner of the goods, such that the left width of the label overlaps with the left width of the goods. The other is an end label affixed to the lower right corner of the goods, such that the right width of the label overlaps with the right width of the goods. The time interval between when the scanning and recognition module scans the end label of the previous goods and before the scanning and recognition module scans the start label of the next goods is used as the time interval between two adjacent goods.

[0033] Based on the average density, neighboring goods connected to the goods to be sorted are selected to construct a goods stacking sequence for the goods to be sorted; By analyzing the position of the goods to be sorted in the stacking sequence, the sorting priority of the goods to be sorted can be obtained.

[0034] It should be noted that the goods are conveyed sequentially on the conveyor belt of the powered narrow belt sorter. If the goods are stacked together, the time interval between their scanning and recognition by the scanning module is much smaller than the interval between other goods. Therefore, in this embodiment, the average density of the goods to be sorted is first obtained based on the time interval between the scanning of the goods to be sorted and their neighboring goods.

[0035] Specifically, the method for obtaining the average density of the goods to be sorted, based on the time interval between each pair of adjacent goods passing through the scanning and recognition module, is as follows: Based on the time sequence in which the goods to be sorted and their adjacent goods pass through the scanning and recognition module, a scanning sequence sequence of the goods to be sorted is constructed; the scanning sequence sequence includes the goods to be sorted. The average density of the goods to be sorted is defined as the average time interval between any two adjacent goods in the scan sequence of the goods to be sorted.

[0036] It should be noted that, in order to avoid the average density being too small because the goods to be sorted are all connected to their neighboring goods, this embodiment presets a minimum time interval of 2 seconds. If the average value of the time interval is less than the minimum time interval, the minimum time interval is used as the average density of the goods to be sorted.

[0037] It should be noted that after obtaining the average density of the goods to be sorted, the lower the probability that two goods with a time interval greater than the average density are in a stacked state, the more likely it is that they are stacked together. Therefore, in this embodiment, the goods to be sorted are used as the center according to the scanning order, and the average density is used to filter the goods that are stacked together with the goods to be sorted, so as to obtain the goods stacking sequence of the goods to be sorted.

[0038] Furthermore, the specific method for constructing the stacking sequence of goods to be sorted by selecting neighboring goods connected to the goods to be sorted based on the average density is as follows: In the scanning sequence of the goods to be sorted, taking the goods to be sorted as the center, if the time interval between the goods to be sorted and the previous neighboring goods is less than the average density, the previous neighboring goods of the goods to be sorted are recorded as the first preceding neighboring goods of the goods to be sorted; if the time interval between the first preceding neighboring goods of the goods to be sorted and the previous neighboring goods is less than the average density, the previous neighboring goods of the first preceding neighboring goods of the goods to be sorted are recorded as the second preceding neighboring goods of the goods to be sorted, and so on, until there exists a constant a such that the time interval between the a-th preceding neighboring goods of the goods to be sorted and the previous neighboring goods is greater than or equal to the average density, or the a-th preceding neighboring goods is the first sequence value of the scanning sequence of the goods to be sorted, and all preceding neighboring goods of the goods to be sorted are recorded as the set of preceding neighboring goods of the goods to be sorted. Similarly, taking the goods to be sorted as the center, the average density is used to filter the neighboring goods after the goods to be sorted in the scanning sequence of the goods to be sorted, so as to obtain the set of the next neighboring goods of the goods to be sorted. The preceding adjacent goods set and the following adjacent goods set of the goods to be sorted constitute the goods stacking sequence of the goods to be sorted in chronological order.

[0039] It should be noted that after obtaining the stacking sequence of the goods to be sorted, the closer the goods to be sorted are to the middle of the stacking sequence, the lower their priority for sorting, so as to avoid bringing the connected goods into the wrong sorting port when sorting the goods to be sorted first.

[0040] Furthermore, by analyzing the position of the goods to be sorted in the stacking sequence, the specific method for determining the sorting priority of the goods to be sorted is as follows: The sorting priority of the goods to be sorted is obtained based on the minimum distance between the serial number of the goods to be sorted in the goods stacking sequence and the serial numbers of the first and last serial numbers of the goods stacking sequence.

[0041] As an example, the sorting priority of goods to be sorted is obtained as follows: The minimum difference between the sequence number of the goods to be sorted in the goods stacking sequence and the first and last sequence numbers of the goods stacking sequence is recorded as the minimum spacing of the goods to be sorted. The ratio of the minimum spacing of the goods to be sorted to the length of the goods stacking sequence is recorded as the sorting priority of the goods to be sorted.

[0042] Step S003: Based on the shape parameters of each item in the historical cargo sequence of each matching sorting point, obtain the stacking density index of each matching sorting point.

[0043] It should be noted that when goods pass through the scanning and recognition module, the powered narrow belt sorter will determine the belt carrying each item. When the goods arrive at the corresponding sorting port, the belt will rotate and throw the goods to the corresponding sorting port. During this process, the powered narrow belt sorter needs to make intelligent decisions to achieve load balancing and avoid excessive congestion at one sorting port while other sorting ports are idle. Through intelligent decision-making, packages are dynamically allocated to different sorting ports with the same destination, so that the workload of all sorting ports tends to be averaged.

[0044] It should be further explained that when dynamically allocating packages to different sorting stations for the same destination in the traditional way, it is mainly based on the type and size of the goods. However, goods of the same size are prone to gaps, meaning that the goods cannot fit perfectly, causing the downstream chute and collection bag to overflow. Even if the sorting station is theoretically usable, if packages of the same size are sorted for a long time, the chute and collection bag may become nearly full and pile up. At the same time, the inability of packages to fit together also affects space and sorting efficiency. Therefore, this embodiment obtains the stacking density index of each matching sorting station by analyzing the shape parameters of each goods in the historical goods sequence of each matching sorting station.

[0045] Preferably, the specific steps for obtaining the stacking density index of each matching sorting point based on the sorting order and shape parameter distribution of each item in the historical cargo sequence of each matching sorting point are as follows: Record any matching sorting point as the target matching sorting point; Based on the shape parameters of each item in the historical cargo sequence of the target matching sorting point, obtain the historical cargo volume sequence of the target matching sorting point; Analyze the distribution of cargo volume in the historical cargo volume sequence to obtain the historical sorting rationality of the target matching sorting point; Based on the order of cargo volumes in the historical cargo volume sequence, the historical cargo volume sequence is divided to obtain several uniform volume segments for the target matching sorting port. The unified volume segment is divided to obtain several large volume segments and several small volume segments for the target matching sorting port; Based on the order of several large-volume segments and several small-volume segments of the target matching sorting port, and combined with the historical sorting rationality, the stacking density index of the target matching sorting port is obtained.

[0046] Specifically, the steps to obtain the historical cargo volume sequence of the target matching sorting point based on the shape parameters of each cargo in the historical cargo sequence are as follows: Based on the three-dimensional shape parameters of each item in the historical cargo sequence of the target matching sorting point, calculate the volume of each item in the historical cargo sequence of the target matching sorting point. The volumes of all goods in the historical cargo sequence of the target matching sorting port are arranged in the order of the historical cargo sequence to form the historical cargo volume sequence of the target matching sorting port.

[0047] It should be noted that if the volume distribution of goods in the historical cargo volume sequence of the target matching sorting port is larger, it indicates that the goods entering the sorting port are more disordered and fewer in number. In this case, the possibility of high load and congestion at the sorting port is smaller, indicating that the sorting at the sorting port is more reasonable in the historical process.

[0048] Specifically, the method for analyzing the distribution of cargo volume in the historical cargo volume sequence to obtain the historical sorting rationality of the target matching sorting point is as follows: The ratio of the length of the historical cargo volume sequence of the target matching sorting point to the mean of the lengths of the historical cargo volume sequences of all other matching sorting points is denoted as the load factor of the target matching sorting point. It should be noted that if the average length of the historical cargo volume sequence of all other matching sorting ports is 0, then the average length of the historical cargo volume sequence of all other matching sorting ports will be calculated as 1.

[0049] The historical sorting rationality of the target matching sorting port is obtained. The historical sorting rationality is inversely proportional to the load coefficient and directly proportional to the distribution of cargo volume in the historical cargo volume sequence of the target matching sorting port.

[0050] As an example, this embodiment defines the historical sorting rationality of the target matching sorting port as the product of the variance of the cargo volume in the historical cargo volume sequence of the target matching sorting port and the load coefficient after inverse proportional normalization.

[0051] It should be noted that the variance of the cargo volume in the historical cargo volume sequence of the target matching sorting port is used to represent the distribution of cargo volume in the historical cargo volume sequence of the target matching sorting port. The larger the value, the larger the distribution. In this embodiment, an exponential function with the natural constant as the base is used to perform inverse proportional normalization on the load coefficient. The normalization is a well-known existing technology and will not be described in detail in this embodiment.

[0052] It should be noted that, due to the different sources of goods obtained from various stations, some stations have uniform goods size in the historical goods sorted at the sorting point. This results in uniform volume of goods sorted over a long period of time, even if the volume distribution of the goods is large, the volume of the goods remains uniform over a long period of time. Therefore, this embodiment analyzes the order of the historical goods volume sequence and then divides the historical goods volume sequence according to the uniformity of volume to obtain several uniform volume segments of the target matching sorting point.

[0053] Specifically, the method for dividing the historical cargo volume sequence into several uniform volume segments for the target matching sorting port based on the order of cargo volumes in the historical cargo volume sequence is as follows: Based on the cargo volume and cargo order of the historical cargo volume sequence of the target matching sorting port, a hierarchical clustering algorithm is used to cluster the historical cargo volume sequence of the target matching sorting port to obtain several clusters. Each cluster is recorded as a unified volume segment of the target matching sorting port.

[0054] Furthermore, the step of dividing the unified volume segment into several large volume segments and several small volume segments for the target matching sorting port is as follows: Get the average volume of goods in each uniform volume segment, and get the average of the average volumes of goods in all uniform volume segments; The uniform volume segments whose average cargo volume is greater than or equal to the average cargo volume are denoted as the large volume segments of the target matching sorting port, and other uniform volume segments are denoted as the small volume segments of the target matching sorting port.

[0055] It should be noted that the above-mentioned large volume segments and small volume segments of the target matching sorting port represent the goods entering the target matching sorting port in a continuous period of time. When more large goods enter the target matching sorting port in a continuous period of time, it indicates that the goods cannot fit together, resulting in more gaps. In this case, the stacking density index is higher, and vice versa. Then, combined with the historical sorting rationality, the stacking density index of the target matching port is obtained.

[0056] Specifically, the steps for obtaining the stacking density index of the target matching sorting port based on the order of several large-volume segments and several small-volume segments, combined with the historical sorting rationality, are as follows: Based on the order of several large volume segments and several small volume segments of the target matching sorting port, obtain the stacking weight of each large volume segment and each small volume segment of the target matching sorting port. Based on the length and stacking weight of each large and small volume segment of the target matching sorting port, and combined with the historical sorting rationality, the stacking density index of the target matching sorting port is obtained.

[0057] It should be noted that during the sorting process, the larger or smaller volume segments that are closer to the goods to be sorted are located on the surface of the downstream chute and the collection bag, and the greater the impact of the gaps between them on the goods to be sorted.

[0058] Based on this, the specific method by which this embodiment obtains the stacking weight of each large volume segment and each small volume segment of the target matching sorting port according to the order of several large volume segments and several small volume segments is as follows: Obtain the number of goods from the last item in each large volume segment and each small volume segment of the target matching sorting port to the goods to be sorted; Obtain the stacking weight of each large volume segment and each small volume segment at the target matching sorting port, wherein the stacking weight is inversely proportional to the quantity of goods.

[0059] As an example, this embodiment takes the result of inversely normalizing the number of goods from the last item to the goods to be sorted in each large volume segment of the target matching sorting port, and records it as the stacking weight of each large volume segment of the target matching sorting port. The stacking weight of each small volume segment of the target matching sorting port is denoted as the result of inversely normalizing the distance between the last item and the item to be sorted in each small volume segment.

[0060] Furthermore, based on the length and stacking weight of each large and small volume segment of the target matching sorting port, and combined with the historical sorting rationality, the specific steps for obtaining the stacking density index of the target matching sorting port are as follows: The preset influence coefficient is set as 1 for large volume segments and -1 for small volume segments in this embodiment. The product of the length of each large volume segment of the target matching sorting port and the stacking weight is denoted as the stacking contribution coefficient of each large volume segment of the target matching sorting port. The product of the length of each small volume segment of the target matching sorting port and the stacking weight is denoted as the stacking contribution coefficient of each small volume segment of the target matching sorting port. The stacking contribution coefficients of all small and large volume segments at the target matching sorting port are weighted by the influence coefficient, and combined with the historical sorting rationality, to obtain the stacking density index of the target matching sorting port. The stacking density index is positively proportional to the historical sorting rationality.

[0061] As an example, the stacking density index of the target matching sorting port is calculated as follows: in, To match the stacking density index of the sorting port to the target, This represents the total number of small volume segments and large volume segments. The influence coefficient, To determine the historical sorting rationality of the target matching sorting port, when the i-th individual integration segment is a small volume segment, When the i-th individual integral segment is a large volume segment, Let be the accumulation contribution coefficient of the i-th individual integral segment. , for The function is used to normalize the packing density index so that its value ranges from 1 to 2. .

[0062] Step S004: Obtain the sorting port priority sequence of the goods to be sorted based on the shape parameters of the goods to be sorted and the stacking density index. Obtain the optimal sorting port of the goods to be sorted based on the sorting priority and sorting port priority sequence of the goods to be sorted.

[0063] It should be noted that after obtaining the stacking density index of each sorting port, the appropriate volume segments are divided according to the shape parameters of the goods to be sorted, so that when the goods to be sorted are small, they are sorted into the matching sorting port with a larger stacking density index, and when the goods to be sorted are large, they are sorted into the matching sorting port with a smaller stacking density index. Thus, the priority of each matching sorting port is obtained, which constitutes the sorting port priority sequence.

[0064] Preferably, the specific steps for obtaining the sorting port priority sequence of the goods to be sorted based on the shape parameters of the goods to be sorted and the stacking density index are as follows: Based on the shape parameters of the goods to be sorted, obtain the volume of the goods to be sorted; Calculate the average volume of large goods in all large volume segments and the average volume of small goods in all small volume segments for each matching sorting point; If the difference between the volume of the goods to be sorted and the average volume of the large goods at the matching sorting port is less than or equal to the difference between the average volume of the small goods at the matching sorting port, the goods to be sorted are recorded as large goods; otherwise, the goods to be sorted are recorded as small goods. When the goods to be sorted are large items, the stacking density index of the sorting port will be arranged in ascending order to form a sorting port priority sequence for the goods to be sorted. When the goods to be sorted are small items, the stacking density index of the matching sorting ports is arranged in descending order to form a sorting port priority sequence for the goods to be sorted.

[0065] It should be noted that after obtaining the sorting port priority sequence of the goods to be sorted, since the distance between different matching sorting ports and the scanning and recognition module is different, the goods with higher sorting priority will be sorted first during the decision-making sorting process. Therefore, the sorting port priority sequence is reordered according to the sorting priority, and then the optimal sorting port is selected to sort the goods to be sorted.

[0066] Specifically, the steps to obtain the optimal sorting port for the goods to be sorted, based on the sorting priority and sorting port priority sequence, are as follows: The result of inversely normalizing the distance from each matching sorting port to the scanning and recognition module in the priority sequence of the sorting ports of the goods to be sorted is denoted as the order coefficient of each matching sorting port in the priority sequence of the sorting ports of the goods to be sorted. The larger the order coefficient, the closer the goods are to the scanning and recognition module, and the higher the sorting priority they should be assigned to the matching sorting port. Conversely, the farther away the goods are, the lower the sorting priority they should be assigned to the matching sorting port.

[0067] The difference between the order coefficient of each matching sorting point and the sorting priority of the goods to be sorted is recorded as the order priority of each matching sorting point. The first matching sorting port after reordering the product of the order priority and stacking density index of each matching sorting port in the sorting port priority sequence of the goods to be sorted according to the sorting port priority sequence is recorded as the optimal sorting port of the goods to be sorted. When the powered narrow belt sorter transports the goods to be sorted to its optimal sorting port, the belt of the powered narrow belt sorter rotates and sorts the goods into its optimal sorting port, realizing the intelligent sorting decision of the powered narrow belt sorter.

[0068] It should be noted that the embodiments used in this example The model only represents negative correlations and constraints. The model output results are in... Within the interval, This is the input to this model; in specific implementations, it can be replaced with other models that have the same purpose. This embodiment is merely an example. The description will be based on a model, without making any specific limitations.

[0069] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A dynamic weighing and sorting method applicable to high-speed logistics scenarios, characterized in that, The method includes the following steps: Obtain the shape parameters of the goods to be sorted and several adjacent goods, and obtain the historical goods sequence of each matching sorting port; Analyze the density and connectivity of the goods to be sorted with their neighboring goods to obtain the sorting priority of the goods to be sorted; Based on the distribution of sorting order and shape parameters of each item in the historical cargo sequence of each matching sorting point, the stacking density index of each matching sorting point is obtained. The sorting port priority sequence of the goods to be sorted is obtained based on the shape parameters of the goods to be sorted and the stacking density index. The optimal sorting port of the goods to be sorted is obtained based on the sorting priority and sorting port priority sequence of the goods to be sorted.

2. The dynamic weighing and sorting method applicable to high-speed logistics scenarios according to claim 1, characterized in that, The step of obtaining the shape parameters of the goods to be sorted and several adjacent goods, and obtaining the historical goods sequence of each matching sorting port includes: Any item on the conveyor belt of the powered narrow belt sorter that passes through the scanning and identification module before the sorting section is recorded as an item to be sorted. The number of adjacent items is preset, and the number of adjacent items that have passed through the scanning and identification module before and after the item to be sorted are recorded as the adjacent items of the item to be sorted. The shape parameters of the goods to be sorted and their neighboring goods are obtained by reading the identification of the scanning and recognition module. Obtain the destination of the goods to be sorted based on the identification of the goods to be sorted, and record the sorting ports whose destinations are the same as the destinations of the goods to be sorted as the matching sorting ports of the goods to be sorted. The sequence of goods sorted to the matching sorting port is denoted as the historical goods sequence of the matching sorting port. The order of the historical goods sequence is the order in which the goods were sorted to the matching sorting port.

3. The dynamic weighing and sorting method applicable to high-speed logistics scenarios according to claim 1, characterized in that, The analysis of the density and connectivity of the goods to be sorted with their neighboring goods to obtain the sorting priority includes: Based on the time sequence in which the goods to be sorted and their adjacent goods pass through the scanning and recognition module, a scanning sequence sequence of the goods to be sorted is constructed; The average density of the goods to be sorted is the average time interval between every two adjacent goods in the scanning sequence of the goods to be sorted. Based on the average density, neighboring goods connected to the goods to be sorted are selected to construct a goods stacking sequence for the goods to be sorted; The sorting priority of the goods to be sorted is obtained based on the minimum distance between the serial number of the goods to be sorted in the goods stacking sequence and the serial numbers of the first and last serial numbers of the goods stacking sequence.

4. The dynamic weighing and sorting method applicable to high-speed logistics scenarios according to claim 3, characterized in that, The specific steps for obtaining the cargo stacking sequence include: In the scanning sequence of the goods to be sorted, taking the goods to be sorted as the center, if the time interval between the goods to be sorted and the previous neighboring goods is less than the average density, the previous neighboring goods of the goods to be sorted are recorded as the first preceding neighboring goods of the goods to be sorted; if the time interval between the first preceding neighboring goods of the goods to be sorted and the previous neighboring goods is less than the average density, the previous neighboring goods of the first preceding neighboring goods of the goods to be sorted are recorded as the second preceding neighboring goods of the goods to be sorted, and so on, until there exists a constant a such that the time interval between the a-th preceding neighboring goods of the goods to be sorted and the previous neighboring goods is greater than or equal to the average density, or the a-th preceding neighboring goods is the first sequence value of the scanning sequence of the goods to be sorted, and all preceding neighboring goods of the goods to be sorted are recorded as the set of preceding neighboring goods of the goods to be sorted. Centered on the goods to be sorted, the average density is used to filter the neighboring goods after the goods to be sorted in the scanning sequence of the goods to be sorted, so as to obtain the set of the next neighboring goods of the goods to be sorted. The preceding adjacent goods set and the following adjacent goods set of the goods to be sorted constitute the goods stacking sequence of the goods to be sorted in chronological order.

5. The dynamic weighing and sorting method applicable to high-speed logistics scenarios according to claim 1, characterized in that, The step of obtaining the stacking density index for each matching sorting point based on the distribution of sorting order and shape parameters of each item in the historical cargo sequence of each matching sorting point includes: Record any matching sorting point as the target matching sorting point; Based on the three-dimensional shape parameters of each item in the historical cargo sequence of the target matching sorting point, calculate the volume of each item in the historical cargo sequence of the target matching sorting point. The volumes of all goods in the historical cargo sequence of the target matching sorting point are arranged in the order of the historical cargo sequence to form the historical cargo volume sequence of the target matching sorting point; Analyze the distribution of cargo volume in the historical cargo volume sequence to obtain the historical sorting rationality of the target matching sorting point; Based on the cargo volume and cargo order of the historical cargo volume sequence of the target matching sorting point, the hierarchical clustering algorithm is used to cluster the historical cargo volume sequence of the target matching sorting point to obtain several clusters, and each cluster is recorded as a unified volume segment of the target matching sorting point. Get the average volume of goods in each uniform volume segment, and get the average of the average volumes of goods in all uniform volume segments; The uniform volume segment with an average cargo volume greater than or equal to the average cargo volume is denoted as the large volume segment of the target matching sorting port, and other uniform volume segments are denoted as the small volume segments of the target matching sorting port. Based on the order of several large volume segments and several small volume segments of the target matching sorting port, obtain the stacking weight of each large volume segment and each small volume segment of the target matching sorting port. Based on the length and stacking weight of each large and small volume segment of the target matching sorting port, and combined with the historical sorting rationality, the stacking density index of the target matching sorting port is obtained.

6. The dynamic weighing and sorting method applicable to high-speed logistics scenarios according to claim 5, characterized in that, The specific steps for obtaining the rationality of historical sorting include: The ratio of the length of the historical cargo volume sequence of the target matching sorting point to the mean of the lengths of the historical cargo volume sequences of all other matching sorting points is denoted as the load factor of the target matching sorting point. The historical sorting rationality of the target matching sorting port is obtained. The historical sorting rationality is inversely proportional to the load coefficient and directly proportional to the distribution of cargo volume in the historical cargo volume sequence of the target matching sorting port.

7. The dynamic weighing and sorting method applicable to high-speed logistics scenarios according to claim 5, characterized in that, The specific steps for obtaining the stacked weights include: Obtain the number of goods from the last item in each large volume segment and each small volume segment of the target matching sorting port to the goods to be sorted; Obtain the stacking weight of each large volume segment and each small volume segment at the target matching sorting port, wherein the stacking weight is inversely proportional to the quantity of goods.

8. The dynamic weighing and sorting method applicable to high-speed logistics scenarios according to claim 5, characterized in that, The process of obtaining the stacking density index of the target matching sorting port based on the length and stacking weight of each large and small volume segment of the target matching sorting port, combined with the historical sorting rationality, includes: The product of the length of each large volume segment of the target matching sorting port and the stacking weight is denoted as the stacking contribution coefficient of each large volume segment of the target matching sorting port. The product of the length of each small volume segment of the target matching sorting port and the stacking weight is denoted as the stacking contribution coefficient of each small volume segment of the target matching sorting port. The stacking contribution coefficients of all small and large volume segments of the target matching sorting port are weighted according to the preset influence coefficients, and combined with the historical sorting rationality, to obtain the stacking density index of the target matching sorting port. The stacking density index is positively proportional to the historical sorting rationality.

9. The dynamic weighing and sorting method applicable to high-speed logistics scenarios according to claim 1, characterized in that, The step of obtaining the sorting port priority sequence of the goods to be sorted based on the shape parameters and the packing density index, and obtaining the optimal sorting port of the goods to be sorted based on the sorting priority and the sorting port priority sequence, includes: Obtain the order coefficient of each matching sorting port in the sorting port priority sequence of the goods to be sorted; The difference between the order coefficient of each matching sorting point and the sorting priority of the goods to be sorted is recorded as the order priority of each matching sorting point. The first matching sorting port after reordering the product of the order priority and stacking density index of each matching sorting port in the sorting port priority sequence of the goods to be sorted according to the sorting port priority sequence is recorded as the optimal sorting port of the goods to be sorted. When the powered narrow belt sorter transports the goods to be sorted to its optimal sorting port, the belt of the powered narrow belt sorter rotates and sorts the goods into its optimal sorting port.

10. The dynamic weighing and sorting method applicable to high-speed logistics scenarios according to claim 9, characterized in that, The specific steps for obtaining the order coefficient include: Based on the shape parameters of the goods to be sorted, obtain the volume of the goods to be sorted; Calculate the average volume of large goods in all large volume segments and the average volume of small goods in all small volume segments for each matching sorting point; If the difference between the volume of the goods to be sorted and the average volume of the large goods at the matching sorting port is less than or equal to the difference between the average volume of the small goods at the matching sorting port, the goods to be sorted are recorded as large goods; otherwise, the goods to be sorted are recorded as small goods. When the goods to be sorted are large items, the stacking density index of the sorting port will be arranged in ascending order to form a sorting port priority sequence for the goods to be sorted. When the goods to be sorted are small items, the stacking density index of the matching sorting port is arranged in descending order to form a sorting port priority sequence for the goods to be sorted. The result of inversely normalizing the distance from each matching sorting port to the scanning and recognition module in the priority sequence of the sorting ports of the goods to be sorted is denoted as the order coefficient of each matching sorting port in the priority sequence of the sorting ports of the goods to be sorted.

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